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At least 523 records · Page 29

Orbit determination of highly elliptical Earth orbiters using improved Doppler data-processing modes

A navigation error covariance analysis of four highly elliptical Earth orbits is described, with apogee heights ranging from 20,000 to 76,800 km and perigee heights ranging from 1,000 to 5,000 km. This analysis differs from earlier studies in that improved navigation data-processing modes were used to reduce the radio metric data. For this study, X-band (8.4-GHz) Doppler data were assumed to be acquired from two Deep Space Network radio antennas and reconstructed orbit errors propagated over a single day. Doppler measurements were formulated as total-count phase measurements and compared to the traditional formulation of differenced-count frequency measurements. In addition, an enhanced data-filtering strategy was used, which treated the principal ground system calibration errors affecting the data as filter parameters. Results suggest that a 40- to 60-percent accuracy improvement may be achievable over traditional data-processing modes in reconstructed orbit errors, with a substantial reduction in reconstructed velocity errors at perigee. Historically, this has been a regime in which stringent navigation requirements have been difficult to meet by conventional methods.

Estefan, J. A.↗

Dual-Use Aspects of System Health Management

System Health Management functionality is an essential part of any space launch system. Health management functionality is an integral part of mission reliability, since it is needed to verify the reliability before the mission starts. Health Management is also a key factor in life cycle cost reduction and in increasing system availability. The degree of coverage needed by the system and the degree of coverage made available at a reasonable cost are critical parameters of a successful design. These problems are not unique to the launch vehicle world. In particular, the Intelligent Vehicle Highway System, commercial aircraft systems, train systems, and many types of industrial production facilities require various degrees of system health management. In all of these applications, too, the designers must balance the benefits and costs of health management in order to optimize costs. The importance of an integrated system is emphasized. That is, we present the case for considering health management as an integral part of system design, rather than functionality to be added on at the end of the design process. The importance of maintaining the system viewpoint is discussed in making hardware and software tradeoffs and in arriving at design decisions. We describe an approach to determine the parameters to be monitored in any system health management application. This approach is based on Design of Experiments (DOE), prototyping, failure modes and effects analyses, cost modeling and discrete event simulation. The various computer-based tools that facilitate the approach are discussed. The approach described originally was used to develop a fault tolerant avionics architecture for launch vehicles that incorporated health management as an integral part of the system. Finally, we discuss generalizing the technique to apply it to other domains. Several illustrations are presented.

Owens, P. R.↗

Mathematical Analysis and Optimization of Infiltration Processes

A variety of infiltration techniques can be used to fabricate solid materials, particularly composites. In general these processes can be described with at least one time dependent partial differential equation describing the evolution of the solid phase, coupled to one or more partial differential equations describing mass transport through a porous structure. This paper presents a detailed mathematical analysis of a relatively simple set of equations which is used to describe chemical vapor infiltration. The results demonstrate that the process is controlled by only two parameters, alpha and beta. The optimization problem associated with minimizing the infiltration time is also considered. Allowing alpha and beta to vary with time leads to significant reductions in the infiltration time, compared with the conventional case where alpha and beta are treated as constants.

Chang, H.-C.↗

SHAO Analysis Center 2012 Annual Report

The Shanghai Astronomical Observatory (SHAO) Analysis Center in 2012 continued routine VLBI data analysis and produced earth orientation parameter (EOP), terrestrial reference frame (TRF), and celestial reference frame (CRF) information, which was submitted to the IVS quarterly. The activities of SHAO also consisted of data reduction of the Chinese VLBI Network (CVN), spacecraft navigation using the VLBI technique, and some research activities.

Wang, Guangli↗

An Observation‐Driven Approach to Improve Vegetation Phenology in a Global Land Surface Model

An empirical model calibration approach is presented that aims to approximate missing biosphere processes in a global land surface model without the need for substantial model structural changes. The strategy is implemented here using the NASA Catchment‐CN land surface model and Moderate Resolution Imaging Spectroradiometer (MODIS) observations of the fraction of absorbed photosynthetically active radiation (FPAR). Existing plant functional types (PFTs) of the Catchment‐CN model are divided into three subtypes, based on the bias between the model‐simulated and MODIS‐observed FPAR. Separate sets of vegetation parameters for each subtype are then calibrated at a small number of grid cells with homogeneous, single‐PFT land cover, using MODIS FPAR reference observations from 2003 to 2009. The effectiveness of the empirical approach at improving the realism of modeled vegetation dynamics is investigated with two global model simulations for the period 2010–2016, one using the newly calibrated parameter values and the other using the original values. Globally, the calibrated parameters reduce the root mean square error (RMSE) of the modeled FPAR with respect to MODIS by 0.029 (∼10%) on average. In some regions, substantially larger RMSE reductions are achieved. RMSE reductions are primarily driven by model bias reductions, with neutral effects on the temporal correlation skill. While the empirical approach is suitable for achieving consistent model improvements, it is shown to be sensitive to the characteristics of the model error, specifically a dominance of the bias component in the case of Catchment‐CN. Ultimately, more fundamental model structural changes may be required to achieve better improvements.

J. Kolassa↗

Evaluation of Global Simulations of Aerosol Particle and Cloud Condensation Nuclei Number, with Implications for Cloud Droplet Formation

A total of 16 global chemistry transport models and general circulation models have participated in this study; 14 models have been evaluated with regard to their ability to reproduce the near-surface observed number concentration of aerosol particles and cloud condensation nuclei (CCN), as well as derived cloud droplet number concentration (CDNC). Model results for the period 2011-2015 are compared with aerosol measurements (aerosol particle number, CCN and aerosol particle composition in the submicron fraction) from nine surface stations located in Europe and Japan. The evaluation focuses on the ability of models to simulate the average across time state in diverse environments and on the seasonal and short-term variability in the aerosol properties. There is no single model that systematically performs best across all environments represented by the observations. Models tend to underestimate the observed aerosol particle and CCN number concentrations, with average normalized mean bias (NMB) of all models and for all stations, where data are available, of -24% and -35% for particles with dry diameters > 50 and > 120nm, as well as -36% and -34% for CCN at supersaturations of 0.2% and 1.0%, respectively. However, they seem to behave differently for particles activating at very low supersaturations (< 0.1%) than at higher ones. A total of 15 models have been used to produce ensemble annual median distributions of relevant parameters. The model diversity (defined as the ratio of standard deviation to mean) is up to about 3 for simulated N3 (number concentration of particles with dry diameters larger than 3 nm) and up to about 1 for simulated CCN in the extra-polar regions. A global mean reduction of a factor of about 2 is found in the model diversity for CCN at a supersaturation of 0.2% (CCN(0.2)) compared to that for N3, maximizing over regions where new particle formation is important. An additional model has been used to investigate potential causes of model diversity in CCN and bias compared to the observations by performing a perturbed parameter ensemble (PPE) accounting for uncertainties in 26 aerosol-related model input parameters. This PPE suggests that biogenic secondary organic aerosol formation and the hygroscopic properties of the organic material are likely to be the major sources of CCN uncertainty in summer, with dry deposition and cloud processing being dominant in winter. Models capture the relative amplitude of the seasonal variability of the aerosol particle number concentration for all studied particle sizes with available observations (dry diameters larger than 50, 80 and 120nm). The short-term persistence time (on the order of a few days) of CCN concentrations, which is a measure of aerosol dynamic behavior in the models, is underestimated on average by the models by 40% during winter and 20% in summer.

cloud droplets↗

Reduction and analysis of ATS-6 data

Results obtained from the analysis of data returned by the energetic particle spectrometer on ATS 6 are presented. The study of the energetic electron environment and the effects of the solar wind parameters on the energetic electrons trapped at the synchronous altitude are emphasized.

Paulikas, G. A.↗

A Multi-Sensor, Low Volume, Automated Culture System for Space Biology Experiments

Optical density (absorbance) is commonly used in microbiology to measure cell concentration and other colorimetric indicators. It is the main type of bioscience data returned from the BioSentinel small spacecraft mission, which was recently launched as a secondary payload on Artemis I. The flight unit takes absorbance measurements of yeast cultures at 570 nm, 630 nm, and 850 nm to track cell concentration and oxidation-reduction (redox) state of the metabolic indicator dye alamarBlue over time [1]. Because the data returned from a small spacecraft mission is necessarily limited, BioSentinel uses a specialized ground-based experiment apparatus to map the absorbance data onto several other parameters. This culture apparatus is composed of a polycarbonate base and lid which contain ports for several commercial sensors, including a standard 12 mm dissolved oxygen probe, gaseous CO2, fluid pressure, and two micro-probes for measuring pH and redox potential. It also contains a pressure relief valve, a rubber membrane for culture interaction, and a 12mm port for the custom optical probe designed to match in-flight measurements. Modules in two corners expand the culture volume into narrow columns, enabling solid-state optical density measurement and dielectric spectroscopy. The apparatus can be fit to a plate for magnetic stirring. The apparatus’s optical probe allows mapping between the flight unit’s optical data and the additional parameters measured by the ground-based experiments. Within the probe, a linear actuator pulls a plunger, drawing culture volume into the optical path. The actuator then pushes out the plunger and culture volume, cleaning any stray yeast from the inside surface of the probe. The probe chassis is 3D-printed from biocompatible resin with the optoelectronics cured inside an optically clear conformal coat which functions as a lens. To optimize the probe’s dimensions, including optical path, a test harness was developed to manipulate and measure distance while the LED light sources and photodiode detector are in operation. The test harness was composed of two 3/64” thick polycarbonate plates mounted to a set of calipers. The LEDs and photodiode were mounted on the outside of each plate. A cuvette of sample fluid was then clamped between the plates in line between the LEDs and photodiode. The test harness generated a 78% signal change between water and a dye standard for the green (570 nm) LED, a 90% signal change for the red (630 nm) LED, and a 25% signal change between water and overgrown yeast for the infrared (850 nm) LED. The improvements to the ground experiment apparatus (culture volume reduction, inclusion of an optical probe to measure flight-like optical data, and magnetic stirring for culture homogeneity) allow for more flight-like measurements to be taken and more accurate mapping of these additional parameters to the optical data returned from the flight unit. This enhancement to mission science return will give insight into how deep space radiation may affect human biology for future long-term space exploration.

Multi-Sensor↗

Application of Machine Learning Techniques in Calibration and Data Reduction of Multi-Hole Probes

This work presents procedures to implement machine learning methods in the existing algorithms for multi-hole probe calibrations and data reduction. It is shown here, that utilizing artificial neural networks (ANNs) can reduce the amount of calibration data that needs to be acquired in order to obtain a specific calibration uncertainty, by more than 50% while simultaneously reducing data reduction times significantly. ANNs were used instead of the surface fitting methods, where first, the directional calibration coefficients related to the flow angles are calculated based on the pressure measurements, and then the flow angles are used as a set of the input parameters for the following ANNs to define Mach number and static and total pressure iteratively. In a second approach, novel calibration coefficients were used to directly relate the pressure measurements from five-hole probe to the quantities of interest thus, eliminating the need for iterative algorithms used in the conventional surface fitting methods. The advantageous features of this method are an average increase of less than 1% in the calibration uncertainty for flow angles and significant reduction of the data reduction times (few seconds). In addition, we confirmed the methodology to avoid over-fitting and under-fitting.

Machine Learning↗

Model reduction in integrated controls-structures design

It is the objective of this paper to present a model reduction technique developed for the integrated controls-structures design of flexible structures. Integrated controls-structures design problems are typically posed as nonlinear mathematical programming problems, where the design variables consist of both structural and control parameters. In the solution process, both structural and control design variables are constantly changing; therefore, the dynamic characteristics of the structure are also changing. This presents a problem in obtaining a reduced-order model for active control design and analysis which will be valid for all design points within the design space. In other words, the frequency and number of the significant modes of the structure (modes that should be included) may vary considerably throughout the design process. This is also true as the locations and/or masses of the sensors and actuators change. Moreover, since the number of design evaluations in the integrated design process could easily run into thousands, any feasible order-reduction method should not require model reduction analysis at every design iteration. In this paper a novel and efficient technique for model reduction in the integrated controls-structures design process, which addresses these issues, is presented.

Maghami, Peiman G.↗

Noise reduction of EBF propulsive-lift systems

In a recently completed program, static and wind tunnel measurements have been made of the basic noise, noise reduction, and performance characteristics of externally blown flap (EBF) propulsive-lift systems. The static tests were performed on an outdoor model rig. Noise evaluations were made for parameters such as basic system geometry, flap slot dimension variation, elimination of flap slots, sweep angle variation, passive flap trailing edge modifications, active (blowing) trailing edge modifications, and for an ejector/decayer exhaust system. The wind tunnel evaluation determined forward speed effects on EBF systems noise characteristics. The results from the experimental programs are discussed as to their application to full scale short haul aircraft.

Gibson, J. S.↗

Application of the aerodynamic energy concept to flutter suppression and gust alleviation by use of active controls

The effects of active controls on flutter suppression and gust alleviation of the Arava twin turboprop STOL transport and the Westwind twinjet business transport are investigated. The active control surfaces are introduced in pairs which include, in any chosen wing strip, a 20-percent chord leading-edge control and a 20-percent chord trailing-edge control. Each control surface is driven by a combined linear-rotational sensor system located on the activated strip. The control law is based on the concept of aerodynamic energy and utilizes previously optimized control law parameters based on two-dimensional aerodynamic theory. The best locations of the activated system along the span of the wing are determined for bending-moment alleviation, reduction in fuselage accelerations, and flutter suppression. The effectiveness of the activated system over a wide range of maximum control deflections is also determined. Two control laws are investigated. The first control law utilizes both rigid-body and elastic contributions of the motion. The second control law employs primarily the elastic contribution of the wing and leads to large increases in the activated control effectiveness as compared with the basic control law. The results indicate that flutter speed can be significantly increased (over 70 percent increase) and that the bending moment due to gust loading can be almost totally eliminated by a control system of about 10 to 20 percent span with reasonable control-surface rotations.

Nissim, E.↗

The Application of Recent Techniques in Flight Flutter Testing

The relative merits of sinusoidal excitation versus random atmospheric turbulence was investigated. The randomdec and autocorrelation methods were used to analyze data from a Learjet flight test. A parameter identification digital program, using least squares approach, was developed to determine the aeroelastic characteristics of a two mode system. The flight test program, computer program, and data reduction procedure is presented. Final results of the two modes of excitation obtained by Randomdec method are discussed.

Abla, M. A.↗

Preliminary test results of the joint FAA-USAF-NASA runway research program. Part 1: Traction measurements of several runways under wet and dry conditions with a Boeing 727, a diagonal-braked vehicle, and a mu-meter

The stopping distance, brake application velocity, and time of brake application were measured for two modern jet transports, along with the NASA diagonal-braked vehicle and the British Mu-Meter on several runways, which when wetted, cover the range of slipperiness likely to be encountered in the United States. Tests were designed to determine if correlation between the aircraft and friction measuring vehicles exists. The test procedure, data reduction techniques, and preliminary test results obtained with the Boeing 727, the Douglas DC-9, and the ground vehicles are given. Time histories of the aircraft test run parameters are included.

Horne, W. B.↗

Noise characteristics of upper surface blown configurations: Summary

A systematic experimental program was conducted to develop a data base for the noise and related flow characteristics of upper surface blown configurations. The effect of various geometric and flow parameters was investigated experimentally. The dominant noise was identified from the measured flow and noise characteristics to be generated downstream of the trailing edge. The possibilities of noise reduction techniques were explored. An upper surface blown (USB) noise prediction program was developed to calculate noise levels at any point and noise contours (footprints). Using this noise prediction program and a cruise performance data base, aircraft design studies were conducted to integrate low noise and good performance characteristics. A theory was developed for the noise from the highly sheared layer of a trailing edge wake. Theoretical results compare favorably with the measured noise of the USB model.

Reddy, N. N.↗

Trajectory-Estimation Error Analysis

Orbital and Geodetic Parameter Estimation Error Analysis Program (ORAN) is Bayesian least-squares simulation program for orbital trajectories. ORAN does not process data; rather, computes accuracy of results of data reduction if measurements are processed by minimum-variance data-reduction program. Actual data used to provide time when given measurement was available and estimated noise on that measurement.

Putney, B.↗

Stability analysis of a buck regulator employing input filter compensation

The interaction between the input filter and the regulator often causes serious degradation of performance. The reduction in loop gain due to input filter interaction can result in system instability. An exact stability analysis of the buck regulator system is presented. The input filter parameter values are varied and system instability is predicted for the case without feedforward. The eigenvalues of the system can be brought back into the unit circle and the system thus stabilized with the addition of the feedforward loop. Measurements made for the cases with and without feedforward confirm the analytical prediction.

Kelkar, S. S.↗

Venus Gravity: Global Field Results

The Pioneer Venus Orbiter has provided a vast amount of gravity data, since March 1979. High resolution results have revealed the high correlation between topography and gravity. These data were acquired at relatively low spacecraft altitudes (150 km) where atmospheric effects and high frequency variations were significant and modelling with global spherical harmonics was difficult. During 1982 data were acquired over a complete Venus rotation where the lowest altitudes were 1000 km or more, thus removing atmospherics and high frequency gravity effects. These data that have been reduced to produce a tenth degree and order spherical harmonic model of the global gravity field of Venus. The reduction technique used a least squares where 78 independent arcs of data were combined in a simultaneous inversion. The tenth degree and order gravity field solution has 117 parameters describing the spherical harmonic coefficients. This provides approximately 1800 km feature resolution. These coefficients are presented as a geoid map.

Mottinger, N. A.↗