OSIRIS-REx: Sample Return from Asteroid (101955) Bennu

In May of 2011, NASA selected the Origins, Spectral Interpretation, Resource Identification, and Security–Regolith Explorer (OSIRIS-REx) asteroid sample return mission as the third mission in the New Frontiers program. The other two New Frontiers missions are New Horizons, which explored Pluto during a flyby in July 2015 and is on its way for a flyby of Kuiper Belt object 2014 MU69 on January 1, 2019, and Juno, an orbiting mission that is studying the origin, evolution, and internal structure of Jupiter. The spacecraft departed for near-Earth asteroid (101955) Bennu aboard an United Launch Alliance Atlas V 411 evolved expendable launch vehicle at 7:05 p.m. EDT on September 8, 2016, on a seven-year journey to return samples from Bennu. The spacecraft is on an outbound-cruise trajectory that will result in a rendezvous with Bennu in November 2018. The science instruments on the spacecraft will survey Bennu to measure its physical, geological, and chemical properties, and the team will use these data to select a site on the surface to collect at least 60 g of asteroid regolith. The team will also analyze the remote-sensing data to perform a detailed study of the sample site for context, assess Bennu’s resource potential, refine estimates of its impact probability with Earth, and provide ground-truth data for the extensive astronomical data set collected on this asteroid. The spacecraft will leave Bennu in 2021 and return the sample to the Utah Test and Training Range (UTTR) on September 24, 2023.

     

Numerical prediction and wind tunnel experiment for a pitching unmanned combat air vehicle

The low-speed flowfield for a generic unmanned combat air vehicle (UCAV) is investigated both experimentally and numerically. A wind tunnel experiment was conducted with the Boeing 1301 UCAV at a variety of angles of attack up to 70 degrees, both statically and with various frequencies of pitch oscillation (0.5, 1.0, and 2.0 Hz). In addition, pitching was performed about three longitudinal locations on the configuration (the nose, 35% MAC, and the tail). Solutions to the unsteady, laminar, compressible Navier–Stokes equations were obtained on an unstructured mesh to match results from the static and dynamic experiments. The computational results are compared with experimental results for both static and pitching cases. Details about the flowfield, including vortex formation and interaction, are shown and discussed, including the non-linear aerodynamic characteristics of the vehicle.     

Intelligent sensing and classification in ad hoc networks: a case study

Wireless ad hoc networks have fundamentally altered today's battlefield, with applications ranging from unmanned air vehicles to randomly deployed sensor networks. Security and vulnerabilities in wireless ad hoc networks have been considered at different layers, and many attack strategies have been proposed, including denial of service (DoS) through the intelligent jamming of the most critical packet types of flows in a network. This investigates the effectiveness of intelligent jamming in wireless ad hoc networks using the Dynamic Source Routing (DSR) and TCP protocols and introduces an intelligent classifier to facilitate the jamming of such networks. Assuming encrypted packet headers and contents, our classifier is based solely on the observable characteristics of size, inter-arrival timing, and direction and classifies packets with up to "9.4% accuracy in our experiments.     

Experiences in accurately predicting time-dependent flows

As computational fluid dynamics matures, researchers attempt to perform numerical simulations on increasingly complex aerodynamic flows. One type of flow that has become feasible to simulate is massively separated flow fields, which exhibit high levels of flow unsteadiness. While traditional computational fluid dynamic approaches may be able to simulate these flows, it is not obvious what restrictions should be followed in order to insure that the numerical simulations are accurate and trustworthy. Our research group has considerable experience in computing massively separated flow fields about various aircraft configurations, which has led us to examine the factors necessary for making high-quality time-dependent flow computations. The factors we have identified include: grid density and local refinement, the numerical approach, performing a time-step study, the use of sub-iterations for temporal accuracy, the appropriate use of temporal damping, and the use of appropriate turbulence models. We have a variety of cases from which to draw results, including delta wings and the F-18C, F-16C, and F-16XL aircraft. Results show that while it is possible to obtain accurate unsteady aerodynamic computations, there is a high computational cost associated with performing the calculations. Rules of thumb and possible shortcuts for accurate prediction of massively separated flows are also discussed.     

Performance analysis of conformal conical arrays for airborne vehicles

Conformal array apertures have great potential for providing high performance, low weight systems with little or no impact to the aerodynamic design of the air vehicle. A performance analysis of conformal conical arrays for a national airborne radar application is presented. The conical array geometry is chosen for its similarity to an aircraft or missile nosecone. Performance capabilities are analyzed for a number of antenna performance parameters including scan volume, sidelobe levels, grating lobes, beamwidth, directivity, element count, and cross-polarization     

Laboratory Evaluation Unit for the Automatic Calibration System

Automatic calibration denotes a system of computer-controlled self-calibrating electrical measurements. Its purpose is to minimize the calibration support required for electrical measurements in maintenance or check-out applications. The system utilizes techniques whereby all electrical measurements are automatically reduced to and expressed in terms of several basic standards. Measurement data are transmitted to a digital computer for computation of the value of the unknown parameter. Automatic self-calibration procedures are carried out just before unknown inputs are measured. Development of instrumentation known as the automatic calibration program, laboratory evaluation unit has been accomplished. This unit automatically measures and calibrates a wide range of the most common dc and low-frequency electrical parameters. Only three single valued, certified standards are included: a 1-V cell, a 1-? resistor, and a 1-MHz oscillator.     

The Biasing Effect of Random Bit Errors on Binary Telemetry Data

Random bit errors that occur in PCM data during the various phases of the telemetry-data-processing system will not only add a component of mean square error to the experimental data but will also bias it. This paper derives a formula for the bias and describes some of the characteristics of the bias.     

Software approach to access UWB interference on GPS receivers

Ever since the FCC approved the use of UWB devices in commercial and federal bands, various agencies whose operations and/or products rely on the integrity of signals within certain "restricted" radio frequency bands have voiced concerns over the potential impact of the UWB interference. GPS signals are among these "restricted" bands. Several groups in the GPS community have conducted experimental studies concerning the impact of UWB interference on the performance of various grades of commercial and aviation GPS receivers. In this paper, we present a software approach to simulate and evaluate UWB interference on GPS receivers. The software approach provides greater flexibility in the design of testing scenarios, such as the inclusion of a large number of aggregated UWB devices, the generation of new UWB signals and modulation schemes, and the possibility of extending the study to new GPS signals. The paper discusses a general framework for developing algorithms to evaluate UWB and GPS interference under a wide variety of hardware and software conditions. This framework consists of three classes of components: input, processing, and analysis. The input components are responsible for the generation of UWB signal waveforms and modulation schemes, and GPS signals. The processing components include a simulated model of GPS RF front end and software implementation of GPS processing blocks, such as acquisition, tracking, and post-processing. The analysis components focus on the study of specific receiver processing component outputs. Both real and simulated UWB signals can be used in the study. The real UWB signals are primarily used to validate the simulation procedure, whereas the simulated UWB signals are used to allow the immediate incorporation of new UWB waveforms and modulations in the evaluations. This paper presents details of the software components developed and the preliminary results achieved     

Neural network development for the forecasting of upper atmosphere parameter distributions

This paper presents a neural network modeling approach to forecast electron concentration distributions in the 150–600 km altitude range above Arecibo, Puerto Rico. The neural network was trained using incoherent scatter radar data collected at the Arecibo Observatory during the past two decades, as well as the Kp geomagnetic index provided by the National Space Science Data Center. The data set covered nearly two solar cycles, allowing the neural network to model daily, seasonal, and solar cycle variations of upper atmospheric parameter distributions. Two types of neural network architectures, feedforward and Elman recurrent, are used in this study. Topics discussed include the network design, training strategy, data analysis, as well as preliminary testing results of the networks on electron concentration distributions.