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Sampling darts and launching apparatus built to collect particles in vertical plume of hot gas. In original application, hot gas plume is rocket-engine exhaust during test firing. Dart passes made at various heights, depending on launch angle and launch-gas pressure. Adaptable to variety of terrestrial uses like research on particulate emissions of volcanoes or determining origin of building fire while still burning.
The University of Denver Aerosol Group proposed to adapt an impactor system for the collection of particles emitted by aircraft. The collection substrates were electron microscope grids which were analyzed by Dr. Pat Sheridan using a transmission electron microscope. The impactor was flown in the SNIFF behind aircraft and engine emissions were sampled. This report details the results of that work.
Proposals for continuing the search for extant life on Mars are primarily predicated on the assumption that specialized environmental niches that could support a biota may exist on the planet. Before attempting any critical tests for extant organisms, either in situ or on returned samples, it is imperative to determine whether any such sites actually exist. If, through remote sensing and landed instrumentation, sites of potential biological interest are discovered and characterized, biological tests can then more effectively be planned to elicit the presence of organisms that are adapted to living in these particular environments.
NASA has funded a project called the Hunt for Observable Signatures of Terrestrial Systems (HOSTS) to survey nearby solar type stars to determine the amount of warm zodiacal dust in their habitable zones. The goal is not only to determine the luminosity distribution function but also to know which individual stars have the least amount of zodiacal dust. It is important to have this information for future missions that directly image exoplanets as this dust is the main source of astrophysical noise for them. The HOSTS project utilizes the Large Binocular Telescope Interferometer (LBTI), which consists of two 8.4-m apertures separated by a 14.4-m baseline on Mt. Graham, Arizona. The LBTI operates in a nulling mode in the mid-infrared spectral window (8-13 micrometers), in which light from the two telescopes is coherently combined with a 180 degree phase shift between them, producing a dark fringe at the location of the target star. In doing so the starlight is greatly reduced, increasing the contrast, analogous to a coronagraph operating at shorter wavelengths. The LBTI is a unique instrument, having only three warm reflections before the starlight reaches cold mirrors, giving it the best photometric sensitivity of any interferometer operating in the mid-infrared. It also has a superb Adaptive Optics (AO) system giving it Strehl ratios greater than 98% at 10 micrometers. In 2014 into early 2015 LBTI was undergoing commissioning. The HOSTS. project team passed its Operational Readiness Review (ORR) in April 2015. The team recently published papers on the target sample, modeling of the nulled disk images, and initial results such as the detection of warm dust around eta Corvi. Recently a paper was published on the data pipeline and on-sky performance. An additional paper is in preparation on Beta Leo. We will discuss the scientific and programmatic context for the LBTI project, and we will report recent progress, new results, and plans for the science verification phase that started in February 2016, and for the survey.
We have designed a cubic spline wavelet decomposition for the Sobolev space H(sup 2)(sub 0)(I) where I is a bounded interval. Based on a special 'point-wise orthogonality' of the wavelet basis functions, a fast Discrete Wavelet Transform (DWT) is constructed. This DWT transform will map discrete samples of a function to its wavelet expansion coefficients in O(N log N) operations. Using this transform, we propose a collocation method for the initial value boundary problem of nonlinear PDE's. Then, we test the efficiency of the DWT transform and apply the collocation method to solve linear and nonlinear PDE's.
Drilling deep into the subsurface of planetary bodies in the Solar System for samples acquisition enables critical capabilities for future NASA exploration missions in its quest to understand the origins of the Solar System and potentially the search for life. Such planetary bodies as Mars and Europa are key targets for potential missions that would require reaching great depths. Performing drilling while using minimal mass/volume systems and with low energy consumption are the main requirements that are imposed on such technologies. A wireline deep drill, called Auto-Gopher-2, is currently being developed as a joint effort between JPL and Honeybee Robotics Ltd. The Auto-Gopher II is a wireline rotary piezo-percussive deep drilling mechanism that combines formation breaking by rotating and piezoelectric actuator hammering and cuttings removal by rotating a fluted bit. The hammering mechanism is based on the Ultrasonic/Sonic Drill/Corer (USDC) mechanism that has been developed as an adaptable tool for many drilling and coring applications. The USDC uses an intermediate ball-shape free-mass to transform high frequency vibrations of a piezoelectric transducer horn tip into sonic hammering of the drill bit. The lessons learned from the previous studies are being implemented into the development of the Auto-Gopher-II, an autonomous deep wireline drill with integrated cuttings and sample management and drive electronics. Subsystems of the wireline drill are being developed in parallel at JPL and Honeybee Robotics, Ltd. Issues related to the bit and its ability to retain the cuttings for caching and removal are currently being addressed. This paper presents the development efforts of the piezoelectric actuator, cuttings removal and retention flutes and drive electronics.
Two full-scale passive Earth Entry Vehicles (EEV) with realistic structure, surrogate sample container, and surrogate Thermal Protection System (TPS) were built at NASA Langley Research Center (LaRC) and tested at the Utah Test and Training Range (UTTR). The main test objective was to demonstrate structural integrity and investigate possible impact response deviations of the realistic vehicle as compared to rigid penetrometer responses. With the exception of the surrogate TPS and minor structural differences in the back shell construction, the two test vehicles were identical in geometry and both utilized the Integrated Composite Stiffener Structure (ICoSS) structural concept in the forward shell. The ICoSS concept is a lightweight and highly adaptable composite concept developed at NASA LaRC specifically for entry vehicle TPS carrier structures. The instrumented test vehicles were released from a helicopter approximately 400 m above ground. The drop height was selected such that at least 98% of the vehicles terminal velocity would be achieved. While drop tests of spherical penetrometers and a low fidelity aerodynamic EEV model were conducted at UTTR in 1998 and 2000, this was the first time a passive EEV with flight-like structure, surrogate TPS, and sample container was tested at UTTR for the purpose of complete structural system validation. Test results showed that at a landing vertical speed of approximately 30 m/s, the test vehicle maintained structural integrity and enough rigidity to penetrate the sandy clay surface thus attenuating the landing load, as measured at the vehicle CG, to less than 600 g. This measured deceleration was found to be in family with rigid penetrometer test data from the 1998 and 2000 test campaigns. Design implications of vehicle structure/soil interaction with respect to sample container and sample survivability are briefly discussed.
Optimal experimental design is a classic topic in statistics, with many well-studied problems, applications, and solutions. The design problem we study is the placement of sensors to monitor spatiotemporal processes, explicitly accounting for the temporal dimension in our modeling and optimization. We observe that recent advancements in computational sciences often yield large datasets based on physics-based simulations, which are rarely leveraged in experimental design. We introduce a novel model-based sensor placement criterion, along with a highly-efficient optimization algorithm, which integrates physics-based simulations and Bayesian experimental design principles to identify sensor networks that “minimize information loss” from simulated data. Our technique relies on sparse variational inference and (separable) Gauss-Markov priors, and thus may adapt many techniques from Bayesian experimental design. We validate our method through a case study monitoring air temperature in Phoenix, Arizona, using state-of-the-art physics-based simulations. Our results show our framework to be superior to random or quasi-random sampling, particularly with a limited number of sensors. We conclude by discussing practical considerations and implications of our framework, including more complex modeling tools and real-world deployments.
Identical Bennett radio-frequency ion mass spectrometer instruments on the Pioneer Venus Bus and Orbiter have provided the first in-situ measurements of the detailed composition of the planet's ionosphere. The sensitivity, resolution, and dynamic range are sufficient to provide measurements of the solar-wind-induced bow-shock, the ionopause, and highly structured distributions of up to 16 thermal ion species within the ionosphere. The use of adaptive scan and detection circuits and servo-controlled logic for ion mass and energy analysis permits detection of ion concentrations as low as 5 ions/cu cm and ion flow velocities as large as 9 km/sec for O(+). A variety of commandable modes provides ion sampling rates ranging from 0.1 to 1.6 sec between measurements of a single constituent. A lightweight sensor and electronics housing are features of a compact instrument package.
A proposed first generation human interface control panel is described which will be used to control SKITTER, a three-legged lunar walking machine. Under development at Georgia Tech, SKITTER will be a multi-purpose, un-manned vehicle capable of preparing a site for the proposed lunar base in advance of the arrival of men. This walking machine will be able to accept modular special purpose tools, such as a crane, a core sampling drill, and a digging device, among others. The project was concerned with the design of a human interface which could be used, from earth, to control the movements of SKITTER on the lunar surface. Preliminary inquiries were also made into necessary modifications required to adapt the panel to both a shirt-sleeve lunar environment and to a mobile unit which could be used by a man in a space suit at a lunar work site.
A theory has been developed at the University of Virginia which explains the effects of including an ideal predictor in the forward loop of a linear error-sampled system. It has been shown that the presence of this ideal predictor tends to stabilize the class of systems considered. A prediction controller is merely a system which anticipates a signal or part of a signal before it actually occurs. It is understood that an exact prediction controller is physically unrealizable. However, in systems where the input tends to be repetitive or limited, (i.e., not random) near ideal prediction is possible. In order for the controller to act as a stability compensator, the predictor must be designed in a way that allows it to learn the expected error response of the system. In this way, an unstable system will become stable by including the predicted error in the system transfer function. Previous and current prediction controller include pattern recognition developments and fast-time simulation which are applicable to the analysis of linear sampled data type systems. The use of pattern recognition techniques, along with a template matching scheme, has been proposed as one realizable type of near-ideal prediction. Since many, if not most, systems are repeatedly subjected to similar inputs, it was proposed that an adaptive mechanism be used to 'learn' the correct predicted error response. Once the system has learned the response of all the expected inputs, it is necessary only to recognize the type of input with a template matching mechanism and then to use the correct predicted error to drive the system. Suggested here is an alternate approach to the realization of a near-ideal error prediction controller, one designed using Neural Networks. Neural Networks are good at recognizing patterns such as system responses, and the back-propagation architecture makes use of a template matching scheme. In using this type of error prediction, it is assumed that the system error responses be known for a particular input and modeled plant. These responses are used in the error prediction controller. An analysis was done on the general dynamic behavior that results from including a digital error predictor in a control loop and these were compared to those including the near-ideal Neural Network error predictor. This analysis was done for a second and third order system.
G-TAG is a software tool for the multibody simulation of a spacecraft with a robotic arm and a sampling mechanism, which performs a touch-and-go (TAG) maneuver for sampling from the surface of a small celestial body. G-TAG utilizes G-DYN, a multi-body simulation engine described in the previous article, and interfaces to controllers, estimators, and environmental forces that affect the spacecraft. G-TAG can easily be adapted for the analysis of the mission stress cases to support the design of a TAG system, as well as for comprehensive Monte Carlo simulations to analyze and evaluate a particular TAG system design. Any future small-body mission will benefit from using G-TAG, which has already been extensively used in Comet Odyssey and Galahad Asteroid New Frontiers proposals.
Fundamental to many of NASA's in-space transportation missions is the capture and handling of various objects and vehicles in various orbits for servicing, debris disposal, sample retrieval, and assembly without the benefit of sufficient grapple fixtures and docking ports. To perform similar material handling tasks on Earth, pincher grippers, suction grippers, or magnetic chucks are used, but are unable to reliably grip aluminum and composite spacecraft, insulation, radiators, solar arrays, or extra-terrestrial objects in the vacuum of outer space without dedicated handles in the right places. The electronic Flexible Electrostatic Technologies for space Capture and Handling (FETCH) will enable reliable and compliant gripping (soft dock) of practically any object in various orbits or surfaces without dedicated mechanical features, very low impact capture, and built-in proximity sensing without any conventional actuators. Originally developed to handle semiconductor and glass wafers during vacuum chamber processing without contamination, the normal rigid wafer handling chucks are replaced with thin metal foil segments laminated in flexible insulation driven by commercial off-the-shelf solid state, high-voltage power supplies. Preliminary testing in NASA Marshall Space Flight Center's (MSFC's) Flat Floor Robotics Lab demonstrated compliant alignment and gripping with a full-sized, 150-lb microsat mockup and translation before a clean release with a flip of a switch. The flexible electrostatic gripper pads can be adapted to various space applications with different sizes, shapes, and foil electrode layouts even with openings through the gripper pads for addition of guidance sensors or injection of permanent adhesives. With gripping forces estimated between 0.5 and 2.5 lb/in2 or 70-300 lb/ft2 of surface contact, the FETCH can turn on and off rapidly and repeatedly to enable sample handling, soft docking, in-space assembly, precision relocation, and surface translation for accurate anchoring.
Here, we adapt the minima hopping method (MHM) to the problem of interfacial structure prediction and apply it to study a canonical problem, the tilt grain boundaries in SrTiO 3 . Our method employs a hybrid approach by first exploring the potential energy surface (PES) of different grain boundary samplings with an empirical force field, among which the fifteen candidates with lower energies are then refined using ab initio density functional theory (DFT) calculations. During the exploratory stage, we bias the search using a local order parameter to primarily sample various reconstructions in the vicinity of the interface, while preserving the crystallinity of the bulk regions. We further enhance the search by incorporating initial structures with rigid body displacements to account for translational variations between bulk phases, enabling the MHM to effectively generate both stoichiometric and nonstoichiometric SrTiO 3 Σ3(111)[110] and Σ3(112)[110] grain boundaries. From an algorithmic standpoint, MHM outperforms earlier studies based on genetic algorithms (GA) by identifying more stable interfacial structures of several SrTiO 3 grain boundaries. The performance of the present implementation of the MHM approach is primarily limited by exploring an approximate description of the PES with a rather simple Buckingham potential. This limitation leads to variations in performance when compared to approaches utilizing more advanced surrogate PES models, such as direct DFT-PES sampling or GA with the embedded atom method (EAM). Despite the present limitations, the MHM approach is able to yield interfacial structures with comparable or lower interfacial energies in specific cases, such as Σ3(111)[110] Γ=1, ±0.5 and Σ3(112)[110] Γ= ±1, −2, underscoring the robustness of the MHM approach even with a simple approximation of the DFT PES. The MHM interfacial structure prediction method thus offers an efficient approach to understanding the grain boundaries and heterointerfaces at the atomic scale, providing an important prerequisite for effective materials design.
In a collaborative effort between the FAA and NASA, a simulation was conducted to look at the issues involved with flying a large, widebody aircraft in the terminal area using MLS-RNAV procedures. A variety of approach paths, departure paths, and holding patterns were investigated during the course of the study, which included the participation of subject pilots. The simulation made use of paths designed by the FAA Office of Aviation Standards and employed Langley's Visual Motion Simulator (VMS) for their execution. Data obtained from this simulation will be used to support the joint FAA/USAF MLS flight test and demonstration project. This paper describes the flight simulation facility adapted to model terminal area maneuvers for jet transport aircraft using the Microwave Landing System (MLS). A description of the overall project will be presented first, along with a discussion of the guidance schemes used, followed by a description of the simulation hardware and software. A sample of the resulting data will also be presented.
Three strategies for adaptive control of cooperative dual-arm robots are described. In the position-position control strategy, the adaptive controllers ensure that the end-effector positions of both arms track desired trajectories in Cartesian space despite unknown time-varying interaction forces exerted through the load. In the position-hybrid control strategy, the adaptive controller of one arm controls end-effector motions in the free directions and applied forces in the constraint directions, while the adaptive controller of the other arm ensures that the end-effector tracks desired position trajectories. In the hybrid-hybrid control strategy, the adaptive controllers ensure that both end-effectors track reference position trajectories while simultaneously applying desired forces on the load. In all three control strategies, the cross-coupling effects between the arms are treated as disturbances which are rejected by the adaptive controllers while following desired commands in a common frame of reference. The adaptive controllers do not require the complex mathematical model of the arm dynamics or any knowledge of the arm dynamic parameters or the load parameters such as mass and stiffness. The controllers have simple structures and are computationally fast for on-line implementation with high sampling rates.
The principles and operation of MMAX, a symbolic-computation program which automates the process of generating property matrices for structural materials, are briefly described and illustrated with sample analyses of a rubberlike material and an elastoplastic material. MMAX is written in LISP under the symbolic finite-element generator FINGER and the general symbolic manipulator MACSYMA; it first derives the formulas required by mathematical manipulation, and then translates the formulas into FORTRAN code, adapted to the particular type of machine to be used for the numerical calculations. This approach is shown to combine efficiently the advantages of symbolic and numerical computation for engineering applications.
Nine preflight variables related to fluid, electrolyte, and cardiovascular status from 64 first-time Shuttle crewmembers were differentially weighted by discrimination analysis to predict the incidence and severity of each crewmember's space sickness as rated by NASA flight surgeons. The nine variables are serum uric acid, red cell count, environmental temperature at the launch site, serum phosphate, urine osmolality, serum thyroxine, sitting systolic blood pressure, calculated blood volume, and serum chloride. Using two methods of cross-validation on the original samples (jackknife and a stratefied random subsample), these variables enable the prediction of space sickness incidence (NONE or SICK) with 80 percent sickness and space severity (NONE, MILD, MODERATE, of SEVERE) with 59 percent success by one method of cross-validation and 67 percent by another method. Addition of a tenth variable, hours spent in the Weightlessness Environment Training Facility (WETF) did not improve the prediction of space sickness incidences but did improve the prediction of space sickness severity to 66 percent success by the first method of cross-validation of original samples and to 71 percent by the second method. Results to date suggest the presence of predisposing physiologic factors to space sickness that implicate fluid shift etiology. The data also suggest that prior exposure to fluid shift during WETF training may produce some circulatory pre-adaption to fluid shifts in weightlessness that results in a reduction of space sickness severity.