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The metallographic characterization, analysis, and property measurement of ground samples for comparison with those processed on Skylab are described. Experiments on metals melting and exothermic brazing are summarized, and results are presented.
System of microwave instrumentation and data-processing equipment developed to enable ground-based calibration of microwave scanning-beam landing system (MSBLS) at distances of about 500 to 1,000 ft from MSBLS transmitting antenna. Ensures accuracy of MSBLS near touchdown point, without having to resort to expense and complex logistics of aircraft-based testing. Modified versions prove useful in calibrating aircraft instrument landing systems.
NASA has developed a set of 14 draft roadmaps to guide the development of space technologies under the leadership of the NASA Office of the Chief Technologist (OCT). Each of these roadmaps focuses on a particular technology area (TA). The roadmaps are intended to foster the development of advanced technologies and concepts that address NASA's needs and contribute to other aerospace and national needs. OCT requested that the National Research Council conduct a study to review the draft roadmaps, gather and assess relevant community input, and make recommendations and suggest priorities to inform NASA's decisions as it finalizes its roadmaps. The statement of task states that "based on the results of the community input and its own deliberations, the steering committee will prepare a brief interim report that addresses high-level issues associated with the roadmaps, such as the advisability of modifying the number or technical focus of the draft NASA roadmaps." This interim report, which does not include formal recommendations, addresses that one element of the study charge. NASA requested this interim report so that it would have the opportunity to make an early start in modifying the draft roadmaps based on feedback from the panels and steering committee. The final report will address all other tasks in the statement of task. In particular, the final report will include a prioritization of technologies, will describe in detail the prioritization process and criteria, and will include specific recommendations on a variety of topics, including many of the topics mentioned in this interim report. In developing both this interim report and the final report to come, the steering committee draws on the work of six study panels organized by technical area, loosely following the organization of the 14 roadmaps, as follows: A Panel 1: Propulsion and Power TA01 Launch Propulsion Systems TA02 In-Space Propulsion Technologies TA03 Space Power and Energy Storage Systems TA13 Ground and Launch Systems Processing B Panel 2: Robotics, Communications, and Navigation TA04 Robotics, TeleRobotics, and Autonomous Systems TA05 Communication and Navigation Systems C Panel 3: Instruments and Computing TA08 Science Instruments, Observatories, and Sensor Systems TA11 Modeling, Simulation, Information Technology, and Data Processing D Panel 4: Human Health and Surface Exploration TA06 Human Health, Life Support, and Habitation Systems TA07 Human Exploration Destination Systems E Panel 5: Materials Panel TA10 Nanotechnology TA12 Materials, Structures, Mechanical Systems, and Manufacturing TA14 Thermal Management Systems F Panel 6: Entry, Descent, and Landing Panel TA09 Entry, Descent, and Landing Systems In addition to drawing on the expertise represented on the steering committee and panels, the committee obtained input from each of 14 public workshops held on each of the 14 roadmaps. At these 1-day workshops, invited speakers, guests, and members of the public engaged in discussions on the different technology areas and their value to NASA. Broad community input was also solicited from a public website, where more than 240 public comments were received on the draft roadmaps in response to application of criteria (such as benefit, risk and reasonableness, and alignment with NASA and national goals) that the steering committee established. This interim report reflects the results of deliberations by the steering committee in light of these public inputs as well as additional inputs from the six panels. The steering committee's final report will be completed early in 2012. That report will prioritize the technologies that span the entire scope of the 14 roadmaps and provide additional guidance on crosscutting themes and other relevant topics.
Surveyor project composite telemetry processing system including signal processor, ground equipment, computer data program, etc
Abstract. Atmospheric aerosols affect the global energy budget by scattering and absorbing sunlight (direct effects) and by changing the microphysical structure, lifetime, and coverage of clouds (indirect effects). Both aerosol direct and indirect effects are affected by the vertical distribution of aerosols in the atmosphere, which is further influenced by a range of processes, such as aerosol dynamics, long-range transport, and entrainment. However, many observations of these processes are based on ground measurements, limiting our ability to understand the vertical distribution of aerosols and simulate their impact on clouds and climate. In this work, we examined the vertical heterogeneity of aerosols over the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) using data collected from the Holistic Interactions of Shallow Clouds, Aerosols and Land Ecosystems (HI-SCALE) campaign. The vertical profiles of meteorological and aerosol physiochemical properties up to 2500 m above are examined based on the 38 flights conducted during the HI-SCALE campaign. The aerosol properties over the SGP show strong vertical heterogeneity and seasonal variabilities. The aerosol concentrations at the surface are the highest due to strong emissions at ground level. In general, the mode diameter of aerosols during summer (∼ 100 nm) is larger than that during spring (∼ 30 nm), a result of enhanced condensational growth due to enriched volatile organic compounds in summer. The concentration of aerosols below 30 nm in the boundary layer (BL) (e.g., below 1000 m) during spring is higher than that during summer, a result of the stronger new particle formation (NPF) events due to the reduced condensation sink in spring. In the BL, the size of the aerosols gradually increases with altitude due to condensational growth and cloud processing. However, the chemical composition of the aerosols remained similar, with organics and sulfates representing 59.8 ± 2.2 % and 22.7 ± 2.1 %, respectively, of the total mass in the BL. Through the vertical profiles of aerosol properties, we observed NPF events in the upper BL during 7 out of 38 research flights, where the newly formed particles continue to grow as they are mixed down to the surface. There is also an indication that deep convection brings aerosols from the free troposphere (FT) to the surface, where they grow to contribute to the cloud condensation nuclei (CCN). Overall, the vertical heterogeneity of aerosols over the SGP is influenced by aerosol dynamics (new particle formation, growth, and cloud processing) and transport processes (mixing in the BL, long-range transport, entrainment, and convective downward transport). Case studies showing the influence of these factors are discussed.
An overview of synthetic aperture radar (SAR) technology is presented in vugraph form. The following topics are covered: an SAR ground data system; SAR signal processing algorithms; SAR correlator architectures; and current and future trends.
This paper offers a comprehensive view of flight system integration and test (I&T) lessons learned related to mishaps and close calls, focusing on what can be done to improve the I&T process to avoid recurrence. Specific areas within the realm of I&T that are covered in this paper include: I&T team communication and training; design of flight and ground systems for I&T; planning and scheduling; configuration management and process documentation; ground support equipment and tools; cleanrooms and contamination; mechanical integration, handling, and deployments; electrical integration and electrostatic discharge; functional testing and troubleshooting; environmental testing and facilities; and launch site operations. To illustrate "real-world" lessons learned for I&T, examples from throughout the history of the U.S. space program are presented. Also presented are some best practices for I&T that can help mitigate mishaps and close calls on the ground or during flight.
The 2017 Decadal Survey for Earth Science and Applications from Space (ESAS 2017) identifies a critical need for improving our understanding of Planetary Boundary Layer (PBL) processes and air-surface fluxes as well as why clouds, convection, and heavy precipitation occur when and where they do. Lidars are uniquely capable of collecting high precision and high spatio-temporal observations that have been used for atmospheric process studies from the ground, aircraft, and space. The wind lidar team at the NASA Langley Research Center (LaRC) started the development of Doppler wind lidar more than a decade ago to demonstrate technologies required for an Earth-orbiting system to globally measure wind profiles. Since then, an airborne Doppler Aerosol WiNd (DAWN) lidar system has been developed and participated in a series of field campaigns. The Doppler Aerosol WiNd (DAWN) lidar uses atmospheric aerosol motion to derive vertical profiles of horizontal wind speed and direction beneath the aircraft. In September 2022, DAWN, along with a suite of other instruments, was flown on a NASA DC-8 as part of The Convective Processes EXperiment – Cabo Verde (CPEX-CV) field campaign. A main objective of CPEX was to obtain a comprehensive set of temperature, humidity and, particularly, wind observations over tropical waters in undisturbed conditions, Saharan dust outbreaks, and in the vicinity of scattered through organized deep convection in all phases of the convective life cycle. DAWN collected data for approximately 90 hours across 13 CPEX-CV science flights. Airborne Vertical Atmospheric Profiling System (AVAPS) dropsondes were dropped throughout the flight for profiling the atmosphere and validating the DAWN instrument. DAWN had co-located data with 347 AVAPS NRD41 dropsondes, providing 32,117 vertical levels for a comprehensive validation of DAWN wind retrievals. DAWN showed very good agreement with dropsondes of ~0.2 m/s bias and ~1.8 m/s RMS. Given this agreement, DAWN is considered to be a worthy reference dataset, and its retrievals have been compared to winds derived from GOES Atmospheric Motion Vectors (AMVs), Advanced Scatterometer winds (ASCAT), and model data from GFS, GEOS, and MERRA-2 to better understand the quality of our current models and satellite wind observations. The proposed presentation will provide a brief description of the DAWN instrument, discuss the synergistic observations collected across a wide range of atmospheric conditions sampled during the CPEX-CV flights, and a summary of comparisons between DAWN, GOES AMV, ASCAT, and model analyses/predictions, with an emphasis on the PBL.
The development of the Sampling and Caching Subsystem (SCS) on the JPL Perseverance Rover lies at the intersection of testing, robotics, and geology. The SCS team established three primary system test campaigns and venues to aid in the development of SCS through verification and validation testing – Qualification Model Dirty Testing (QMDT) to provide a venue for testing in a Martian environment, Vehicle System Testbed (VSTB) for testing while integrated with the mobility subsystem on Martian-like terrain, and the Flight Software Testbed (FSWTB) for conducting tests using the flight motor controllers and software system on a hexapod which had the ability to simulate rover tilt. Each venue contributed a vital piece to the SCS building blocks. However, the QMDT venue operating within a 10-ft diameter Thermal Vacuum chamber to simulate Martian environment provided a sui generis opportunity to fine tune the entire sampling and caching process while building the team’s knowledge base about rock drillability, system life, and target selection. On Earth, because Martian rocks are not readily available, the development team must utilize geoanalogs to the rocks and regolith on Mars. Geologists on the team helped establish a set of standard rock types to use for Mars missions, like Basalt, Sandstone, Mudstone, Gypsum, and other related geoanalogs. These geoanalogs are characterized with a standard suite of tests for density, compressibility, and other characteristics to categorize potential drillability. This concept of drillability is what links the geoanalogs on Earth to the samples we collect on Mars. With the simulant characteristics defined, these geoanalog rocks are ready to be drilled into as we do on the Martian surface. A key aspect of interacting with the surface on Mars is rock target identification and selection. The Perseverance robotic system uses the on-board cameras, instrumentation, and software to collect enough information to identify potential scientific targets. With the targets identified, SCS can place the Corer and abrade the surface or collect a sample. For a ground test activity like QMDT, the test team did not have all of the camera and instrumentation systems that the rover does, so the team developed ground test equivalents to process a rock, build a target map, and define the target. The team constructed a Rock Scanning Station to build a 3D point cloud of the rock. This point cloud was then processed and evaluated with predefined and programmed criteria in a Target Downselect Tool. A primary output of the Target Downselect Tool is a defined target that can be uploaded directly to the robotic software system to simulate and build the robotic sequences used in tests. With these insights and programmatic definition of targets, the QMDT test team was able to make the same decisions that the Perseverance surface operations team does. In addition, valuable lessons learned from developing the target selection ground tools and using them were implemented into the tools used for surface operations.
This paper presents the results of uncertainty modeling of sonic boom noise generation from commercial supersonic transport considering the Spalart-Allmaras (SA) turbulence modeling parameters as well as Mach number, angle of attack and altitude. Sample generation and analysis for this uncertainty model was performed by UQPCE, which is a software package developed at the NASA Langley Research Center. To build the uncertainty model, 42 cases of sonic boom noise calculation were performed. Computation of the ground noise can be briefly summarized in two steps. First, the near field pressure waveforms are sampled from CFD calculation using the NASA Langley’s FUN3D solver. Second, this information is passed to an atmospheric propagation code, sBOOM, which solves an augmented Burger’s equation and simulates how the near field waveforms will change while passing through the atmosphere. The ground signature is further processed to obtain the perceived loudness, PLdB. Having a high spatial resolution near the shockwave in the CFD calculation is critical in sonic boom noise prediction. Because the variation in the input parameters for the current uncertainty quantification (UQ) study is likely to lead to change in shock location, angle and strength, the grid adaptation for shock capturing is independently applied for each condition. The final mesh used in the CFD calculation consists of approximately 420 million cells. The pressure signatures are sampled at three, four and five body lengths away from the aircraft to make sure the three dimensional effects around the aircraft are resolved. The results of the UQ analysis shows that within the three aleatory variables, the angle of attack had the most impact against ground noise, followed by the altitude and the Mach number. Between the two SA model parameters, the Kármán constant (𝜅) was significantly more important than the turbulent Prandtl number (𝜎), but these two parameters were only marginally significant in the overall prediction variance in ground noise. The UQ procedure explained in this paper can be widely applied to other model parameters.
This paper presents the results of uncertainty modeling of sonic boom noise generation from commercial supersonic transport considering the Spalart-Allmaras (SA) turbulence modeling parameters as well as Mach number, angle of attack and altitude. Sample generation and analysis for this uncertainty model was performed by UQPCE, which is a software package developed at the NASA Langley Research Center. To build the uncertainty model, 42 cases of sonic boom noise calculation were performed. Computation of the ground noise can be briefly summarized in two steps. First, the near field pressure waveforms are sampled from CFD calculation using the NASA Langley’s FUN3D solver. Second, this information is passed to an atmospheric propagation code, sBOOM, which solves an augmented Burger’s equation and simulates how the near field waveforms will change while passing through the atmosphere. The ground signature is further processed to obtain the perceived loudness, PLdB. Having a high spatial resolution near the shock wave in the CFD calculation is critical in sonic boom noise prediction. Because the variation in the input parameters for the current uncertainty quantification (UQ) study is likely to lead to change in shock location, angle and strength, the grid adaptation for shock capturing is independently applied for each condition. The final mesh used in the CFD calculation consists of approximately 420 million cells. The pressure signatures are sampled at three, four and five body lengths away from the aircraft to make sure the three dimensional effects around the aircraft are resolved. The results of the UQ analysis shows that within the three aleatory variables, the angle of attack had the most impact against ground noise, followed by the altitude and the Mach number. Between the two SA model parameters, the Kármán constant (𝜅) was significantly more important than the turbulent Prandtl number (𝜎), but these two parameters were only marginally significant in the overall prediction variance in ground noise. The UQ procedure explained in this paper can be widely applied to other model parameters.
To better understand the ground effect encountered by slender wing supersonic transport aircraft, a test was conducted at NASA Langley Research Center's 14 x 22 foot Subsonic Wind Tunnel in October, 1997. Emphasis was placed on improving the accuracy of the ground effect data by using a "dynamic" technique in which the model's vertical motion was varied automatically during wind-on testing. This report describes and evaluates different aspects of the dynamic method utilized for obtaining ground effect data in this test. The method for acquiring and processing time data from a dynamic ground effect wind tunnel test is outlined with details of the overall data acquisition system and software used for the data analysis. The removal of inertial loads due to sting motion and the support dynamics in the balance force and moment data measurements of the aerodynamic forces on the model is described. An evaluation of the results identifies problem areas providing recommendations for future experiments. Test results are validated by comparing test data for an elliptical wing planform with an Elliptical wing planform section with a NACA 0012 airfoil to results found in current literature. Major aerodynamic forces acting on the model in terms of lift curves for determining ground effect are presented. Comparisons of flight and wind tunnel data for the TU-144 are presented.
Primitive bodies (asteroids and comets), which have remained relatively unaltered since their formation, are important targets for scientific missions that seek to understand the evolution of the solar system. Often the first step is to fly by these bodies with robotic spacecraft. The key to maximizing data returns from these flybys is to determine the spacecraft trajectory relative to the target body-in short, navigate the spacecraft- with sufficient accuracy so that the target is guaranteed to be in the instruments' field of view. The most powerful navigation data in these scenarios are images taken by the spacecraft of the target against a known star field (onboard astrometry). Traditionally, the relative trajectory of the spacecraft must be estimated hours to days in advance using images collected by the spacecraft. This is because of (1)!the long round-trip light times between the spacecraft and the Earth and (2)!the time needed to downlink and process navigation data on the ground, make decisions based on the result, and build and uplink instrument pointing sequences from the results. The light time and processing time compromise navigation accuracy considerably, because there is not enough time to use more accurate data collected closer to the target-such data are more accurate because the angular capability of the onboard astrometry is essentially constant as the distance to the target decreases, resulting in better "plane-of- sky" knowledge of the target. Excellent examples of these timing limitations are high-speed comet encounters. Comets are difficult to observe up close; their orbits often limit scientists to brief, rapid flybys, and their coma further restricts viewers from seeing the nucleus in any detail, unless they can view the nucleus at close range. Comet nuclei details are typically discernable for much shorter durations than the roundtrip light time to Earth, so robotic spacecraft must be able to perform onboard navigation. This onboard navigation can be accomplished through a self- contained system that by eliminating light time restrictions dramatically improves the relative trajectory knowledge and control and subsequently increases the amount of quality data collected. Flybys are one-time events, so the system's underlying algorithms and software must be extremely robust. The autonomous software must also be able to cope with the unknown size, shape, and orientation of the previously unseen comet nucleus. Furthermore, algorithms must be reliable in the presence of imperfections and/or damage to onboard cameras accrued after many years of deep-space operations. The AutoNav operational flight software packages, developed by scientists at the Jet Propulsion Laboratory (JPL) under contract with NASA, meet all these requirements. They have been directly responsible for the successful encounters on all of NASA's close-up comet-imaging missions (see Figure !1). AutoNav is the only system to date that has autonomously tracked comet nuclei during encounters and performed autonomous interplanetary navigation. AutoNav has enabled five cometary flyby missions (Table!1) residing on four NASA spacecraft provided by three different spacecraft builders. Using this software, missions were able to process a combined total of nearly 1000 images previously unseen by humans. By eliminating the need to navigate spacecraft from Earth, the accuracy gained by AutoNav during flybys compared to ground-based navigation is about 1!order of magnitude in targeting and 2!orders of magnitude in time of flight. These benefits ensure that pointing errors do not compromise data gathered during flybys. In addition, these benefits can be applied to flybys of other solar system objects, flybys at much slower relative velocities, mosaic imaging campaigns, and other proximity activities (e.g., orbiting, hovering, and descent/ascent).
Meteorologists at NASA's Goddard Space Flight Center are conducting an extensive program of research in weather and climate related phenomena. This paper focuses on meteorological image processing applications directed toward gaining a detailed understanding of severe weather phenomena. In addition, the paper discusses the ground data handling and image processing systems used at the Goddard Space Flight Center to support severe weather research activities and describes three specific meteorological studies which utilized these facilities.
Lidars are uniquely capable of collecting high precision and high spatio-temporal observations that have been used for atmospheric process studies from the ground, aircraft, and space for over 30 years. The Atmospheric Dynamics Mission Aeolus (ADM-Aeolus), the first-ever spaceborne Doppler wind lidar, was developed by the European Space Agency and launched in August 2018. The ADM-Aeolus Atmospheric Laser Doppler Instrument (ALADIN) observes profiles of the component of the wind vector and aerosol optical properties along the instrument’s line-of-sight direction on a global scale. Two airborne lidar systems have been developed at NASA Langley Research Center in recent years that collect measurements in support of several NASA Earth Science Division focus areas. The Doppler Aerosol WiNd (DAWN) lidar measures vertical profiles of horizontal wind speed and direction. The High Altitude Lidar Observatory (HALO) measure high resolution profiles of atmospheric water vapor (WV) and aerosol and cloud optical properties. Though new space-based missions with advanced capabilities such as Aeolus are continuously being conceived and developed, there are limitations in terms of spatial and vertical detail and measurement precision that can be accomplished from space, thus airborne remote sensing observations like those from DAWN and HALO are required to fill these observational gaps as well as to calibrate and validate space-based measurements. Over a two-week period in April 2019 during their Aeolus Cal/Val Test Flight campaign, NASA conducted five research flights over the Eastern Pacific Ocean with the DC-8 aircraft to 1) demonstrate the DAWN Doppler wind lidar, HALO high spectral resolution lidar aerosol/cloud measurement and differential absorption lidar WV measurement capabilities across a range of atmospheric conditions, 2) demonstrate Aeolus Cal/Val flight strategies and compare DAWN and HALO measurements with Aeolus to gain an initial perspective of Aeolus performance, and 3) demonstrate how atmospheric dynamic processes can be resolved and better understood through simultaneous observations of wind, WV, and aerosol profile observations, coupled with numerical model and other remote sensing observations. This paper provides a brief description of the DAWN and HALO instruments, discusses the synergistic observations collected across a wide range of atmospheric conditions sampled during the DC-8 flights, and a summary of the validation of DAWN, HALO, and Aeolus observations and comparisons.
Earthquake source spectra provide unique insights into the earthquake rupture process. Motivated by previous research suggesting that complex fault geometries enhance high‐frequency seismic radiation, we study the influence of fault network geometry on earthquake source spectra using multiple independent observations. At regional scales, we examine correlations of stress drop measurements with surface fault trace misalignment in Southern California, Japan, and Central Italy. At a global scale, we examine correlations of moment‐rate function complexity of large earthquakes with focal mechanism variability, a proxy for local fault complexity. Despite significant scatter in the observations, we find overall consistent positive correlations. The concept that elastic interactions of discrete fault structures during the earthquake rupture process generates high‐frequency ground motions offers a coherent framework for interpreting our observations. These findings suggest that variations in fault complexity explain why some earthquakes produce stronger high‐frequency ground motions than others.
The Scintec MFAS Sodar (Multiple-Frequency Acoustic Sounder) is an autonomous, ground-based acoustic remote sensing system designed to measure vertical profiles of horizontal wind speed, wind direction, and vertical velocity in the lower atmosphere. The instrument transmits sequences of acoustic pulses and detects the Doppler-shifted sound waves backscattered by small-scale temperature and velocity fluctuations caused by atmospheric turbulence. From these Doppler shifts, the system derives three-dimensional wind vectors by combining radial velocities from multiple beam orientations.The MFAS Sodar operates with a first usable range gate beginning at approximately 30 m above ground level and a configurable vertical resolution of 10 m. Under favorable acoustic conditions, the system provides wind profiles extending up to 600 m above ground level. Measurements are processed into 15-minute averaged profiles containing wind speed, direction, vertical velocity, and diagnostic quantities such as signal-to-noise ratio and echo strength.This dataset was collected at the Argonne Testbed for Multiscale Observational Science (ATMOS) facility in Lemont, Illinois, as part of DOE's CROCUS Urban Integrated Field Laboratory (UIFL) initiative. The purpose of these observations is to characterize the vertical wind structure and boundary-layer evolution across the urban–suburban gradient of the greater Chicago region. In particular, these data are intended to improve understanding of how local meteorology, such as lake-breeze penetration, nocturnal jets, and daytime mixing, varies between the densely built urban core and the suburban periphery. The MFAS observations provide critical context for evaluating high-resolution model simulations and for integrating with complementary lidar, radar, and in-situ meteorological measurements within the broader CROCUS UIFL network.All data are archived in NetCDF (Network Common Data Form) format and include wind and diagnostic parameters. The files can be accessed and analyzed using standard software that supports NetCDF, such as Python (e.g., xarray, netCDF4), MATLAB, R (e.g., ncdf4, raster), or Panoply (NASA’s NetCDF visualization application).
Feedback integrating circuit with grounded capacitor for signal processing