Technology, Data Bases and System Analysis for Space-to-Ground Optical Communications
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Six astronauts on the Shuttle Transport System (STS) participated in an investigation on the pharmacokinetics of promethazine (PMZ), a medication used for the treatment of space motion sickness (SMS) during flight. Each crewmember completed the protocol once during flight and repeated thirty days after returned to Earth. Saliva samples were collected at scheduled times for 72 h after PMZ administration; more frequent samples were collected on the ground than during flight owing to schedule constraints in flight. PMZ concentrations in saliva were determined by a liquid chromatographic/mass spectrometric (LC-MS) assay and pharmacokinetic parameters (PKPs) were calculated using actual flight and ground-based data sets and using time-matched sampling schedule on ground to that during flight. Volume of distribution (V(sub c)) and clearance (Cl(sub s),) decreased during flight compared to that from time-matched ground data set; however, Cl(sub s) and V(sub c) estimates were higher for all subjects when partial ground data sets were used for analysis. Area under the curve (AUC) normalized with administered dose was similar in flight and partial ground data; however AUC was significantly lower using time-matched sampling compared with the full data set on ground. Half life (t(sub 1/2)) was longest during flight, shorter with matched-sampling schedule on ground and shortest when complete data set from ground was used. Maximum concentration (C(sub max)), time for C(sub max), (t(sub max)), parameters of drug absorption, depicted a similar trend with lowest and longest respectively, during flight, lower with time-matched ground data and highest and shortest with full ground data.
New system requirements pertaining to thermal optical properties and coating electrical properties are commonly specified on non-low earth orbit missions. An increasing number of projects are specifying coatings with a surface resistivity of less than lE-9 ohm/square to mitigate electrostatic charge buildup events over a range of operational temperatures. There are a limited number of coatings that. meet these electrical property requirements while having flight derived optical properties in representative environments. Goddard Space Flight Center Code 546, Contamination and Thermal Coatings Group has recently explored the variety of electrically conductive white coatings available through domestic vendors to evaluate properties to meet project requirements in a geostationary orbit. The lack of significant flight data in representative environments required the careful selection of samples in ground based tests to establish end of life thermal properties. Attention must be given to the origin and pedigree of samples used on past on-orbit experiments to insure that the present formulations for the materials are similar and will react in similar manner.
We seek to combine high-resolution remotely sensed data with models and ground truth measurements, in the context of a Geographical Information System, integrated with specialized image processing software. We will use this integrated system to analyze the data from two Case Studies, one at a bore Al forest site, the other a tropical forest site. We will assess the information content of the different components of the data, determine the optimum data combinations to study biogeophysical changes in the forest, assess the best way to visualize the results, and validate the models for the forest response to different radar wavelengths/polarizations. During the 1990's, unprecedented amounts of high-resolution images from space of the Earth's surface will become available to the applications scientist from the LANDSAT/TM series, European and Japanese ERS-1 satellites, RADARSAT and SIR-C missions. When the Earth Observation Systems (EOS) program is operational, the amount of data available for a particular site can only increase. The interdisciplinary scientist, seeking to use data from various sensors to study his site of interest, may be faced with massive difficulties in manipulating such large data sets, assessing their information content, determining the optimum combinations of data to study a particular parameter, visualizing his results and validating his model of the surface. The techniques to deal with these problems are also needed to support the analysis of data from NASA's current program of Multi-sensor Airborne Campaigns, which will also generate large volumes of data. In the Case Studies outlined in this proposal, we will have somewhat unique data sets. For the Bonanza Creek Experimental Forest (Case I) calibrated DC-8 SAR data and extensive ground truth measurement are already at our disposal. The data set shows documented evidence to temporal change. The Belize Forest Experiment (Case II) will produce calibrated DC-8 SAR and AVIRIS data, together with extensive measurements on the tropical rain forest itself. The extreme range of these sites, one an Arctic forest, the other a tropical rain forest, has been deliberately chosen to find common problems which can lead to generalized observations and unique problems with data which raise issues for the EOS System.
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We present the analysis of the event OGLE-2017-BLG-1186 from the 2017 Spitzer microlensing campaign. This is a remarkable microlensing event because its source is photometrically bright and variable, which makes it possible to perform an asteroseismic analysis using ground-based data. We find that the source star is an oscillating red giant with average timescale of ∼9 d. The asteroseismic analysis also provides us source properties including the source angular size (∼27 μas) and distance (∼11.5 kpc), which are essential for inferring the properties of the lens. When fitting the light curve, we test the feasibility of Gaussian processes (GPs) in handling the correlated noise caused by the variable source. We find that the parameters from the GP model are generally more loosely constrained than those from the traditional χ(exp 2) minimization method. We note that this event is the first microlensing system for which asteroseismology and GPs have been used to account for the variable source. With both finite-source effect and microlens parallax measured, we find that the lens is likely a ∼0.045 Mʘ brown dwarf at distance ∼9.0 kpc, or a ∼0.073 Mʘ ultracool dwarf at distance ∼9.8 kpc. Combining the estimated lens properties with a Bayesian analysis using a Galactic model, we find a ∼ 35 per cent probability for the lens to be a bulge object and ∼ 65 per cent to be a background disc object.
The MSS and TM sensor performances were evaluated by studying both the sensors and the characteristics of the data. Information content analysis, image statistics, band-to-band registration, the presence of failed or failing detectors, and sensor resolution are discussed. The TM data were explored from the point of view of adequacy of the ground processing and improvements that could be made to compensate for sensor problems and deficiencies. Radiometric correction processing, compensation for a failed detector, and geometric correction processing are also considered.
A post flight solar illumination data package was created by the LDEF thermal analysis data group in support of the LDEF science office data group. The data presented was prepared with the Thermal Radiation Analysis System (TRASYS) program. Ground tracking data was used to calculate daily orbital beta angles for the calculation of resultant fluxes. This data package will be useful in calculation of solar illumination fluent for a variety of beta angle orbital conditions encountered during the LDEF mission.
Introduction: Artificial intelligence (AI) has long been considered a potential mechanism to explore increasingly challenging environments, including those with extreme temperatures and pressures, limited communication capabilities, or those with demanding terrain. We posit that missions in extreme environments could deploy an onboard AI focused on science observations and goals in order to augment a traditional concept(s) of operations (ConOps). An onboard AI capability could perform functions such as data analysis in order to make high-level decisions, including prioritized data transmission for analysis by ground-based teams or autonomously-guided follow-on analyses that maximize science return. Such a capability would empower missions to respond to scientific data of interest in real-time; a mission could make observations and perform a preliminary analysis to alert ground-based scientists to an observation of interest, enabling an informed, rapid response from Earth-based teams. Enceladus Case Study for Onboard AI: We are developing an onboard AI capability for real-time telemetry response that formulates and carries-out informed decisions in service to established mission goals, enabling increased science return of a mission. We focus our AI development for use on a constellation of SmallSats orbiting Enceladus. Our Enceladus case study tests autonomous decision-making capabilities in scenarios with complex orbital dynamics, plume ejecta, extreme cold environments, power restrictions, and a requirement to maximize science return for a potential positive detection of life, while critically evaluating the potential for false positives. Telemetry includes simulated scientific data, spacecraft onboard operational data (e.g., position, velocity, and rotation), and engineering hardware performance data. Enceladus SmallSat Constellation. Our constellation includes eight SmallSat spacecraft in an 8:35 resonant orbit-based formation, leveraging Saturn’s gravitational forces to maintain stable orbits with global coverage around Enceladus. To our knowledge, we simulate the first stable configuration of multiple spacecraft in closed orbits around Enceladus, using a full ephemeris force model (Russell and Lara, 2009). Each spacecraft’s orbit will precess, causing an eastward ground track shift (from an orbiter’s perspective) of each spacecraft for each orbit. However, all spacecraft return to their original positions relative to Enceladus after eight Enceladus revolutions around Saturn. We model communication pathways between SmallSats to understand how information would need to be transmitted across the constellation to enable AI-driven decision-making and resource allocation across the fleet. Capability Demonstration. Our simulated capability demonstration inputs position, velocity, and rotation telemetry from our Enceladus-focused constellation simulations, and mass spectrometry data collected from abiotic and biotic laboratory-analog ocean world experiments (Theiling et al., 2018; Theiling, 2021; Da Poian et al., 2023). Data from these experiments are used to simulate MS measurements and different scenarios of science observations for onboard analysis performed on each of the eight spacecraft. For these demonstrations, we integrate 24 machine learning (ML) algorithms into an onboard intelligence as a ‘knowledge base’, including algorithms evaluating data quality and those predicting (with % confidence) gas composition, ocean aqueous chemistry, and whether the sample was influenced by microbial life. The onboard AI capability is designed to use the knowledge base to come to a consensus-based decision in the interpretation of the observed data in order to request additional action outside of a pre-defined ConOps. Requested actions could include e.g., prioritized downlink to Earth (for analysis by ground-based teams) or follow-on analyses performed across the constellation. The spacecraft’s intelligent onboard planner must then determine whether sufficient resources (e.g., time, power, etc.) are available and weigh the request with mission priorities. In our simulation, the constellation is able to identify potential biosignatures using onboard ML algorithms, evaluate the confidence of that prediction, and perform follow-on analyses across the fleet to confirm the detection, in order to best prepare a transmission of these data to Earth-based teams.
This is the second annual performance report for our grant "Membership and Coronal Activity in the NGC 2232 and Cr 140 Open Clusters." We propose to identify X-ray sources and extract net source counts in 8 archival ROSAT HRI images in the regions of the NGC 2232 and Cr 140 open clusters. These X-ray data will be combined with ground-based photometry and spectroscopy in order to identify G, K, and early-M type cluster members. At present, no members later than approximately F5 are currently known for either cluster. With ages of approximately 25 Myr and at a distance of just 320 - 360 pc, the combined late-type membership of the NGC 2232 and Cr 140 clusters will yield an almost unique sample of solar-type stars in the post-T Tauri/pre-main sequence phase of evolution. These stars will be used to assess the level and dispersion in coronal activity levels, as part of a probe of the importance of magnetic braking and the level of magnetic dynamo activity, for solar-type stars just before they reach the ZAMS. Over the past year we have successfully acquired all of the ground-based data necessary to support the analysis of the archival ROSAT X-ray data in the regions around both of these clusters. By the end of 2001 we expect to have completed the reduction and analysis of the ground-based photometry and spectroscopy and will begin the integration of these data with the ROSAT X-ray data. A certain amount of pressure to complete the work on NGC 2232 is coming from the SIRTF project, as this cluster may be a key component to a circumstellar disk evolution GTO program. We are only too happy to try to help and have worked to speed the analysis as much as possible. The primary activity to be undertaken in the next few months is the integration of the groundbased photometry and spectroscopy with the archival ROSAT X-ray data and then writing the paper summarizing our results. The most time consuming portion of this next phase is, of course, seeing the paper through publication in a peer-reviewed journal. Therefore, we have requested a no-cost extension to the grant to allow us to bring this project to a conclusion.
Progress in the compilation and analysis of airborne and ground data to determine the relationship between the maximum surface minus maximum air temperature differential (delta Tsa) and available water (PAW) is reported. Also, results of an analysis of HCMM images to determine the effect of cloud cover on the availability of HCMM-type data are presented. An inverse relationship between delta Tsa and PAW is indicated along with stable delta Tsa vs. PAW distributions for fully developed canopies. Large variations, both geographical and diurnal, in the cloud cover images are reported. The average monthly daytime cloud cover fluctuated between 40 and 60 percent.
The ACCESS Project (formerly Space Network) will implement an optical communications ground segment to support the Orion Artemis II Optical Communications (O2O) demonstration as part of the next manned human spaceflight mission to the moon, Artemis II. O2O implements laser communication (lasercomm) technology for operational use on the Orion series of spacecraft, as a development test objective (DTO), in order to demonstrate the feasibility and operational utility of lasercomm for human spaceflight missions. O2O consists of three segments: Space Segment, Ground Segment, and Operations Segment. The Space Segment consists of the Space Terminal Element and the Orion spacecraft. The Space Terminal Element effort is managed by the GSFC Laser-Enhanced Mission Communications Navigation and Operational Services (LEMNOS) project in collaboration with MIT Lincoln Laboratory. The Ground Segment consists of an optical ground terminal (GT) at the White Sands Complex (WSC), which is being developed in collaboration with MIT Lincoln Laboratory, the Ground Segment Operations and Analysis (GSOA) element and Ground Data Element (GDE), and a second optical GT in the Optical Communications Telescope Laboratory (OCTL) at the JPL Table Mountain Facility. The Operations Segment consists of the Artemis II Mission Control Center (MCC), the Lasercomm Space Terminal Console (LSTC), and the Lasercomm Link Planning & Analysis Center (LPAC), all located at the Johnson Space Center (JSC). O2O utilizes pulse-position modulation (PPM) direct-to-earth services resulting in an 80 Mbps downlink data rate from lunar orbit. The O2O concept of operations is to provide optical services for a minimum of 1 hour per day for each day of the Artemis II mission. O2O will utilize a 10-20 Mbps uplink data rate and 40-260 Mbps downlink data rate, depending on the Artemis II mission phase. The ACCESS project will also provide a centralized mission data interface for user data distribution and storage to the MCC and perform planning and scheduling of services in coordination with the Operations Segment for the O2O Ground Segment. The O2O Ground Segment will support the following O2O mission phases: Pre-Mission Planning; Daily Operations Planning; Event Execution; and Post-Pass Reporting. O2O will be used to exchange data files between Orion and the MCC and to distribute real-time video through the optical downlink service to the MCC; which would not be possible without the high-bandwidth link that O2O will provide to Orion. In this paper, I will discuss the O2O Ground Segment development approach and how it will support these critical O2O functions: plan and schedule the contact; acquire and track the optical link; flow information bidirectionally; distribute information; and control and accommodate the system.
Numerical filtering technique to remove earth rotation effects from ground observatory data of geomagnetic field measurements
Despite evidence from ground-based data that flow over mountains is a dominant source of gravity waves (GWs) for the Northern Hemisphere winter middle atmosphere, GW-related signals in global limb radiances from the Microwave Limb Sounder (MLS) on the Upper Atmosphere Research Satellite (UARS) have shown little direct evidence of mountain waves.
A three year program was conducted at the NASA Langley Research Center (LaRC) Aeroelasticity Branch (AB) and Transonic Dynamics Tunnel (TDT) with the primary objective to acquire scaled steady and dynamic ground-wind loads (GWL) wind-tunnel data for rollout, on-pad stay, and on-pad launch configurations for the Ares I-X Flight Test Vehicle (FTV). The experimental effort was conducted to obtain an understanding of the coupling of aerodynamic and structural characteristics that can result in large sustained wind-induced oscillations (WIO) on such a tall and slender launch vehicle and to generate a unique database for development and evaluation of analytical methods for predicting steady and dynamic GWL, especially those caused by vortex shedding, and resulting in significant WIO. This paper summarizes the wind-tunnel test program that employed two dynamically-aeroelastically scaled GWL models based on the Ares I-X Flight Test Vehicle. The first model tested, the GWL Checkout Model (CM), was a relatively simple model with a secondary objective of restoration and development of processes and methods for design, fabrication, testing, and data analysis of a representative ground wind loads model. In addition, parametric variations in surface roughness, Reynolds number, and protuberances (on/off) were investigated to determine effects on GWL characteristics. The second windtunnel model, the Ares I-X GWL Model, was significantly more complex and representative of the Ares I-X FTV and included the addition of simplified rigid geometrically-scaled models of the Kennedy Space Center (KSC) Mobile Launch Platform (MLP) and Launch Complex 39B primary structures. Steady and dynamic base bending moment as well as model response and steady and unsteady pressure data was acquired during the testing of both models. During wind-tunnel testing of each model, flow conditions (speed and azimuth) where significant WIO occurred, were identified and thoroughly investigated. Scaled data from the Ares I-X GWL model test was used in the determination of worst-case loads for the analysis of Ares I-X FTV design wind conditions. Finally, this paper includes a brief discussion of the limited full-scale GWL data acquired during the rollout and on-pad stay of the Ares I-X FTV that was launched from KSC on October 28, 2009.
The stress, mass, and energy-dissipation budgets of Crary Ice Rise are analyzed using field data collected during the 1983-1985 austral summers and in previous field programs. In addition, the net back pressure and ice-discharge rate along the grounding lines of ice streams are calculated to assess the effect of the ice rise on the surrounding flow. Comparison of the ice-rise budgets with the analysis of grounding-line data confirms the influence of the ice rise on ice-sheet stability, and suggests that Crary Ice Rise may have formed recently in response to an acceleration of one of the ice streams. It is concluded that feedback between ice-stream acceleration and ice-rise formation may control the future evolution of the above ice stream and promote long-term grounding-line stability in the face of strong natural fluctuations.
A contract with the Data Systems and Analysis Directorate contains a specified level of resources related to a specific set of work in support of three divisions within the Data Systems and Analysis Directorate. The divisions are Institutional Data Systems Division, Ground Data Systems Division, and Mission Planning and Analysis Division. The Statement of work defines at a functional requirements level the type of support to be provided to the three divisions. The contract provides for further technical direction to the contractor through issuance of Job Orders. The Job order is the prime method of further defining the work to be done, allocating a portion of the total resources in the contract to the defined tasks, and further delegating technical responsibility.
An energy budget approach to evaluating the SKYLAB X/5-detector S-192 data for prediction of soil moisture and evapotranspiration rate was pursued. A test site which included both irrigated and dryland agriculture in Southern Texas was selected for the SL-4 SKYLAB mission. Both vegetated and fallow fields were included. Data for a multistage analysis including ground, NC-130B aircraft, RB-57F aircraft, and SKYLAB altitudes were collected. The ground data included such measurements as gravimetric soil moisture, percent of the ground covered by green vegetation, soil texture, net radiation, soil temperature gradients, surface emittance, soil heat flux, air temperature and humidity gradients, and cultural practices. Ground data were used to characterize energy budgets and to evaluate the utility of an energy budget approach for determining soil moisture differences among twelve specific agricultural fields.