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At least 199 records · Page 11

James Webb Space Telescope Navigation Optimization Challenges

The James Webb Space Telescope (JWST) is a NASA flagship mission launched on December 25, 2021. The early orbit phase was highlighted by three midcourse correction burns that were performed to maneuver the vehicle into a libration orbit at the second Sun-Earth-Moon (SEM) libration point (L2). During the coast to L2, the vehicle’s primary observatory and sunshield were deployed. Once the tennis-court-sized sunshield was unfurled and tensioned into place, the large area exposed to solar radiation pressure (SRP) dictated that the SRP force model would need to account for the vehicle’s geometry, reflective properties, and orientation relative to the Sun. Following the insertion of JWST into its L2 libration orbit on January 24, 2022, the commissioning phase for the vehicle’s observatory commenced along with the first cycle of routine station-keeping maneuvers. The NASA Goddard Space Flight Center’s Flight Dynamics Facility (FDF) provides navigation services for the JWST mission. The FDF serves as the prime or backup navigation operations center for more than 30 active missions spanning a wide array of flight regimes performing orbit determination, maneuver planning, trajectory optimization, and tracking data evaluation. Definitive orbit determination for JWST is performed by the FDF using an Extended Kalman Filter (EKF) to estimate the vehicle’s trajectory and reflective properties using Deep Space Network (DSN) TRK-2-34 tracking data and spacecraft attitude telemetry. For the purposes of orbit prediction and station-keeping maneuver targeting, the sensitivity of the SRP force to the vehicle’s orientation requires that predictive attitude information must be incorporated to generate accurate orbit predictions and maneuver plans. Predictive attitude plans are provided to the FDF by the JWST Spacecraft Operations Center (SOC). Short-term (28 day) orbit predictions are propagated using a Short Range Attitude Plan (SRAP) to model the vehicle’s future attitude states for up to a week. SRAP attitude data is highly reliable, as it reflects finalized planned attitude states that the vehicle will be commanded to attain during the ensuing week. A Long Range Attitude Plan (LRAP) can be implemented to model predicted attitude states beyond one week, but these predictions are tentative and subject to revision due to changes in science operations plans. Instead, a conservative approach of applying a Sun-Pointing Neutral (SPN) attitude configuration is utilized for long-term (2 year) orbit predictions where reliable planned attitude data is not available. SPN attitude mode aligns the net SRP force along the JWST-to-Sun vector where it becomes independent of the vehicle’s angle of rotation about this vector, defined as the Sun yaw. Given the dynamic instability of the libration orbit, station-keeping thrust must be applied in either the sunward or anti-sunward direction to balance the resulting orbit. The attitude constraints of the vehicle also impose limits on the available pointing directions for station-keeping thrusters. The thrusters cannot be aligned with the optimal pointing direction for sunward maneuvers, rendering sunward maneuvers to be significantly less fuel efficient than anti-sunward maneuvers. Consequently, station-keeping maneuvers must be targeted to balance the orbit while ensuring that the next maneuver will also be performed in the anti-sunward direction to optimize propellant usage. When targeting a station-keeping maneuver, the attitude and SRP modeling configuration which is applied to the predicted post-maneuver trajectory will dictate the direction of the subsequent station-keeping maneuver, assuming nominal propulsion system performance. If the predicted post-maneuver attitude states result in an SRP model which under-predicts the cumulative SRP impact on the post-maneuver orbit, a targeted anti-sunward maneuver will be larger than necessary and the next maneuver will need to be executed sunward in order to compensate. In contrast, an anti-sunward maneuver which is targeted using an SRP model which over-predicts the cumulative SRP impact will achieve station-keeping while ensuring that the next maneuver will likewise be performed anti-sunward. For this reason, station-keeping maneuvers are targeted while applying the SPN attitude mode, as this mode entails the largest possible SRP area cross-section and therefore a larger modeled cumulative SRP impact. This paper documents the NASA Goddard Space Flight Center’s FDF support for JWST on-orbit operations and the analysis projects undertaken utilizing the experiences and data accumulated throughout the first full year of routine science operations. The results of these analysis efforts have been used to implement improvements to orbit prediction accuracy and maneuver efficiency which have the potential to prolong the lifespan of JWST to continue to conduct ground-breaking infrared astronomy for decades to come.

Flight Dynamics↗

The Ejectable Data Recorder: A Lean, Risk-Informed Approach for Hardware Development

NASA is developing the Orion spacecraft to transport crew from the Earth to the Moon as part of the Artemis series of missions. To provide a crew escape capability from pre-launch through ascent, the Orion vehicle is equipped with a Launch Abort System (LAS), built by Lockheed Martin, which pulls the capsule away from the launch vehicle in the event of an abort scenario. The Ascent Abort 2 (AA-2) test flight occurred on July 2, 2019,and tested a production version of the LAS to ensure that it can operate as intended, and to collect a large data set from hundreds of sensors on the vehicle to support Orion flight certification. In the original AA-2 architecture, a single-string set of communications antennas on the LAS would downlink all of the in-flight test data to ground stations. However, that communications architecture was predicted to have data dropouts during abort and jettison of the LAS, and would not support data transmission at all after LAS jettison. As a result, a comprehensive trade study was completed, yielding the addition of antennas on the crew module (CM), a buffer/rebroadcast capability for key portions of the flight, and an ejectable data recorder (EDR) subsystem. This EDR subsystem would serve as a backup to the radio frequency (RF) communications system, and would be non-flight critical, providing a unique capability that enabled management to take a different approach with the hardware and software development. The Crew Module and Separation Ring were developed as “Class 1”Flight Hardware, albeit with some tailoring approaches to enable efficiencies. The Class 1 designation requires full rigor for flight hardware and software, documenting everything that happens to a piece of hardware from procurement through disposal, requiring a full spectrum of acceptance tests, and the highest rigor of quality assurance processes. At the other end of the spectrum, Class 3hardware is controlled, but not intended for flight, and leaves the level of rigor up to the project manager. This classification is often used for research and development projects. Similarly,Class-1E has been recently defined at NASA for ISS payloads and technology development projects that are not flight critical and do not need the full rigor of Class 1 to be successful. The EDR subsystem was challenged at commencement to adopt a skunkworks and agile-like approach to hardware development, allowing for a different risk posture than the rest of the AA-2 hardware. After initially pursuing Class 1 processes, the EDR subsystem design evolved to incorporating numerous commercial components, leading to re-designation as a Class-1E subsystem. The resulting EDR subsystem was fully successful in meeting all flight system requirements, and achieved 100% retrieval of flight test data. This paper will discuss the risk posture of the EDR subsystem and the subsequent tailoring that was enacted as part of its Class-1E status.

EDR↗

Satellite mobile data service for Canada

A commercial mobile satellite system which is to be constructed and operated in Canada is examined. This is done in two phases. First, mobile data services was introduced. Hub equipment and 3000 mobile data terminals were supplied. Over the satellite tests were performed. The mobile data service provides full two way digital messaging automatic vehicle location and fleet management services. The second phase is to construct, launch and make operational the MSAT satellite and associated network control facilities. The implementation is examined of the mobile data service in Canada, including the technical description. Marketing and applications are also examined.

Egan, Glenn R.↗

Data Center Waste Heat as an Emerging Urban Thermal Hazard: First Field Measurements of Neighborhood-Scale Air Temperature Impacts

Data centers are among the fastest-growing sources of concentrated anthropogenic heat in urban environments. Despite heat flux densities that exceed peak solar irradiance by a factor of 2–6, their thermal impacts on adjacent communities have never been directly measured or reported in the peer-reviewed literature. This short communication addresses that gap by presenting the first vehicle-based traverse measurements of air temperature in residential neighborhoods downwind of operational data centers. Five traverses at four facilities in the Phoenix, Arizona metropolitan area, ranging from a 36 MW single-building data center in Mesa to a 169 MW colocation campus in Chandler, reveal downwind air temperature warming as high as 2.2 °C, with average downwind air temperatures 0.7–0.9 °C warmer than corresponding upwind areas. Thermal signatures were detectable at distances up to 500 m from facility perimeters. The 36 MW Mesa facility rejects waste heat equivalent to the electricity consumption of approximately 40,000 households, while the 169 MW Chandler campus is equivalent to over 180,000 households, both concentrated into footprints smaller than a single residential subdivision. With U.S. data center capacity projected to more than double by 2030, these findings establish data center anthropogenic waste heat as a previously undocumented urban thermal hazard demanding attention from the data center and urban planning communities.

Phoenix↗

Perseverance Rover’s Robotic Arm and Turret Mounted Instruments’ Surface Commissioning

The Robotic Arm (RA) on the Perseverance rover is an integral component of the Sampling and Caching System necessary for completing the science goals of the Mars 2020 mission. While the Perseverance rover was based on the Curiosity rover which landed in 2012, the Robotic Arm was redesigned to carry a much larger turret with a new suite of payloads. Shortly after Perseverance landed in Jezero Crater, a series of checkouts was completed with the RA during the first 100 sols of the mission in order to ensure proper functionality of the RA and the instruments mounted on the turret. This period of time in the mission was called Surface Operations Transition (SOX). The objective of SOX was to systematically execute checkout activities for all the basic functionality so that the RA and instruments, as well as other rover components, could be released for scientific exploration.RA activities during SOX can be divided into a few different categories: Mechanism Checkouts, Rover Visual Inspections, Performance Characterization, and Instrument Functional Checkouts. Many of these checkouts built off of each other such that each subsequent activity would verify incrementally complex functionality. Many of the defined activities were executed several times throughout the development of the rover and served as a check that the RA’s performance is consistent with testing on Earth. Other activities were developed uniquely for SOX to respond to challenges discovered during development. They were designed to be verifiable without the help of ground support equipment or previous executions on the flight hardware to compare against.This paper discusses the formulation and conception of the various RA SOX checkout activities, verification and testing required to certify them for flight, execution of the activities on Mars, issues encountered, and finally results and findings as the mission transitioned to nominal science operations. We will be presenting the results and analysis using downlinked imaging and data from the flight vehicle to show how we verified the performance of the Robotic Arm and the turret mounted instruments in order to transition to science operations with a clean bill of health.

Edgett, Kenneth↗

Fatigue loads spectra derivation for the Space Shuttle: Second cycle

Some of the environments and loads experienced by the Space Shuttle or future reusable space vehicles are unique, while others are similar to those encountered by commercial and/or military aircraft. Prior to the Space Transportation System (STS) flights, fatigue loads spectra were generated for the Space Shuttle based on anticipated environments and assumptions that were shown not to be applicable to the actual flight environments the vehicle experienced. This resulted in the need to generate a new cycle of fatigue loads spectra, which was based on measured flight data as well as mission profiles, reflecting the various types of service and operations the vehicle and payloads experienced.

Ortasse, Raphael↗

Space Telescope Control System science user operations

The Space Telescope science users will have a flexible and efficient means of accessing the capabilities provided by the ST Pointing Control System, particularly with respect to managing the overal acquisition and pointing functions. To permit user control of these system functions - such as vehicle scanning, tracking, offset pointing, high gain antenna pointing, solar array pointing and momentum management - a set of special instructions called 'constructs' is used in conjuction with command data packets. This paper discusses the user-vehicle interface and introduces typical operational scenarios.

Dougherty, H. J.↗

Crew interface specification development study for in-flight maintenance and stowage functions

The need and potential solutions for an orderly systems engineering approach to the definition, management and documentation requirements for in-flight maintenance, assembly, servicing, and stowage process activities of the flight crews of future spacecraft were investigated. These processes were analyzed and described using a new technique (mass/function flow diagramming), developed during the study, to give visibility to crew functions and supporting requirements, including data products. This technique is usable by NASA for specification baselines and can assist the designer in identifying both upper and lower level requirements associated with these processes. These diagrams provide increased visibility into the relationships between functions and related equipments being utilized and managed and can serve as a common communicating vehicle between the designer, program management, and the operational planner. The information and data product requirements to support the above processes were identified along with optimum formats and contents of these products. The resulting data product concepts are presented to support these in-flight maintenance and stowage processes.

Carl, J. G.↗

Raw_data_Batch_I: State Street

Date of collection: May 18, 2023 Location: State Street, Chicago, IL This data set contains lidar and vision data collected along State Street. The vehicle started from outside of the McCormick Tribune Campus Center at the Illinois Institute of Technology’s Mies Campus and headed north along State Street, until the north end of State Street in the Gold Coast. The data contains the following Robot Operating System (ROS) topics: - /Central_Camera_blurred – Image flow from coaxial camera heading, vehicle front. - /Left_Camera_blurred – Image flow from left camera, 60° from central camera on the left side. - /Right_Camera_blurred – Image flow from right camera, 60° from central camera on the right side. - /camera0/camera_info – Intrinsic and distortion information of left camera. - /camera0/projection_matrix – Extrinsic matrix of left camera from lidar. - /camera2/camera_info – Intrinsic and distortion information of central camera. - /camera2/projection_matrix – Extrinsic matrix of central camera from lidar. - /camera5/camera_info – Intrinsic and distortion information of right camera. - /camera5/projection_matrix – Extrinsic matrix of right camera from lidar. - /novatel/oem7/bestpos – Latitude, longitude, and elevation information from NovAtel GNSS-INS system. - /points_raw – VLP-32 lidar point cloud. - /tf – Vehicle base frame. The data are organized into a data description file and one or more ROS .bag files, dependent on original file size. The data description file provides information about the data collection date, location, and detailed mapping, while the .bag file(s) contain the actual data. Please note that for the purpose of securing personally identifiable information, all license plates and faces included in this publication have been intentionally blurred during real-time processing. ![state street image](state-street.png)

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Spatiotemporal Automatic Calibration of Infrastructure Lidar, Radar, and Camera with a Global Navigation Satellite System

Robust and accurate perception is important for modern intelligent transportation systems (ITS), which use sensors of various modalities for data fusion to create a digital twin of an intersection. Sensor calibration is an important process that creates a unified coordinate frame for the sensor output data so that it can be used for data fusion. Classical approaches for sensor calibration are time-consuming, require an overlapping field of view for feature matching, and are not feasible for ITS application as they cause disruptions in the flow of traffic. In this paper, we present a spatiotemporal automatic calibration approach to calibrate multiple infrastructure lidar, radar, and cameras installed at a traffic intersection. The approach uses global navigation satellite system (GNSS) positioning information shared by connected vehicles, and when the vehicle is detected by the sensor, we match the sensor detections with the GNSS coordinates. The proposed algorithm is evaluated with a real-world dataset utilizing detections from two radars, cameras, and lidars with a test vehicle instrumented with a post-processing kinematic (PPK)-corrected GNSS driving past the sensors installed at a four-way traffic intersection. The experimental results show that the proposed automatic calibration approach can achieve the transformation with a root mean squared error of less than 0.5 for radar and lidar and less than 2 for camera detections. The ability to rapidly calibrate sensors not only benefits initial installations, but can also be used for system health monitoring, while utilizing available connected vehicle data to test the real-time sensor fidelity and operational status.

ADVANCED PROPULSION SYSTEMS,ENERGY CONSERVATION, C↗

Skylab 2 facilities and environmental measurements program

A list of the facilities and environmental measurements to be monitored in support of the Skylab 2 vehicle is presented. The data include measurement identification number, description, transducer operating range, recorder type, and drawings illustrating measurement location.

Source record↗

Improved NOAA weather satellite scheduled for NASA launch

A description of the GOES-E mission is presented and includes the instrumentation of the satellite, data acquisition, spacecraft description, and Delta Launch Vehicle description. The launch operations are presented and include major launch events, post-launch events, and a review of the Delta/GOES-E team.

Source record↗

Mass storage systems for data transport in the early space station era 1992-1998

NASA's Space Station Program will provide a vehicle to deploy an unprecedented number of data producing experiments and operational devices. Peak down link data rates are expected to be in the 500 megabit per second range and the daily data volume could reach 2.4 terabytes. Such startling requirements inspired an internal NASA study to determine if economically viable data storage solutions are likely to be available to support the Ground Data Transport segment of the NASA data system. To derive the requirements for data storage subsystems, several alternative data transport architectures were identified with different degrees of decentralization. Data storage operations at each subsystem were categorized based on access time and retrieval functions, and reduced to the following types of subsystems: First in First out (FIFO) storage, fast random access storage, and slow access with staging. The study showed that industry funded magnetic and optical storage technology has a reasonable probability of meeting these requirements. There are, however, system level issues that need to be addressed in the near term.

Carper, Richard↗

Fuzzy logic applications to expert systems and control

A considerable amount of work on the development of fuzzy logic algorithms and application to space related control problems has been done at the Johnson Space Center (JSC) over the past few years. Particularly, guidance control systems for space vehicles during proximity operations, learning systems utilizing neural networks, control of data processing during rendezvous navigation, collision avoidance algorithms, camera tracking controllers, and tether controllers have been developed utilizing fuzzy logic technology. Several other areas in which fuzzy sets and related concepts are being considered at JSC are diagnostic systems, control of robot arms, pattern recognition, and image processing. It has become evident, based on the commercial applications of fuzzy technology in Japan and China during the last few years, that this technology should be exploited by the government as well as private industry for energy savings.

Lea, Robert N.↗

Reach performance while wearing the Space Shuttle launch and entry suit during exposure to launch accelerations

Crewmen aboard the Space Shuttle are subjected to accelerations during ascent (the powered flight phase of launch) which range up to +3 G(sub x). Despite having 33 missions and nine years experience, not to mention all the time spent in development prior to the first flight, no truly quantitative reach study wearing actual crew equipment, using actual Shuttle seats and restraints has ever been done. What little information exists on reach performance while under acceleration has been derived primarily from subjective comments gathered retrospectively from Shuttle flight crews during their post mission debrief. This lack of reach performance data has resulted in uncertainty regarding emergency procedures that can realistically be performed during and actual Shuttle ascent versus what is practiced in the ground-fixed and motion-based Shuttle Simulators. With the introduction on STS-26 of the current Shuttle escape system, the question of reach performance under launch accelerations was once again raised. The escape system's requirement that each crewman wear a Launch/Entry Suit (LES), parachute harness, and parachute were all anticipated to contribute to a further degradation of reach performance during Shuttle ascent accelerations. In order to answer the reach performance question in a quantitative way, a photogrammetric method was chosen so that the actual reach values and associated envelopes could be captured. This would allow quantitative assessment of potential task performance impact and identify areas where changes to our Shuttle ascent emergency procedures might be required. Also, such a set of reach values would be valid for any similar acceleration profile using the same crew equipment. Potential Space Station applications of this data include predicting reach performance during Assured Crew Return Vehicle (ACRV) operations.

Bagian, James P.↗

The X-33 range Operations Control Center

This paper describes the capabilities and features of the X-33 Range Operations Center at NASA Dryden Flight Research Center. All the unprocessed data will be collected and transmitted over fiber optic lines to the Lockheed Operations Control Center for real-time flight monitoring of the X-33 vehicle. By using the existing capabilities of the Western Aeronautical Test Range, the Range Operations Center will provide the ability to monitor all down-range tracking sites for the Extended Test Range systems. In addition to radar tracking and aircraft telemetry data, the Telemetry and Radar Acquisition and Processing System is being enhanced to acquire vehicle command data, differential Global Positioning System corrections and telemetry receiver signal level status. The Telemetry and Radar Acquisition Processing System provides the flexibility to satisfy all X-33 data processing requirements quickly and efficiently. Additionally, the Telemetry and Radar Acquisition Processing System will run a real-time link margin analysis program. The results of this model will be compared in real-time with actual flight data. The hardware and software concepts presented in this paper describe a method of merging all types of data into a common database for real-time display in the Range Operations Center in support of the X-33 program. All types of data will be processed for real-time analysis and display of the range system status to ensure public safety.

Shy, Karla S.↗