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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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NASA NTRS1992

Preliminary structural design of a lunar transfer vehicle aerobrake

An aerobrake concept for a Lunar transfer vehicle was weight optimized through the use of the Taguchi design method, structural finite element analyses and structural sizing routines. Six design parameters were chosen to represent the aerobrake structural configuration. The design parameters included honeycomb core thickness, diameter to depth ratio, shape, material, number of concentric ring frames, and number of radial frames. Each parameter was assigned three levels. The minimum weight aerobrake configuration resulting from the study was approx. half the weight of the average of all twenty seven experimental configurations. The parameters having the most significant impact on the aerobrake structural weight were identified.

Bush, Lance B.↗
NASA NTRS2009

Lunar Surface Operations: Surface Duration - Part 2

The objectives of this slide presentation are to review the activities on the lunar surface during the stay. The objectives include (1) Summarize Lunar Module Basics emphasizing module layout and storage. (2) Identify the primary activities occurring during each of the lunar s urface timelines, (3) List the EVA Prep tasks, (4) Identify the EVA Objectives, (5) Identify the activities associated with Post EVA (6) Describe the lessons learned during both EVA and Non EVA activities. Included are overview drawings of the Lunar Roving Vehicle, pictures of the tools, and sample return containers. There are also time lines for the Apollo 11, and Apollo 12 through 14, Apollo 15, Apollo 16 and Apollo 17. Diagrams of the EVA suits are shown, including the Liquid Cooling Garment, and the Pressure Garment Assembly. The activity prior to the EVA are reviewed. The science mission assignments of each mission are viewed. The activities after the EVA are reviewed

Interbartolo, Michael↗
NASA NTRS2014

NASA Space Launch System Operations Outlook

The National Aeronautics and Space Administration's (NASA) Space Launch System (SLS) Program, managed at the Marshall Space Flight Center (MSFC), is working with the Ground Systems Development and Operations (GSDO) Program, based at the Kennedy Space Center (KSC), to deliver a new safe, affordable, and sustainable capability for human and scientific exploration beyond Earth's orbit (BEO). Larger than the Saturn V Moon rocket, SLS will provide 10 percent more thrust at liftoff in its initial 70 metric ton (t) configuration and 20 percent more in its evolved 130-t configuration. The primary mission of the SLS rocket will be to launch astronauts to deep space destinations in the Orion Multi-Purpose Crew Vehicle (MPCV), also in development and managed by the Johnson Space Center. Several high-priority science missions also may benefit from the increased payload volume and reduced trip times offered by this powerful, versatile rocket. Reducing the life-cycle costs for NASA's space transportation flagship will maximize the exploration and scientific discovery returned from the taxpayer's investment. To that end, decisions made during development of SLS and associated systems will impact the nation's space exploration capabilities for decades. This paper will provide an update to the operations strategy presented at SpaceOps 2012. It will focus on: 1) Preparations to streamline the processing flow and infrastructure needed to produce and launch the world's largest rocket (i.e., through incorporation and modification of proven, heritage systems into the vehicle and ground systems); 2) Implementation of a lean approach to reachback support of hardware manufacturing, green-run testing, and launch site processing and activities; and 3) Partnering between the vehicle design and operations communities on state-ofthe- art predictive operations analysis techniques. An example of innovation is testing the integrated vehicle at the processing facility in parallel, rather than sequentially, saving both time and money. These themes are accomplished under the context of a new cross-program integration model that emphasizes peer-to-peer accountability and collaboration towards a common, shared goal. Utilizing the lessons learned through 50 years of human space flight experience, SLS is assigning the right number of people from appropriate backgrounds, providing them the right tools, and exercising the right processes for the job. The result will be a powerful, versatile, and capable heavy-lift, human-rated asset for the future human and scientific exploration of space.

Hefner, William Keith↗
NASA NTRS2014

NASA Space Launch System Operations Outlook

The National Aeronautics and Space Administration's (NASA) Space Launch System (SLS) Program, managed at the Marshall Space Flight Center (MSFC), is working with the Ground Systems Development and Operations (GSDO) Program, based at the Kennedy Space Center (KSC), to deliver a new safe, affordable, and sustainable capability for human and scientific exploration beyond Earth's orbit (BEO). Larger than the Saturn V Moon rocket, SLS will provide 10 percent more thrust at liftoff in its initial 70 metric ton (t) configuration and 20 percent more in its evolved 130-t configuration. The primary mission of the SLS rocket will be to launch astronauts to deep space destinations in the Orion Multi- Purpose Crew Vehicle (MPCV), also in development and managed by the Johnson Space Center. Several high-priority science missions also may benefit from the increased payload volume and reduced trip times offered by this powerful, versatile rocket. Reducing the lifecycle costs for NASA's space transportation flagship will maximize the exploration and scientific discovery returned from the taxpayer's investment. To that end, decisions made during development of SLS and associated systems will impact the nation's space exploration capabilities for decades. This paper will provide an update to the operations strategy presented at SpaceOps 2012. It will focus on: 1) Preparations to streamline the processing flow and infrastructure needed to produce and launch the world's largest rocket (i.e., through incorporation and modification of proven, heritage systems into the vehicle and ground systems); 2) Implementation of a lean approach to reach-back support of hardware manufacturing, green-run testing, and launch site processing and activities; and 3) Partnering between the vehicle design and operations communities on state-of-the-art predictive operations analysis techniques. An example of innovation is testing the integrated vehicle at the processing facility in parallel, rather than sequentially, saving both time and money. These themes are accomplished under the context of a new cross-program integration model that emphasizes peer-to-peer accountability and collaboration towards a common, shared goal. Utilizing the lessons learned through 50 years of human space flight experience, SLS is assigning the right number of people from appropriate backgrounds, providing them the right tools, and exercising the right processes for the job. The result will be a powerful, versatile, and capable heavy-lift, human-rated asset for the future human and scientific exploration of space.

Hefner, William Keith↗
NASA NTRS1986

Independent Orbiter Assessment (IOA): Analysis of the elevon subsystem

The results of the Independent Orbiter Assessment (IOA) of the Failure Modes and Effects Analysis (FMEA) and Critical Items List (CIL) are presented. The IOA approach features a top-down analysis of the hardware to determine failure modes, criticality, and potential critical items. To preserve independence, this analysis was accomplished without reliance upon the results contained within the NASA FMEA/CIL documentation. This report documents the independent analysis results for the Orbiter Elevon system hardware. The elevon actuators are located at the trailing edge of the wing surface. The proper function of the elevons is essential during the dynamic flight phases of ascent and entry. In the ascent phase of flight, the elevons are used for relieving high wing loads. For entry, the elevons are used to pitch and roll the vehicle. Specifically, the elevon system hardware comprises the following components: flow cutoff valve; switching valve; electro-hydraulic (EH) servoactuator; secondary delta pressure transducer; bypass valve; power valve; power valve check valve; primary actuator; primary delta pressure transducer; and primary actuator position transducer. Each level of hardware was evaluated and analyzed for possible failure modes and effects. Criticality was assigned based upon the severity of the effect for each failure mode. Of the 25 failure modes analyzed, 18 were determined to be PCIs.

Wilson, R. E.↗
NASA NTRS1991

Dynamics Explorer-1 (DE-1)

The Dynamics Explorer (DE) mission is designed to study the Earth's electromagnetic fields at varying heights up to 4 Earth radii. The DE-1 was launched on a Delta 3913 launch vehicle from the Western Test Range and was placed in a 561 x 23279 km orbit with a 90 degree inclination. The Deep Space Network (DSN) began to support this extended mission on February 1, 1985. Coverage consists of five passes per day that last for 45 minutes each. Information is given in tabular form for DSN support, frequency assignments, telemetry, command, and tracking mission responsibility.

Gordon, F.↗
NASA NTRSDate not supplied

Development of the BOLT II Roughness Experiment for Flight

BOLT II is a sounding rocket research project with the goal of studying hypersonic boundary layer transition and turbulence. The BOLT II research vehicle is based on a three-dimensional geometry (a slightly longer version of BOLT) with concave surfaces and swept leading edges that provides two separate and distinct, also redundant, flow paths for conducting measurements. One side of BOLT II is dedicated to smooth surface transition and turbulence, to better study the natural instability processes, while the other has been assigned to study forced transition and turbulence using discrete roughness trips. The present paper is intended to document the primary drivers and decisions made leading up to finalizing the roughness side experiment for the BOLT II flight.

Hypersonic↗
NASA NTRSDate not supplied

Development of the BOLT II Roughness Experiment for Flight

BOLT II is a sounding rocket research project with the goal of studying hypersonic boundary layer transition and turbulence. The BOLT II research vehicle is based on a three-dimensional geometry (a slightly longer version of BOLT) with concave surfaces and swept leading edges that provides two separate and distinct, also redundant, flow paths for conducting measurements. One side of BOLT II is dedicated to smooth surface transition and turbulence, to better study the natural instability processes, while the other has been assigned to study forced transition and turbulence using discrete roughness trips. The present paper is intended to document the primary drivers and decisions made leading up to finalizing the roughness side experiment for the BOLT II flight.

hypersonic↗
NASA NTRS2025

Provider of Services for Urban Air Mobility (PSU) Prototype Simulation (X5) Final Report

Urban Air Mobility (UAM) is a new air transportation service concept to carry passengers or cargo in metropolitan areas, leveraged by innovative aircraft and air traffic automation technologies. NASA has conducted a series of simulations, called the X-series simulation, to evaluate the UAM concept of operations and support the development of airspace procedures and services for UAM operations. The simulation called “X5” was conducted in 2023 to test a Provider of Services for UAM (PSU) prototype developed by NASA for UAM flight planning, strategic conflict management support, and data exchange between UAM operators. In this simulation, two strategic conflict management capabilities, Demand-Capacity Balancing and Sequencing and Scheduling, were further investigated. This document describes the UAM system architecture modeled, the X5 simulation environment to be executed (e.g., traffic scenario and UAM airspace construct), and the strategic conflict management processes developed and evaluated in this study. Then, the simulation results are provided using several system performance metrics, such as the number of operations planned and activated, demand-capacity imbalances detected and resolved, and pre-departure delays. Based on these metrics, the test findings and lessons learned from this simulation are discussed. NASA developed a PSU prototype as part of a reference implementation of UAM system architecture and evolved strategic conflict management capabilities for UAM operations from the previous collaborative simulations with industry partners. Below is the summary of the achievements: - Aligned NASA’s UAM reference architecture with the FAA’s UAM ConOps notional architecture - Extended UAM airspace management capabilities to include 1) Demand-Capacity Balancing (DCB) to ensure operators coordinate planned usage of shared vertiports, and 2) Sequencing and Scheduling (S&S) at UAM corridor entry and exit points to help facilitate an orderly flow of traffic - Defined the PSU information exchange APIs and requirements towards informing industry standards - Developed and tested a NASA PSU prototype as reference implementation to validate the requirements and APIs - Developed a prototype service connecting NASA’s PSU and the FAA system for testing future PSU-ATM interface requirements - Tested NASA-developed assumptions for UAM operations such as airspace design, procedures, vehicle performance, and strategic conflict management methods to inform future Cooperative Operating Practices (COPs) development with industry - Evaluated system performance metrics such as number of simultaneous operations and ground delays that can help define system-level requirements. The simulation results showed that the UAM traffic demand could be managed to minimize the needs of tactical separation provision with ground delays assigned by DCB and S&S. These accomplishments and the lessons learned from the PSU Prototype X5 simulation activities will be valuable inputs for the Air Mobility Pathfinders (AMP) project, which is NASA’s new project to create and evaluate a reference architecture for safe, secure, and scalable UAM operations.

Simulation↗
NASA NTRSDate not supplied

Manual Crew Override of Vehicle Landings Following G-Transitions

BACKGROUND Manual control during exploration spaceflight consists of both planned automated supervisory control and unplanned crew override. This crew override capability is critical to enable overall mission success during landing contingencies. However, the introduction of manual override capabilities must be implemented to enable crews to mitigate risks introduced by human error. Adaptive changes in the sensorimotor system can manifest during g-transitions as spatial disorientation. While training and landing aids enable successful landing through disorientation, these adaptive changes may increase cognitive demand that needs to be accounted for in the manual control strategy. It is important to characterize these effects as soon as possible following the G-transition to develop appropriate countermeasures. METHODS In this study, we will examine operational piloting tasks following International Space Station (ISS) missions in a simulated lunar landing using a six-degree-of-freedom (6DOF) motion base. The motion-based simulation will be implemented in our laboratory at the Johnson Space Center (JSC) and will be available within hours following the return from commercial crew landings. The primary goals of this study are (1) to understand the impact of spaceflight on crew ability to perform manual crew override tasks, (2) to examine how adaptive changes in vestibular and cognitive function relate to changes in manual crew override proficiency, and (3) compare performance during late “just-in-time” on-board training with early post-flight crew performance. The impact of spaceflight on piloting capability will be assessed from pre- versus post-flight changes in crewmembers assigned to either short duration (< 30 day) or long duration (~6- month) missions to the International Space Station (ISS). Individual differences in post-flight vestibular and cognitive changes include motion sickness reports, measures of tilt motion perception accuracy and precision, and dual-task tracking. During the 6DOF lunar simulation, the crew will manually takeover attitude and rate-of-descent to the nominal or re-designated landing aim point during the approach phase. The outcome measures for the lunar crew override tasks will be the percent time maintaining actual vehicle states, e.g., attitude and rate-of-descent, within recommended guidance during the landing approach, number and maximum deviation outside limits, and root mean square error (RMSE). Given that “just-in-time” (JIT) training is an operational expectation for the Human Landing System (HLS) program, all participants will perform late inflight JIT training for each manual crew override task in which they will participate. Crew proficiency will be captured inflight during JIT training that will be implemented on a laptop with hand controllers to allow the crewmember to practice the landing task procedures like the approach implemented for JIT training with Shuttle landing and ISS telerobotic tasks. COUNTERMEASURE UPDATES The lunar lander simulation has been implemented onto a two-laptop display system where subjects select from alternative landing points, based upon avoiding hazards that the on-board system identifies during the landing. The subject makes inputs using a rotational hand controller (i.e., joystick) and a translational hand controller, which are processed by simulated vehicle dynamics to update the vehicle attitude and rate of descent. Subjects will utilize a combination of flight, situation, and status displays to monitor the state of the simulated vehicle. The simulation exports tilt and translation movements to a 6DOF motion base synced to visual movements and provides representative vestibular cues to the subject while performing the task inside an enclosed cabin featuring a simulated lunar out-the-window view and a heads-down lander cockpit view. RELEVANCE This project will deliver an operational demonstration of crew override capability following spaceflight and identify potential deficits that may require remediation. Comparison of individual vestibular and cognitive changes with crew override performance will help better characterize the manual control risks associated with sensorimotor alterations. The inclusion of “just-in-time” on-board training will ensure we are characterizing changes in override proficiency with this expected countermeasure in place. ACKNOWLEDGEMENTS: The authors acknowledge contributions from Draper, HLS Joint Test Panel, Crew HLS Interfaces for Piloting Working Group, and Dynamic Skills Trainer (DST) Lab toward the development of the lunar landing simulation. This project is funded by the Human Health Countermeasures Element.

Austin M Bollinger↗
NASA NTRS2007

Automated Target Planning for FUSE Using the SOVA Algorithm

The SOVA algorithm was originally developed under the Resilient Systems and Operations Project of the Engineering for Complex Systems Program from NASA s Aerospace Technology Enterprise as a conceptual framework to support real-time autonomous system mission and contingency management. The algorithm and its software implementation were formulated for generic application to autonomous flight vehicle systems, and its efficacy was demonstrated by simulation within the problem domain of Unmanned Aerial Vehicle autonomous flight management. The approach itself is based upon the precept that autonomous decision making for a very complex system can be made tractable by distillation of the system state to a manageable set of strategic objectives (e.g. maintain power margin, maintain mission timeline, and et cetera), which if attended to, will result in a favorable outcome. From any given starting point, the attainability of the end-states resulting from a set of candidate decisions is assessed by propagating a system model forward in time while qualitatively mapping simulated states into margins on strategic objectives using fuzzy inference systems. The expected return value of each candidate decision is evaluated as the product of the assigned value of the end-state with the assessed attainability of the end-state. The candidate decision yielding the highest expected return value is selected for implementation; thus, the approach provides a software framework for intelligent autonomous risk management. The name adopted for the technique incorporates its essential elements: Strategic Objective Valuation and Attainability (SOVA). Maximum value of the approach is realized for systems where human intervention is unavailable in the timeframe within which critical control decisions must be made. The Far Ultraviolet Spectroscopic Explorer (FUSE) satellite, launched in 1999, has been collecting science data for eight years.[1] At its beginning of life, FUSE had six gyros in two IRUs and four reaction wheels. Over time through various failures, the satellite has been left with one reaction wheel on the vehicle skew axis and two gyros. To remain operational, a control scheme has been implemented using the magnetic torque rods and the remaining momentum wheel.[2] As a consequence, there are attitude regions where there is insufficient torque authority to overcome environmental disturbances (e.g. gravity gradient torques). The situation is further complicated by the fact that these attitude regions shift inertially with time as the spacecraft moves through earth s magnetic field during the course of its orbit. Under these conditions, the burden of planning targets and target-to-target slew maneuvers has increased significantly since the beginning of the mission.[3] Individual targets must be selected so that the magnetic field remains roughly aligned with the skew wheel axis to provide enough control authority to the other two orthogonal axes. If the field moves too far away from the skew axis, the lack of control authority allows environmental torques to pull the satellite away from the target and can potentially cause it to tumble. Slew maneuver planning must factor the stability of targets at the beginning and end, and the torque authority at all points along the slew. Due to the time varying magnetic field geometry relative to any two inertial targets, small modifications in slew maneuver timing can make large differences in the achievability of a maneuver.

Heatwole, Scott↗
NASA NTRS1991

Broadcasting Satellite-3A and -3B (BS-3A and 3B)

The BS-3A and -3B will provide direct color TV broadcasting to the Japanese mainland and remote islands. The satellites will be launched from Tanegashima Space Center by a type H-1 launch vehicle. The coverage will consist of the 26-m antenna and the 34-m antenna as a backup support for the transfer and drift orbits. Maximum support will consist of one 8-hour track per station for a seven day period, plus 23 days of contingency support from all complexes. Information is given in tabular form for Deep Space Network support, frequency assignments, telemetry, command, and tracking support responsibility.

Horii, M.↗
NASA NTRS1991

French direct TV broadcast satellite (TDF-1 and -2)

The French Direct TV Broadcast Satellite (TDF-1 and -2) missions are to provide three channels of TV and sound broadcasting to France within the 12 to 18 GHz bands. The satellites will be placed in a geostationary orbit at 19 degrees west longitude. The satellites will be launched from the Centre Spatial Guyanis in French Guiana on an Ariane launch vehicle. The Deep Space Network (DSN) will support the transfer and drift orbit mission phases. The coverage will consist of the 26-m antennas at Goldstone and Canberra as prime support. Maximum support will consist of two 8-hour tracks per station for a 7-day period, plus 14 days contingency support. Information is given in tabular form for DSN coverage, frequency assignments, telemetry, command, and tracking support responsibility.

Vacheyroux, R.↗
NASA NTRSDate not supplied

Exploration Atmosphere Demonstration of A Multi-Functional Integrated Medical Device (Tempus Pro)

INTRODUCTION The Exploration Medical Capability (ExMC) element within the Human Research Program and the Exploration Medical Integrated Product Team (XMIPT) within the Mars Campaign Office seek to advance medical system design and risk-informed decision-making for exploration missions. This includes assessment of candidate devices and their compatibility within a variety of increasingly Earth-independent medical scenarios. The Tempus Pro (Remote Diagnostic Technologies, Ltd., Philips Corp., Farnborough, UK) is a commercial-off-the-shelf (COTS), multi-functional integrated medical device capable of vital signs monitoring, with built-in procedure support (iAssist), patient record and telemedicine communication features, and medical imaging (e.g., camera, laryngoscope, ultrasound) that meets multiple exploration medical capability needs. One of several hypobaric atmospheres being considered for exploration vehicles is 8.2 psi with 34% oxygen. To assess the useability of the Tempus Pro in such environments by individuals without formal medical training, the unit was tested in May and June of 2023 at the Johnson Space Center 20-Foot Exploration Atmosphere Chamber in conjunction with the Exploration Atmospheres-2 (EA-2) study. TECHNOLOGY DEMONSTRATION Eight subjects in the EA-2 study were assigned roles as the caregiver or patient – or both in the case of a self-exam – and caregivers were asked to place sensors for 3-Lead ECG, non-invasive blood pressure (NIBP), pulse oximetry (SpO2), and temperature using Tempus Pro’s iAssist. Depending on the procedure, additional tasks included an oropharyngeal exam of the throat with the laryngoscope and capturing ultrasound images of a cardiac subxiphoid view or of the user’s choice from a pre-specified list. Scenarios ranged from remote-guided to fully autonomous operations and surveyed the effectiveness of support, amount of support desired, and importance of support by type (e.g., written crew procedures, iAssist and device guidance, remote console guidance, etc.). Feedback from the subjects and the support personnel was also gathered to inform future designs for training and support and to determine what operations are plausible given different levels of each. An unweighted NASA task load index (TLX) was used to profile the demands of using the device, however the sample size does not support statistics. The research was exploratory in nature and qualitative information was the main goal. Calibration checks on the Tempus Pro were conducted before and after chamber testing to ensure the device was in useable condition. RESULTS All subjects performed their tasks successfully and found the Tempus Pro easy to use with the support provided. The calibration checks outside the chamber showed that the Tempus Pro remained unchanged and measurements inside the chamber were within normal values. Caregivers taking the NASA TLX reported mean scores ≤ 41/100 showing the tasks to be undemanding and less demanding with repeated use (~20/100). Novice users were able to easily connect sensors and take vital signs with the guidance from Tempus Pro’s iAssist feature. For more complex tasks, such as the oropharyngeal exam and ultrasound image acquisition, guidance beyond iAssist was needed, primarily from a supporting physician. Feedback on the importance of support types varied by person and scenario but greater than 50% of the support used by each was non-native to the device. Overall opinions were positive, but the ultrasound users expressed a lack of confidence in their results and 3 out of 4 desired more time, training, or support. Subjects found the sensors to be comfortable and comparable to prior experiences with such devices, except for the blood pressure cuff, which squeezed too tightly for uncomfortably long periods. Many observations provoked discussion, especially regarding ultrasound, that will aide decisions about future demonstrations.

R. S. Miller↗
NASA NTRS2023

Monitoring Airspace Complexity and Determining Contributing Factors

The national airspace has evolved over many years to accommodate increased traffic demand while simultaneously maintaining air travel as one of the safest forms of transportation. One of the reasons for this success is the ability of the air traffic control system and the operators to adapt and accommodate to situations that routinely disrupt normal operations. These situations may include: adverse weather, delays, early arrivals, equipment outages, and other factors that are outside the operators’ ability to control. These factors can lead to states where automation is unable to properly handle these issues, and therefore air traffic controllers and pilots have to intervene — ultimately increasing communication between operators resulting in higher workload. As controller workload increases to handle sub-optimal operating conditions, complexity increases. This is because, under these conditions humans are required to make tactical decisions in response to external factors. This results in a departure from the original strategic plan where operations would be more efficiently managed. Human operators manage airspace complexity under rigid regulations but in a constantly changing environment. The airspace is divided into sectors and the number of aircraft assigned to each controller is limited for safe handling. Some prior studies devised airspace complexity metrics in commercial aviation and related these metrics to controller workload. The upper bounds on the system load are pre-determined. Such bounds on complexity make for a safe system, but the system cannot scale and adapt to autonomous, dense, and heterogeneous traffic — including the many types of Unmanned Aerial Vehicles (UAVs) envisioned to be added to the operations. We hypothesize that, as traffic density and heterogeneity grow, and other key metrics change, there will be phase transitions at which the way traffic should be managed changes significantly. We offer a method for in-time detection of contributing factors that lead to phase transitions, characterized by increased complexity. To the best of our knowledge, there is no tool similar to ours that identifies such contributing factors or precursor patterns.

Precursor↗
NASA NTRS2007

Coronas-F Orbit Monitoring and Re-Entry Prediction

Russian scientific satellite CORONAS-F was launched on July, 31, 2001. The object was inserted in near-circular orbit with the inclination 82.5deg and a mean altitude approx. 520 km. Due to the upper atmosphere drag CORONAS-F was permanently descended and as a result on December, 6, 2005 it has finished the earth-orbital flight, having lifetime in space approx. 4.5 years. The satellite structural features and its flight attitude control led to the significant variations of its ballistic coefficient during the flight. It was a cause of some specific difficulties in the fulfillment of the ballistic and navigation support of this space vehicle flight. Besides the main mission objective CORONAS-F also has been selected by the Inter-Agency Space Debris Coordination Committee (IADC) as a target object for the next regular international re-entry test campaign on a program of surveillance and re-entry prediction for the hazard space objects within their de-orbiting phases. Spacecraft (S/C) CORONAS-F kept its working state right up to the end of the flight - down to the atmosphere entry. This fact enabled to realization of the additional research experiments, concerning with an estimation of the atmospheric density within the low earth orbits (LEO) of the artificial satellites, and made possible to continue track the S/C during final phase of its flight by means of Russian regular command & tracking system, used for it control. Thus there appeared a unique possibility of using for tracking S/C at its de-orbiting phase not only passive radar facilities, belonging to the space surveillance systems and traditionally used for support of the IADC re-entry test campaigns, but also more precise active trajectory radio-tracking facilities from the ground control complex (GCC) applied for this object. Under the corresponding decision of the Russian side such capability of additional high-precise tracking control of the CORONAS-F flight in this period of time has been implemented. The organizing of the CORONAS-F ballistic and navigational support (BNS) and solving its main tasks (such as S/C orbit determination (OD) and its motion prediction and connected with them) both for regular mission stage and for additional flight program were realized by the group of specialists from the Mission Control Center (MCC). MCC was also assigned as a principal organization from the Russian side for participation in the 7th IADC re-entry test campaign on CORONAS-F. The CORONAS-F flight features and space environments circumstances during its flight as well as a methodology and technology of spacecraft ballistic and navigational support are given below. The BNS results for different phases of S/C flight, including the results of its re-entry predictions, obtained during the realization of the 7th IADC test campaign are submitted. The accuracy of space vehicle re-entry prediction and its dependence on various factors are analyzed in more details.

Ivanov, N. M.↗
NASA NTRS1979

The space transportation system

Design features of the Space Shuttle orbiter vehicle, main engine, solid rocket booster, external tank, and inertial and spinning solid upper stages are presented. Space Shuttle facilities at Kennedy Space Center are discussed, together with the long duration exposure facility, a reusable, unmanned gravity-gradient stabilized, free-flying structure which can accomodate both active and passive experiments requiring long-term space exposure. Standard and optional Shuttle services are outlined, and preliminary flight assignments are described.

Hamon, W. J.↗
NASA NTRS2007

Video Guidance Sensor and Time-of-Flight Rangefinder

A proposed video guidance sensor (VGS) would be based mostly on the hardware and software of a prior Advanced VGS (AVGS), with some additions to enable it to function as a time-of-flight rangefinder (in contradistinction to a triangulation or image-processing rangefinder). It would typically be used at distances of the order of 2 or 3 kilometers, where a typical target would appear in a video image as a single blob, making it possible to extract the direction to the target (but not the orientation of the target or the distance to the target) from a video image of light reflected from the target. As described in several previous NASA Tech Briefs articles, an AVGS system is an optoelectronic system that provides guidance for automated docking of two vehicles. In the original application, the two vehicles are spacecraft, but the basic principles of design and operation of the system are applicable to aircraft, robots, objects maneuvered by cranes, or other objects that may be required to be aligned and brought together automatically or under remote control. In a prior AVGS system of the type upon which the now-proposed VGS is largely based, the tracked vehicle is equipped with one or more passive targets that reflect light from one or more continuous-wave laser diode(s) on the tracking vehicle, a video camera on the tracking vehicle acquires images of the targets in the reflected laser light, the video images are digitized, and the image data are processed to obtain the direction to the target. The design concept of the proposed VGS does not call for any memory or processor hardware beyond that already present in the prior AVGS, but does call for some additional hardware and some additional software. It also calls for assignment of some additional tasks to two subsystems that are parts of the prior VGS: a field-programmable gate array (FPGA) that generates timing and control signals, and a digital signal processor (DSP) that processes the digitized video images. The additional timing and control signals generated by the FPGA would cause the VGS to alternate between an imaging (direction-finding) mode and a time-of-flight (range-finding mode) and would govern operation in the range-finding mode.

Bryan, Thomas↗