Lessons learned from five years of multi-mission operations
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multi-mission operations multi-mission operations↗
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Mission analysis for design of a SEP multi-mission spacecraft.
Study of the multimission capability of a solar electric propulsion spacecraft. The study includes such factors as spacecraft constraints, payload variations with launch opportunity, propellant on-loading and off-loading requirements, and limitations in thrusting time, throttling range and steering. The study determined that a single spacecraft design, with P sub zero = 12 kW and I sub s = 3000 sec launched by a Titan IIIC or Titan IIID/Centaur can be used to conduct at least five diverse missions: Eros rendezvous, 1 AU out-of-ecliptic, Mercury orbiter, Jupiter flyby/probe, and Jupiter orbiter. Flight time and injection velocity vary as needed to achieve the desired payload capability. The mission analysis approach and results are presented.
Driver, J. M.↗
Multi-Mission Radioisotope Thermoelectric Generator Experience on Mars
The Mars Science Laboratory (MSL) Curiosity rover has been operating on Mars using the F1 Multi-Mission Radioisotope Thermoelectric Generator (MMRTG) for over one and one-half Mars years (over three Earth years). During this extended period, Curiosity has provided a wealth of information about operating with a MMRTG in the Mars surface environment. This paper discusses MMRTG performance over the life of the mission as affected not only by expected radioisotope degradation, but also by the thermal environment, including seasonal, wind, and time-of-sol effects. Additionally, issues related to MMRTG internal shorts will be discussed including detection, impacts on operations, and clearing the shorts.
RTG↗
Standard power regulator for the multi-mission modular spacecraft
The Standard Power Regulator Unit (SPRU) which forms the central building block of the Modular Power Subsystem (MPS) for the Multi-mission Modular Spacecraft (MMS) is described. A functional description of the SPRU is presented, detailing key design features, operational characteristics, and internal redundancy as well as giving block and schematic diagrams for all major subassemblies. The description of a qualification test program consisting of ten sequences ranging from a physical examination of the unit to calculating vibration and sine sweep of power on shock tests is presented. The results showed that some significant anomalies were encountered but no catastrophic failures were indicated, although several power module failures were found due to overvoltage malfunctions of the solar array stimulator.
Kichak, R. A.↗
A Multi-Mission Deep Space Telecommunications Analysis Tool: The Telecom Forecaster Predictor
The Telecom Forecaster Predictor (TFP) fulfills the need for a powerful, easily adaptable, multi-mission telecommunications analysis tool.
Telecom Forecaster Predictor TFP Telecom Analysis ↗
Environmental Controls and Life Support System (ECLSS) Design for a Multi-Mission Space Exploration Vehicle (MMSEV)
Engineers at Johnson Space Center (JSC) are developing an Environmental Control and Life Support System (ECLSS) design for the Multi-Mission Space Exploration Vehicle (MMSEV). The purpose of the MMSEV is to extend the human exploration envelope for Lunar, Near Earth Object (NEO), or Deep Space missions by using pressurized exploration vehicles. The MMSEV, formerly known as the Space Exploration Vehicle (SEV), employs ground prototype hardware for various systems and tests it in manned and unmanned configurations. Eventually, the system hardware will evolve and become part of a flight vehicle capable of supporting different design reference missions. This paper will discuss the latest MMSEV ECLSS architectures developed for a variety of design reference missions, any work contributed toward the development of the ECLSS design, lessons learned from testing prototype hardware, and the plan to advance the ECLSS toward a flight design.
Stambaugh, Imelda↗
Environmental Controls and Life Support System (ECLSS) Design for a Multi-Mission Space Exploration Vehicle (MMSEV)
Engineers at Johnson Space Center (JSC) are developing an Environmental Control and Life Support System (ECLSS) design for the Multi-Mission Space Exploration Vehicle (MMSEV). The purpose of the MMSEV is to extend the human exploration envelope for Lunar, Near Earth Object (NEO), or Deep Space missions by using pressurized exploration vehicles. The MMSEV, formerly known as the Space Exploration Vehicle (SEV), employs ground prototype hardware for various systems and tests it in manned and unmanned configurations. Eventually, the system hardware will evolve and become part of a flight vehicle capable of supporting different design reference missions. This paper will discuss the latest MMSEV ECLSS architectures developed for a variety of design reference missions, any work contributed toward the development of the ECLSS design, lessons learned from testing prototype hardware, and the plan to advance the ECLSS toward a flight design.
Stambaugh, Imelda↗
Development Of FIAT-Based Thermal Protection System Mass Estimating Relationships For NASA's Multi-Mission Earth Entry Concept
Mass Estimating Relationships (MERs) have been developed for use in the Program to Optimize Simulated Trajectories II (POST2) as part of NASA's multi-mission Earth Entry Vehicle (MMEEV) concept. MERs have been developed for the thermal protection systems of PICA and of Carbon Phenolic atop Advanced Carbon-Carbon on the forebody and for SIRCA and Acusil II on the backshell. How these MERs were developed, the resulting equations, model limitations, and model accuracy are discussed herein.
Sepka, Steven↗
Development of FIAT-based Thermal Protection System Mass Estimating Relationships for NASA's Multi-Mission Earth Entry Concep
Mass Estimating Relationships (MERs) have been developed for use in the Program to Optimize Simulated Trajectories II (POST2) as part of NASA's multi-mission Earth Entry Vehicle (MMEEV) concept. MERs have been developed for the thermal protection systems of PICA and of Carbon Phenolic atop Advanced Carbon-Carbon on the forebody and for SIRCA and Acusil II on the backshell. How these MERs were developed, the resulting equations, model limitations, and model accuracy are discussed herein.
MER↗
Multi-Mission Space Exploration Vehicle Concept Simulation of Operations in Proximity to a Near Earth Object
This paper details a project to simulate the dynamics of a proposed Multi-Mission Space Exploration Vehicle (MMSEV), and modeling the control of this spacecraft. A potential mission of the MMSEV would be to collect samples from a Near-Earth Object (NEO), a mission which would require the spacecraft to be able to navigate to an orbit keeping it stationary over an area of a spinning asteroid while a robotic arm interacts with the surface.
Near Earth Object (NEO)↗
SHARP: A multi-mission AI system for spacecraft telemetry monitoring and diagnosis
The Spacecraft Health Automated Reasoning Prototype (SHARP) is a system designed to demonstrate automated health and status analysis for multi-mission spacecraft and ground data systems operations. Telecommunications link analysis of the Voyager II spacecraft is the initial focus for the SHARP system demonstration which will occur during Voyager's encounter with the planet Neptune in August, 1989, in parallel with real-time Voyager operations. The SHARP system combines conventional computer science methodologies with artificial intelligence techniques to produce an effective method for detecting and analyzing potential spacecraft and ground systems problems. The system performs real-time analysis of spacecraft and other related telemetry, and is also capable of examining data in historical context. A brief introduction is given to the spacecraft and ground systems monitoring process at the Jet Propulsion Laboratory. The current method of operation for monitoring the Voyager Telecommunications subsystem is described, and the difficulties associated with the existing technology are highlighted. The approach taken in the SHARP system to overcome the current limitations is also described, as well as both the conventional and artificial intelligence solutions developed in SHARP.
Lawson, Denise L.↗
SHARP - A multi-mission AI system for spacecraft telemetry monitoring and diagnosis
The Spacecraft Health Automated Reasoning Prototype (SHARP) is a system designed to demonstrate automated health and status analysis for multi-mission spacecraft and ground data systems operations. Telecommunications link analysis of the Voyager II spacecraft is the initial focus for the SHARP system demonstration which will occur during Voyager's encounter with the planet Neptune in August, 1989, in parallel with real-time Voyager operations. The SHARP system combines conventional computer science methodologies with artificial intelligence techniques to produce an effective method for detecting and analyzing potential spacecraft and ground systems problems. The system performs real-time analysis of spacecraft and other related telemetry, and is also capable of examining data in historical context. A brief introduction is given to the spacecraft and ground systems monitoring process at the Jet Propulsion Laboratory. The current method of operation for monitoring the Voyager Telecommunications subsystem is described, and the difficulties associated with the existing technology are highlighted. The approach taken in the SHARP system to overcome the current limitations is also described, as well as both the conventional and artificial intelligence solutions developed in SHARP.
Lawson, Denise L.↗
SHARP: A multi-mission artificial intelligence system for spacecraft telemetry monitoring and diagnosis
The Spacecraft Health Automated Reasoning Prototype (SHARP) is a system designed to demonstrate automated health and status analysis for multi-mission spacecraft and ground data systems operations. Telecommunications link analysis of the Voyager 2 spacecraft is the initial focus for the SHARP system demonstration which will occur during Voyager's encounter with the planet Neptune in August, 1989, in parallel with real time Voyager operations. The SHARP system combines conventional computer science methodologies with artificial intelligence techniques to produce an effective method for detecting and analyzing potential spacecraft and ground systems problems. The system performs real time analysis of spacecraft and other related telemetry, and is also capable of examining data in historical context. A brief introduction is given to the spacecraft and ground systems monitoring process at the Jet Propulsion Laboratory. The current method of operation for monitoring the Voyager Telecommunications subsystem is described, and the difficulties associated with the existing technology are highlighted. The approach taken in the SHARP system to overcome the current limitations is also described, as well as both the conventional and artificial intelligence solutions developed in SHARP.
Lawson, Denise L.↗
Artificial intelligence for multi-mission planetary operations
A brief introduction is given to an automated system called the Spacecraft Health Automated Reasoning Prototype (SHARP). SHARP is designed to demonstrate automated health and status analysis for multi-mission spacecraft and ground data systems operations. The SHARP system combines conventional computer science methodologies with artificial intelligence techniques to produce an effective method for detecting and analyzing potential spacecraft and ground systems problems. The system performs real-time analysis of spacecraft and other related telemetry, and is also capable of examining data in historical context. Telecommunications link analysis of the Voyager II spacecraft is the initial focus for evaluation of the prototype in a real-time operations setting during the Voyager spacecraft encounter with Neptune in August, 1989. The preliminary results of the SHARP project and plans for future application of the technology are discussed.
Atkinson, David J.↗
A Comprehensive Structural Dynamic Analysis Approach for Multi Mission Earth Entry Vehicle (MMEEV) Development
The anticipated NASA Mars Sample Return Mission (MSR) requires a simple and reliable method in which to return collected Martian samples back to earth for scientific analysis. The Multi-Mission Earth Entry Vehicle (MMEEV) is NASA's proposed solution to this MSR requirement. Key aspects of the MMEEV are its reliable and passive operation, energy absorbing foam-composite structure, and modular impact sphere (IS) design. To aid in the development of an EEV design that can be modified for various missions requirements, two fully parametric finite element models were developed. The first model was developed in an explicit finite element code and was designed to evaluate the impact response of the vehicle and payload during the final stage of the vehicle's return to earth. The second model was developed in an explicit code and was designed to evaluate the static and dynamic structural response of the vehicle during launch and reentry. In contrast to most other FE models, built through a Graphical User Interface (GUI) pre-processor, the current model was developed using a coding technique that allows the analyst to quickly change nearly all aspects of the model including: geometric dimensions, material properties, load and boundary conditions, mesh properties, and analysis controls. Using the developed design tool, a full range of proposed designs can quickly be analyzed numerically and thus the design trade space for the EEV can be fully understood. An engineer can then quickly reach the best design for a specific mission and also adapt and optimize the general design for different missions.
Perino, Scott↗
Detection of Rossby Waves in Multi-Parameters in Multi-Mission Satellite Observations and HYCOM Simulations in the Indian Ocean
Rossby waves are difficult to detect with in situ methods. However, as we show in this paper, they can be clearly identified in multi-parameters in multi-mission satellite observations of sea surface height (SSH), sea surface temperature (SST) and ocean color observations of chlorophyll-a (chl-a), as well as 1/12-deg global HYbrid Coordinate Ocean Model (HYCOM) simulations of SSH, SST and sea surface salinity (SSS) in the Indian Ocean. While the surface structure of Rossby waves can be elucidated from comparisons of the signal in different sea surface parameters, models are needed to gain direct information about how these waves affect the ocean at depth. The first three baroclinic modes of the Rossby waves are inferred from the Fast Fourier Transform (FFT), and two-dimensional Radon Transform (2D RT). At many latitudes the first and second baroclinic mode Rossby wave phase speeds from satellite observations and model parameters are identified.
SSH (SEA SURFACE HEIGHT)↗
Object-oriented technologies in a multi-mission data system
The Operations Engineering Laboratory (OEL) at JPL is developing new technologies that can provide more efficient and productive ways of doing business in flight operations. Over the past three years, we have worked closely with the Multi-Mission Control Team to develop automation tools, providing technology transfer into operations and resulting in substantial cost savings and error reduction. The OEL development philosophy is characterized by object-oriented design, extensive reusability of code, and an iterative development model with active participation of the end users. Through our work, the benefits of object-oriented design became apparent for use in mission control data systems. Object-oriented technologies and how they can be used in a mission control center to improve efficiency and productivity are explained. The current research and development efforts in the JPL Operations Engineering Laboratory are also discussed to architect and prototype a new paradigm for mission control operations based on object-oriented concepts.
Murphy, Susan C.↗
Joint ESA-NASA Multi-Mission Algorithm and Analysis Platform (MAAP)
The scientific community is faced with a need for greatly improved data sharing, analysis, visualization and advanced collaboration based firmly on open science principles. Recent and upcoming launches of new satellite missions with more complex and voluminous data, as well as the ever more urgent need to better understand the global carbon budget and related ecological processes, provided the immediate rational for the ESA-NASA Multi-mission Algorithm and Analysis Platform (MAAP). This highly collaborative joint project of ESA and NASA established a framework between ESA and NASA to share data, science algorithms and compute resources in order to foster and accelerate scientific research conducted by ESA and NASA EO data users. Presented to the public in October 2021, the current version of MAAP provides a common cloud-based platform with computing capabilities co-located with the data, a collaborative coding and analysis environment, and a set of interoperable tools and algorithms developed to support the estimation and visualization of global above-ground biomass. Data from the Global Ecosystem Dynamics Investigation (GEDI) mission on the International Space Station and the Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) have been instrumental in the first products of MAAP including the first comprehensive map of Boreal above-ground Biomass and a current Global Biomass Harmonization Activity, but the platform is also being specifically designed to support the forthcoming ESA Biomass mission and incorporate data from the upcoming NASA-ISRO SAR (NISAR) mission. While these missions and the corresponding research which includes airborne, field, and calibration/validation data collection and analyses, provide a wealth of data and information relating to global biomass estimation, they also present data storing, processing and sharing challenges. The NISAR mission alone will produce about 80TB/day. These large data volumes present a challenge that would otherwise place accessibility limits on the scientific community and impact scientific progress. Other challenges being addressed by MAAP include: 1) Enabling researchers to easily discover, process, visualize and analyze large volumes of data from both agencies; 2) Providing a wide variety of data in the same coordinate reference frame to enable comparison, analysis, data evaluation, and data generation; 3) Providing a version-controlled science algorithm development environment that supports tools, co-located data and processing resources; and 4) Addressing intellectual property and sharing challenges related to collaborative algorithm development and sharing of data and algorithms. MAAP products can be explored on the MAAP Dashboard at https://earthdata.nasa.gov/maap-biomass or the joint platform entrance at scimaap.net. MAAP also can be accessed through individual NASA (https://maap-project.org) and ESA (https://esa-maap.org/) landing pages.
cloud computing↗