Results for “space science missions” — Page 18

NASA NTRSDate not supplied

Biological Research and Space Health Enabled by Machine Learning to Support Deep Space Missions

A key science goal of the NASA “Moon to Mars” campaign is to understand how biology responds to the Lunar, Martian, and deep space environments in order to advance fundamental knowledge, reduce risk, and support safe, productive human space missions. Through the powerful emerging computer science approaches of artificial intelligence (AI) and machine learning (ML), a paradigm shift has begun in biomedical science and engineered astronaut health systems, to enable Earth-independence and autonomy of mission operations. We present a decadal view of AI/ML architecture to support deep space mission goals, developed in concert with leaders in the field. We describe current AI/ML methods to support 1) fundamental biology, 2) in situ analytics, 3) high performance computing hardware, 4) automated science, 5) self-driving labs, 6) remote data management, 7) integrated real-time mission biomonitoring, and 8) a Precision Space Health system. Cutting-edge AI/ML approaches that can be integrated to support these domains include active learning, explainable AI, adaptive learning, causal inference, knowledge graphs, federated learning, transfer learning, and large language models. Finally, we present results from several current ML projects that are underway in the field to address key challenges of small sample n, high feature count, heterogeneity, and sparse data. These include 1) connecting omics data to phenotypic data using an ensemble model to infer causality of spaceflight rodent liver health disruption, 2) usage of explainable ML to interrogate the muscular underpinnings of spaceflight muscle atrophy, 3) ML models analyzing and determining directed acyclic graphs of human space health risk leveraging rodent bone datasets, 4) usage of large pre-trained models connecting biomedical knowledgebases with small spaceflight datasets to understand gene-to-gene interaction networks, and 5) a suite of benchmarked open science datasets (spaceflight mouse liver; radiation DNA damage) enabling programmers to identify the best ML algorithms to answer space biological science questions.

space biology↗

NASA NTRSDate not supplied

Biological Research and Space Health Enabled by Machine Learning to Support Deep Space Missions

A key science goal of the NASA “Moon to Mars” campaign is to understand how biology responds to the Lunar, Martian, and deep space environments in order to advance fundamental knowledge, reduce risk, and support safe, productive human space missions. Through the powerful emerging computer science approaches of artificial intelligence (AI) and machine learning (ML), a paradigm shift has begun in biomedical science and engineered astronaut health systems, to enable Earth-independence and autonomy of mission operations. We present a decadal view of AI/ML architecture to support deep space mission goals, developed in concert with leaders in the field. We describe current AI/ML methods to support 1) fundamental biology, 2) in situ analytics, 3) high performance computing hardware, 4) automated science, 5) self-driving labs, 6) remote data management, 7) integrated real-time mission biomonitoring, and 8) a Precision Space Health system. Cutting-edge AI/ML approaches that can be integrated to support these domains include active learning, explainable AI, adaptive learning, causal inference, knowledge graphs, federated learning, transfer learning, and large language models. Finally, we present results from several current ML projects that are underway in the field to address key challenges of small sample n, high feature count, heterogeneity, and sparse data. These include 1) connecting omics data to phenotypic data using an ensemble model to infer causality of spaceflight rodent liver health disruption, 2) usage of explainable ML to interrogate the muscular underpinnings of spaceflight muscle atrophy, 3) ML models analyzing and determining directed acyclic graphs of human space health risk leveraging rodent bone datasets, 4) usage of large pre-trained models connecting biomedical knowledgebases with small spaceflight datasets to understand gene-to-gene interaction networks, and 5) a suite of benchmarked open science datasets (spaceflight mouse liver; radiation DNA damage) enabling programmers to identify the best ML algorithms to answer space biological science questions.

space biology↗

NASA NTRSDate not supplied

BioSentinel: Leading the Way for Deep Space CubeSat Missions

Flagship science missions are not alone in Deep Space thanks to BioSentinel, a 6U spacecraft launched on Artemis-1. BioSentinel is one of the longest operating CubeSats beyond cislunar space. The subsystems and COTS components of the BioSentinel bus are a template for future deep space missions, and the lessons learned from over a year of operations will enable improved performance for the next missions. BioSentinel achieved its unprecedented performance for an SLS secondary payload due to preparation, planning, and a robust design. Pre-launch antenna and interface testing with both DSN and ESA confirmed command and data pathways and allowed for operational flexibility in the critical early hours post-deployment. Mission Operations simulations prior to launch identified potential risks and primed operators to respond in flight, preparing the team to react quickly to successfully detumble the spacecraft and enter a power-positive state. The spacecraft would not have survived without the inclusion of the trailblazing 3D-printed composite cold gas propulsion system. The non-standard tank geometry enabled efficient use of the limited space available in the CubeSat, as well as the capability to detumble the spacecraft and manage momentum, while providing sufficient margin to execute potential delta-V maneuvers. The Iris radio has operated for over 18 months with no significant issues. Initial Iris performance estimates have been accurate throughout the mission. BioSentinel continues to collect data on thermal conditions and to validate our performance models with real-world knowledge. We have received exemplary support from our DSN partners. Following the conclusion of the primary science mission, the Linear Energy Transfer (LET) Spectrometer continued to collect solar and galactic radiation data from its location in heliocentric orbit. The free space dataset offered by the BioSentinel LET is a valuable source of data for model validation and future mission planning. As the spacecraft travels farther from Earth it is poised to provide longitudinally distributed measurements of solar particle events during solar maximum. The lessons learned from BioSentinel suggest key areas to enhance performance. The ability to upload modified flight software can increase the stability of memory management. Additional heaters in the propulsion system design have already proven successful on the Starling mission. Streamlining mission operations can reduce costs, increase data return, and better utilize DSN time. Enhancements such as these will facilitate reliable, long-duration deep space exploration using the proven BioSentinel 6U CubeSat bus.

BioSentinel↗

DOE OSTI2021

Mission Operations Center for Lawrence Livermore National Laboratory Space Science & Security Program

Space mission operations has grown in line with the development of new space and ground technology. Originally, the philosophy for a space mission was to keep the spacecraft as simple as possible and have as much of the mission complexity on the ground where engineers can fix, control and access things. This was mostly due to immature space technologies and associated risk, as well as cost to develop complex and capable ground stations was relatively cheaper than complex space missions. This led to large room withs multiple computers and an army of engineers and operators sitting at computers and monitoring specific spacecraft information during operations. With development of new space technologies, a lot of functions that were kept and constantly monitored on the ground have been automated and completely integrated into the spacecraft, reducing the number of operators and engineers needed to operate a mission. With the paradigm shift in increasing spacecraft technologies, improved computer technologies, and scaling down space mission size; the mission operations centers have also adapted to changes. More organizations are becoming space-faring institutions and have developed mission operations centers for their unique missions.

42 ENGINEERING↗

NASA NTRSDate not supplied

Biological Research and Space Health Enabled by Machine Learning to Support Deep Space Missions

A key science goal of the NASA “Moon to Mars” campaign is to understand how biology responds to the Lunar, Martian, and deep space environments in order to advance fundamental knowledge and support human space missions. Through artificial intelligence (AI) and machine learning (ML), a paradigm shift has begun in space biosciences and engineered astronaut health systems, to enable Earth-independence and mission operations autonomy. We describe current AI/ML methods to support 1) fundamental biology, 2) in situ analytics, 3) high performance computing, 4) automated science, 5) self-driving labs, 6) remote data management, 7) integrated mission biomonitoring, and 8) a Precision Space Health system. AI/ML approaches that can be integrated to support these domains include active learning, explainable AI, adaptive learning, causal inference, knowledge graphs, federated learning, transfer learning, and large language models. Finally, we present results from several current ML projects that are underway in the space biology field to address key challenges of small sample n, high feature count, heterogeneity, and sparse data. These include 1) connecting omics to phenotypic data using an ensemble model to infer causality of rodent liver health disruption, 2) usage of explainable ML to interrogate muscular underpinnings of muscle atrophy, 3) ML models analyzing and determining directed acyclic graphs of human health risk leveraging rodent bone datasets, 4) usage of large pre-trained models connecting biomedical knowledgebases with small spaceflight datasets to understand gene-to-gene interactions, and 5) a suite of benchmarked open science datasets enabling programmers to identify best algorithms to answer space biology questions.

space biology↗

NASA NTRS2013

Using NASA's Space Launch System to Enable Game Changing Science Mission Designs

NASA's Marshall Space Flight Center is directing efforts to build the Space Launch System (SLS), a heavy-lift rocket that will help restore U.S. leadership in space by carrying the Orion Multi-Purpose Crew Vehicle and other important payloads far beyond Earth orbit. Its evolvable architecture will allow NASA to begin with Moon fly-bys and then go on to transport humans or robots to distant places such as asteroids, Mars, and the outer solar system. Designed to simplify spacecraft complexity, the SLS rocket will provide improved mass margins and radiation mitigation, and reduced mission durations. These capabilities offer attractive advantages for ambitious missions such as a Mars sample return, by reducing infrastructure requirements, cost, and schedule. For example, if an evolved expendable launch vehicle (EELV) were used for a proposed mission to investigate the Saturn system, a complicated trajectory would be required with several gravity-assist planetary fly-bys to achieve the necessary outbound velocity. The SLS rocket, using significantly higher C3 energies, can more quickly and effectively take the mission directly to its destination, reducing trip times and cost. As this paper will report, the SLS rocket will launch payloads of unprecedented mass and volume, such as monolithic telescopes and in-space infrastructure. Thanks to its ability to co-manifest large payloads, it also can accomplish complex missions in fewer launches. Future analyses will include reviews of alternate mission concepts and detailed evaluations of SLS figures of merit, helping the new rocket revolutionize science mission planning and design for years to come.

Creech, Stephen D.↗

NASA NTRS2014

Investigation of the Effects of Cathode Flow Fraction and Position on the Performance and Operation of the High Voltage Hall Accelerator

The National Aeronautics and Space Administration (NASA) Science Mission Directorate In- Space Propulsion Technology office is sponsoring NASA Glenn Research Center (GRC) to develop a 4 kW-class Hall thruster propulsion system for implementation in NASA science missions. Tests were performed within NASA GRC Vacuum Facility 5 at background pressure levels that were six times lower than what has previously been attained in other vacuum facilities. A study was conducted to assess the impact of varying the cathode-to-anode flow fraction and cathode position on the performance and operational characteristics of the High Voltage Hall Accelerator (HiVHAc) thruster. In addition, the impact of injecting additional xenon propellant in the vicinity of the cathode was also assessed. Cathode-to-anode flow fraction sensitivity tests were performed for power levels between 1.0 and 3.9 kW. It was found that varying the cathode flow fraction from 5 to approximately 10% of the anode flow resulted in the cathode-to-ground voltage becoming more positive. For an operating condition of 3.8 kW and 500 V, varying the cathode position from a distance of closest approach to 600 mm away did not result in any substantial variation in thrust but resulted in the cathode-to-ground changing from -17 to -4 V. The change in the cathode-to-ground voltage along with visual observations indicated a change in how the cathode plume was coupling to the thruster discharge. Finally, the injection of secondary xenon flow in the vicinity of the cathode had an impact similar to increasing the cathode-to-anode flow fraction, where the cathode-to-ground voltage became more positive and discharge current and thrust increased slightly. Future tests of the HiVHAc thruster are planned with a centrally mounted cathode in order to further assess the impact of cathode position on thruster performance.

Cathode Coupling↗

NASA NTRS1990

United States microgravity programs

The U.S. Microgravity Program encompasses research initiatives of the NASA Office of Space Science and Applications and Office of Commercial Programs. NASA involvement in space missions extends to the U.S Microgravity Laboratory, the International Microgravity Laboratory, the Space Life Sciences Mission, and planned activities aboard the Japanese and German Spacelab missions. Flight programs under the aegis of NASA's Centers for the Commercial Development of Space will employ the Space Shuttle-based Commercial Middeck Augmentation Module and the Suborbital and Orbital Expendable Launch Vehicles. The projected Space Station will include a significant microgravity program.

Ott, Richard H.↗

NASA NTRSDate not supplied

Biological Research and Space Health Enabled by Machine Learning to Support Deep Space Missions

A key science goal of the NASA “Moon to Mars” campaign is to understand how biology responds to the Lunar, Martian, and deep space environments in order to advance fundamental knowledge, reduce risk, and support safe, productive human space missions. Through the powerful emerging approaches of artificial intelligence (AI) and machine learning (ML), a paradigm shift has begun in biomedical science and engineered astronaut health systems, to enable Earth independence and autonomy of mission operations. Here we present an overview of AI/ML architecture to support deep space mission goals, developed with leaders in the field. First, we focus on the fundamental biological research that supports our understanding of physiological responses to spaceflight, and we describe current efforts to support AI/ML research including data standardization and data engineering through maximally open and FAIR (findable, accessible, interoperable, reusable) databases and the generation of AI-ready datasets for reuse and analysis. We also discuss remote data management frameworks for research data as well as environmental and health data that are generated during deep space missions. We highlight several research projects that leverage data standardization and management for fundamental biological discovery to uncover the complex effects of space travel on living systems. Next, we provide an overview of cutting-edge AI/ML approaches that can be integrated to support remote monitoring and analysis during deep space missions, including generative models and large language models to learn the underlying biomedical patterns and predict outcomes or answer questions during off world medical scenarios. We also describe current AI/ML methods to support this research and monitoring through automated cloud-based labs which enable limited human intervention and closed-loop experimentation in remote settings. These labs could support mission autonomy by analyzing environmental data streams, and would be facilitated through in situ analytics capabilities to avoid sending large raw data files through low bandwidth communications. Finally, in the context of deep space missions with limited communications or access to medical advice from Earth, we describe a solution for integrated, real-time mission biomonitoring across hierarchical levels from continuous environmental monitoring, to wearables and point-of-care devices, to molecular and physiological monitoring. We introduce a precision space health system that will ensure that the future of space health is predictive, preventative, participatory and personalized.

artificial intelligence↗

NASA NTRS1987

JPL future missions and energy storage technology implications

The mission model for JPL future programs is presented. This model identifies mission areas where JPL is expected to have a major role and/or participate in a significant manner. These missions are focused on space science and applications missions, but they also include some participation in space station activities. The mission model is described in detail followed by a discussion on the needs for energy storage technology required to support these future activities.

Pawlik, Eugene V.↗

NASA NTRSDate not supplied

NASA’s Space Launch System: High C3 Launch Capability for Science Missions

As NASA’s initial Space Launch System (SLS) Block 1 vehicle enters integration and stacking operations at Kennedy Space Center (KSC) this year in preparation for a 2021 launch, work is in progress on future more powerful variants of the vehicle. Available in the mid 2020s and 2030s, Block 1B and Block 2 will feature increased performance and unparalleled volume for payloads, providing an enabling launch option for science mission planners. The baseline SLS architecture consists of two five-segment solid rocket boosters and four RS-25 LH2/LOX engines. The evolved Block 1B and Block 2 vehicles use a four-engine LH2/LOX upper stage and can be outfitted with an 8.4 m-diameter pay-load fairing. Additional upper stages can be packaged in the 8.4 m fairing to enable high C3 (in the range of 300 km2/sec2) missions to Mercury, the Jovian system, the ice giants, the Kuiper Belt and beyond.

Stephen D Creech↗

NASA NTRS2008

Gas Foil Bearing Misalignment and Unbalance Effects

The effects of misalignment and unbalance on gas foil bearings are presented. The future of U.S. space exploration includes plans to conduct science missions aboard space vehicles, return humans to the Moon, and place humans on Mars. All of these endeavors are of long duration, and require high amounts of electrical power for propulsion, life support, mission operations, etc. One potential source of electrical power of sufficient magnitude and duration is a nuclear-fission-based system. The system architecture would consist of a nuclear reactor heat source with the resulting thermal energy converted to electrical energy through a dynamic power conversion and heat rejection system. Various types of power conversion systems can be utilized, but the Closed Brayton Cycle (CBC) turboalternator is one of the leading candidates. In the CBC, an inert gas heated by the reactor drives a turboalternator, rejects excess heat to space through a heat exchanger, and returns to the reactor in a closed loop configuration. The use of the CBC for space power and propulsion is described in more detail in the literature (Mason, 2003). In the CBC system just described, the process fluid is a high pressure inert gas such as argon, krypton, or a helium-xenon mixture. Due to the closed loop nature of the system and the associated potential for damage to components in the system, contamination of the working fluid is intolerable. Since a potential source of contamination is the lubricant used in conventional turbomachinery bearings, Gas Foil Bearings (GFB) have high potential for the rotor support system. GFBs are compliant, hydrodynamic journal and thrust bearings that use a gas, such as the CBC working fluid, as their lubricant. Thus, GFBs eliminate the possibility of contamination due to lubricant leaks into the closed loop system. Gas foil bearings are currently used in many commercial applications, both terrestrial and aerospace. Aircraft Air Cycle Machines (ACMs) and ground-based microturbines have demonstrated histories of successful long-term operation using GFBs (Heshmat et al., 2000). Small aircraft propulsion engines, helicopter gas turbines, and high-speed electric motors are potential future applications.

Howard, Samuel A.↗

NASA NTRS1995

Visualization: A pathway to enhanced scientific productivity in the expanding missions of Space and Earth Sciences

The movement toward the solution of problems involving large-scale system science, the ever-increasing capabilities of three-dimensional, time-dependent numerical models, and the enhanced capabilities of 'in situ' and remote sensing instruments bring a new era of scientific endeavor that requires an important change in our approach to mission planning and the task of data reduction and analysis. Visualization is at the heart of the requirements for a much-needed enhancement in scientific productivity as we face these new challenges. This article draws a perspective on the problem as it crosses discipline boundaries from solar physics to atmospheric and ocean sciences. It also attempts to introduce visualization as a new approach to scientific discovery and a tool which expedites and improves our insight into physically complex problems. A set of simple illustrations demonstrates a number of visualization techniques and the discussion emphasizes the trial-and-error and search-and-discover modes that are necessary for the techniques to reach their full potential. Further discussions also point to the importance of integrating data access, management, mathematical operations, and visualization into a single system. Some of the more recent developments in this area are reviewed.

Szuszczewicz, E. P.↗

NASA NTRS2019

NASA's Space Launch System: Payload Opportunities for Lunar Exploration, Science Missions

Nearing its first launch, the Space Launch System (SLS), NASA’s new super heavy-lift launch vehicle, offers highly energetic launches that deliver more mass and provide more volume in 8.4 m-diameter and potentially larger fairings to make a new generation of deep space missions possible. An evolvable launcher available in crew, crew with a co-manifested payload (CPL) and cargo-only configurations, SLS is a crucial capability to enable astronauts to return to the Moon, but it also offers key benefits for science missions. NASA’s 21st-century return to the Moon recently received a formal name: the Artemis program. In addition to the core enabling capabilities of SLS and the Orion crew spacecraft, NASA will also enlist international and commercial partnerships for Artemis. The Agency intends to build a scientific outpost in lunar orbit, the Gateway, from which human and robotic missions to and from the surface can rendezvous. SLS will launch Orion on a series of missions leading to landing the first woman and the next man on the Moon as part of Artemis. SLS uses proven propulsion systems: two solid rocket boosters and four RS-25s engines that have been upgraded to provide more thrust and operate in the SLS environment. SLS Block 1 uses a modified Delta IV Heavy upper stage, called the Interim Cryogenic Propulsion Stage (ICPS) and lifts at least 26 metric tons (t) to trans-lunar injection (TLI). The Block 1 vehicle can also be outfitted with a 5 m-diameter fairing. Block 1B, the next major variant, also uses solid rocket boosters and RS-25 engines to achieve Earth escape velocity, but replaces the single-engine liquid hydrogen (LH2)/liquid oxygen (LOX) ICPS with a four-engine LH2/LOX Exploration Upper Stage (EUS) to increase mass to TLI to 34-37 t, depending on crew or cargo configuration. In the Block 1B crew configuration, a 10 m-tall Universal Stage Adapter (USA) connects the vehicle to Orion and can carry a CPL up to 10 t. The USA provides 286 m3 of unpressurized volume for payloads. For large payloads, 8.4 m- and 10 m-diameter cargo fairings in 19.1 m and 27.4 m lengths are possible. The ultimate SLS vehicle, Block 2, incorporates evolved boosters to reach a lift capacity of more than 45 t to TLI. The capabilities of SLS not only make new missions to the Moon possible, but also game-changing science missions, such as deployment of large-aperture space telescopes, spacecraft to the ice giants or even probes to the interstellar medium. This paper will discuss the capabilities of SLS, the vehicle’s planned evolution, missions that can effectively utilize the vehicle and manufacturing status of the vehicle.

Creech, Stephen D.↗

NASA NTRS2019

NASA's Space Launch System: Payload Opportunities for Lunar Exploration, Science Missions

Nearing its first launch, the Space Launch System (SLS), NASA’s new super heavy-lift launch vehicle, offers highly energetic launches that deliver more mass and provide more volume in 8.4 m-diameter and potentially larger fairings to make a new generation of deep space missions possible. An evolvable launcher available in crew, crew with a co-manifested payload (CPL) and cargo-only configurations, SLS is a crucial capability to enable astronauts to return to the Moon, but it also offers key benefits for science missions. NASA’s 21st-century return to the Moon recently received a formal name: the Artemis program. In addition to the core enabling capabilities of SLS and the Orion crew spacecraft, NASA will also enlist international and commercial partnerships for Artemis. The Agency intends to build a scientific outpost in lunar orbit, the Gateway, from which human and robotic missions to and from the surface can rendezvous. SLS will launch Orion on a series of missions leading to landing the first woman and the next man on the Moon as part of Artemis. SLS uses proven propulsion systems: two solid rocket boosters and four RS-25s engines that have been upgraded to provide more thrust and operate in the SLS environment. SLS Block 1 uses a modified Delta IV Heavy upper stage, called the Interim Cryogenic Propulsion Stage (ICPS) and lifts at least 26 metric tons (t) to trans-lunar injection (TLI). The Block 1 vehicle can also be outfitted with a 5 m-diameter fairing. Block 1B, the next major variant, also uses solid rocket boosters and RS-25 engines to achieve Earth escape velocity, but replaces the single-engine liquid hydrogen (LH2)/liquid oxygen (LOX) ICPS with a four-engine LH2/LOX Exploration Upper Stage (EUS) to increase mass to TLI to 34-37 t, depending on crew or cargo configuration. In the Block 1B crew configuration, a 10 m-tall Universal Stage Adapter (USA) connects the vehicle to Orion and can carry a CPL up to 10 t. The USA provides 286 m3 of unpressurized volume for payloads. For large payloads, 8.4 m- and 10 m-diameter cargo fairings in 19.1 m and 27.4 m lengths are possible. The ultimate SLS vehicle, Block 2, incorporates evolved boosters to reach a lift capacity of more than 45 t to TLI. The capabilities of SLS not only make new missions to the Moon possible, but also game-changing science missions, such as deployment of large-aperture space telescopes, spacecraft to the ice giants or even probes to the interstellar medium. This paper will discuss the capabilities of SLS, the vehicle’s planned evolution, missions that can effectively utilize the vehicle and manufacturing status of the vehicle.

Creech, Steve↗

NASA NTRS1998

Deep Space 2: The Mars Microprobe Project and Beyond

The Mars Microprobe Project, or Deep Space 2 (DS2), is the second of the New Millennium Program planetary missions and is designed to enable future space science network missions through flight validation of new technologies. A secondary goal is the collection of meaningful science data. Two micropenetrators will be deployed to carry out surface and subsurface science. The penetrators are being carried as a piggyback payload on the Mars Polar Lander cruise ring and will be launched in January 1999. The microprobe has no active control, attitude determination, or propulsive systems. It is a single stage from separation until landing and will passively orient itself due to its aerodynamic design. The aeroshell will be made of a nonerosive heat shield material, Silicon impregnated Reusable Ceramic Ablator(SIRCA), developed at Ames Research Center. The aeroshell shatters on impact, at which time the probe separates into an aftbody that remains at the surface and a forebody that penetrates into the subsurface. Each probe has a total mass of up to 3 kg, including the aeroshell. The impact velocity will be about 180 meters per second. The forebody will experience up to 30,000 g's and penetrate between 0.3 and 2 meters, depending on the ice content of the soil. The aftbody deceleration will be up to 80,000 g. The penetrators arrive in December 1999. The landing ellipse latitude range is 73 deg-77 deg S. The longitude will be selected by the Mars Surveyor Project to place the lander on the polar layered deposits in the range of 180 deg -230 deg W. The two micropenetrators are likely to land within 100 km of the Mars Surveyor Lander, on the polar deposits. The likely arrival date is L(sub s) = 256, late southern spring. The nominal mission lasts 2 days. A science team was selected in April 1998.

Smrekar, S. E.↗

NASA NTRS1999

New Millenium Program Serving Earth and Space Sciences

A cross-Enterprise program is to identify and validate flight breakthrough technologies that will significantly benefit future space science and earth science missions. The breakthrough technologies are: enable new capabilities to meet earth and space science needs and reducing costs of future missions. The flight validation are: mitigates risks to first users and enables rapid technology infusion into future missions.

Li, Fuk↗

NASA NTRS2004

SIM PlanetQuest: Science with the Space Interferometry Mission

SIM - the Space Interferometry Mission - will perform precision optical astrometry on objects as faint as R magnitude 20. It will be the first space-based astrometric interferometer, operating in the optical band with a 10-m baseline. The Project is managed by the Jet Propulsion Laboratory, California Institute of Technology, in close collaboration with two industry partners, Lockheed Martin Missiles and Space, and TRW Inc., Space and Electronics Group. Launch of SIM is currently planned for 2009. In its wide-angle astrometric mode, SIM will yield 4 microarcsecond absolute position and parallax measurements. Astrometric planet searches will be done in a narrow-angle mode, with an accuracy of 4 microarcseconds or better in a single measurement. As a pointed rather than a survey instrument, SIM will maintain.its astrometric accuracy down to the faintest, magnitudes, opening up the opportunity for astrometry of active galactic nuclei to better than 10 pas. SIM will define a new astrometric reference frame, using a grid of approximately 1500 stars with positions accurate to 4 microarcseconds. The SIM Science Team comprises the Principal Investigators of ten Key Projects, and five Mission Scientists contributing their expertise to specific areas of the mission. Their science programs cover a wide range of topics in Galactic and extragalactic astronomy. They include: searches for low-mass planets - including analogs to our own solar system - tlie formation and dynamics of our Galaxy, calibration of the cosmic distance scale, and fundamental stellar astrophysics. All of the science observing on SIM is competitively awarded; the Science Team programs total about 40% of the total available, and the remainder will be assigned via future NASA competitions. This report is a compilation of science summaries by members of the Science Team, and it illustrates the wealth of scientific problems that microarcsecond-precision astrometry can contribute to. More information on SIM, including copies of this report, may be obtained from the project web site, at http://sim. jpl.nasa.gov.

Unwin, Stephen↗