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At least 883 records · Page 49

Assimilation of SMOS Retrieved Soil Moisture into the Land Information System

Soil moisture retrievals from the Soil Moisture and Ocean Salinity (SMOS) instrument are assimilated into the Noah land surface model (LSM) within the NASA Land Information System (LIS). Before assimilation, SMOS retrievals are bias-corrected to match the model climatological distribution using a Cumulative Distribution Function (CDF) matching approach. Data assimilation is done via the Ensemble Kalman Filter. The goal is to improve the representation of soil moisture within the LSM, and ultimately to improve numerical weather forecasts through better land surface initialization. We present a case study showing a large area of irrigation in the lower Mississippi River Valley, in an area with extensive rice agriculture. High soil moisture value in this region are observed by SMOS, but not captured in the forcing data. After assimilation, the model fields reflect the observed geographic patterns of soil moisture. Plans for a modeling experiment and operational use of the data are given. This work helps prepare for the assimilation of Soil Moisture Active/Passive (SMAP) retrievals in the near future.

Data Assimilation↗

Towards Human-Friendly Efficient Control of Multi-Robot Teams

This paper explores means to increase efficiency in performing tasks with multi-robot teams, in the context of natural Human-Multi-Robot Interfaces (HMRI) for command and control. The motivating scenario is an emergency evacuation by a transport convoy of unmanned ground vehicles (UGVs) that have to traverse, in shortest time, an unknown terrain. In the experiments the operator commands, in minimal time, a group of rovers through a maze. The efficiency of performing such tasks depends on both, the levels of robots' autonomy, and the ability of the operator to command and control the team. The paper extends the classic framework of levels of autonomy (LOA), to levels/hierarchy of autonomy characteristic of Groups (G-LOA), and uses it to determine new strategies for control. An UGVoriented command language (UGVL) is defined, and a mapping is performed from the human-friendly gesture-based HMRI into the UGVL. The UGVL is used to control a team of 3 robots, exploring the efficiency of different G-LOA; specifically, by (a) controlling each robot individually through the maze, (b) controlling a leader and cloning its controls to followers, and (c) controlling the entire group. Not surprisingly, commands at increased G-LOA lead to a faster traverse, yet a number of aspects are worth discussing in this context.

multi-robot control↗

Preliminary Results of the OCTL to OICETS Optical Link Experiment (OTOOLE)

JPL in collaboration with JAXA and NICT demonstrated a 50Mb/s downlink and 2Mb/s uplink bi-directional link with the LEO OICETS satellite. The experiments were conducted in May and June over a variety of atmospheric conditions. Bit error rates of 10-(sup 1) to less than 10-? were measured on the downlink. This paper describes the preparations, precursor experiments, and operations for the link. It also presents the analyzed downlink data results.

Table Mountain↗

Clinical Outcome Metrics for Optimization of Robust Training

Introduction: The emphasis of this research is on the Human Research Program (HRP) Exploration Medical Capability's (ExMC) "Risk of Unacceptable Health and Mission Outcomes Due to Limitations of In-Flight Medical Capabilities." Specifically, this project aims to contribute to the closure of gap ExMC 2.02: We do not know how the inclusion of a physician crew medical officer quantitatively impacts clinical outcomes during exploration missions. The experiments are specifically designed to address clinical outcome differences between physician and non-physician cohorts in both near-term and longer-term (mission impacting) outcomes. Methods: Medical simulations will systematically compare success of individual diagnostic and therapeutic procedure simulations performed by physician and non-physician crew medical officer (CMO) analogs using clearly defined short-term (individual procedure) outcome metrics. In the subsequent step of the project, the procedure simulation outcomes will be used as input to a modified version of the NASA Integrated Medical Model (IMM) to analyze the effect of the outcome (degree of success) of individual procedures (including successful, imperfectly performed, and failed procedures) on overall long-term clinical outcomes and the consequent mission impacts. The procedures to be simulated are endotracheal intubation, fundoscopic examination, kidney/urinary ultrasound, ultrasound-guided intravenous catheter insertion, and a differential diagnosis exercise. Multiple assessment techniques will be used, centered on medical procedure simulation studies occurring at 3, 6, and 12 months after initial training (as depicted in the following flow diagram of the experiment design). Discussion: Analysis of procedure outcomes in the physician and non-physician groups and their subsets (tested at different elapsed times post training) will allow the team to 1) define differences between physician and non-physician CMOs in terms of both procedure performance (pre-IMM analysis) and overall mitigation of the mission medical impact (IMM analysis); 2) refine the procedure outcome and clinical outcome metrics themselves; 3) refine or develop innovative medical training products and solutions to maximize CMO performance; and 4) validate the methods and products of this experiment for operational use in the planning, execution, and quality assurance of the CMO training process The team has finalized training protocols and developed a software training/testing tool in collaboration with Butler Graphics (Detroit, MI). In addition to the "hands on" medical procedure modules, the software includes a differential diagnosis exercise (limited clinical decision support tool) to evaluate the diagnostic skills of participants. Human subject testing will occur over the next year.

Ebert, D.↗

Efficient Entropy Stable Gauss Collocation Methods

The construction of high-order entropy stable collocation schemes on quadrilateral and hexahedral elements has relied on the use of Gauss-Legendre-Lobatto collocation points and their equivalence with summation-by-parts (SBP) finite difference operators. In this work, we show how to efficiently generalize the construction of semidiscrete, entropy stable schemes on tensor product elements to Gauss points and generalized SBP operators. Numerical experiments suggest 8 that the use of Gauss points significantly improves accuracy on curved meshes.

Jesse Chan↗

LunaNet: A Flexible and Extensible Lunar Exploration Communications and Navigation Infrastructure and the Inclusion of SmallSat Platforms

As NASA establishes a sustained presence on the Moon and ventures further into the solar system, the need for a robust interplanetary communications and navigation architecture increases. LunaNet, an extensible and scalable lunar communications and navigation architecture, is being developed to answer this growing need. The LunaNet architecture will provide users with three services: networking services, positioning, navigation and timing services, and science utilization services. With LunaNet in place, users will experience an operational environment similar to that experienced by users on Earth. The agency’s plan for solar system exploration necessitates both government and commercial participation, and the LunaNet architecture supports this goal as well, encouraging global participation from commercial and international partners, other government agencies, academia, and federally funded research development centers. This paper provides a high-level description of the LunaNet architecture, discusses how SmallSat platforms and technologies may provide critical capabilities, and defines the role that SmallSats can play within the architecture.

Communications↗

Recent Developments in Vertical Bloch Line Data Storage

Data storage systems based on vertical Bloch lines have been fabricated in 2 um bubble garnet material. The input/output line was fully operational, and experiments in reading and writing showed an encouraging correlation between input and output.

data↗

NASA Lunar Exploration – Gateway’s Power and Propulsion Element Communications Links

As a key part of NASA’s Artemis program to return to the moon, the Lunar Gateway will provide a platform for staging lunar missions, for gaining experience in operations beyond earth orbit, and for creating sustainable infrastructure. Of specific interest, the Lunar Gateway will provide communications support to landers, orbiters, and surface systems, including in the South Polar Region where direct line of sight (LOS) to Earth is limited or non-existent. A foundational segment of the Gateway is the Power and Propulsion Element (PPE), which will carry: solar arrays to provide power to the Gateway; electric propulsion to maintain the Gateway in its operational orbit; and communication links between the Earth and Gateway, the Moon and Gateway, and relays from the Moon to the Earth. PPE Communication Links include an X-band link to Earth for Command, Ranging, and Telemetry (CR&T), which also carries low to medium rate data; a Ka-band Direct to Earth(DTE) link for high rate data transmissions; and a Ka-band Lunar link for high data rate connections to lunar systems. This paper describes the PPE communication links from a technical perspective. Other Gateway links supported by other modules are outside the scope of this paper.

ARTEMIS↗

InSight Robotic Arm Testing Activities for HP3 Mole Anomaly Recovery on Mars

The InSight lander’s Heat Flow and Physical Properties Package (HP3) was deployed on Mars in February 2019and began attempting to penetrate to its target depth range of3-5 meters shortly thereafter. However, the mole’s downwardprogress stopped after only 35 cm of penetration. In response,the project convened an Anomaly Response Team (ART) andsince then has been attempting to diagnose the problem andassist the mole using the tools available on Mars. The key assetused in this effort has been the Instrument Deployment System(IDS), which includes two cameras and a robotic InstrumentDeployment Arm (IDA). Since the IDS was originally intendedonly to deploy InSight’s primary instruments to the Martiansurface, new testbed setups, experiments, and operational protocols (e.g., command sequences) were required and had to bedeveloped on a short timeline. The HP3 Mole ART first focusedon gathering all observable data on Mars about the state ofthe mole and Support Structure Assembly (SSA), as well asthe physical properties of the Martian regolith. This includedusing the robotic arm to point the IDC at the SSA duringdiagnostic hammering attempts to observe motion of the SSAand science tether. Images taken during these attempts revealedsome motion of the SSA, but no apparent change in mole depth.At JPL, the IDS and Testbed teams re-created the hardwareconfiguration on Mars based on limited knowledge of the mole’sstate. They devised and tested techniques to use the roboticarm and cameras to accomplish previously untested activitieson Mars, including imaging the HP3, using the IDA to interactwith the terrain, and using the IDA to move the SSA awayfrom the partially-embedded mole. The team executed the morepromising techniques on Mars. After diagnostic hammering onMars, the team decided to move the SSA to gain visibility ofthe mole’s configuration and access to the soil around the mole.After developing the technique and practicing the maneuver inthe InSight testbed, the team lifted the SSA on Mars and placedit behind the mole. This revealed a pit surrounding the nowexposed mole, observations of which provided essential cluesfor determining the root cause of the mole’s lack of progress.The IDS and Testbed teams altered the testbed to match thesituation on Mars. They devised IDA techniques to determinethe Martian soil properties and assist the mole’s descent. Theytested these techniques in the testbed and executed the more978-1-7281-2734-7/20/$31.00 c 2021 IEEE. Copyright 2020 CaliforniaInstitute of Technology. U.S. Government sponsorship acknowledged.promising ones on Mars. These include using the robotic arm toalter the regolith near the mole and to push on the mole while ithammers. This paper discusses the anomaly resolution testing inthe testbed at JPL, describes how the IDS team prepared for theanomaly recovery activities on Mars, and provides preliminaryresults of the efforts to assist the HP3 mole on Mars.

Kim, Junggon↗

InSight Robotic Arm Testing Activities for HP3 Mole Anomaly Recovery on Mars

The InSight lander’s Heat Flow and Physical Properties Package (HP3 ) was deployed on Mars in February 2019 and began attempting to penetrate to its target depth range of 3-5 meters shortly thereafter. However, the mole’s downward progress stopped after only 35 cm of penetration. In response, the project convened an Anomaly Response Team (ART) and since then has been attempting to diagnose the problem and assist the mole using the tools available on Mars. The key asset used in this effort has been the Instrument Deployment System (IDS), which includes two cameras and a robotic Instrument Deployment Arm (IDA). Since the IDS was originally intended only to deploy InSight’s primary instruments to the Martian surface, new testbed setups, experiments, and operational protocols (e.g., command sequences) were required and had to be developed on a short timeline. The HP3 Mole ART first focused on gathering all observable data on Mars about the state of the mole and Support Structure Assembly (SSA), as well as the physical properties of the Martian regolith. This included using the robotic arm to point the IDC (Instrument Deployment Camera) at the SSA during diagnostic hammering attempts to observe motion of the SSA and science tether. Images taken during these attempts revealed some motion of the SSA, but no apparent change in mole depth. At JPL, the IDS and Testbed teams re-created the hardware configuration on Mars based on limited knowledge of the mole’s state. They devised and tested techniques to use the robotic arm and cameras to accomplish previously untested activities on Mars, including imaging the HP3 , using the IDA to interact with the terrain, and using the IDA to move the SSA away from the partially-embedded mole. The team executed the more promising techniques on Mars. After diagnostic hammering on Mars, the team decided to move the SSA to gain visibility of the mole’s configuration and access to the soil around the mole. After developing the technique and practicing the maneuver in the InSight testbed, the team lifted the SSA on Mars and placed it behind the mole. This revealed a pit surrounding the now exposed mole, observations of which provided essential clues for determining the root cause of the mole’s lack of progress. The IDS and Testbed teams altered the testbed to match the situation on Mars. They devised IDA techniques to determine the Martian soil properties and assist the mole’s descent. They tested these techniques in the testbed and executed the more promising ones on Mars. These include using the robotic arm to alter the regolith near the mole and to push on the mole while it hammers. This paper discusses the anomaly resolution testing in the testbed at JPL, describes how the IDS team prepared for the anomaly recovery activities on Mars, and provides preliminary results of the efforts to assist the HP3 mole on Mars.

Kim, Junggon↗

Natural Language Understanding and Extraction of Flight Constraints Recorded in Letters of Agreement

This paper presents an automated information extraction and inference technique using natural language processing for extracting flight operational procedures and constraints embedded in heritage air traffic management documents. The extracted flight constraints can be digitized and fit into existing airspace information exchange models such as the Aeronautical Information Exchange Model (AIXM). This approach offers a digitized solution to disseminate airspace operating conditions to diverse air users and stakeholders in the National Airspace System (NAS). Furthermore, the digitized flight procedures can provide operational flexibility for emerging advanced air mobility providers and reduce traffic controller workload while maintaining current safety standards. To demonstrate this process, 1,972 Letters of Agreement (LOAs) have been selected for processing, named entity extraction, constraint identification and extraction. This dataset is derived from a subset of documents related to Air Route Traffic Control Centers (ARTCC) operations. We experimented with various traditional information extraction techniques, state-of-the-art machine learning and deep learning models to perform named entity recognition and pattern recognition on our dataset. We present the results from our experiments and demonstrate 99.0% F-1 score for named entity recognition, and a 96.6% accuracy for our entire workflow up to named entity recognition. We also discuss constraint definitions using generic patterned templates and extensions to this work in applying entity linking to digitally extracting relevant constraints.

Natural Language Processing↗

Natural Language Understanding and Extraction of Flight Constraints Recorded in Letters of Agreement

This paper presents an automated information extraction and inference technique using natural language processing for extracting flight operational procedures and constraints embedded in heritage air traffic management documents. The extracted flight constraints can be digitized and fit into existing airspace information exchange models such as the Aeronautical Information Exchange Model (AIXM). This approach offers a digitized solution to disseminate airspace operating conditions to diverse air users and stakeholders in the National Airspace System (NAS). Furthermore, the digitized flight procedures can provide operational flexibility for emerging advanced air mobility providers and reduce traffic controller workload while maintaining current safety standards. To demonstrate this process, 1,972 Letters of Agreement (LOAs) have been selected for processing, named entity extraction, constraint identification and extraction. This dataset is derived from a subset of documents related to Air Route Traffic Control Centers (ARTCC) operations. We experimented with various traditional information extraction techniques, state-of-the-art machine learning and deep learning models to perform named entity recognition and pattern recognition on our dataset. We present the results from our experiments and demonstrate 99.0% F-1 score for named entity recognition, and a 96.6% accuracy for our entire workflow up to named entity recognition. We also discuss constraint definitions using generic patterned templates and extensions to this work in applying entity linking to digitally extracting relevant constraints.

Natural Language Processing↗

Mars 2020 Perseverance Rover Surface Operations Commissioning Phase Overview

This paper presents work done by the Mars 2020 Project to plan, test, and execute the Mars 2020 Perseverance Rover surface operations commissioning phase. Immediately after the successful landing of Mars 2020 Perseverance rover at Jezero Crater on February 18, 2021, the rover autonomously initiated mission critical commanding necessary to transition the vehicle from a Cruise/EDL to Surface operations configuration. This began the surface operations commissioning phase, referred to as Surface Operations Transition (SOX). The objective of SOX phase is to establish vehicle health and safety and to verify that the operational characteristics of the vehicle, now operating in the Martian environment, are as-expected and safe to proceed into nominal operations. The SOX commissioning phase is organized into six logical sub-phases occurring in the following chronological order; (1) SOX1a, (2) FSW Transition, (3) SOX1b, (4) SOX2a, (5) Heli, (6) SOX2b. In total, the SOX commissioning phase was expected to take up-to 111 sols (Martian days). The Perseverance rover is an extremely complex, highly-integrated, robotic system-of-systems that requires numerous activities to incrementally and methodically verify their safe operations. This paper will discuss the development process used to plan, test, and execute the SOX commissioning phase for Mars 2020 Perseverance rover surface operations. We will discuss key challenges associated with SOX development as well as actual operations execution experience.

Koch, Justin↗

Designing the Imaging and Breadboard System for FBCE-TL Project

This presentation outlines the support work done on designing the imaging and breadboard system of the Transfer Line (TL) project, which is the third module for the Flow Boiling and Condensation Experiment (FBCE) operating in the Fluids Integrated Rack on-board the International Space Station (ISS). The goal of the FBCE is to serve as a facility for flow boiling and condensation investigating two-phase flow and heat transfer data in microgravity. The TL module aims use existing FBCE hardware to study cryogenic chilldown, a large component of cryogenic propellant tank transfer research. The TL test module will perform chilldown studies with normal-perfluorohexane (nPFH), a cryogenic simulant, flowing through a super-heated line, which is heated through the process of Joule-heating. SolidWorks and Creo were used to create electrically conductive pipe junctions that connect and seal several Indium Tin Oxide (ITO) coated sapphire tube sections together to allow for low leak probability fluid flow and circumferentially uniform electrical current density. It is necessary to understand and calculate the thermal expansion of the tubing sections such that the junctions would not leak at anticipated operating temperatures and pressures, would maintain electrical contact, and not crack the crystalline tubes. Optical imaging techniques were used to build an experimentally validated image remapping process for flight-like setups of cylindrical tubes. Then MATLAB was used to create an algorithm that distorts an image based on the refraction of light passing through the mediums we were imaging through to accurately visualize the cryogenic chilldown that is of scientific interest. This research will assist NASA to move forward with long-duration spaceflight missions where knowledge of efficient heat transfer processes becomes more critical.

imaging system↗

NASA's Small Spacecraft and Distributed Systems: Development and Demonstration of Technologies Enabling Swarms and New Spacecraft Platforms with AI and Edge Computing

NASA’s Small Spacecraft & Distributed Systems (SSDS) within the Research and Technology Mission Directorate (RTMD) expands U.S. capability to execute unique missions through targeted investment, rapid development, and flight demonstration of small spacecraft technologies applicable to exploration, science and the commercial space sector. SSDS strategically invests in technology development and on-orbit demonstrations executed across NASA, other government agencies, industry, and academia. The program’s University SmallSat Technology Partnerships initiative awards academic researchers with the opportunity to collaborate with NASA to mature innovative technology. Capabilities aligned with RTMD’s technology shortfalls and interests - power, processing, propulsion, sensors, communications, autonomous navigation, architectures, and advanced applications like artificial intelligence (AI), machine learning, and edge computing - are prioritized in SSDS investments. These investments enable distributed, autonomous, and cooperative small spacecraft systems that support swarm missions extending beyond low Earth orbit into cislunar and deep space. This paper highlights representative SSDS flight demonstrations that mature these capabilities to enable a future operational infrastructure needed to support sustained exploration of the Moon and beyond. SSDS’s investment strategy emphasizes rapid development and on-orbit demonstration to validate spacecraft technologies required for swarms and distributed mission architectures. The Starling swarm technology demonstration mission exemplifies this approach by advancing distributed spacecraft autonomy, cooperative operations, and space situational awareness. Extended flight testing and ongoing studies of next generation swarm configurations and on-orbit space traffic monitoring and management continue to inform future swarm designs. DiskSat’s four-spacecraft demonstration mission represents SSDS’s strategic vision to expand the design space for future small spacecraft through its commitment to advance novel platform concepts that can impact how science is performed on orbit. Continuing to invest in future platforms, the notional PY12 concept is a 12-spacecraft swarm hosting neuromorphic processors and is envisioned as an on-orbit testbed for AI, edge computing, and positioning, navigation and timing technologies. SSDS also invests in single-spacecraft technology demonstrations that underpin the success of future swarm missions and accelerate the availability of validated technologies across the small spacecraft ecosystem. Examples of such demonstrations include Pathfinder Technology Demonstrator-3 (PTD-3), which performed high-rate optical communications; PTD-R, which demonstrated a camera capable of simultaneous ultraviolet and short-wave infrared optical sensing; and CAPSTONE, the Cislunar Autonomous Positioning System Technology and Operations Navigation Experiment, which validated autonomous navigation in cislunar space. Collectively, SSDS-funded demonstrations advance capabilities across swarms and illustrate a coordinated investment strategy to mature high-impact technologies required for autonomous, distributed, and cooperative small spacecraft systems for low Earth orbit, cislunar, and deep space applications. Technology demonstrations strengthen SSDS partnerships with industry, academia, and other government agencies, and promote small spacecraft community adoption of capabilities required to close technical gaps for swarm missions.

Jan Stupl↗

NASA's Small Spacecraft and Distributed Systems: Development and Demonstration of Technologies Enabling Swarms and New Spacecraft Platforms with AI and Edge Computing

NASA’s Small Spacecraft & Distributed Systems (SSDS) within the Research and Technology Mission Directorate (RTMD) expands U.S. capability to execute unique missions through targeted investment, rapid development, and flight demonstration of small spacecraft technologies applicable to exploration, science and the commercial space sector. SSDS strategically invests in technology development and on-orbit demonstrations executed across NASA, other government agencies, industry, and academia. The program’s University SmallSat Technology Partnerships initiative awards academic researchers with the opportunity to collaborate with NASA to mature innovative technology. Capabilities aligned with RTMD’s technology shortfalls and interests - power, processing, propulsion, sensors, communications, autonomous navigation, architectures, and advanced applications like artificial intelligence (AI), machine learning, and edge computing - are prioritized in SSDS investments. These investments enable distributed, autonomous, and cooperative small spacecraft systems that support swarm missions extending beyond low Earth orbit into cislunar and deep space. This paper highlights representative SSDS flight demonstrations that mature these capabilities to enable a future operational infrastructure needed to support sustained exploration of the Moon and beyond. SSDS’s investment strategy emphasizes rapid development and on-orbit demonstration to validate spacecraft technologies required for swarms and distributed mission architectures. The Starling swarm technology demonstration mission exemplifies this approach by advancing distributed spacecraft autonomy, cooperative operations, and space situational awareness. Extended flight testing and ongoing studies of next generation swarm configurations and on-orbit space traffic monitoring and management continue to inform future swarm designs. DiskSat’s four-spacecraft demonstration mission represents SSDS’s strategic vision to expand the design space for future small spacecraft through its commitment to advance novel platform concepts that can impact how science is performed on orbit. Continuing to invest in future platforms, the notional PY12 concept is a 12-spacecraft swarm hosting neuromorphic processors and is envisioned as an on-orbit testbed for AI, edge computing, and positioning, navigation and timing technologies. SSDS also invests in single-spacecraft technology demonstrations that underpin the success of future swarm missions and accelerate the availability of validated technologies across the small spacecraft ecosystem. Examples of such demonstrations include Pathfinder Technology Demonstrator-3 (PTD-3), which performed high-rate optical communications; PTD-R, which demonstrated a camera capable of simultaneous ultraviolet and short-wave infrared optical sensing; and CAPSTONE, the Cislunar Autonomous Positioning System Technology and Operations Navigation Experiment, which validated autonomous navigation in cislunar space. Collectively, SSDS-funded demonstrations advance capabilities across swarms and illustrate a coordinated investment strategy to mature high-impact technologies required for autonomous, distributed, and cooperative small spacecraft systems for low Earth orbit, cislunar, and deep space applications. Technology demonstrations strengthen SSDS partnerships with industry, academia, and other government agencies, and promote small spacecraft community adoption of capabilities required to close technical gaps for swarm missions.

Jan Stupl↗

OARE and SAMS on STS-94/MSL-1

Four microgravity acceleration measurement instruments were included on MSL-1 to measure the accelerations and vibrations to which science experiments were exposed during their operation on the mission. The data were processed and presented to the principal investigators in a variety of formats to aid their assessment of the microgravity environment during their experiment operations. Two accelerometer systems managed by the NASA Lewis Research Center (LeRC) supported the MSL-1 mission: the Orbital Acceleration Research Experiment (OARE), and the Space Acceleration Measurement System (SAMS). In addition, the Microgravity Measurement Assembly (MMA) and the Quasi- Steady Acceleration Measurement (QSAM) system, both sponsored by the Microgravity Research Division, collected acceleration data as a part of the MSL-1 mission. The NIMA was funded and designed by the European Space Agency in the Netherlands (ESA/ESTEC), and the QSAM system was funded and designed by the German Space Agency (DLR). The Principal Investigator Microgravity Services (PIMS) project at the NASA Lewis Research Center (LeRC) supports Principal Investigators (PIs) of the Microgravity science community as they evaluate the effects of acceleration on their experiments. PIMS primary responsibility is to support NASA-sponsored investigators in the area of acceleration data analysis and interpretation. A mission summary report was prepared and published by PIMS in order to furnish interested experiment investigators with a guide for evaluating the acceleration environment during the MSL-1 mission.

Moskowitz, Milton↗