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An Exploratory Evaluation of UAS Detect and Avoid Operations in the Terminal Environment

New technical standards for Unmanned Aircraft Systems (UAS) detect and avoid (DAA) systems mark recent progress toward realizing the goal of full integration of UAS into the National Airspace System (NAS). The DAA system is intended to provide a means of compliance with operating regulations that required pilots on board manned aircraft to remain "well clear" of other aircraft which is accomplished through out-the-window visual acquisition of other aircraft and application of a subjective judgment of safe separation. The requirements for the DAA system, including the specification of a DAA well clear threshold as well as functional requirements for detecting, tracking, alerting and guidance processing, and displays, are specified in DO-365, Minimum Operational Performance Standards (MOPS) for DAA Systems developed within RTCA Special Committee 228 (SC-228). Intended as the first in a series of phased versions, these requirements are frequently referred to as the "Phase 1" DAA system. The Phase 1 DAA system is limited for use by aircraft transitioning to and from Class A or special use airspace, through Class D, E, and G airspace. In particular, the Phase 1 DAA MOPS are not intended for terminal airspace operations, a critical gap for enabling a full range of UAS operations. The application of the Phase 1 DAA system and DAA well clear threshold within the terminal area is predicted to result in a high number of unnecessary alerts when the UAS is safely separated from other traffic. The goal of the present study was to examine pilot performance and operational issues related to the operation of the Phase 1 DAA system in a terminal area. This experiment was intended as an exploratory study that would be used to inform the development of a new terminal area-specific DAA well clear definition, and associated alerting and guidance requirements. The two main objectives of this study were to: 1) characterize pilot behavior in the terminal environment with the Phase 1 DAA system, and 2) investigate the effect of modifications to the Phase 1 DAA alerting and guidance structure. In particular, the authors were interested in determining whether the removal of specific alerting and guidance levels, without changing the DAA well clear definition or alerting thresholds, would impact pilot performance while conducting terminal operations. The results indicate that the Phase 1 well clear definition and alerting and guidance resulted in frequent alerting that degraded pilots' ability to discriminate between encounters where another aircraft was safely separated versus when a maneuver was necessary. The resulting impact on pilot performance was slower response times and higher frequency and severity of losses of DAA well clear compared to those observed for experiments examining pilot performance in the en route environment. There was no significant effect of alerting and guidance display configuration on pilot performance.

Rorie, Conrad↗

Induction of Micronuclei in Human Fibroblasts across the Bragg Curve of Energetic Si and Fe Ions

The space environment consists of a varying field of radiation particles including high-energy ions, with spacecraft shielding material providing the major protection to astronauts from harmful exposure. Unlike low-LET gamma or X-rays, the presence of shielding does not always reduce the radiation risks for energetic charged particle exposure. Since the dose delivered by the charged particle increases sharply as the particle approaches the end of its range, a position known as the Bragg peak, the Bragg curve does not necessarily represent the biological damage along the particle traversal since biological effects are influenced by the track structure of both primary and secondary particles. Therefore, the biological Bragg curve is dependent on the energy and the type of the primary particle, and may vary for different biological endpoints. We studied micronuclei (MN) induction across the Bragg curve of Si and Fe ions at incident energies of 300 MeV/nucleon and 1 GeV/nucleon. A quantitative biological response curve did not reveal an increased yield of MN at the location of the Bragg peak. However, the ratio of mono- to bi-nucleated cells, which indicates inhibition in cell progression, increased at the Bragg peak location. These results confirm the hypothesis that severely damaged cells at the Bragg peak are likely to go through reproduction death.

Wu, H.↗

Optical Measurement Techniques for Rocket Engine Testing and Component Applications: Digital Image Correlation and Dynamic Photogrammetry

NASA Marshall Space Flight Center (MSFC) has been advancing dynamic optical measurement systems, primarily Digital Image Correlation, for extreme environment rocket engine test applications. The Digital Image Correlation (DIC) technology is used to track local and full field deformations, displacement vectors and local and global strain measurements. This technology has been evaluated at MSFC through lab testing to full scale hotfire engine testing of the J-2X Upper Stage engine at Stennis Space Center. It has been shown to provide reliable measurement data and has replaced many traditional measurement techniques for NASA applications. NASA and AMRDEC have recently signed agreements for NASA to train and transition the technology to applications for missile and helicopter testing. This presentation will provide an overview and progression of the technology, various testing applications at NASA MSFC, overview of Army-NASA test collaborations and application lessons learned about Digital Image Correlation.

Gradl, Paul↗

WBS 4.1.2.31 Bioproduct Transition System Dynamics

Bioproducts are chemicals derived from a biomass feedstock; they can be produced on their own or as co-products of a biorefinery that also produces biofuels. Bioproducts have historically been difficult to scale up and bring to market, despite a broad understanding developed within BETO of the various conversion processes that can be used to produce bioproducts. Expanding the bioproducts industry by bringing more bioproducts to market would have a variety of positive impacts. Growth in the bioproducts industry would support the biofuels industry by enabling biorefinery co-products that yield additional revenue streams, allowing biofuel selling prices to be reduced and expanding the biofuels market. A larger bioproducts industry also has the potential to reduce carbon and other emissions associated with the U.S. chemical sector and contribute to increased price stability in some areas of the chemical market by shifting portions of the chemical sector away from reliance on fossil feedstocks. The key barrier to realizing these positive impacts is a lack of knowledge around the factors that prevent or enable bioproducts to reach the commercial market. To date, there has been essentially no research done on how successful bioproducts (commercially produced bioproducts that have captured market share) become successful, why failed bioproducts fail, and what the similarities and differences are between successful and failed bioproducts. The current project addresses this knowledge gap with a decision support tool that can be used by investors, technology developers and government agencies to bring more bioproducts to market, thereby simultaneously growing the bioproducts and biofuels industries. Development of the decision support tool was based on research on the technology development process and success rates in analogous industries, data gathered during previous BETO-funded projects, and a series of interviews with subject-matter experts within BETO, the bioproducts industry, and the investment community. This information formed a knowledge base around how bioproducts are developed from applied research to commercial scale was assembled, which was used to build the Bioproduct Transition Dynamics (BTD) model, a system dynamics (SD) model that tracks bioproduct development projects from applied research through the 'valley of death' of piloting and demoing to commercial scale production. The end-of-project goal is to release the BTD, along with supporting documentation, as a transparent open-source model that will inform decisions around bioproduct development and investments and enable more bioproducts to reach the market. The BTD takes as inputs techno-economic data on specific bioproducts, behavioral parameters for developers and investors, expectations around government support, and exogenous market factors. Model outputs include bioproduct technological progress over time, a cash flow statement for the development project, and market share estimates. Following initial model development, a sensitivity analysis was performed on a subset of model inputs to determine, first, if the BTD could be used to answer analysis questions of interest to BETO, and second, which of the inputs considered were most influential on bioproduct success. Results indicate that the BTD can be used to identify scenarios that enable bioproduct development, and that 'soft' or semi-quantitative factors play a large role in determining if a bioproduct will reach the market. A workshop was also held for subject-matter experts and prospective BTD users in July 2018. The workshop covered BTD model logic, input data and assumptions as well as the sensitivity analysis results and a discussion of potential use cases. Workshop feedback was used to identify additional model development tasks and was incorporated into a draft technical report completed in September 2018. BTD model development, validation and application will continue through 2019.

09 BIOMASS FUELS↗

Ground observations of a space laser for the assessment of its in-orbit performance

The wind mission Aeolus of the European Space Agency was a groundbreaking achievement for Earth observation. Between 2018 and 2023, the space-borne lidar instrument ALADIN onboard the Aeolus satellite measured atmospheric wind profiles with global coverage, which contributed to improving the accuracy of numerical weather prediction. The precision of the wind observations, however, declined over the course of the mission due to a progressive loss of the atmospheric backscatter signal. The analysis of the root cause was supported by the Pierre Auger Observatory in Argentina whose fluorescence detector registered the ultraviolet laser pulses emitted from the instrument in space, thereby offering an estimation of the laser energy at the exit of the instrument for several days in 2019, 2020, and 2021. The reconstruction of the laser beam not only allowed for an independent assessment of the Aeolus performance, but also helped to improve the accuracy in the determination of the laser beam’s ground track on single pulse level. The results presented in this paper set a precedent for the monitoring of space lasers by ground-based telescopes and open new possibilities for the calibration of cosmic-ray observatories.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

VML 3.0 Reactive Sequencing Objects and Matrix Math Operations for Attitude Profiling

VML (Virtual Machine Language) has been used as the sequencing flight software on over a dozen JPL deep-space missions, most recently flying on GRAIL and JUNO. In conjunction with the NASA SBIR entitled "Reactive Rendezvous and Docking Sequencer", VML version 3.0 has been enhanced to include object-oriented element organization, built-in queuing operations, and sophisticated matrix / vector operations. These improvements allow VML scripts to easily perform much of the work that formerly would have required a great deal of expensive flight software development to realize. Autonomous turning and tracking makes considerable use of new VML features. Profiles generated by flight software are managed using object-oriented VML data constructs executed in discrete time by the VML flight software. VML vector and matrix operations provide the ability to calculate and supply quaternions to the attitude controller flight software which produces torque requests. Using VML-based attitude planning components eliminates flight software development effort, and reduces corresponding costs. In addition, the direct management of the quaternions allows turning and tracking to be tied in with sophisticated high-level VML state machines. These state machines provide autonomous management of spacecraft operations during critical tasks like a hypothetic Mars sample return rendezvous and docking. State machines created for autonomous science observations can also use this sort of attitude planning system, allowing heightened autonomy levels to reduce operations costs. VML state machines cannot be considered merely sequences - they are reactive logic constructs capable of autonomous decision making within a well-defined domain. The state machine approach enabled by VML 3.0 is progressing toward flight capability with a wide array of applicable mission activities.

VML (Virtual Machine Language)↗

Three-Dimensional Distribution of a Major Desert Dust Outbreak over East Asia in March 2008 Derived from IASI Satellite Observations

We describe the daily evolution of the three-dimensional (3D) structure of a major dust outbreak initiated by an extratropical cyclone over East Asia in early March 2008, using new aerosol retrievals derived from satellite observations of IASI (Infrared Atmospheric Sounding Interferometer). A novel auto-adaptive Tikhonov-Phillips-type approach called AEROIASI is used to retrieve vertical profiles of dust extinction coefficient at 10 microns for most cloud-free IASI pixels, both over land and ocean. The dust vertical distribution derived from AEROIASI is shown to agree remarkably well with along-track transects of Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) spaceborne lidar vertical profiles (mean biases less than 110 meters, correlation of 0.95, and precision of 260 meters for mean altitudes of the dust layers). AEROIASI allows the daily characterization of the 3D transport pathways across East Asia of two dust plumes originating from the Gobi and North Chinese deserts. From AEROIASI retrievals, we provide evidence that (i) both dust plumes are transported over the Beijing region and the Yellow Sea as elevated layers above a shallow boundary layer, (ii) as they progress eastward, the dust layers are lifted up by the ascending motions near the core of the extratropical cyclone, and (iii) when being transported over the warm waters of the Japan Sea, turbulent mixing in the deep marine boundary layer leads to high dust concentrations down to the surface. AEROIASI observations and model simulations also show that the progression of the dust plumes across East Asia is tightly related to the advancing cold front of the extratropical cyclone.

Cuesta, Juan↗

Recent Progress in the International Laser Ranging Service (ILRS)

The International Laser Ranging Service (ILRS) provides Satellite Laser Ranging (SLR) and Lunar Laser Ranging (LLR) observations and data products with a focus on Earth and Lunar science and engineering applications. The basic observables are the precise two-way time-of-flight of ultra-short laser pulses from ground stations to retroreflector arrays on satellites and the Moon and the one-way time-of-flight measurements to space-borne receivers (transponders). SLR is one of the four space geodetic techniques (along with VLBI, GNSS, and DORIS). The International Terrestrial Reference Frame (ITRF) development, maintained by IERS, is based on these geodetic observations. Fundamental data products include accurate satellite ephemerides, Earth orientation parameters, three dimensional coordinates and velocities of the ILRS tracking stations, time-varying geocenter coordinates, static and time-varying coefficients of the Earth’s gravity field, fundamental physical constants, lunar ephemerides and librations, and lunar orientation parameters. The ILRS continues to expand spatial and temporal coverage of SLR observations. New stations with new technologies are being deployed; existing stations are being upgraded. Some of these stations are multi-technique Core Sites. New satellites are expanding applications and strengthening the ILRS contribution to the reference frame. New analysis, modeling, and data processing techniques are improving data products. New campaigns are expanding our applications into relativity and the study of non-gravitational forces. New activities are underway on Lunar Laser Ranging, Time Transfer, and Space Debris Tracking, helping to expand laser ranging applications. This talk will give an update on the current ILRS activities and their impact on ILRS data products.

Report on the ILRS activities↗

Workflow Agents vs. Expert Systems: Problem Solving Methods in Work Systems Design

During the 1980s, a community of artificial intelligence researchers became interested in formalizing problem solving methods as part of an effort called "second generation expert systems" (2nd GES). How do the motivations and results of this research relate to building tools for the workplace today? We provide an historical review of how the theory of expertise has developed, a progress report on a tool for designing and implementing model-based automation (Brahms), and a concrete example how we apply 2nd GES concepts today in an agent-based system for space flight operations (OCAMS). Brahms incorporates an ontology for modeling work practices, what people are doing in the course of a day, characterized as "activities." OCAMS was developed using a simulation-to-implementation methodology, in which a prototype tool was embedded in a simulation of future work practices. OCAMS uses model-based methods to interactively plan its actions and keep track of the work to be done. The problem solving methods of practice are interactive, employing reasoning for and through action in the real world. Analogously, it is as if a medical expert system were charged not just with interpreting culture results, but actually interacting with a patient. Our perspective shifts from building a "problem solving" (expert) system to building an actor in the world. The reusable components in work system designs include entire "problem solvers" (e.g., a planning subsystem), interoperability frameworks, and workflow agents that use and revise models dynamically in a network of people and tools. Consequently, the research focus shifts so "problem solving methods" include ways of knowing that models do not fit the world, and ways of interacting with other agents and people to gain or verify information and (ultimately) adapt rules and procedures to resolve problematic situations.

Clancey, William J.↗

Lidar study of storm tops

Satellite thermal and visible observations are routinely used for storm tracking and diagnostics. In recent years attempts have also been made to apply satellite measurements to the study of evolutional factors for storms such as divergence and subsidence mechanisms. These studies involve analysis of the thermal height structure of the storm tops as obtained from the satellite observations. An outstanding problem is the importance of emissivity effects for the interpretation of the storm top thermal radiance measurements. In part to understand the correct interpretation of satellite observations, a storm top observation experiment involving advanced instrumentation on board a high altitude NASA aircraft has been in progress. A downlooking lidar system is an important part of the instrument complement. A combined analysis of the lidar return data and thermal radiance measurements was developed to study cloud top emissivity effects and their relation to satellite observations. Some preliminary conclusions are given.

Spinhirne, J. D.↗

A Journey with MOM

In late 2013, the Indian Space Research Organization (ISRO) launched its "Mars Orbiter Mission" (MOM). ISRO engaged NASA's Jet Propulsion Laboratory (JPL) for navigation services to support ISRO's objectives of MOM achieving and maintaining Mars orbit. The navigation support included planning, documentation, testing, orbit determination, maneuver design /analysis, and tracking data analysis. Several of MOM's attributes had an impact on navigation processes, e.g., S -band telecommunications, Earth Orbit Phase maneuvers, and frequent angular momentum desaturation s (AMDs). The primary source of tracking data was NASA/ JPL's Deep Space Network (DSN); JPL also conducted a performance assessment of Indian Deep Space Network (IDSN) tracking data. Planning for the Mars Orbit Insertion (MOI) was complicated by a pressure regulator failure that created uncertainty regarding MOM's main engine and raised potential planetary protection issues. A successful main engine test late on approach resolved these issues; it was quickly followed by a successful MOI on 24-September - 2014 at 02:00 UTC. Less than a month later, Comet Siding Spring's Mars flyby necessitated plans to minimize potential spacecraft damage. At the time of this writing, MOM's orbital operations continue, and plans to extend JPL 's support are in progress. This paper covers the JPL 's support of MOM through the Comet Siding Spring event.

Mars orbiter↗

Supporting Global Air Quality Management Needs With A Flexible Data Fusion Tool for Estimation and Forecasting in Google Earth Engine

High spatial and temporal resolution air quality estimation and forecasting can be enhanced by combining global data sources, like chemical transport models and satellite remote sensing, with local information from regulatory and low-cost air quality monitors. Successful integration of data from these diverse sources is complicated by many factors, however, including differences in spatial and temporal resolution, data availability and latency issues, varying data quality, and large computational and data storage requirements. This presentation will provide an overview of a NASA-funded effort to develop the foundation for future operationalization of air quality forecasting for world-wide end-users and integration into their air quality management decision processes, which will be achieved in future phases of this multi-year project. We will summarize our progress in developing a data fusion system using the Google Earth Engine platform which can integrate model, satellite, and surface-level monitoring datasets to enhance estimation and forecasting of air-quality-relevant pollutants at sub-daily and sub-city scales. The tool is being developed in close cooperation with several city- and regional-level air quality managers in the USA and around the world. Our end-goal is to provide these air quality managers with the information they need to assess and anticipate the impacts of poor air quality, track changes in air quality due to ongoing mitigation efforts and land use changes, and identify ways to improve their air quality monitoring strategies. This presentation will focus on recent advances achieved through the project, including integration of multiple air quality datasets in a prototype data fusion system in Google Earth Engine, the quantification of uncertainties associated with our data fusion approach, and the development of user interfaces and visualization tools to convey air quality information in a way which best meets end-user needs.

Carl Malings↗

Supporting Global Air Quality Management Needs With A Flexible Data Fusion Tool for Estimation and Forecasting in Google Earth Engine

High spatial and temporal resolution air quality estimation and forecasting can be enhanced by combining global data sources, like chemical transport models and satellite remote sensing, with local information from regulatory and low-cost air quality monitors. Successful integration of data from these diverse sources is complicated by many factors, however, including differences in spatial and temporal resolution, data availability and latency issues, varying data quality, and large computational and data storage requirements. This presentation will provide an overview of a NASA-funded effort to develop the foundation for future operationalization of air quality forecasting for world-wide end-users and integration into their air quality management decision processes, which will be achieved in future phases of this multi-year project. We will summarize our progress in developing a data fusion system using the Google Earth Engine platform which can integrate model, satellite, and surface-level monitoring datasets to enhance estimation and forecasting of air-quality-relevant pollutants at sub-daily and sub-city scales. The tool is being developed in close cooperation with several city- and regional-level air quality managers in the USA and around the world. Our end-goal is to provide these air quality managers with the information they need to assess and anticipate the impacts of poor air quality, track changes in air quality due to ongoing mitigation efforts and land use changes, and identify ways to improve their air quality monitoring strategies. This presentation will focus on recent advances achieved through the project, including integration of multiple air quality datasets in a prototype data fusion system in Google Earth Engine, the quantification of uncertainties associated with our data fusion approach, and the development of user interfaces and visualization tools to convey air quality information in a way which best meets end-user needs.

Carl Malings↗

Automated Progress Monitoring in Modular Construction Factories Using Computer Vision and Building Information Modeling

Modular construction methods have recently gained interest due to the advantages offered in terms of safety, quality, and productivity for projects. In this method, a significant portion of the construction is performed off-site in factories where modular components are built in different workstations, assembled on the production line, and shipped to the site for installation. Due to the labor-intensive nature of tasks, cycle times in modular construction factories are highly variable, which commonly leads to major bottlenecks and delays in construction projects. To remedy this effect, recent methods rely on sensors such as RFID to monitor the production process, which is reportedly expensive, and intrusive to the work process. Recently, computer vision-based methods have been proposed to track the production process in modular construction factories. However, these methods overlook monitoring the assembly process on the production line. Therefore, this paper presents a method to monitor the assembly process by integrating computer vision-based methods with Building Information Modeling (BIM). The proposed method detects the modular units using object segmentation; superimposes the installation area with the corresponding 2D region using BIM, and identifies the installation of the components using image processing techniques. The proposed method has been validated using surveillance videos captured from a modular construction factory in the US. Successful implementation of the proposed method can lead to timely identification of delays during the assembly process and reduce delays in modular integrated construction projects.

building information modeling↗

Tracking DO 2 with Compensatory Reserve during Whole Blood Resuscitation in Baboons

Background Hemorrhagic shock can be mitigated by timely and accurate resuscitation designed to restore adequate delivery of oxygen (DO 2 ) by increasing cardiac output (CO). However, standard care of using systolic blood pressure (SBP) as a guide for resuscitation has proven ineffective and can be associated with increased morbidity. We have developed a novel vital sign called the compensatory reserve (CRM) generated from analysis of arterial pulse waveform feature changes that has been validated in experimental and clinical models of hemorrhage. We tested the hypothesis that thresholds of DO 2 could be accurately defined by CRM while avoiding over resuscitation during whole blood resuscitation following a 25% hemorrhage in non‐human primates. Methods To accomplish this, adult male baboons (n=12) were exposed to a progressive controlled hemorrhage that resulted in an average (± SD) maximal reduction of 601 ± 18 ml of their estimated circulating blood volume of 1,262 ± 64 ml based on body weight. Values of DO 2 were calculated as the product of CO times O 2 carrying capacity of hemoglobin (i.e., Hb content × 1.34). Results Average (± SD) CRM increased from 6 ± 5 % at the end of hemorrhage to 70 ± 7 % at the end of resuscitation. DO 2 of 12.1, 10.3, and 7.0 ml O 2 ·kg −1 ·min −1 were calculated at 0% (baseline), 12.5% and 25% blood loss. By linear regression, CRM values of 6% (decompensation), 35%, and 68% corresponded to calculated DO 2 values of 6.0, 9.2, and 12.1 ml O 2 ·kg −1 ·min −1 during resuscitation. As such, return of CRM to baseline during resuscitation with only ~ 450 ml provided adequate DO 2 (12.5 ml O 2 ·kg −1 ·min −1 ) while total blood volume replacement (~600 ml) resulted in over resuscitation as indicated by an average increase in SBP (+17 mmHg) and CO (+0.1 L/min) over baseline values. Conclusion Consistent with our hypothesis, thresholds of DO 2 were associated with specific CRM values. A target resuscitation CRM value of 70% minimized the requirement for whole blood, while avoiding over resuscitation. Furthermore, CRM at 0% provided a noninvasive metric for determining critical DO 2 at approximately 5.4 ml O 2 ·kg −1 ·min −1 . Support or Funding Information This research was supported in part by appointment of Ms. Koons to the Postgraduate Research Fellowship Program at the US Army Institute of Surgical Research administered by the Oak Ridge Institute for Science and Education through an interagency agreement between the US Department of Energy and USAMRMC. Study funding was provided by a grant from the US Army Combat Casualty Care Research Program (D‐009‐2014‐USAISR). Linearregression of the relationship between DO 2 and compensatory reserve during whole blood resuscitation in baboons. Data are expressed as mean ± SE. image Linearregression of the relationship between DO 2 and compensatory reserve during whole blood resuscitation in baboons. Data are expressed as mean ± SE. This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .

Koons, Natalie Jane↗

Reliability measurement during software development

Measurement of software reliability was carried out during the development of data base software for a multi-sensor tracking system. Every run made during this project was scored as success or failure, and supporting data were collected on forms for further analysis. The failure ratio (number of failures per calendar interval divided by total number of runs) and failure rate (number of failures divided by CPU time for the interval) were found to be consistent measures, on a month-to-month basis as well as from module to module, and therefore considered valid indicators of reliability in this environment. Trend lines could be established from these measurements that provide good visualization of the progress on the job as a whole as well as on individual modules. Over one-half of the observed failures were due to factors associated with the specific run submission rather than with the code proper.

Hecht, H.↗

Development of an Autonomous Lidar Instrument for Use on a UAV Platform in Support of Homeland Security

Researchers at NASA's Goddard Space Flight Center have developed an autonomous aerosol backscatter lidar instrument for use on the high-altitude ER-2 aircraft (for more information please visit http://cpl.gsfc.nasa.gov). Work is currently underway to transfer this instrument to a UAV platform such as Global Hawk. While the NASA applications are Earth science and satellite validation, there is clearly a Homeland Security application for such an instrument. One novel concept is to have a fleet of UAVs stationed around the country, each UAV having a payload including a lidar instrument. In the event of attack, the appropriate UAV(s) could be launched for purposes of, e.g., plume detection and tracking that are critical for decision support. While the existing lidar instrument is not directly capable of biological species discrimination, it is capable of plume tracking and thus can demonstrate to DHS the capabilities and utility of such instruments. Using NASA funding we will have an instrument ready to fly on Global Hawk by end of 2005. We would like to find partners, either within private industry or within DHS who would be willing to contribute aircraft access and flight hours for a demonstration flight. Longer-term partnerships to develop more advanced and more capable types of lidar instruments are also desirable. In this presentation we will detail the existing ER-2 lidar instrument and show measurement results, show the progress made on adapting to the Global Hawk platform, present concepts for DHS uses of such instruments, and openly pursue partnership opportunities.

McGill, Matthew↗

Mission Operations and Command Assurance: Automating an Operations TQM Task

A long-term program is in progress at JPL to reduce cost and risk of mission operations through defect prevention and error management. A major element of this program, Mission Operations and Command Assurance (MO&QA), provides a system level function on flight projects to instill quality in mission operations. MO&CA embodies the Total Quality Management (TQM) principle of Continuous Process Inprovement (CPI) and uses CPI in applying automation to mission operations to reduce risk and costs. MO&CA has led efforts to apply and has implemented automation in areas that impact the daily flight project environment including Incident Surprise Anomoly tracking and reporting; command data verification, tracking, and reporting; and command support data usage. MO&CA's future work in automation will take into account that future missions systems must be designed to avoid increasing error through the introduction of automation, while adapting to the demands of smaller flight teams.

automation↗