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Case Study Analyses of the SUCCESS DC-8 Scanning Lidar Database

Under project SUCCESS (Subsonic Aircraft Contrail and Cloud Effects Special Study) funded by the Atmospheric Effects of Aviation Program, SRI International (SRI) developed an angular scanning backscatter lidar for operation on the NASA DC-8 research aircraft and deployed the scanning lidar during the SUCCESS field campaign. The primary purpose of the lidar was to generate real-time video displays of clouds and contrails above, ahead of, and below the DC-8 as a means to help position the aircraft for optimum cloud and contrail sampling by onboard in situ sensors, and to help extend the geometrical domain of the in situ sampling records. A large, relatively complex lidar database was collected and several data examples were processed to illustrate the value of the lidar data for interpreting the other data records collected during SUCCESS. These data examples were used to develop a journal publication for the special SUCCESS Geophysical Research Letters issue. The data examples justified data analyses of a larger part of the DC-8 lidar database and is the objective of the current study. Efficient processing of the SUCCESS DC-8 scanning lidar database required substantial effort to enhance hardware and software components of the data system that was used for the initial analyses. MATLAB instructions are used to generate altitude and distance color-coded lidar displays corrected for effects introduced by aircraft pitch and forward movement during an angular scan time interval. Onboard in situ sensor atmospheric measurements are propagated to distances ahead of the DC-8 using recorded aircraft velocity so that they can be plotted on the lidar displays for comparison with lidar remotely observed aerosol distributions. Resulting lidar and in situ sensor polar scan displays over extended sampling intervals are integrated into a time series movie format for 36 case studies. Contrails and clouds were detected to ranges of 15 km by the forward-viewing angular scanning lidar and were progressively mapped as the aircraft approached and penetrated them. Near aircraft lidar observations were much better correlated with in situ sensor observations than lidar observations at greater distances ahead of the aircraft. The major cause of this difference was thought to be the about 2 deg. offset of the lidar viewing direction from the flight direction. Contrail spatial distributions were not of the quality obtainable from ground-based lidar observations. This results because contrails tend to become horizontally stratified, vertical distance between angular lidar observations increases with increased distance from the aircraft, and erratic aircraft motions during an angular scan. The most useful lidar observations were made with lidar viewing directions of vertically upward or vertically downward. These provided real-time information on aircraft altitudes to achieve optimum in situ cloud and contrail sampling. At sampling altitudes, the forward viewing angular scanning observations were useful for fine-tuning the aircraft altitude for cloud and contrail penetration. Best information on cloud and contrail properties were obtained from vertically directed lidar observations as the aircraft performed a series of upward and downward penetrations of contrails. This operational mode was especially well suited for lidar and radiometric evaluation of cloud and contrail optical and radiative properties. The vertical viewing lidar detected ice crystals thought to be precipitating from an aircraft contrail and their scavenging by a cirrus cloud layer. The lidar display indicates that the crystals are effective for increasing cirrus cloud density. Vertical angular scanning observations can evaluate the sharp decrease in lidar backscatter for small off-vertical viewing directions that result from horizontally aligned ice crystals and perhaps can provide additional information on crystal shapes. The about 2 deg. offset of the lidar viewing direction from the flight direction is thought to have greatly degraded the forward-viewing angular scanning observations and this mode of operation was not fully evaluated. However, the reasoning for this capability remains valid and the angular scan presentations collected during this program justifies modification of the lidar pod for true forward direction lidar viewing during future cloud and contrail studies.

Uthe, Edward E.↗

Simulation of Guidance, Navigation, and Control Systems for Formation Flying Missions

Concepts for missions of distributed spacecraft flying in formation abound. From high resolution interferometry to spatially distributed in-situ measurements, these mission concepts levy a myriad of guidance, navigation, and control (GNC) requirements on the spacecraft/formation as a single system. A critical step toward assessing and meeting these challenges lies in realistically simulating distributed spacecraft systems. The Formation Flying TestBed (FFTB) at NASA Goddard Space Flight Center's (GSFC) Guidance, Navigation, and Control Center is a hardware-in-the-loop simulation and development facility focused on GNC issues relevant to formation flying systems. The FFTB provides a realistic simulation of the vehicle dynamics and control for formation flying missions in order to: (1) conduct feasibility analyses of mission requirements, (2) conduct and answer mission and spacecraft design trades, and (3) serve as a host for GNC software and hardware development and testing. The initial capabilities of the FFTB are based upon an integration of high fidelity hardware and software simulation, emulation, and test platforms developed or employed at GSFC in recent years, including a high-fidelity Global Positioning System (GPS) simulator which has been a fundamental component of the GNC Center's GPS Test Facility. The FFTB will be continuously evolving over the next several years from a tool with capabilities in GPS navigation hardware/software-in-the-loop analysis and closed loop GPS-based orbit control algorithm assessment. Eventually, it will include full capability to support all aspects of multi-sensor, absolute and relative state determination and control, in all (attitude and orbit) degrees of freedom, as well as information management for satellite clusters and constellations. A detailed description of the FFTB architecture is presented in the paper.

Burns, Rich↗

Integrated System Health Management: Pilot Operational Implementation in a Rocket Engine Test Stand

This paper describes a credible implementation of integrated system health management (ISHM) capability, as a pilot operational system. Important core elements that make possible fielding and evolution of ISHM capability have been validated in a rocket engine test stand, encompassing all phases of operation: stand-by, pre-test, test, and post-test. The core elements include an architecture (hardware/software) for ISHM, gateways for streaming real-time data from the data acquisition system into the ISHM system, automated configuration management employing transducer electronic data sheets (TEDS?s) adhering to the IEEE 1451.4 Standard for Smart Sensors and Actuators, broadcasting and capture of sensor measurements and health information adhering to the IEEE 1451.1 Standard for Smart Sensors and Actuators, user interfaces for management of redlines/bluelines, and establishment of a health assessment database system (HADS) and browser for extensive post-test analysis. The ISHM system was installed in the Test Control Room, where test operators were exposed to the capability. All functionalities of the pilot implementation were validated during testing and in post-test data streaming through the ISHM system. The implementation enabled significant improvements in awareness about the status of the test stand, and events and their causes/consequences. The architecture and software elements embody a systems engineering, knowledge-based approach; in conjunction with object-oriented environments. These qualities are permitting systematic augmentation of the capability and scaling to encompass other subsystems.

Figueroa, Fernando↗

Flight Test 4 Preliminary Results: NASA Ames SSI

Realization of the expected proliferation of Unmanned Aircraft System (UAS) operations in the National Airspace System (NAS) depends on the development and validation of performance standards for UAS Detect and Avoid (DAA) Systems. The RTCA Special Committee 228 is charged with leading the development of draft Minimum Operational Performance Standards (MOPS) for UAS DAA Systems. NASA, as a participating member of RTCA SC-228 is committed to supporting the development and validation of draft requirements as well as the safety substantiation and end-to-end assessment of DAA system performance. The Unmanned Aircraft System (UAS) Integration into the National Airspace System (NAS) Project conducted flight test program, referred to as Flight Test 4, at Armstrong Flight Research Center from April -June 2016. Part of the test flights were dedicated to the NASA Ames-developed Detect and Avoid (DAA) System referred to as JADEM (Java Architecture for DAA Extensibility and Modeling). The encounter scenarios, which involved NASA's Ikhana UAS and a manned intruder aircraft, were designed to collect data on DAA system performance in real-world conditions and uncertainties with four different surveillance sensor systems. Flight test 4 has four objectives: (1) validate DAA requirements in stressing cases that drive MOPS requirements, including: high-speed cooperative intruder, low-speed non-cooperative intruder, high vertical closure rate encounter, and Mode CS-only intruder (i.e. without ADS-B), (2) validate TCASDAA alerting and guidance interoperability concept in the presence of realistic sensor, tracking and navigational errors and in multiple-intruder encounters against both cooperative and non-cooperative intruders, (3) validate Well Clear Recovery guidance in the presence of realistic sensor, tracking and navigational errors, and (4) validate DAA alerting and guidance requirements in the presence of realistic sensor, tracking and navigational errors. The results will be presented at RTCA Special Committee 228 in support of final verification and validation of the DAA MOPS.

Detect-And-Avoid (DAA)↗

NeMO-Net – The Neural Multi-Modal Observation & Training Network for Global Coral Reef Assessment

We present NeMO-Net, the Srst open-source deep convolutional neural network (CNN) and interactive learning and training software aimed at assessing the present and past dynamics of coral reef ecosystems through habitat mapping into 10 biological and physical classes. Shallow marine systems, particularly coral reefs, are under significant pressures due to climate change, ocean acidification, and other anthropogenic pressures, leading to rapid, often devastating changes, in these fragile and diverse ecosystems. Historically, remote sensing of shallow marine habitats has been limited to meter-scale imagery due to the optical effects of ocean wave distortion, refraction, and optical attenuation. NeMO-Net combines 3D cm-scale distortion-free imagery captured using NASA FluidCam and Fluid lensing remote sensing technology with low resolution airborne and spaceborne datasets of varying spatial resolutions, spectral spaces, calibrations, and temporal cadence in a supercomputer-based machine learning framework. NeMO-Net augments and improves the benthic habitat classification accuracy of low-resolution datasets across large geographic ad temporal scales using high-resolution training data from FluidCam.NeMO-Net uses fully convolutional networks based upon ResNet and ReSneNet to perform semantic segmentation of remote sensing imagery of shallow marine systems captured by drones, aircraft, and satellites, including WorldView and Sentinel. Deep Laplacian Pyramid Super-Resolution Networks (LapSRN) alongside Domain Adversarial Neural Networks (DANNs) are used to reconstruct high resolution information from low resolution imagery, and to recognize domain-invariant features across datasets from multiple platforms to achieve high classification accuracies, overcoming inter-sensor spatial, spectral and temporal variations.Finally, we share our online active learning and citizen science platform, which allows users to provide interactive training data for NeMO-Net in 2D and 3D, integrated within a deep learning framework. We present results from the PaciSc Islands including Fiji, Guam and Peros Banhos 1 1 2 1 3 1 where 24-class classification accuracy exceeds 91%.

Chirayath, Ved↗

A Simulation Framework for Precision Landing and Hazard Avoidance Technology Assessments

To meet NASA’s challenge to return humans to the Moon in 2024 and establish a sustainable presence in 2028 requires advances in autonomous spacecraft navigation. The Safe and Precise Landing Integrated Capabilities Evolution (SPLICE) project, which leverages previous work at NASA to develop multi-mission precision landing and hazard avoidance technologies, is using a multi-faceted approach to achieve the advanced landing requirements. In addition to increasing the technology readiness level of key sensors and developing high performance space computing, SPLICE uses simulations to determine navigation requirements and evaluate sensor performance. The effort evaluates various precision landing concepts of operations, not only for the lunar human and robotic missions, but also for potential missions to other solar system destinations. This paper summarizes the six degree-of-freedom high fidelity simulation framework, trajectory design methodology, and sensor models being considered for a variety of precision lander missions. Initial results of the navigation sensor performance for a human Mars mission are presented. Finally, trade and sensitivity studies are outlined for future work to fully characterize sensor performance assumptions and modifications required to achieve precision landing and hazard avoidance.

Alicia Dwyer Cianciolo↗

NOR Flash Memory Scrubbing Application for Boot File Preservation of NASA’s Descent and Landing Computer (DLC)

Progress on NASA’s Safe and Precise Landing Integrated Capabilities Evolution (SPLICE) project continues, specifically with this development of the Descent and Landing Computer (DLC). One of the DLC’s primary contributions as a SPLICE technology is its implementation of algorithms and operation of sensors to autonomously guide a spacecraft in performing more precise and safer landings on celestial bodies such as the Moon and Mars [1]. The second iteration of the DLC is known as the Engineering Test Unit (ETU) and one of its desired functionalities is the ability to preserve the fidelity of the system’s boot file through the use of memory scrubbing [2]. The ETU has two primary boards, one for housing a Multi-Processor System on a Chip (MPSoC) and the other for housing a Xilinx Kintex Ultrascale FPGA*. To emulate a memory scrubbing function implemented on the ETU’s FPGA board, the design and testing of a software application was performed on a Xilinx KCU105 FPGA evaluation board. The memory scrubbing application had to meet certain key criteria such as (1) properly utilize with the flash memory’s Serial Peripheral Interface (SPI) to read, write, and erase flash memory properly, (2) be able to detect arbitrarily large or small amounts of bit-errors, (3) be able to correct all detected errors, and (4) perform memory scrubbing indefinitely and autonomously. A prototype implementation was constructed and tested, demonstrating successful detection and correction of bit errors in multiple configurations. In the form of burst errors or singular bit flips, and in amounts of errors ranging from one to fifteen (per 256 Bytes), the application was successful in preserving memory fidelity.

Flash memory↗

LiDAR-Inertial Based Navigation and Mapping for Precision Landing

Future lander missions will travel to ambitious, scientifically interesting locations near rough and dangerous terrain. They will need to operate with limited prior information about the terrain, and under varying lighting conditions. Landing safely and precisely in the face of these challenges is difficult for existing vision-based landing systems, which require detailed orbital reconnaissance, a priori hazard maps, and impose time-of-day restrictions on landing to ensure similar lighting conditions in orbital and descent imagery. Advanced 3D imaging LiDAR systems currently under development, and originally intended for single-scan hazard detection, have the potential to be operated continuously from altitudes of up to 5 km. Used together with existing inertial measurement units (IMUs), these sensors open a path-to-flight for a full navigation and mapping system, which could replace or augment a traditional landing sensor suite. A landing system based around these sensors can perform accurate altimetry, map-relative localization (MRL), LiDAR-inertial odometry, and map refinement in an illumination-insensitive manner, over unknown or partially known terrain. This paper outlines preliminary work on a LiDAR-inertial landing system that: estimates the spacecraft trajectory during entry, descent, and landing (EDL); and maps the topography of the terrain below, for future use in hazard detection and avoidance. An incremental, factor graph based, smoothing approach is used to solve for the maximum a posteriori trajectory of spacecraft states. Integrated IMU measurements and features tracked in adjacent range and intensity images are used to estimate motion (LiDAR-inertial odometry). LiDAR scans are binned into motion-corrected digital elevation models (DEMs), which are matched to an existing orbital topographic map to provide absolute position information (MRL). The estimated trajectory is then used to project the LiDAR scans into the map frame, creating a variable-resolution quadtree topographic map suitable for hazard detection and avoidance. Existing topographic maps from throughout the solar system (i.e., Earth, the Moon, Mars, Ceres, Vesta, Europa, Enceladus, and Eros) are upsampled for use in EDL simulations. The Mars 2020 Lander Vision System Simulator (LVSS) is extended to simulate LiDAR-inertial data for realistic EDL trajectories. Results of the algorithm operating on the simulated data are presented. Estimated spacecraft trajectory and refined map are compared to ground truth to assess estimation accuracy.

Katake, Anup↗

Autonomous power system brassboard

The Autonomous Power System (APS) brassboard is a 20 kHz power distribution system which has been developed at NASA Lewis Research Center, Cleveland, Ohio. The brassboard exists to provide a realistic hardware platform capable of testing artificially intelligent (AI) software. The brassboard's power circuit topology is based upon a Power Distribution Control Unit (PDCU), which is a subset of an advanced development 20 kHz electrical power system (EPS) testbed, originally designed for Space Station Freedom (SSF). The APS program is designed to demonstrate the application of intelligent software as a fault detection, isolation, and recovery methodology for space power systems. This report discusses both the hardware and software elements used to construct the present configuration of the brassboard. The brassboard power components are described. These include the solid-state switches (herein referred to as switchgear), transformers, sources, and loads. Closely linked to this power portion of the brassboard is the first level of embedded control. Hardware used to implement this control and its associated software is discussed. An Ada software program, developed by Lewis Research Center's Space Station Freedom Directorate for their 20 kHz testbed, is used to control the brassboard's switchgear, as well as monitor key brassboard parameters through sensors located within these switches. The Ada code is downloaded from a PC/AT, and is resident within the 8086 microprocessor-based embedded controllers. The PC/AT is also used for smart terminal emulation, capable of controlling the switchgear as well as displaying data from them. Intelligent control is provided through use of a T1 Explorer and the Autonomous Power Expert (APEX) LISP software. Real-time load scheduling is implemented through use of a 'C' program-based scheduling engine. The methods of communication between these computers and the brassboard are explored. In order to evaluate the features of both the brassboard hardware and intelligent controlling software, fault circuits have been developed and integrated as part of the brassboard. A description of these fault circuits and their function is included. The brassboard has become an extremely useful test facility, promoting artificial intelligence (AI) applications for power distribution systems. However, there are elements of the brassboard which could be enhanced, thus improving system performance. Modifications and enhancements to improve the brassboard's operation are discussed.

Merolla, Anthony↗

Swarms of Micron-Sized Sensors

A paper presents the concept of swarms of micron-sized and smaller carriers of sensing equipment, denoted generally as controllable granular matter, to be used in exploring remote planets and interplanetary space. The design and manufacture of controllable granular matter would exploit advances in microelectromechanical systems and nanotechnology. Depending on specific designs and applications, controllable granular matter could have characteristics like those of powders, sands, or aerosols, which would be dispersed into the environments to be explored: For example, sensory grains could be released into orbit around a planet, spread out over ground, or dispersed into wind or into a body of liquid. The grains would thus become integral parts of multiphase environments, where they would function individually and/or collectively to gather information about the environments. In cases of clouds of grains dispersed in outer space, it may be feasible to use laser beams to shape the clouds to perform specific functions. To enable the full utilization of controllable granular matter, it is necessary to advance the knowledge of the dynamics and controllable characteristics of both individual grains and the powders, sands, or aerosols of which they are parts.

Quadrelli, Marco↗

Feasibility of using GPS measurements for OMV attitude update

This paper presents the results of a feasibility study to determine whether the measurements from GPS satellites can be used to estimate the OMV attitude to an accuracy comparable to the onboard sun sensors, i.e., better than 0.5 degree in each axis. The results documented in this paper demonstrate that OMV attitude can be estimated to an accuracy of 0.1 - 0.5 degree in each axis by processing GPS measurements in an onboard integrated, 17-state GPS/inertial navigation filter. The result is particularly significant for missions of short duration burns where accurate attitude information is needed to minimize guidance and control errors. It is shown that the GPS attitude technique described in this paper can be easily implemented in the current OMV navigation system design. Results reported in this paper are expected to support the goal of developing a fault-tolerant guidance, navigation, and control system offering an improved total navigation performance for the OMV.

Upadhyay, Triveni N.↗

Petri net controllers for distributed robotic systems

Petri nets are a well established modelling technique for analyzing parallel systems. When coupled with an event-driven operating system, Petri nets can provide an effective means for integrating and controlling the functions of distributed robotic applications. Recent work has shown that Petri net graphs can also serve as remarkably intuitive operator interfaces. In this paper, the advantages of using Petri nets as high-level controllers to coordinate robotic functions are outlined, the considerations for designing Petri net controllers are discussed, and simple Petri net structures for implementing an interface for operator supervision are presented. A detailed example is presented which illustrates these concepts for a sensor-based assembly application.

Lefebvre, D. R.↗

Attitude Control System Design for the Solar Dynamics Observatory

The Solar Dynamics Observatory mission, part of the Living With a Star program, will place a geosynchronous satellite in orbit to observe the Sun and relay data to a dedicated ground station at all times. SDO remains Sun- pointing throughout most of its mission for the instruments to take measurements of the Sun. The SDO attitude control system is a single-fault tolerant design. Its fully redundant attitude sensor complement includes 16 coarse Sun sensors, a digital Sun sensor, 3 two-axis inertial reference units, 2 star trackers, and 4 guide telescopes. Attitude actuation is performed using 4 reaction wheels and 8 thrusters, and a single main engine nominally provides velocity-change thrust. The attitude control software has five nominal control modes-3 wheel-based modes and 2 thruster-based modes. A wheel-based Safehold running in the attitude control electronics box improves the robustness of the system as a whole. All six modes are designed on the same basic proportional-integral-derivative attitude error structure, with more robust modes setting their integral gains to zero. The paper details the mode designs and their uses.

Starin, Scott R.↗

SpaceCube v2.0 Space Flight Hybrid Reconfigurable Data Processing System

This paper details the design architecture, design methodology, and the advantages of the SpaceCube v2.0 high performance data processing system for space applications. The purpose in building the SpaceCube v2.0 system is to create a superior high performance, reconfigurable, hybrid data processing system that can be used in a multitude of applications including those that require a radiation hardened and reliable solution. The SpaceCube v2.0 system leverages seven years of board design, avionics systems design, and space flight application experiences. This paper shows how SpaceCube v2.0 solves the increasing computing demands of space data processing applications that cannot be attained with a standalone processor approach.The main objective during the design stage is to find a good system balance between power, size, reliability, cost, and data processing capability. These design variables directly impact each other, and it is important to understand how to achieve a suitable balance. This paper will detail how these critical design factors were managed including the construction of an Engineering Model for an experiment on the International Space Station to test out design concepts. We will describe the designs for the processor card, power card, backplane, and a mission unique interface card. The mechanical design for the box will also be detailed since it is critical in meeting the stringent thermal and structural requirements imposed by the processing system. In addition, the mechanical design uses advanced thermal conduction techniques to solve the internal thermal challenges.The SpaceCube v2.0 processing system is based on an extended version of the 3U cPCI standard form factor where each card is 190mm x 100mm in size The typical power draw of the processor card is 8 to 10W and scales with application complexity. The SpaceCube v2.0 data processing card features two Xilinx Virtex-5 QV Field Programmable Gate Arrays (FPGA), eight memory modules, a monitor FPGA with analog monitoring, Ethernet, configurable interconnect to the Xilinx FPGAs including gigabit transceivers, and the necessary voltage regulation. The processor board uses a back-to-back design methodology for common parts that maximizes the board real estate available. This paper will show how to meet the IPC 6012B Class 3A standard with a 22-layer board that has two column grid array devices with 1.0mm pitch. All layout trades such as stack-up options, via selection, and FPGA signal breakout will be discussed with feature size results. The overall board design process will be discussed including parts selection, circuit design, proper signal termination, layout placement and route planning, signal integrity design and verification, and power integrity results. The radiation mitigation techniques will also be detailed including configuration scrubbing options, Xilinx circuit mitigation and FPGA functional monitoring, and memory protection.Finally, this paper will describe how this system is being used to solve the extreme challenges of a robotic satellite servicing mission where typical space-rated processors are not sufficient enough to meet the intensive data processing requirements. The SpaceCube v2.0 is the main payload control computer and is required to control critical subsystems such as autonomous rendezvous and docking using a suite of vision sensors and object avoidance when controlling two robotic arms.

Xilinx FPGA↗

Advanced Wavefront Sensing and Control Testbed (AWCT)

The Advanced Wavefront Sensing and Control Testbed (AWCT) is built as a versatile facility for developing and demonstrating, in hardware, the future technologies of wave front sensing and control algorithms for active optical systems. The testbed includes a source projector for a broadband point-source and a suite of extended scene targets, a dispersed fringe sensor, a Shack-Hartmann camera, and an imaging camera capable of phase retrieval wavefront sensing. The testbed also provides two easily accessible conjugated pupil planes which can accommodate the active optical devices such as fast steering mirror, deformable mirror, and segmented mirrors. In this paper, we describe the testbed optical design, testbed configurations and capabilities, as well as the initial results from the testbed hardware integrations and tests.

active optics↗

Extraction and Separation Modeling of Orion Test Vehicles with ADAMS Simulation

The Capsule Parachute Assembly System (CPAS) project has increased efforts to demonstrate the performance of fully integrated parachute systems at both higher dynamic pressures and in the presence of wake fields using a Parachute Compartment Drop Test Vehicle (PCDTV) and a Parachute Test Vehicle (PTV), respectively. Modeling the extraction and separation events has proven challenging and an understanding of the physics is required to reduce the risk of separation malfunctions. The need for extraction and separation modeling is critical to a successful CPAS test campaign. Current PTV-alone simulations, such as Decelerator System Simulation (DSS), require accurate initial conditions (ICs) drawn from a separation model. Automatic Dynamic Analysis of Mechanical Systems (ADAMS), a Commercial off the Shelf (COTS) tool, was employed to provide insight into the multi-body six degree of freedom (DOF) interaction between parachute test hardware and external and internal forces. Components of the model include a composite extraction parachute, primary vehicle (PTV or PCDTV), platform cradle, a release mechanism, aircraft ramp, and a programmer parachute with attach points. Independent aerodynamic forces were applied to the mated test vehicle/platform cradle and the separated test vehicle and platform cradle. The aero coefficients were determined from real time lookup tables which were functions of both angle of attack ( ) and sideslip ( ). The atmospheric properties were also determined from a real time lookup table characteristic of the Yuma Proving Grounds (YPG) atmosphere relative to the planned test month. Representative geometries were constructed in ADAMS with measured mass properties generated for each independent vehicle. Derived smart separation parameters were included in ADAMS as sensors with defined pitch and pitch rate criteria used to refine inputs to analogous avionics systems for optimal separation conditions. Key design variables were dispersed in a Monte Carlo analysis to provide the maximum expected range of the state variables at programmer deployment to be used as ICs in DSS. Extensive comparisons were made with Decelerator System Simulation Application (DSSA) to validate the mated portion of the ADAMS extraction trajectory. Results of the comparisons improved the fidelity of ADAMS with a ramp pitch profile update from DSSA. Post-test reconstructions resulted in improvements to extraction parachute drag area knock-down factors, extraction line modeling, and the inclusion of ball-to-socket attachments used as a release mechanism on the PTV. Modeling of two Extraction parachutes was based on United States Air Force (USAF) tow test data and integrated into ADAMS for nominal and Monte Carlo trajectory assessments. Video overlay of ADAMS animations and actual C-12 chase plane test videos supported analysis and observation efforts of extraction and separation events. The COTS ADAMS simulation has been integrated with NASA based simulations to provide complete end to end trajectories with a focus on the extraction, separation, and programmer deployment sequence. The flexibility of modifying ADAMS inputs has proven useful for sensitivity studies and extraction/separation modeling efforts. 1

Fraire, Usbaldo, Jr.↗

A 190 by 244 charge-coupled area image sensor with interline transfer organization

A 190 x 244 element charge coupled area image sensor has been designed, fabricated and tested. This sensor employs an interline transfer organization and buried n-channel technology. It features a novel on-chip charge integrator and a distributed floating gate amplifier for high and low light level applications. The X-Y element count has been chosen to establish the capability of producing an NTSC compatible video signal. The array size is also compatible with the Super 8 lens format. The first few sample devices have been successfully operated at full video bandwidth for both high and low light levels with the charge amplifier system.

Walsh, L. R.↗

Remote water monitoring system

A remote water monitoring system is described that integrates the functions of sampling, sample preservation, sample analysis, data transmission and remote operation. The system employs a floating buoy carrying an antenna connected by lines to one or more sampling units containing several sample chambers. Receipt of a command signal actuates a solenoid to open an intake valve outward from the sampling unit and communicates the water sample to an identifiable sample chamber. Such response to each signal receipt is repeated until all sample chambers are filled in a sample unit. Each sample taken is analyzed by an electrochemical sensor for a specific property and the data obtained is transmitted to a remote sending and receiving station. Thereafter, the samples remain isolated in the sample chambers until the sampling unit is recovered and the samples removed for further laboratory analysis.

Grana, D. C.↗