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At least 577 records · Page 32

Prospective Evaluation of Thoracic Ultrasound in the Detection of Pneumothorax

Introduction: Pneumothorax (PTX) occurs commonly in trauma patients and is confirmed by examination and radiography. Thoracic ultrasound (VIS) has been suggested as an alternative method for rapidly diagnosing PTX when X-ray is unavailable as in rural, military, or space flight settings; however, its accuracy and specificity are not known. Methods: We evaluated the accuracy of thoracic U/S detection of PTX compared to radiography in stable, emergency patients with a high suspicion of PTX at a Level-l trauma center over a 6-month period. Following University and NASA Institutional Review Board approval, informed consent was obtained from patients with penetrating or blunt chest trauma, or with a history consistent with PTX. Whenever possible, the presence or absence of the " lung sliding" sign or the "comet tail" artifact were determined by U/S in both hemithoraces by residents instructed in thoracic U/S before standard radiologic verification of PTX. Results were recorded on data sheets for comparison to standard radiography. Results: Thoracic VIS had a 94% sensitivity; two PTX could not be reliably diagnosed due to subcutaneous air; the true negative rate was 100%. In one patient, the VIS exam was positive while X ray did not confirm PTX; a follow-up film 1 hour later demonstrated a small PTX. The average time for bilateral thoracic VIS examination was 2 to 3 minutes. Conclusions: Thoracic ultrasound reliably diagnoses pneumothorax. Presence of the "lung sliding" sign conclusively excludes pneumothorax. Expansion of the FAST examination to include the thorax should be investigated.

Schwarz, K. W.↗

ORDEM 3.0 and MASTER-2009 Modeled Small Debris Population Comparison

The latest versions of the two premier orbital debris engineering models, NASA's ORDEM 3.0 and ESA's MASTER-2009, have been publicly released within the last year. Both models have gone through significant advancements since inception, and now represent the state-of-the-art in orbital debris knowledge of their respective agencies. The purpose of these models is to provide satellite designers/operators and debris researchers with reliable estimates of the artificial debris environment in near-Earth orbit. The small debris environment within the size range of 1 mm to 1 cm is of particular interest to both human and robotic spacecraft programs. These objects are much more numerous than larger trackable debris but are still large enough to cause significant, if not catastrophic, damage to spacecraft upon impact. They are also small enough to elude routine detection by existing observation systems (radar and telescope). Without reliable detection the modeling of these populations has always coupled theoretical origins with supporting observational data in different degrees. This paper describes the population generation and categorization of both ORDEM 3.0 and MASTER-2009; their sources (both known and presumed), current supporting data and theory, and methods of population verification. Fluxes on spacecraft for chosen orbits are presented and discussed. Future collaborative analysis is noted.

Krisko, P. H.↗

Unmanned Vehicle Material Flammability Test

Microgravity fire behaviour remains poorly understood and a significant risk for spaceflight An experiment is under development that will provide the first real opportunity to examine this issue focussing on two objectives: a) Flame Spread. b) Material Flammability. This experiment has been shown to be feasible on both ESA's ATV and Orbital Science's Cygnus vehicles with the Cygnus as the current base-line carrier. An international topical team has been formed to develop concepts for that experiment and support its implementation: a) Pressure Rise prediction. b) Sample Material Selection. This experiment would be a landmark for spacecraft fire safety with the data and subsequent analysis providing much needed verification of spacecraft fire safety protocols for the crews of future exploration vehicles and habitats.

Urban, David L.↗

High-Resolution Mesoscale Model Setup for the Eastern Range and Wallops Flight Facility

Mesoscale weather conditions can have an adverse effect on space launch, landing, ground processing, and weather advisories, watches, and warnings at the Eastern Range (ER) in Florida and Wallops Flight Facility (WFF) in Virginia. During summer, land-sea interactions across Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS) lead to sea breeze front formation, which can spawn deep convection that can hinder operations and endanger personnel and resources. Many other weak locally-driven low-level boundaries and their interactions with the sea breeze front and each other can also initiate deep convection in the KSC/CCAFS area. These convective processes often last 60 minutes or less and pose a significant challenge to the local forecasters. Surface winds during the transition seasons (spring and fall) pose the most difficulties for the forecasters at WFF. They also encounter problems forecasting convective activity and temperature during those seasons. Therefore, accurate mesoscale model forecasts are needed to better forecast a variety of unique weather phenomena. Global and national scale models cannot properly resolve important local-scale weather features at each location due to their horizontal resolutions being much too coarse. Therefore, a properly tuned local data assimilation (DA) and forecast model at a high resolution is needed to provide improved capability. To accomplish this, a number of sensitivity tests were performed using the Weather Research and Forecasting (WRF) model in order to determine the best DA/model configuration for operational use at each of the space launch ranges to best predict winds, precipitation, and temperature. A set of Perl scripts to run the Gridpoint Statistical Interpolation (GSI)/WRF in real-time were provided by NASA's Short-term Prediction Research and Transition Center (SPoRT). The GSI can analyze many types of observational data including satellite, radar, and conventional data. The GSI/WRF scripts use a cycled GSI system similar to the operational North American Mesoscale (NAM) model. The scripts run a 12-hour pre-cycle in which data are assimilated from 12 hours prior up to the model initialization time. A number of different model configurations were tested for both the ER and WFF by varying the horizontal resolution on which the data assimilation was done. Three different grid configurations were run for the ER and two configurations were run for WFF for archive cases from 27 Aug 2013 through 10 Nov 2013. To quantify model performance, standard model output will be compared to the Meteorological Assimilation Data Ingest System (MADIS) data. The MADIS observation data will be compared to the WRF forecasts using the Model Evaluation Tools (MET) verification package. In addition, the National Centers for Environmental Prediction's Stage IV precipitation data will be used to validate the WRF precipitation forecasts. The author will summarize the relative skill of the various WRF configurations and how each configuration behaves relative to the others, as well as determine the best model configuration for each space launch range.

Watson, Leela R.↗

Space Suit Portable Life Support System (PLSS) 2.0 Unmanned Vacuum Environment Testing

For the first time in more than 30 years, an advanced space suit Portable Life Support System (PLSS) design was operated inside a vacuum chamber representative of the flight operating environment. The test article, PLSS 2.0, was the second system-level integrated prototype of the advanced PLSS design, following the PLSS 1.0 Breadboard that was developed and tested throughout 2011. Whereas PLSS 1.0 included five technology development components with the balance the system simulated using commercial-off-the-shelf items, PLSS 2.0 featured first generation or later prototypes for all components less instrumentation, tubing and fittings. Developed throughout 2012, PLSS 2.0 was the first attempt to package the system into a flight-like representative volume. PLSS 2.0 testing included an extensive functional evaluation known as Pre-Installation Acceptance (PIA) testing, Human-in-the-Loop testing in which the PLSS 2.0 prototype was integrated via umbilicals to a manned prototype space suit for 19 two-hour simulated EVAs, and unmanned vacuum environment testing. Unmanned vacuum environment testing took place from 1/9/15-7/9/15 with PLSS 2.0 located inside a vacuum chamber. Test sequences included performance mapping of several components, carbon dioxide removal evaluations at simulated intravehicular activity (IVA) conditions, a regulator pressure schedule assessment, and culminated with 25 simulated extravehicular activities (EVAs). During the unmanned vacuum environment test series, PLSS 2.0 accumulated 378 hours of integrated testing including 291 hours of operation in a vacuum environment and 199 hours of simulated EVA time. The PLSS prototype performed nominally throughout the test series, with two notable exceptions including a pump failure and a Spacesuit Water Membrane Evaporator (SWME) leak, for which post-test failure investigations were performed. In addition to generating an extensive database of PLSS 2.0 performance data, achievements included requirements and operational concepts verification, as well as demonstration of vehicular interfaces, consumables sizing and recharge, and water quality control.

Watts, Carly↗

Comprehension of Spacecraft Telemetry Using Hierarchical Specifications of Behavior

A key challenge in operating remote spacecraft is that ground operators must rely on the limited visibility available through spacecraft telemetry in order to assess spacecraft health and operational status. We describe a tool for processing spacecraft telemetry that allows ground operators to impose structure on received telemetry in order to achieve a better comprehension of system state. A key element of our approach is the design of a domain-specific language that allows operators to express models of expected system behavior using partial specifications. The language allows behavior specifications with data fields, similar to other recent runtime verification systems. What is notable about our approach is the ability to develop hierarchical specifications of behavior. The language is implemented as an internal DSL in the Scala programming language that synthesizes rules from patterns of specification behavior. The rules are automatically applied to received telemetry and the inferred behaviors are available to ground operators using a visualization interface that makes it easier to understand and track spacecraft state. We describe initial results from applying our tool to telemetry received from the Curiosity rover currently roving the surface of Mars, where the visualizations are being used to trend subsystem behaviors, in order to identify potential problems before they happen. However, the technology is completely general and can be applied to any system that generates telemetry such as event logs.

Runtime monitoring↗

External Contamination Integration of Visiting Vehicles on the International Space Station

The International Space Station (ISS) is an on-orbit platform for science utilization in low Earth orbit. The induced contamination environment can impact performance, mission success, and science utilization. Cargo and crew vehicles visiting the ISS represent significant sources of contamination. The Space Environments Team of the ISS Program Office has developed visiting vehicle requirements and methodologies to address the increasingly complex challenge of integrating multiple visiting vehicles while maintaining overall ISS contamination control requirements. The external contamination control requirements are summarized and the integration and verification process is described along with required data deliverables. Contamination characterization data deliverables address vacuum-exposed materials, thrusters, vacuum venting, and particulate releases. Visiting vehicle external contamination analyses are conducted by the ISS Space Environments Team to certify compliance with external contamination control requirements. Unpressurized cargo contamination analyses are also performed to characterize induced contamination to payloads while in transit to ISS. Efforts to confirm the visiting vehicle contamination modeling and analysis process based on on-orbit data are discussed.

outgassing↗

Magnetic Suspension Wind Tunnel Reconstruction Using an Extended Kalman Filter Framework

A Kalman filter tool has been created for processing data from NASA Langley’s Magnetic Suspension and Balance System. The filter is formulated to estimate aerodynamic parameters of a model that is levitated magnetically in the test section of the wind tunnel. The Kalman filter tool is a modification of an existing code that has been in use for solving trajectory reconstruction problems and has been validated through previous use supporting many flight projects. Modifications to the code were implemented to add the capability to process data from the magnetic suspension wind tunnel. In particular, the main modifications were to the equations of motion to add models for magnetic and aerodynamic forces and moments. The code has been tested using simulation data to provide a known truth for verification.

Christopher D. Karlgaard↗

Unconservatism of Linear-Elastic Fracture Mechanics (LEFM) Analysis Post Autofrettage

The scope of the NASA Engineering and Safety Center (NESC) Unconservatism of Linear-Elastic Fracture Mechanics (LEFM) Analysis Post Autofrettage assessment was to evaluate the influence of the elastic-plastic autofrettage cycle on elastic cycles post autofrettage and generate data to support damage tolerance life analysis verification approach. The decision to include an elastic-plastic autofrettage cycle is informed by other factors beyond damage tolerance, including manufacturing and fatigue crack initiation. The results of the NESC assessment are contained in this report.

Linear-Elastic Fracture Mechanics↗

NASA’s Developments in Cryogenic Fluid Management Technology

NASA has been pursuing the development and demonstration of enabling and enhancing technologies for Cryogenic Fluid Management (CFM) in collaboration with the US industry. NASA’s vision for current and future space exploration requires high-performance chemical and nuclear propulsion solutions that utilize cryogens. The Agency will use cryogenic fluids for Earth-to-orbit transportation, human missions to the Moon and Mars, planetary exploration, and in-situ resource utilization (ISRU) production. All these architectures will require state-of-the-art long-duration storage on the surface and in-space transfer for refueling. This paper focuses on key CFM technology developments completed or ongoing by the Cryogenic Fluid Management Portfolio Office within NASA’s Space Technology Mission Directorate. The CFM Portfolio Office, partnered with US aerospace industry, has invested in CFM technology ground and flight demonstrations, focused on maturing CFM hardware and operations for Artemis and Moon to Mars activities. These demonstrations additionally provide NASA with data to inform numerical modeling activities for verification and validation of design tools and approaches for future missions. This paper includes discussion on remaining high-priority open CFM technology gaps for Mar-forward architectures and initiatives for closure.

Cryogenic Fluid Management↗

Software reliability report

There are many software reliability models which try to predict future performance of software based on data generated by the debugging process. Unfortunately, the models appear to be unable to account for the random nature of the data. If the same code is debugged multiple times and one of the models is used to make predictions, intolerable variance is observed in the resulting reliability predictions. It is believed that data replication can remove this variance in lab type situations and that it is less than scientific to talk about validating a software reliability model without considering replication. It is also believed that data replication may prove to be cost effective in the real world, thus the research centered on verification of the need for replication and on methodologies for generating replicated data in a cost effective manner. The context of the debugging graph was pursued by simulation and experimentation. Simulation was done for the Basic model and the Log-Poisson model. Reasonable values of the parameters were assigned and used to generate simulated data which is then processed by the models in order to determine limitations on their accuracy. These experiments exploit the existing software and program specimens which are in AIR-LAB to measure the performance of reliability models.

Wilson, Larry↗

Development of a Response Surface Thermal Model for Orion Mated to the International Space Station

A study was performed to determine if a Design of Experiments (DOE)/Response Surface Methodology could be applied to on-orbit thermal analysis and produce a set of Response Surface Equations (RSE) that accurately predict vehicle temperatures. The study used an integrated thermal model of the International Space Station and the Orion Outer mold line model. Five separate factors were identified for study: yaw, pitch, roll, beta angle, and the environmental parameters. Twenty external Orion temperatures were selected as the responses. A DOE case matrix of 110 runs was developed. The data from these cases were analyzed to produce an RSE for each of the temperature responses. The initial agreement between the engineering data and the RSE predictions was encouraging, although many RSEs had large uncertainties on their predictions. Fourteen verification cases were developed to test the predictive powers of the RSEs. The verification showed mixed results with some RSE predicting temperatures matching the engineering data within the uncertainty bands, while others had very large errors. While this study to not irrefutably prove that the DOE/RSM approach can be applied to on-orbit thermal analysis, it does demonstrate that technique has the potential to predict temperatures. Additional work is needed to better identify the cases needed to produce the RSEs

Miller, Stephen W.↗

High Speed PC Based Data Acquisition and Instrumentation for Measurement of Simulated Low Earth Orbit Thermally Induced Disturbances

The Hubble Space Telescope (HST) Disturbance Verification Test (DVT) was conducted to characterize responses of the Observatory's new set of rigid solar array's (SA3) to thermally induced 'creak' or stiction releases. The data acquired in the DVT were used in verification of the HST Pointing Control System on-orbit performance, post-Servicing Mission 3B (SM3B). The test simulated the on-orbit environment on a deployed SA3 flight wing. Instrumentation for this test required pretest simulations in order to select the correct sensitivities. Vacuum compatible, highly accurate accelerometers and force gages were used for this test. The complexity of the test, as well as a short planning schedule, required a data acquisition system that was easy to configure, highly flexible, and extremely robust. A PC Windows oriented data acquisition system meets these requirements, allowing the test engineers to minimize the time required to plan and perform complex environmental test. The SA3 DVT provided a direct practical and complex demonstration of the versatility that PC based data acquisition systems provide. Two PC based data acquisition systems were assembled to acquire, process, distribute, and provide real time processing for several types of transducers used in the SA3 DVT. A high sample rate digital tape recorder was used to archive the sensor signals. The two systems provided multi-channel hardware and software architecture and were selected based on the test requirements. How these systems acquire and processes multiple data rates from different transducer types is discussed, along with the system hardware and software architecture.

Sills, Joel W., Jr.↗

Simplifying Operations with an Uplink/Downlink Integration Toolkit

The Operations Engineering Lab (OEL) at JPL has developed a simple, generic toolkit to integrate the uplink/downlink processes (often called closing the loop) in JPL's Multimission Ground Data System. This toolkit provides capabilities for integrating telemetry verification points with predicted spacecraft commands and ground events in the Mission Sequence of Events (SOE) document. This toolkit is designed to greatly simplify the user's ability to access and view telemetry data, and also provide a means to view this data in a context of the commands and ground events that are used to interpret it. This paper will discuss the toolkit implementation, including design trade-offs and future for enhancing the automated capabilities.

ground↗

Ignition-and-Growth Modeling of NASA Standard Detonator and a Linear Shaped Charge

The main objective of this study is to quantitatively investigate the ignition and shock sensitivity of NASA Standard Detonator (NSD) and the shock wave propagation of a linear shaped charge (LSC) after being shocked by NSD flyer plate. This combined explosive train was modeled as a coupled Arbitrary Lagrangian-Eulerian (ALE) model with LS-DYNA hydro code. An ignition-and-growth (I&G) reactive model based on unreacted and reacted Jones-Wilkins-Lee (JWL) equations of state was used to simulate the shock initiation. Various NSD-to-LSC stand-off distances were analyzed to calculate the shock initiation (or failure to initiate) and detonation wave propagation along the shaped charge. Simulation results were verified by experimental data which included VISAR tests for NSD flyer plate velocity measurement and an aluminum target severance test for LSC performance verification. Parameters used for the analysis were obtained from various published data or by using CHEETAH thermo-chemical code.

Oguz, Sirri↗

Convective Weather Forecast Quality Metrics for Air Traffic Management Decision-Making

Since numerical weather prediction models are unable to accurately forecast the severity and the location of the storm cells several hours into the future when compared with observation data, there has been a growing interest in probabilistic description of convective weather. The classical approach for generating uncertainty bounds consists of integrating the state equations and covariance propagation equations forward in time. This step is readily recognized as the process update step of the Kalman Filter algorithm. The second well known method, known as the Monte Carlo method, consists of generating output samples by driving the forecast algorithm with input samples selected from distributions. The statistical properties of the distributions of the output samples are then used for defining the uncertainty bounds of the output variables. This method is computationally expensive for a complex model compared to the covariance propagation method. The main advantage of the Monte Carlo method is that a complex non-linear model can be easily handled. Recently, a few different methods for probabilistic forecasting have appeared in the literature. A method for computing probability of convection in a region using forecast data is described in Ref. 5. Probability at a grid location is computed as the fraction of grid points, within a box of specified dimensions around the grid location, with forecast convection precipitation exceeding a specified threshold. The main limitation of this method is that the results are dependent on the chosen dimensions of the box. The examples presented Ref. 5 show that this process is equivalent to low-pass filtering of the forecast data with a finite support spatial filter. References 6 and 7 describe the technique for computing percentage coverage within a 92 x 92 square-kilometer box and assigning the value to the center 4 x 4 square-kilometer box. This technique is same as that described in Ref. 5. Characterizing the forecast, following the process described in Refs. 5 through 7, in terms of percentage coverage or confidence level is notionally sound compared to characterizing in terms of probabilities because the probability of the forecast being correct can only be determined using actual observations. References 5 through 7 only use the forecast data and not the observations. The method for computing the probability of detection, false alarm ratio and several forecast quality metrics (Skill Scores) using both the forecast and observation data are given in Ref. 2. This paper extends the statistical verification method in Ref. 2 to determine co-occurrence probabilities. The method consists of computing the probability that a severe weather cell (grid location) is detected in the observation data in the neighborhood of the severe weather cell in the forecast data. Probabilities of occurrence at the grid location and in its neighborhood with higher severity, and with lower severity in the observation data compared to that in the forecast data are examined. The method proposed in Refs. 5 through 7 is used for computing the probability that a certain number of cells in the neighborhood of severe weather cells in the forecast data are seen as severe weather cells in the observation data. Finally, the probability of existence of gaps in the observation data in the neighborhood of severe weather cells in forecast data is computed. Gaps are defined as openings between severe weather cells through which an aircraft can safely fly to its intended destination. The rest of the paper is organized as follows. Section II summarizes the statistical verification method described in Ref. 2. The extension of this method for computing the co-occurrence probabilities in discussed in Section HI. Numerical examples using NCWF forecast data and NCWD observation data are presented in Section III to elucidate the characteristics of the co-occurrence probabilities. This section also discusses the procedure for computing throbabilities that the severity of convection in the observation data will be higher or lower in the neighborhood of grid locations compared to that indicated at the grid locations in the forecast data. The probability of coverage of neighborhood grid cells is also described via examples in this section. Section IV discusses the gap detection algorithm and presents a numerical example to illustrate the method. The locations of the detected gaps in the observation data are used along with the locations of convective weather cells in the forecast data to determine the probability of existence of gaps in the neighborhood of these cells. Finally, the paper is concluded in Section V.

Chatterji, Gano B.↗

Computer program for design and performance analysis of navigation-aid power systems

The paper examines the requirements, design rationale, operation, and verification of a computer program designated as design synthesis/performance analysis (DSPA) computer program, which is capable of performing all the calculations necessary to understand the overall characteristics of solar array/battery power systems for navigation-aid applications. Despite the uncertainties in the erratic solar array degradation data and the potential impact on actual battery behavior, verification of the DSPA is considered successful. The program is shown to have the capability of simulating the performance of solar array/battery navigation-aid power systems. It can also be used to synthesize power system designs and provide essential design and cost data.

Weiner, H.↗

Spacelab development and its operational verification

This paper gives a brief status report on the current Spacelab program and describes how the results of ground and flight tests will be combined to provide the operational verification of the system. For the on-going project, data on design, testing and fabrication plans are presented. In particular, recent changes to meet the constraints of a 'build-to-cost' project are described. In the operational verification of Spacelab, ground and flight tests which ESA and NASA will perform are addressed. The installation of test instrumentation and the performance of integrated tests will be accomplished in the US. Experiments for the first flight will be integrated into Spacelab racks and pallets and simulated mission tests performed. On-orbit, system thermal surveys are planned and stress data will be obtained during launch and re-entry.

Bignier, M.↗