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At least 613 records · Page 34
All sourcesNASA NTRSDOE OSTI
NASA NTRS2010

A Comparison and Evaluation of Real-Time Software Systems Modeling Languages

A model-driven approach to real-time software systems development enables the conceptualization of software, fostering a more thorough understanding of its often complex architecture and behavior while promoting the documentation and analysis of concerns common to real-time embedded systems such as scheduling, resource allocation, and performance. Several modeling languages have been developed to assist in the model-driven software engineering effort for real-time systems, and these languages are beginning to gain traction with practitioners throughout the aerospace industry. This paper presents a survey of several real-time software system modeling languages, namely the Architectural Analysis and Design Language (AADL), the Unified Modeling Language (UML), Systems Modeling Language (SysML), the Modeling and Analysis of Real-Time Embedded Systems (MARTE) UML profile, and the AADL for UML profile. Each language has its advantages and disadvantages, and in order to adequately describe a real-time software system's architecture, a complementary use of multiple languages is almost certainly necessary. This paper aims to explore these languages in the context of understanding the value each brings to the model-driven software engineering effort and to determine if it is feasible and practical to combine aspects of the various modeling languages to achieve more complete coverage in architectural descriptions. To this end, each language is evaluated with respect to a set of criteria such as scope, formalisms, and architectural coverage. An example is used to help illustrate the capabilities of the various languages.

Evensen, Kenneth D.↗
NASA NTRS2015

Developing a Crew Time Model for Human Exploration Missions to Mars

Candidate human missions to Mars require mission lengths that could extend beyond those that have previously been demonstrated during crewed Lunar (Apollo) and International Space Station (ISS) missions. The nature of the architectures required for deep space human exploration will likely necessitate major changes in how crews operate and maintain the spacecraft. The uncertainties associated with these shifts in mission constructs - including changes to habitation systems, transit durations, and system operations - raise concerns as to the ability of the crew to complete required overhead activities while still having time to conduct a set of robust exploration activities. This paper will present an initial assessment of crew operational requirements for human missions to the Mars surface. The presented results integrate assessments of crew habitation, system maintenance, and utilization to present a comprehensive analysis of potential crew time usage. Destination operations were assessed for a short (approx. 50 day) and long duration (approx. 500 day) surface habitation case. Crew time allocations are broken out by mission segment, and the availability of utilization opportunities was evaluated throughout the entire mission progression. To support this assessment, the integrated crew operations model (ICOM) was developed. ICOM was used to parse overhead, maintenance and system repair, and destination operations requirements within each mission segment - outbound transit, Mars surface duration, and return transit - to develop a comprehensive estimation of exploration crew time allocations. Overhead operational requirements included daily crew operations, health maintenance activities, and down time. Maintenance and repair operational allocations are derived using the Exploration Maintainability and Analysis Tool (EMAT) to develop a probabilistic estimation of crew repair time necessary to maintain systems functionality throughout the mission.

Battfeld, Bryan↗
NASA NTRS2015

Time Series Analysis of Insar Data: Methods and Trends

Time series analysis of InSAR data has emerged as an important tool for monitoring and measuring the displacement of the Earth's surface. Changes in the Earth's surface can result from a wide range of phenomena such as earthquakes, volcanoes, landslides, variations in ground water levels, and changes in wetland water levels. Time series analysis is applied to interferometric phase measurements, which wrap around when the observed motion is larger than one-half of the radar wavelength. Thus, the spatio-temporal ''unwrapping" of phase observations is necessary to obtain physically meaningful results. Several different algorithms have been developed for time series analysis of InSAR data to solve for this ambiguity. These algorithms may employ different models for time series analysis, but they all generate a first-order deformation rate, which can be compared to each other. However, there is no single algorithm that can provide optimal results in all cases. Since time series analyses of InSAR data are used in a variety of applications with different characteristics, each algorithm possesses inherently unique strengths and weaknesses. In this review article, following a brief overview of InSAR technology, we discuss several algorithms developed for time series analysis of InSAR data using an example set of results for measuring subsidence rates in Mexico City.

InSAR↗
NASA NTRS2015

Time-Accurate Unsteady Pressure Loads Simulated for the Space Launch System at Wind Tunnel Conditions

A transonic flow field about a Space Launch System (SLS) configuration was simulated with the Fully Unstructured Three-Dimensional (FUN3D) computational fluid dynamics (CFD) code at wind tunnel conditions. Unsteady, time-accurate computations were performed using second-order Delayed Detached Eddy Simulation (DDES) for up to 1.5 physical seconds. The surface pressure time history was collected at 619 locations, 169 of which matched locations on a 2.5 percent wind tunnel model that was tested in the 11 ft. x 11 ft. test section of the NASA Ames Research Center's Unitary Plan Wind Tunnel. Comparisons between computation and experiment showed that the peak surface pressure RMS level occurs behind the forward attach hardware, and good agreement for frequency and power was obtained in this region. Computational domain, grid resolution, and time step sensitivity studies were performed. These included an investigation of pseudo-time sub-iteration convergence. Using these sensitivity studies and experimental data comparisons, a set of best practices to date have been established for FUN3D simulations for SLS launch vehicle analysis. To the author's knowledge, this is the first time DDES has been used in a systematic approach and establish simulation time needed, to analyze unsteady pressure loads on a space launch vehicle such as the NASA SLS.

Alter, Stephen J.↗
NASA NTRS2016

A Quasi-Global Approach to Improve Day-Time Satellite Surface Soil Moisture Anomalies through the Land Surface Temperature Input

Passive microwave observations from various spaceborne sensors have been linked to the soil moisture of the Earth's surface layer. A new generation of passive microwave sensors are dedicated to retrieving this variable and make observations in the single theoretically optimal L-band frequency (1-2 GHz). Previous generations of passive microwave sensors made observations in a range of higher frequencies, allowing for simultaneous estimation of additional variables required for solving the radiative transfer equation. One of these additional variables is land surface temperature, which plays a unique role in the radiative transfer equation and has an influence on the final quality of retrieved soil moisture anomalies. This study presents an optimization procedure for soil moisture retrievals through a quasi-global precipitation-based verification technique, the so-called Rvalue metric. Various land surface temperature scenarios were evaluated in which biases were added to an existing linear regression, specifically focusing on improving the skills to capture the temporal variability of soil moisture. We focus on the relative quality of the day-time (01:30 pm) observations from the Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E), as these are theoretically most challenging due to the thermal equilibrium theory, and existing studies indicate that larger improvements are possible for these observations compared to their night-time (01:30 am) equivalent. Soil moisture data used in this study were retrieved through the Land Parameter Retrieval Model (LPRM), and in line with theory, both satellite paths show a unique and distinct degradation as a function of vegetation density. Both the ascending (01:30 pm) and descending (01:30 am) paths of the publicly available and widely used AMSR-E LPRM soil moisture products were used for benchmarking purposes. Several scenarios were employed in which the land surface temperature input for the radiative transfer was varied by imposing a bias on an existing regression. These scenarios were evaluated through the Rvalue technique, resulting in optimal bias values on top of this regression. In a next step, these optimal bias values were incorporated in order to re-calibrate the existing linear regression, resulting in a quasi-global uniform LST relation for day-time observations. In a final step, day-time soil moisture retrievals using the re-calibrated land surface temperature relation were again validated through the Rvalue technique. Results indicate an average increasing Rvalue of 16.5%, which indicates a better performance obtained through the re-calibration. This number was confirmed through an independent Triple Collocation verification over the same domain, demonstrating an average root mean square error reduction of 15.3%. Furthermore, a comparison against an extensive in situ database (679 stations) also indicates a generally higher quality for the re-calibrated dataset. Besides the improved day-time dataset, this study furthermore provides insights on the relative quality of soil moisture retrieved from AMSR-E's day- and night-time observations.

soil moisture↗
NASA NTRS2017

Dual Extended Kalman Filter for the Identification of Time-Varying Human Manual Control Behavior

A Dual Extended Kalman Filter was implemented for the identification of time-varying human manual control behavior. Two filters that run concurrently were used, a state filter that estimates the equalization dynamics, and a parameter filter that estimates the neuromuscular parameters and time delay. Time-varying parameters were modeled as a random walk. The filter successfully estimated time-varying human control behavior in both simulated and experimental data. Simple guidelines are proposed for the tuning of the process and measurement covariance matrices and the initial parameter estimates. The tuning was performed on simulation data, and when applied on experimental data, only an increase in measurement process noise power was required in order for the filter to converge and estimate all parameters. A sensitivity analysis to initial parameter estimates showed that the filter is more sensitive to poor initial choices of neuromuscular parameters than equalization parameters, and bad choices for initial parameters can result in divergence, slow convergence, or parameter estimates that do not have a real physical interpretation. The promising results when applied to experimental data, together with its simple tuning and low dimension of the state-space, make the use of the Dual Extended Kalman Filter a viable option for identifying time-varying human control parameters in manual tracking tasks, which could be used in real-time human state monitoring and adaptive human-vehicle haptic interfaces.

manual control↗
NASA NTRS2017

Adaptive Time Stepping for Transient Network Flow Simulation in Rocket Propulsion Systems

Fluid and thermal transients found in rocket propulsion systems such as propellant feedline system is a complex process involving fast phases followed by slow phases. Therefore their time accurate computation requires use of short time step initially followed by the use of much larger time step. Yet there are instances that involve fast-slow-fast phases. In this paper, we present a feedback control based adaptive time stepping algorithm, and discuss its use in network flow simulation of fluid and thermal transients. The time step is automatically controlled during the simulation by monitoring changes in certain key variables and by feedback. In order to demonstrate the viability of time adaptivity for engineering problems, we applied it to simulate water hammer and cryogenic chill down in pipelines. Our comparison and validation demonstrate the accuracy and efficiency of this adaptive strategy.

Majumdar, Alok K.↗
NASA NTRS2017

Thermosphere Global Time Response to Geomagnetic Storms Caused by Coronal Mass Ejections

We investigate, for the first time with a spatial superposed epoch analysis study, the thermosphere global time response to 159 geomagnetic storms caused by coronal mass ejections (CMEs) observed in the solar wind at Earth's orbit during the period of September 2001 to September 2011. The thermosphere neutral mass density is obtained from the CHAMP (CHAllenge Mini-Satellite Payload) and GRACE (Gravity Recovery Climate Experiment) spacecraft. All density measurements are intercalibrated against densities computed by the Jacchia-Bowman 2008 empirical model under the regime of very low geomagnetic activity. We explore both the effects of the pre-CME shock impact on the thermosphere and of the storm main phase onset by taking their times of occurrence as zero epoch times (CME impact and interplanetary magnetic field Bz southward turning) for each storm. We find that the shock impact produces quick and transient responses at the two high-latitude regions with minimal propagation toward lower latitudes. In both cases, thermosphere is heated in very high latitude regions within several minutes. The Bz southward turning of the storm onset has a fast heating manifestation at the two high-latitude regions, and it takes approximately 3 h for that heating to propagate down to equatorial latitudes and to globalize in the thermosphere. This heating propagation is presumably accomplished, at least in part, with traveling atmospheric disturbances and complex meridional wind structures. Current models use longer lag times in computing thermosphere density dynamics during storms. Our results suggest that the thermosphere response time scales are shorter and should be accordingly adjusted in thermospheric empirical models.

mass ejections↗
NASA NTRS2016

Predicting Real-Time Safety of the National Airspace System

To gain the situational awareness necessary for informed decision making regarding avoidance of airspace hazards, each operator must consolidate operations-relevant information from disparate sources and apply extensive domain knowledge to correctly interpret not just the current state of the NAS but forecast its (combined) evolution over the duration of the operation. This time- and workload-intensive process is periodically repeated throughout the operation so that changes can be managed in a timely manner.The imprecision, inaccuracies, inconsistency, and incompleteness of the incoming data further challenges the process. To facilitate informed decision making, this paper presents a model-based framework for the textitautomated real-time monitoring and prediction of possible effects of airspace hazards on the safety of the National Airspace System (NAS). First, hazards to flight are identified and transformed into sms, that is, quantities of interest that could be evaluated based on available data and are predictive of an unsafe event. The sms and associated thresholds that specify when an event transitions from emphsafe to emphunsafe are combined with models of airspace operations and aircraft dynamics. The framework can include any hazard to flight that can be modeled quantitatively. Models can be detailed and complex, or they can be considerably simplifed, as appropriate to the application. Real-time NAS safety monitoring and prediction begins with an estimate of the state of the NAS using the dynamic models. Given the state estimate and a probability distribution of future inputs to the NAS, we can then predict the evolution of the NAS - the future state - and the occurrence of hazards and unsafe events. The entire probability distribution of airspace sms is computed, not just point estimates, without significant assumptions regarding the distribution type andor parameters. We demonstrate our overall approach through a simulated scenario in which we predict the occurrence of some unsafe events and show how these predictions evolve in time as flight operations progress. Predictions accounting for common sources of uncertainty are included and it is shown how the predictions improve in time, become more confident, and change dynamically as new information is made available to the prediction algorithm.

safety↗
NASA NTRS2014

A Method for Obtaining High Time and Spatial Resolution Convective Cloud Top Data for the TTL

A method for obtaining high time and spatial resolution convective cloud top data for the TTL Leonhard Pfister, Eric Jensen, Rei Ueyama, Eliot Atlas, and Maria Navarro Convective systems in the tropics have a maximum in the cloud top altitude distribution of about 13.5 km. However, there is a significant tail to this distribution -- a few percent reach the cold point tropopause (CPT) at 16.5 km, and there has been clear evidence of convective mass deposited as high as 19 km in the tropics. The region between 13.5 km and the cold point tropopause is transitional, between the free tropical troposphere where convective mixing dominates, and the stratosphere where slow upward ascent dominates. In this region (the Tropical Tropopause Layer), convective injection, slow ascent, and mixing from midlatitudes all have similar time scales. So, even though only a few percent of convective systems reach the CPT, convection is important. Space Based Lidar and cloud radar measurements have yielded information about long term average statistical distributions of cloud altitude as a function of location. However, we also need time-dependent cloud top altitude and cloud top potential temperature information, primarily to understand the water vapor and TTL cloud distributions. This is because the effect of convection depends on the local temperature, and on the subsequent temperature history. Time dependent cloud top information is also needed to understand short-lived tracers because cross-isentropic flow is time and space dependent. This paper presents a method of obtaining time and space dependent convective cloud top theta (and altitude) information using 3-hourly geostationary brightness temperature data, coupled with global 3 -hourly rainfall estimates and temperature analyses. We explore different mixing algorithms to obtain the most reasonable agreement with near-simultaneous observations by cloudsat and calipso. Observations of short-lived tracers from ATTREX, coupled with short-term trajectories are used to test the method's accuracy. An important caveat is the ambiguity of evaluating convective cloud top altitudes under from combined cloudsat and calipso measurements.

cold point tropopause (CPT)↗
NASA NTRS2016

Maximum Likelihood Synchronization for Pulse Position Modulation with Inter-Symbol Guard Times

Deep space optical communications promises orders-of-magnitude growth in communication capacity, supporting high data rate applications such as video streaming and high-bandwidth science instruments. Pulse position modulation is the modulation format of choice for deep space applications, and by inserting inter-symbol guard times between the symbols, the signal carries the timing information needed by the demodulator. Accurately extracting this timing information is crucial to demodulating and decoding this signal. In this paper we propose a low complexity maximum likelihood timing estimator for pulse position modulation with inter-symbol guard times which significantly outperforms the prior art in this domain. We show that this estimator can achieve the same performance as prior estimators with an order-of-magnitude less signal flux, or multiple orders-of-magnitude less flux-accumulation time. Further we show that this estimator achieves the Cramer-Rao bound, making it asymptotically efficient. This method does not require an explicit synchronization sequence, freeing up channel resources for data transmission.

Rogalin, Ryan↗
NASA NTRS2018

Real-Time Adaptive Drag Minimization Wind Tunnel Investigation of a Flexible Wing with Variable Camber Continuous Trailing Edge Flap System

This paper reports the results of a recently completed real-time adaptive drag minimization wind tunnel investigation of a highly flexible wing wind tunnel model equipped with the Variable Camber Continuous Trailing Flap (VCCTEF) technology at the University of Washington Aeronautical Laboratory (UWAL). The wind tunnel investigation is funded by NASA SBIR Phase II contract with Scientific Systems Company, Inc. (SSCI) and University of Washington (UW) as a subcontractor. The wind tunnel model is a sub-scale Common Research Model (CRM) wing constructed of foam core and fiberglass skin and is aeroelastically scaled to achieve a wing tip deflection of 10% of the wing semi-span which represents a typical wing tip deflection for a modern transport such as Boeing 787. The jig-shape twist of the CRM wing is optimized using a CART3D aero-structural model to achieve the minimum induced drag for the design cruise lift coefficient of 0.5. The wing is equipped with two chord wise cambered segments for each of the six span wise flap sections for a total of 12 individual flap segments that comprise the VCCTEF system. Each of the 12 flap segments is actively controlled by an electric servo-actuator. The real-time adaptive drag optimization strategy includes an on-board aerodynamic model identification, a model excitation, and a real-time drag optimization. The on-board aerodynamic model is constructed parametrically as a function of the angle of attack and flap positions to model the lift and drag coefficients of the wing. The lift coefficient models include a linear model and a second-order model. The drag coefficient models include a quadratic model and a higher-order up to 6th-order model to accurately model the drag coefficient at high angles of attack. The onboard aerodynamic model identification includes a recursive least-squares (RLS) algorithm and a batch least-squares (BLS) algorithm designed to estimate the model parameters. The model excitation method is designed to sample the input set that comprises the angle of attack and the flap positions. Three model excitation methods are developed: random excitation method, sweep method, and iterative angle-of-attack seeking method. The real-time drag optimization includes a generic algorithm developed by SSCI and several optimization methods developed by NASA which include a second-order gradient Newton-Raphson optimization method, an iterative gradient optimization method, a pseudo-inverse optimization method, an analytical optimization method, and an iterative refinement optimization method. The first wind tunnel test entry took place in September 2017. This test revealed major hardware issues and required further redesign of the flap servo mechanisms. The second test entry took place in April 2018. However, the test was not successful due to the issues with the onboard aerodynamic model identification RLS algorithm which incorrectly identified model parameters. This test also provides an experimental comparison study between the VCCTEF and a variable camber discrete trailing edge flap (VCDTEF) without the elastomer transition mechanisms. The experimental result confirms the benefit of the VCCTEF which produces lower drag by 5% than the VCDTEF. The third and final test entry took place in June 2018 after the issues with the RLS algorithm have been identified and corrected. Additional improvements were implemented. These include the BLS algorithm, the iterative angle-of-attack seeking method, the iterative gradient optimization method, and the pseudo-inverse optimization method. The test objectives were successfully demonstrated as the real-time drag optimization identifies several optimal solutions at off-design lift coefficients. The iterative gradient optimization method is found to achieve up to 4.7% drag reduction for the off-design lift coefficient of 0.7. The pseudo-inverse optimization method which does not require the drag coefficient model is found to be quite effective in reducing drag. Up to 9.4% drag reduction for the off-design lift coefficient of 0.7 is achieved with the pseudo-inverse optimization method. The wind tunnel investigation demonstrates the potential of real-time drag optimization technology. Several new capabilities are developed that could enable future adaptive wing technologies for flexible wings equipped with drag control devices such as the VCCTEF.

Drag Optimization↗
NASA NTRS2019

NASA Station Explorer for X-Ray Timing and Navigation Technology (SEXTANT) Mission Operations Architecture

"The Station Explorer for X-Ray Timing and Navigation (SEXTANT) mission is a technology demonstrationenhancement to the Neutron Star Interior Composition Explorer (NICER) mission, a NASA AstrophysicsExplorer Mission of Opportunity to the International Space Station (ISS) that was launched in June of 2017.The NICER instrument is a precision pointing X-ray telescope that provides measurements of neutron stars,which the SEXTANT mission uses to perform autonomous onboard X-ray Pulsar Navigation (XNAV) by usingmilli-second pulsars (MSPs), a category of neutron stars, as timing sources for navigation. By comparing thedetected time of arrival of X-ray photons to a reference of expected pulsar lightcurve timing models, one caninfer a range and range rate measurement based on light time delay. Since both timing and orientationinformation comes from a celestial source, this technology could provide a GPS-like navigation capabilityavailable throughout our Solar System and beyond. Applications that XNAV can support include outer planetand interstellar missions, manned missions, libration orbit missions, and current infrastructure such as the DeepSpace Network (DSN). The SEXTANT team successfully completed a rst demonstration of in-space andautonomous XNAV in November 2017. NICER and SEXTANT have separate teams, with NICER being theprimary team with its own science objectives. Operational modes for both missions must have concurrent andindependent components as well as an integrated ground system. Within this joint mission pro le, SEXTANToperations requires an infrastructure and cadence that is exible to handle concurrent science operations fromthe NICER team, independent autonomous navigation demonstrations, and events within the extensive ISSoperations environment. This paper rst details the infrastructure implemented and its concept of operations.It then describes the operations for the SEXTANT demonstration and lessons learned."

Yu, Wayne H.↗
NASA NTRS2018

Practical Aspects of Real-Time Modeling for the Learn-To-Fly Concept

Practical aspects of autonomous onboard real-time modeling for the NASA Learn-to-Fly concept are examined using flight data from two subscale test aircraft. A practical real-time global nonlinear aerodynamic modeling method is developed and explained, along with the multiple-input excitation needed for effective real-time modeling. Critical issues for integrating real-time global nonlinear aerodynamic modeling and local linear modeling with the real-time learning adaptive control and guidance elements of the Learn-to-Fly algorithm are identified and discussed. Real-time modeling results from NASA Learn-to-Fly flight demonstrations are presented and evaluated using model fit metrics and prediction tests.

Morelli, Eugene A.↗
NASA NTRS2020

Global Aerodynamic Modeling Using Automated Local Model Networks in Real Time

A novel method is presented for automated real-time global aerodynamic modeling using local model networks, known as Smoothed Partitioning with Localized Trees in Real Time (SPLITR), as part of NASA’s Learn-to-Fly technology development initiative. The global nonlinear aerodynamics are partitioned into several local regions known as cells, with the dimension, location, and timing of each partition automatically selected based on a residual characterization procedure, under the constraints of real-time operation. Regression trees represent the successive partitioning of the global flight envelope and describe the evolution of the cell structure. Recursive equation-error least-squares parameter estimation in the time domain is used to estimate a model that represents the local aerodynamics in each region, so that it can be updated independently with non-contiguous data in the range of each cell over time. A weighted superposition of these piecewise local models across the flight envelope forms a global nonlinear model that also accurately captures the local aerodynamics. The SPLITR approach is demonstrated using both simulation and flight data, and the results are analyzed in terms of model predictive capabilities as well as interpretability. The results show that SPLITR can be used to automatically partition complex nonlinear aerodynamic behavior, produce an accurate model, and provide valuable physical insight into the local and global aerodynamics.

Weinstein, Rose↗
NASA NTRSDate not supplied

Evaluation of Performance, Fatigue and Workload During Real-time, Reactive Telerobotic Mission Control Operations

Real-time, reactive telerobotic mission control operations require personnel to actively operate and manage remotely controlled vehicles or robots in real time. Due to the physical separation of the vehicle from the operator, such operations present many additional factors that can influence fatigue (i.e., degraded mental performance) and workload (i.e., mental and physical cost of task requirements), making it difficult to assess how long an individual can safely and accurately conduct operations. The upcoming Volatiles Investigating Polar Exploration Rover (VIPER) mission involves remotely controlling a lunar vehicle from an Earth-based mission control station. METHODS: In order to determine how long personnel could successfully maintain alertness and performance while operating a rover, we studied seven trained operators (i.e., 5 drivers, 2 real-time scientists) in a simulated mission control environment. We further assessed workload in order to determine whether perceived workload levels would change relative to time on task and by time of day. Operators completed two five-hour simulations in a randomized order, beginning at noon and at midnight. Performance was evaluated every 30 minutes using the psychomotor vigilance task (PVT), Karolinska Sleepiness Scale (KSS), and NASA Task Load Index (NASA-TLX). RESULTS: On average, participants rated themselves as sleepier (5.06 ± 2.28) on the night drives compared to the day drives (3.12 ± 1.44; P < .0001). Workload was rated higher during the day drives (37.93 ± 20.09) compared to night (32.09 ± 21.74; P < .01). Lastly, participants had no change in average reaction time between the two drives. CONCLUSIONS: From the analysis, we observed performance began to degrade after approximately three hours of driving. Our findings suggest that rotating drivers at least every three hours would be prudent to allow for breaks, and to minimize performance degradation, particularly during night shifts.

fatigue↗
NASA NTRSDate not supplied

The optimum cost-effective test time for redundant systems with specified reliability and confidence

This paper investigates the optimum test time to determine the number of redundant units needed to achieve high reliability with high confidence. Newly designed systems often have high initial failure rates which can be reduced by testing to find failure modes and remove them by redesign. To accurately estimate the required number of redundant units, the test time must be extended to accurately determine the failure rate. If the measured failure rate is used, there is a 50% chance that the actual hardware failure rate is higher. Using the measured failure rate gives only a 50% confidence that the failure rate and number of spares are not too low. After the test, given the measured failure rate and the desired reliability, the number of spares can be determined and the confidence in the reliability computed. Instead of accepting the reliability results of a fixed duration test, it is possible to set the requirements for both the redundant reliability and the confidence level and then compute the test time needed to minimize the total cost required to achieve these requirements. The confidence that the redundant reliability is not too low is increased by using a higher than measured failure rate to increase the number of spares. The higher number of spares increases cost. Longer test time reduces the variance in the failure rate and the increase in the number of spares, so that test cost increases and spares cost decreases. The total cost is the sum of the cost of the test time and the spares. The optimum test time produces the minimum total cost for the system failure rate, mission length, and required reliability and confidence level. Longer testing is justified by reduced cost. Some examples are given.

Harry W Jones↗
NASA NTRS2017

Solar System Ephemerides, Pulsar Timing, Gravitational Waves, & Navigation

In-spiraling supermassive black holes should emit gravitational waves, which would produce characteristic distortions in the pulse time of arrival residuals from millisecond pulsars. There are multiple national and regional consortia that have constructed pulsar timing arrays by precise timing of different sets of millisecond pulsars. An essential aspect of precision timing is the transfer of the pulsar times of arrival to a (quasi-)inertial reference frame, conventionally taken to be the solar system barycenter. The solar system barycenter is determined from the knowledge of the planetary masses and orbits, which has been re ned over the course of the past 50 years by multiple spacecraft missions. Within the North American Nanohertz Observatory for Gravitational Waves (NANOGrav), uncertainties on the solar system barycenter are emerging as an important element of the overall NANOGrav noise budget. We describe what is known about the solar system barycenter, touch upon how uncertainties in it affect gravitational wave studies with pulsar timing arrays, and consider future trends in spacecraft navigation.

Vallisneri, M.↗