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The Clouds project is well underway to its goal of building a unified distributed operating system supporting the object model. The operating system design uses the object concept of structuring software at all levels of the system. The basic operating system was developed and work is under progress to build a usable system.
Tritium management is critical for the safety, sustainability, and economics of fusion energy systems, and advanced and reliable modeling tools help accelerate the development of tritium technologies. This paper presents the Tritium Migration Analysis Program, Version 8 (TMAP8), an open-source, MOOSE-based application developed to provide state-of-the-art tritium transport and fuel cycle modeling capabilities. TMAP8 aims to expand the capabilities of previous versions (i.e., TMAP4 and TMAP7) by leveraging modern computational techniques, ensuring high software quality assurance standards (key to building trust), and enabling multispecies, multiscale, and multiphysics simulations for integrated tritium transport modeling in complex geometries. This paper outlines TMAP8’s scope and rigorous development practices, emphasizing its transparency, accessibility, modularity, and reliability. We present the current suite of verification and validation cases based on those from TMAP4, demonstrating TMAP8’s accuracy and reliability against analytical solutions and experimental data. Additionally, the paper showcases TMAP8’s integrated fuel cycle modeling capabilities, highlighting its applicability at various scales and levels. The TMAP8 code and documentation are openly available, promoting collaborative development and widespread adoption within the fusion community. Future work will soon expand TMAP8’s verification and validation suite to include those from TMAP7 and other recent experimental studies for validation.
Over the last ten years, lower costs and government incentives for rooftop and utility scale solar photovoltaic (PV) systems have led to a rapid growth in the amount of power generated from this renewable energy source. For example, the cumulative PV generating capacity of 1,160 MW in New York State at the end of 2018 represents a growth of more than 4,000% over the past seven years and almost 400% over the past five years. But increased dependence on this inherently variable energy source introduces the need to anticipate, i.e., forecast, changes in energy production and manage them appropriately. Utilities and grid operators can then use this forecast information to balance changes and maintain stability of the electric grid by adding additional sources or diverting excess supplies for sale or storage, as needed. Current techniques based on persistence modeling are not accurate enough to provide reliable forecasts. With support from the U.S. Department of Energy’s Solar Energy Technology Office (DOE SETO) and the New York Power Authority (NYPA), Brookhaven National Laboratory (BNL), the National Center for Atmospheric Research (NCAR), and the Electric Power Research Institute (EPRI) formed a collaborative team to provide reliable forecasting over a range of time intervals. In addition, the forecasting area was scaled up to about 50 km2, a factor of 20 times larger than previously achieved, so that available solar irradiance could be forecast throughout an entire region including both large generating facilities and distributed rooftop solar arrays. In its role, BNL developed a technology for predicting changes in available solar energy from zero to 30 minutes ahead. This “nowcasting” approach uses inexpensive, off-the-shelf, high definition (HD) imagers with custom software to identify and track the movement of approaching clouds and predict their impact on available solar irradiance. The BNL Nowcasting model improves forecasting accuracy by 20 to 50% over current techniques. Forecasting reliability for low clouds (worst case scenario since they move over solar panels more rapidly than high clouds) was calculated to be 95% accurate for forecast periods of five minute ahead. Reliability decreases with longer forecast time intervals and was calculated to be about 80% for 10 minute forecasts, and about 70% for 20 minutes ahead. Clouds were still reliably tracked by the imager network at 60% accuracy for forecast lead times up to about 30 minutes ahead, and this was determined to be the practical nowcasting limit for low clouds in a network of this scale. This work represents the second phase of a multi-phase effort to develop and deploy solar forecasting at a regional scale so that contributions from distributed rooftop solar resources can be forecast along with solar generating facilities, giving utilities and stakeholders an accurate assessment of future energy production. Additional work is planned to operate the forecasting network in an area upstate New York to assess system reliability under diverse meteorological conditions and to monitor system performance over a full range of seasonal variability.
As with any scientific endeavor, the foundation of icing research at the NASA Glenn Research Center (GRC) is the data acquired during experimental testing. In the case of the GRC Icing Branch, an important part of this data consists of ice tracings taken following tests carried out in the GRC Icing Research Tunnel (IRT), as well as the associated operational and environmental conditions documented during these tests. Over the years, the large number of experimental runs completed has served to emphasize the need for a consistent strategy for managing this data. To address the situation, the Icing Branch has recently elected to implement the IceVal DatAssistant automated data management system. With the release of this system, all publicly available IRT-generated experimental ice shapes with complete and verifiable conditions have now been compiled into one electronically-searchable database. Simulation software results for the equivalent conditions, generated using the latest version of the LEWICE ice shape prediction code, are likewise included and are linked to the corresponding experimental runs. In addition to this comprehensive database, the IceVal system also includes a graphically-oriented database access utility, which provides reliable and easy access to all data contained in the database. In this paper, the issues surrounding historical icing data management practices are discussed, as well as the anticipated benefits to be achieved as a result of migrating to the new system. A detailed description of the software system features and database content is also provided; and, finally, known issues and plans for future work are presented.
The Verification and Validation Assuring Reliability and Security (VARS) project team has developed the proof-of-concept VARS framework which will be implemented in the form of a software tool called Risk-Informed Verification and Validation Recommendation (RIVVR). The framework will provide Energy Delivery System (EDS) stakeholders with cybersecurity focused verification and validation (V&V) approach which includes list of potentially relevant vulnerabilities to test or address, pre-procurement guidance, and separate lists of relevant standards, tools, and techniques (ST2) to be considered by utilities and vendors
The United States' power infrastructure is aging, underfunded, and vulnerable to cyber attack. Emerging smart grid technologies may take some of the burden off of existing systems and make the grid as a whole more efficient, reliable, and secure. The Pacific Northwest National Laboratory (PNNL) is funding research into several aspects of smart grid technology and grid security, creating a software simulation tool that will allow researchers to test power infrastructure control and distribution paradigms by utilizing different smart grid technologies to determine how the grid and these technologies react under different circumstances. Understanding how these systems behave in real-world conditions will lead to new ways to make our power infrastructure more resilient and secure. Demonstrating security in embedded systems is another research area PNNL is tackling. Many of the systems controlling the U.S. critical infrastructure, such as the power grid, lack integrated security and the aging networks protecting them are becoming easier to attack.
The goal of the Advanced On-Board Processor (AOP) development program is to design, build, and flight qualify a highly reliable, moderately priced, digital computer for application on a variety of spacecraft. Included in this development program is the preparation of a complete support software package which consists of an assembler, simulator, loader, system diagnostic, operational executive, and many useful subroutines. The AOP hardware/software system is an extension of the On-Board Processor (OBP) which was developed for general purpose use on earth orbiting spacecraft with its initial application being on-board the fourth Orbiting Astronomical Observatory (OAO-C). Although the OBP possesses the significant features that are required for space application, however, when operating at 100% duty cycle the OBP is too power-consuming for use on many smaller spacecraft. Computer volume will be minimized by implementing the processor and input/output portions of the machine with large scale integrated circuits. Power consumption will be reduced through the use of plated wire and, in some cases, semiconductor memory elements.
The primary objective of the Spacecraft Attitude Precision Pointing and Slewing Adaptive Control (SAPPSAC) experiment is to establish feasibility and evaluate capabilities of a ground-based spacecraft attitude control system, wherein RF command and telemetry links, together with a ground station on-line minicomputer, perform closed loop attitude control of the Applications Technology Satellite-6 (ATS-6). The ground processor is described, including operational characteristics and the controller software. Attitude maneuvers include precision pointing to fixed targets, slewing between targets, and generation of prescribed ground tracks. Test results show high performance and reliability for over 30 hours of on-line control with no serious anomalies. Attitude stabilization relative to a prescribed target has been achieved to better than 0.007 deg in pitch and roll and 0.02 deg in yaw for a period of 43 min. Ground tracks were generated which had maximum latitude/longitude deviations less than 0.15 deg from reference.
A comprehensive and integrated measurement system was identified and a design and development effort initiated to meet the criteria imposed by the National Transonic Facility operating environment. Specific measurement areas receiving concentrated attention include: data acquisition, force measurement, pressure instrumentation, flow visualization techniques, model attitude and model deformation measurement, and temperature measurement. The NTF instrument complex will be centered around four 32-bit, 1-microsecond-cycle-time central processing units connected in a multipoint-distributed network configuration. The principal activities to be supported by these computers are: (1) data base management and processing; (2) research measurement data acquisition and display; (3) tunnel and model control; and (4) process monitoring and communication control. The distributed network approach was chosen to modularize the functional software into definable and implementable parts by the various groups involved in the design and to permit use of similar hardware configurations to improve reliability and maintainability.
The Software Engineering Laboratory was monitoring software development at NASA Goddard Space Flight Center since 1976. The data collection activities of the Laboratory and some of the difficulties of obtaining reliable data are described. In addition, the application of this data collection process to a current prototyping experiment is reviewed.
This paper describes the motivation, conduct, and analysis of some 2500 low-level hardware fault cases applied in automated testing at the NASA Ames Reconfigurable Digital Flight Control System Facility. Fault detection was correlated with hardware and software fault monitoring and, in limited cases, with sensitivity to flight program execution modes. The results are statistically assessed to ascertain system-level reliability implications based on a single-fault model. Extension to multiple-fault models is addressed. The overall methodology/facility itself is judged to be a promising enhancement to current practice.
In recent years, advancements made in computer systems have prompted a move from centralized computing based on timesharing a large mainframe computer to distributed computing based on a connected set of engineering workstations. A major factor in this advancement is the increased performance and lower cost of engineering workstations. The shift to distributed computing from centralized computing has led to challenges associated with the residency of application programs within the system. In a combined system of multiple engineering workstations attached to a mainframe host, the question arises as to how does a system designer assign applications between the larger mainframe host and the smaller, yet powerful, workstation. The concepts related to real time data processing are analyzed and systems are displayed which use a host mainframe and a number of engineering workstations interconnected by a local area network. In most cases, distributed systems can be classified as having a single function or multiple functions and as executing programs in real time or nonreal time. In a system of multiple computers, the degree of autonomy of the computers is important; a system with one master control computer generally differs in reliability, performance, and complexity from a system in which all computers share the control. This research is concerned with generating general criteria principles for software residency decisions (host or workstation) for a diverse yet coupled group of users (the clustered workstations) which may need the use of a shared resource (the mainframe) to perform their functions.
The GEOTAIL spacecraft of the International Solar-Terrestrial Physics Program will use a series of paired lunar swingbys to explore distant parts of the earth's magnetic tail. A 21-day launch window has been calculated for GEOTAIL, in July and August 1992, to start its distant-tail phase with a first lunar swingby (S1) on September 8, 1992. The main launch window in July utilizes 4.5 revolutions in a transfer orbit to S1, with a mid-August contingency window that uses 2.5 transfer-orbit revolutions before S1. Designing a good distant-tail trajectory, and then accurately matching it at S1 for every day in the launch window, seems to be the easiest and most reliable strategy. However, the total delta-V costs of the current designs can probably be reduced, possibly with the help of new interactive software that can be run on personal computers.
Mobile satellite systems are subject to severe fading due to blockage of the line-of-sight (LOS) path by roadside vegetation. A thorough understanding of the fading effects is necessary for the design of a reliable land mobile satellite system (LMSS). Analytical and empirical models are presented for predicting fade statistics for vegetative shadowing of mobile satellite terminals. A software simulator for generating simulated fade data is also presented. A physical model relating physical path parameters to propagation model parameters is presented, and results using the model are shown.
This slide presentation reviews some of the issues concerning verification and validation testing of autonomous spacecraft routinely culminates in the exploration of anomalous or faulted mission-like scenarios using the work involved during the Dawn mission's tests as examples. Prioritizing which scenarios to develop usually comes down to focusing on the most vulnerable areas and ensuring the best return on investment of test time. Rules-of-thumb strategies often come into play, such as injecting applicable anomalies prior to, during, and after system state changes; or, creating cases that ensure good safety-net algorithm coverage. Although experience and judgment in test selection can lead to high levels of confidence about the majority of a system's autonomy, it's likely that important test cases are overlooked. One method to fill in potential test coverage gaps is to automatically generate and execute test cases using algorithms that ensure desirable properties about the coverage. For example, generate cases for all possible fault monitors, and across all state change boundaries. Of course, the scope of coverage is determined by the test environment capabilities, where a faster-than-real-time, high-fidelity, software-only simulation would allow the broadest coverage. Even real-time systems that can be replicated and run in parallel, and that have reliable set-up and operations features provide an excellent resource for automated testing. Making detailed predictions for the outcome of such tests can be difficult, and when algorithmic means are employed to produce hundreds or even thousands of cases, generating predicts individually is impractical, and generating predicts with tools requires executable models of the design and environment that themselves require a complete test program. Therefore, evaluating the results of large number of mission scenario tests poses special challenges. A good approach to address this problem is to automatically score the results based on a range of metrics. Although the specific means of scoring depends highly on the application, the use of formal scoring - metrics has high value in identifying and prioritizing anomalies, and in presenting an overall picture of the state of the test program. In this paper we present a case study based on automatic generation and assessment of faulted test runs for the Dawn mission, and discuss its role in optimizing the allocation of resources for completing the test program.
HEF with weight stack seems to be a very sturdy and reliable exercise device that should function well in a bed rest training setting. A few improvements should be made to both the hardware and software to improve usage efficiency, but largely, this evaluation has demonstrated HEF's robustness. The hardware offers loading to muscles, bones, and joints, potentially sufficient to mitigate the loss of muscle mass and bone mineral density during long-duration bed rest campaigns. With some minor modifications, the HEF with weight stack equipment provides the best currently available means of performing squat, heel raise, prone row, bench press, and hip flexion/extension exercise in a supine orientation.
This paper presents an overview of years of sensor system development and application for aerospace systems. The emphasis of this work is on developing advanced capabilities for measurement and control of aeropropulsion and crew vehicle systems as well as monitoring the safety of those systems. Specific areas of work include chemical species sensors, thin film thermocouples and strain gages, heat flux gages, fuel gages, SiC based electronic devices and sensors, space qualified electronics, and MicroElectroMechanical Systems (MEMS) as well as integrated and multifunctional sensor systems. Each sensor type has its own technical challenges related to integration and reliability in a given application. The general approach has been to develop base sensor technology using microfabrication techniques, integrate sensors with "smart" hardware and software, and demonstrate those systems in a range of aerospace applications. Descriptions of the sensor elements, their integration into sensors systems, and examples of sensor system applications will be discussed. Finally, suggestions related to the future of sensor technology will be given. It is concluded that smart micro/nano sensor technology can revolutionize aerospace applications, but significant challenges exist in maturing the technology and demonstrating its value in real-life applications.
Software Defined Radio (SDR) technology has been proven in the commercial sector since the early 1990's. Today's rapid advancement in mobile telephone reliability and power management capabilities exemplifies the effectiveness of the SDR technology for the modern communications market. In contrast, presently qualified satellite transponder applications were developed during the early 1960's space program. Programmable Ultra Lightweight System Adaptable Radio (PULSAR, NASA-MSFC SDR) technology revolutionizes satellite transponder technology by increasing data through-put capability by, at least, an order of magnitude. PULSAR leverages existing Marshall Space Flight Center SDR designs and commercially enhanced capabilities to provide a path to a radiation tolerant SDR transponder. These innovations will (1) reduce the cost of NASA Low Earth Orbit (LEO) and Deep Space transponders, (2) decrease power requirements, and (3) a commensurate volume reduction. Also, PULSAR increases flexibility to implement multiple transponder types by utilizing the same hardware with altered logic - no analog hardware change is required - all of which can be accomplished in orbit. This provides high capability, low cost, transponders to programs of all sizes. The final project outcome would be the introduction of a Technology Readiness Level (TRL) 7 low-cost CubeSat to SmallSat telemetry system into the NASA Portfolio.