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Sixteen alternative spaceborne nuclear power system concepts were ranked using multiattribute decision analysis to identify promising concepts for further technology development. Four groups interviewed were: safety, systems definition and design, technology assessment, and mission analysis. The ranking results were consistent from group and for different utility function models for individuals.
The year is 2004, NASA has landed and deployed a fleet of rovers on the surface of Mars to continue the exploration of that planet and prepare the way for human visitors. Middle school students at Milton Elementary have been following the mission through the media and Internet as part of Mr. Johnson's Earth and space sciences class. The kids have been working in teams to track the rovers as they move across the surface of Mars on a scale model of the landing site they built from sand and rocks using pictures and video downloaded from the Internet. They also built their own version of a rover that can be driven around the model. The time is 3:36pm. Jim and a couple of his fellow students from class are sitting in the cafeteria waiting for a student council meeting to begin. Mary and several others are on the bus riding home. Kathy is in her father's car waiting to leave the parking lot. On Mars, Rover-3 has just stopped and issued an alert to ground control at NASA's Jet Propulsion Laboratory (JPL). Back at Milton Elementary chimes can be heard going off in the cafeteria, on the school bus, and in Kathy's car. The students are familiar with the drill and each brings up the Mars mission status display on their hand-held PDA device. They've been using their PDAs (those Palm devices that seem to be everywhere today) to obtain real-time position information for each of the rovers throughout the mission. The mission status display tells them that Rover-3 has stopped on the edge of a small gully and isn't quite sure what to do. The students begin considering the options amongst themselves. Should the rover just drive through the gully? If it does, what happens if it gets stuck? Maybe it should turnaround and look for away around the gully? Trough questions. Real questions. Real problems. The students know they will need to be prepared to discuss the options and conduct their own simulations using the models they built in Mr. Johnson's class tomorrow. Much the same way engineers and scientists will be working to solve the problem at NASA. It's a couple of days later, NASA has made a decision on what to do and has issued new commands for Rover-3 to execute at 9:15am Milton Elementary time. Interestingly, NASA's solution to the problem differs from the one favored by the students. 9:16am, chimes can be heard going off throughout Milton Elementary.
A simple analytical criterion is provided for deciding whether a human or automation is best for a failure detection task. The method is based on expected-value decision theory in much the same way as is signal detection. It requires specification of the probabilities of misses (false negatives) and false alarms (false positives) for both human and automation being considered, as well as factors independent of the choice--namely, costs and benefits of incorrect and correct decisions as well as the prior probability of failure. The method can also serve as a basis for comparing different modes of automation. Some limiting cases of application are discussed, as are some decision criteria other than expected value. Actual or potential applications include the design and evaluation of any system in which either humans or automation are being considered.
Results are reported from a new paradigm that uses movement-related brain potentials to detect response preparation based on partial information. The paradigm uses a hybrid choice-reaction go/nogo procedure in which decisions about response hand and whether to respond are based on separate stimulus attributes. A lateral asymmetry in the movement-related brain potential was found on nogo trials without overt movement. The direction of this asymmetry depended primarily on the signaled response hand rather than on properties of the stimulus. When the asymmetry first appeared was influenced by the time required to select the signaled hand, and when it began to differ on go and nogo trials was influenced by the time to decide whether to respond. These findings indicate that both stimulus attributes were processed in parallel and that the asymmetry reflected preparation of the response hand that began before the go/nogo decision was completed.
This article describes methods for online model-based diagnosis of subsystems of the advanced life support system (ALS). The diagnosis methodology is tailored to detect, isolate, and identify faults in components of the system quickly so that fault-adaptive control techniques can be applied to maintain system operation without interruption. We describe the components of our hybrid modeling scheme and the diagnosis methodology, and then demonstrate the effectiveness of this methodology by building a detailed model of the reverse osmosis (RO) system of the water recovery system (WRS) of the ALS. This model is validated with real data collected from an experimental testbed at NASA JSC. A number of diagnosis experiments run on simulated faulty data are presented and the results are discussed.
The long observational record is critical to our understanding of the Earth s climate, but most observing systems were not developed with a climate objective in mind. As a result, tremendous efforts have gone into assessing and reprocessing the data records to improve their usefulness in climate studies. Many challenges remain, such as tracking the improvement of processing algorithms and limited spatial coverage. Reanalyses have fostered significant research, yet reliable global trends in many physical fields are not yet attainable, despite significant advances in data assimilation and numerical modeling. Communication of the strengths, limitations and uncertainties of reprocessed observations and reanalysis data, not only among the community of developers, but also with the extended research community, including the new generations of researchers and the decision makers is crucial for further advancement of the observational data records. WCRP provides the means to bridge the different motivating objectives on which national efforts focus.
Understanding the radiative forcing caused by anthropogenic aerosol sources is essential for making effective emission control decisions to mitigate climate change. We examined the net direct plus indirect radiative forcing caused by carbonaceous aerosol and sulfur emissions in key sectors of China and India using the GISS-E2 chemistry-climate model. Diesel trucks and buses (67 mW/ sq. m) and residential biofuel combustion (52 mW/ sq. m) in India have the largest global mean, annual average forcings due mainly to the direct and indirect effects of BC. Emissions from these two sectors in China have near-zero net global forcings. Coal-fired power plants in both countries exert a negative forcing of about -30 mW/ sq. m from production of sulfate. Aerosol forcings are largest locally, with direct forcings due to residential biofuel combustion of 580 mW/ sq. m over India and 416 mW/ sq. m over China, but they extend as far as North America, Europe, and the Arctic
Agriculture in Sub-Saharan Africa (SSA) is experiencing climate change-related effects that call for integrated regional assessments, yet capacity for these assessments has been low. The Agricultural Model Intercomparison and Improvement Project (AgMIP) is advancing research on integrated regional assessments of climate change that include climate, crop, and economic modeling and analysis. Through AgMIP, regional integrated assessments are increasingly gaining momentum in SSA, and multi-institutional regional research teams (RRTs) centered in East, West, and Southern· Africa are generating new information on climate change impacts and adaptation in selected agricultural systems. The research in Africa is organized into four RRTs and a coordination team. Each of the RRTs in SSA is composed of scientists from the Consultative Group of International Agricultural Research (CGIAR) institutions, National Agriculture Research institutes (NARs), and universities consisting of experts in crop and economic modeling, climate, and information technology. Stakeholder involvement to inform specific agricultural systems to be evaluated, key outputs, and the representative agricultural pathways (RAPs), is undertaken at two levels: regional and national, in order to contribute to decision making at these levels. Capacity building for integrated assessment (lA) is a key component that is undertaken continuously through interaction with experts in regional and SSA-wide workshops, and through joint creation of tools. Many students and research affiliates have been identified and entrained as part of capacity building in IA. Bi-monthly updates on scholarly publications in climate change in Africa also serve as a vehicle for knowledge-sharing. With 60 scientists already trained and actively engaged in IA and over 80 getting monthly briefs on the latest information on climate change, a climate-informed community of experts is gradually taking shape in SSA. (See Part 2, Appendices 3-5 in this volume for AgMIP Regional Workshop reports.)
This plan institutes direction across the Gateway Program and the Element Projects to ensure that Cross Program M&S are produced in a manner that (1) generate the artifacts required for NASA-STD-7009 compliance, (2) ensures interoperability of M&S exchanged and integrated across the program and, (3) drives integrated development efforts to provide cross-domain integrated simulation of the Gateway elements, space environment, and operational scenarios. This direction is flowed down via contractual enforcement to prime contractors and includes both the GMS requirements specified in this plan and the NASASTD- 7009 derived requirements necessary for compliance. Grounding principles for management of Gateway Models and Simulations (M&S) are derived from the Columbia Accident Investigation Board (CAIB) report and the Diaz team report, “A Renewed Commitment to Excellence.” As an outcome of these reports, and in response to Action 4 of the Diaz team report, the NASA Standard for Models and Simulations, NASA-STD-7009 was developed. The standard establishes M&S requirements for development and use activities to ensure proper capture and communication of M&S pedigree and credibility information to Gateway program decision makers. Through the course of the Gateway program life cycle M&S will be heavily relied upon to conduct analysis, test products, support operations activities, enable informed decision making and ultimately to certify the Gateway with an acceptable level of risk to crew and mission. To reduce risk associated with M&S influenced decisions, this plan applies the NASA-STD-7009 requirements to produce the artifacts that support credibility assessments and ensure the information is communicated to program management.
Future air traffic management systems will need to accommodate large numbers of increasingly diverse air vehicles with different operating paradigms. To support this trend, they will digitally share copious amounts of information via a common communication architecture. Operators will deploy programs that create and negotiate flight plans via the architecture’s communication protocols. These programs will autonomously make decisions that must be arbitrated by the architecture and robust to uncertainty. To study interoperability in air traffic management, a new airspace simulation system was composed by integrating a legacy airspace simulation, an air traffic control model, and a new research communication architecture. It was used to evaluate air traffic management concepts by adapting it to handle congested arrival traffic at Newark Liberty International Airport and executing simulations. Results demonstrated the ability of the simulation system to model in detail strategic traffic flow management, predeparture flight planning, and air traffic control working in concert. Subsequent studies can use the simulation system to study interoperability, autonomy, digital communication, and uncertainty in future air traffic management systems.
Future air traffic management systems will need to accommodate large numbers of increasingly diverse air vehicles with different operating paradigms. To support this trend, they will digitally share copious amounts of information via a common communication architecture. Operators will deploy programs that create and negotiate flight plans via the architecture’s communication protocols. These programs will autonomously make decisions that must be arbitrated by the architecture and robust to uncertainty. To study interoperability in air traffic management, a new airspace simulation system was composed by integrating a legacy airspace simulation, an air traffic control model, and a new research communication architecture. It was used to evaluate air traffic management concepts by adapting it to handle congested arrival traffic at Newark Liberty International Airport and executing simulations. Results demonstrated the ability of the simulation system to model in detail strategic traffic flow management, predeparture flight planning, and air traffic control working in concert. Subsequent studies can use the simulation system to study interoperability, autonomy, digital communication, and uncertainty in future air traffic management systems.
Future air traffic management systems will need to accommodate large numbers of increasingly diverse air vehicles with different operating paradigms. To support this trend, they will digitally share copious amounts of information via a common communication architecture. Operators will deploy programs that create and negotiate flight plans via the architecture’s communication protocols. These programs will autonomously make decisions that must be arbitrated by the architecture and robust to uncertainty. To study interoperability in air traffic management, a new airspace simulation system was composed by integrating a legacy airspace simulation, an air traffic control model, and a new research communication architecture. It was used to evaluate air traffic management concepts by adapting it to handle congested arrival traffic at Newark Liberty International Airport and executing simulations. Results demonstrated the ability of the simulation system to model in detail strategic traffic flow management, predeparture flight planning, and air traffic control working in concert. Subsequent studies can use the simulation system to study interoperability, autonomy, digital communication, and uncertainty in future air traffic management systems.
In the past decade, emphasis on promoting “climate literacy” in K-16 science classrooms has increased. Teachers play a critical role in cultivating these opportunities, especially in secondary science classrooms. However, most prior climate education research has focused on students and student learning; little is known about how teachers implement climate-focused curricular interventions. Here, we report findings from a concurrent mixed methods, multiple-case study of four secondary science teachers’ implementation of a new, NGSS-aligned, model-centric climate curriculum module grounded in the use of a data-driven, computer-based climate modeling tool—Easy Global Climate Model (EzGCM). We employ multiple data sources, including video-recorded classroom observations, interviews, and instructional artifacts, and both qualitative and quantitative analyses, to investigate how teachers implemented the curriculum. Findings show that, overall, teachers implemented the curriculum in ways that were less model-centric than designed, placing greater emphasis on EzGCM itself rather than using the model to investigate Earth’s changing climate. Additionally, we present detailed single-case studies of each participant teacher that highlight differences in teachers’ implementation of the curriculum module and their reasoning for making observed instructional decisions. This research sheds light on the design of secondary science learning environments by illustrating the varied ways teachers implement a climate-focused curriculum to support students’ developing climate literacy. This has important implications for the design of climate-focused curriculum and supports for teachers.
The accuracy of streamflow predictions in the EPA's BASINS (Better Assessment Science Integrating Point and Nonpoint Sources) decision support tool is affected by the sparse meteorological data contained in BASINS. The North American Land Data Assimilation System (NLDAS) data with high spatial and temporal resolutions provide an alternative to the NOAA National Climatic Data Center (NCDC)'s station data. This study assessed the improvement of streamflow prediction of the Hydrological Simulation Program-FORTRAN (HSPF) model contained within BASINS using the NLDAS 118 degree hourly precipitation and evapotranspiration estimates in seven watersheds of the Chesapeake Bay region. Our results demonstrated consistent improvements of daily streamflow predictions in five of the seven watersheds when NLDAS precipitation and evapotranspiration data was incorporated into BASINS. The improvement of using the NLDAS data is significant when watershed's meteorological station is either far away or not in a similar climatic region. When the station is nearby, using the NLDAS data produces similar results. The correlation coefficients of the analyses using the NLDAS data were greater than 0.8, the Nash-Sutcliffe (NS) model fit efficiency greater than 0.6, and the error in the water balance was less than 5%. Our analyses also showed that the streamflow improvements were mainly contributed by the NLDAS's precipitation data and that the improvement from using NLDAS's evapotranspiration data was not significant; partially due to the constraints of current BASINS-HSPF settings. However, NLDAS's evapotranspiration data did improve the baseflow prediction. This study demonstrates the NLDAS data has the potential to improve stream flow predictions, thus aid the water quality assessment in the EPA nonpoint water quality assessment decision tool.
The article discusses satellite observation of marine environments via microwave sensors and visible/infrared measurements. Specific applications include the monitoring of physical oceanography, weather and climate, coastal processes, ice processes, and resource use management. Four types of information delivery systems are identified: direct-to-user, regional/local user, global modeling user, and research user modes. Current developments in the marine information system include onboard correlation of synthetic aperture radar images at 10 to 100 m resolutions, and the extraction of wave, ship, iceberg or areal feature information from the image or signal before correlation.
All liquid propellant rocket instability calculations in current use have limited value in the predictive sense and serve mainly as a correlating framework for the available data sets. The well-known n-t model first introduced by Crocco and Cheng in 1956 is still used as the primary analytical tool of this type. A multitude of attempts to establish practical analytical methods have achieved only limited success. These methods usually produce only stability boundary maps that are of little use in making critical design decisions in new motor development programs. Recent progress in understanding the mechanisms of combustion instability in solid propellant rockets"' provides a firm foundation for a new approach to prediction, diagnosis, and correction of the closely related problems in liquid motor instability. For predictive tools to be useful in the motor design process, they must have the capability to accurately determine: 1) time evolution of the pressure oscillations and limit amplitude, 2) critical triggering pulse amplitude, and 3) unsteady heat transfer rates at injector surfaces and chamber walls. The method described in this paper relates these critical motor characteristics directly to system design parameters. Inclusion of mechanisms such as wave steepening, vorticity production and transport, and unsteady detonation wave phenomena greatly enhance the representation of key features of motor chamber oscillatory behavior. The basic theoretical model is described and preliminary computations are compared to experimental data. A plan to develop the new predictive method into a comprehensive analysis tool is also described.
The study elicited over 100 ideas for Space Processing. Of the elicited ideas, more than 20% involved processing of biologicals, or related medical and life sciences applications. Among these were High Purity Separation of Isoenzymes, and Development of Biorhythms applications data. Program planning for four products is outlined. Experimentation and testing resulted in definition of nearly 70 series of tests in ground-based laboratories, sounding rockets, etc., and space shuttle. Development schedules established timing and interrelationships of decisions involved in carrying these products to the point of production. The potential profitability of the four products is determined. Resources needed to achieve full scale production included use of shuttle for transportation, for which cost apportionment model was developed. R and D resources for the four products totalled $46,000,000 with Isoenzymes requiring the smallest expenditure, $4,000,000. A computerized profitability model (INVEST) was used to determine the measures of profitability of each product. Results build confidence that there will be a payoff.
Fuzzy knowledge, that for which the terms of reference are not crisp but overlapped, seems to characterize human expertise. This can be shown from the fact that an experienced human operator can control some complex plants better than a computer can. Proposed here is fuzzy theory to build a fuzzy expert relation matrix (FERM) from given rules or/and examples, either in linguistic terms or in numerical values to mimic human processes of perception and decision making. The knowledge base is codified in terms of many implicit fuzzy rules. Fuzzy knowledge thus codified may also be compared with explicit rules specified by a human expert. It can also provide a basis for modeling the human operator and allow comparison of what a human operator says to what he does in practice. Two experiments were performed. In the first, control of liquid in a tank, demonstrates how the FERM knowledge base is elicited and trained. The other shows how to use a FERM, build up from linguistic rules, and to control an inverted pendulum without a dynamic model.