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At least 1,189 records · Page 66

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NASA NTRSDate not supplied

Natural Language Processing for Extracting Rich Disease Data Aligned To Satellite Meteorological Data

Global climate change is redefining our understanding of how diseases spread. In Sri Lanka, vector-borne diseases such as dengue fever, encephalitis, and leptospirosis historically surged during the monsoon seasons when temperatures were high enough for mosquito eggs to hatch. Unfortunately, due to rising temperatures and more erratic rainfall patterns, mosquito eggs can now hatch year-round and are increasingly unpredictable, leading to an alarmingly increasing number of hospitalizations and deaths. More data is needed to adapt our response to these diseases in an increasingly warmer world. In the contemporary landscape, a wealth of disease information is available, yet accessibility remains limited due to unstructured data formats such as PDFs. Therefore, converting unstructured disease reports into structured formats is necessary for effectively leveraging data. This paper introduces a comprehensive framework for collecting unstructured disease reports and transforming them into analyzable formats. By creating separate models tailored to each data format, we can ensure accuracy compared to general models. These straightforward models enhance accessibility and empower other researchers to use our tools. The returned structured data can then be harnessed for analysis, statistical purposes, and informing evidence-based public health interventions, thus facilitating more informed decision-making in healthcare. We deploy this framework to produce geospatial data for Sri Lanka and Brazil for many different conditions and align these data with satellite environmental data, providing for the first time a structured, aligned powerful dataset for disease modeling.

Open Source Open Science↗

NASA NTRS2014

Soft Factors and Space Mission Failures: Quantifying the Effect of Management Decisions

No abstract available

Command File Errors↗

NASA NTRS1995

Use of agents to implement an integrated computing environment

Integrated Product and Process Development (IPPD) embodies the simultaneous application to both system and quality engineering methods throughout an iterative design process. The use of IPPD results in the time-conscious, cost-saving development of engineering systems. To implement IPPD, a Decision-Based Design perspective is encapsulated in an approach that focuses on the role of the human designer in product development. The approach has two parts and is outlined in this paper. First, an architecture, called DREAMS, is being developed that facilitates design from a decision-based perspective. Second, a supporting computing infrastructure, called IMAGE, is being designed. Agents are used to implement the overall infrastructure on the computer. Successful agent utilization requires that they be made of three components: the resource, the model, and the wrap. Current work is focused on the development of generalized agent schemes and associated demonstration projects. When in place, the technology independent computing infrastructure will aid the designer in systematically generating knowledge used to facilitate decision-making.

Hale, Mark A.↗

NASA NTRS2019

Health Management and Prognostics for Electric Aircraft Powertrain

W and c Any air borne vehicle needs incorporating safety as key parameter of measure, and inclusion of autonomy raises the critical need for safety under autonomous operations. Management of faults and component degradation is key as complexity in autonomous operations grow over the period of time. Therefore, in addition to basic operational requirements, an autonomous electric vehicle should be able to make accurate estimates of its current system health and take the correct decisions to complete its mission successfully. Real-time safety and state-awareness tools are therefore essential for the vehicle to be able to reach its destination in a safe and successful manner. The need for safety assurance and health management capabilities is particularly relevant for aircraft electric propulsion systems, which are relatively new and with limited historical to learn. They are critical systems requiring high power density along with reliability, resilience, efficient management of weight, and operational costs. A model- based fault diagnosis and prognostics approach of complex critical systems can successfully accomplish the safety and state awareness goal for such electric propulsion systems, enabling autonomous decision making capability for safe and efficient operation. To identify critical components in the system a Qualitative Bayesian approach using FMECA is implemented. This requires the assessment of some quantities representing the state of the electric unmanned aerial systems (e-UAS), as well as look-ahead forecasts of such states during the entire flight, presented in form of safety metrics (SM). In-service data and performance data gathered from degraded components sup- ports diagnostic and prognostic methods for these systems, but this data can be difficult to obtain as weight and packaging restrictions reduce redundancy and instrumentation on-board the vehicle. Therefore, an model-based framework should be capable or operating with limited data. In addition to data scarcity, the variability of such complex critical systems re- quires the model-based framework to reason in the presence of uncertainty, such as sensor noise, and modeling imperfections. Quantification of errors and uncertainties in the measured states and quantities is therefore a fundamental step for a precise estimation of such SMs; un-modeled uncertainty may result in erroneous state assessment and un- reliable predictions of future states of e-UAVs. Typical, centralized model-based schemes suffer from inherent disadvantages such as computational complexity, single point of failure, and scalability issues, and therefore may fail in such a complex scenario. This paper presents a methodology for developing a system level diagnostics and prognostics approach using a Qualitative Bayesian FMECA approach along with a formal uncertainty management framework for an e-UAS. In this work we demonstrate the efficacy of the framework to predict effects of sub-system level degradation on vehicle operation incorporating uncertainty management to predict future behavior under different operating conditions.

Kulkarni, Chetan↗

NASA NTRS2016

Remote Sensing and Modeling for Improving Operational Aquatic Plant Management

The California Sacramento-San Joaquin River Delta is the hub for California’s water supply, conveying water from Northern to Southern California agriculture and communities while supporting important ecosystem services, agriculture, and communities in the Delta. Changes in climate, long-term drought, water quality changes, and expansion of invasive aquatic plants threatens ecosystems, impedes ecosystem restoration, and is economically, environmentally, and sociologically detrimental to the San Francisco Bay/California Delta complex. NASA Ames Research Center and the USDA-ARS partnered with the State of California and local governments to develop science-based, adaptive-management strategies for the Sacramento-San Joaquin Delta. The project combines science, operations, and economics related to integrated management scenarios for aquatic weeds to help land and waterway managers make science-informed decisions regarding management and outcomes. The team provides a comprehensive understanding of agricultural and urban land use in the Delta and the major water sheds (San Joaquin/Sacramento) supplying the Delta and interaction with drought and climate impacts on the environment, water quality, and weed growth. The team recommends conservation and modified land-use practices and aids local Delta stakeholders in developing management strategies. New remote sensing tools have been developed to enhance ability to assess conditions, inform decision support tools, and monitor management practices. Science gaps in understanding how native and invasive plants respond to altered environmental conditions are being filled and provide critical biological response parameters for Delta-SWAT simulation modeling. Operational agencies such as the California Department of Boating and Waterways provide testing and act as initial adopter of decision support tools. Methods developed by the project can become routine land and water management tools in complex river delta systems.

Agriculture↗

NASA NTRS1989

Development of the XV-15 tiltrotor research aircraft - Lessons learned

The initial ground rules that guided the decision process during the initial stages of the XV-15 tiltrotor aircraft development are reviewed and reevaluated. A full flight-envelope nonlinear simulation mathematical model is outlined, along with the advantages of a multiaircraft program. Direct involvement of government engineers in all aspects of the program is considered to be beneficial, while the ejection-seat test requirement is not. Utilization of existing components - a rotor, transmissions, and engines - is analyzed, and emphasis is placed on integrated system test plans responsible for producing two reliable aircraft through a complete checkout of the aircraft subsystems before the start of the fligth program. Wind-tunnel and fatigue test requirements are presented, and the decision to go with an all mechanical control system design is addressed.

Schroers, Laurel G.↗

NASA NTRS1994

Integration of the Response Surface Methodology with the Compromise Decision Support Problem in Developing a General Robust Design Procedure

In this paper we introduce a comprehensive and rigorous robust design procedure to overcome some limitations of the current approaches. A comprehensive approach is general enough to model the two major types of robust design applications, namely, robust design associated with the minimization of the deviation of performance caused by the deviation of noise factors (uncontrollable parameters), and robust design due to the minimization of the deviation of performance caused by the deviation of control factors (design variables). We achieve mathematical rigor by using, as a foundation, principles from the design of experiments and optimization. Specifically, we integrate the Response Surface Method (RSM) with the compromise Decision Support Problem (DSP). Our approach is especially useful for design problems where there are no closed-form solutions and system performance is computationally expensive to evaluate. The design of a solar powered irrigation system is used as an example. Our focus in this paper is on illustrating our approach rather than on the results per se.

Chen, Wei↗

NASA NTRS1989

The role of flight planning in aircrew decision performance

The role of flight planning in increasing the safety and decision-making performance of the air transport crews was investigated in a study that involved 48 rated airline crewmembers on a B720 simulator with a model-board-based visual scene and motion cues with three degrees of freedom. The safety performance of the crews was evaluated using videotaped replays of the flight. Based on these evaluations, the crews could be divided into high- and low-safety groups. It was found that, while collecting information before flights, the high-safety crews were more concerned with information about alternative airports, especially the fuel required to get there, and were characterized by making rapid and appropriate decisions during the emergency part of the flight scenario, allowing these crews to make an early diversion to other airports. These results suggest that contingency planning that takes into account alternative courses of action enhances rapid and accurate decision-making under time pressure.

Pepitone, Dave↗

NASA NTRS1990

Automating hypertext for decision support

A decision support system (DSS) shell is being constructed that can support applications in a variety of fields, e.g., engineering, manufacturing, finance. The shell provides a hypertext-style interface for 'navigating' among DSS application models, data, and reports. The traditional notion of hypertext had to be enhanced. Hypertext normally requires manually, pre-defined links. A DSS shell, however, requires that hypertext connections to be built 'on the fly'. The role of hypertext is discussed in augmenting DSS applications and the decision making process. Also discussed is how hypertext nodes, links, and link markers tailored to an arbitrary DSS application were automatically generated.

Bieber, Michael↗

NASA NTRS2014

Uncertainty in Agricultural Impact Assessment

This chapter considers issues concerning uncertainty associated with modeling and its use within agricultural impact assessments. Information about uncertainty is important for those who develop assessment methods, since that information indicates the need for, and the possibility of, improvement of the methods and databases. Such information also allows one to compare alternative methods. Information about the sources of uncertainties is an aid in prioritizing further work on the impact assessment method. Uncertainty information is also necessary for those who apply assessment methods, e.g., for projecting climate change impacts on agricultural production and for stakeholders who want to use the results as part of a decision-making process (e.g., for adaptation planning). For them, uncertainty information indicates the degree of confidence they can place in the simulated results. Quantification of uncertainty also provides stakeholders with an important guideline for making decisions that are robust across the known uncertainties. Thus, uncertainty information is important for any decision based on impact assessment. Ultimately, we are interested in knowledge about uncertainty so that information can be used to achieve positive outcomes from agricultural modeling and impact assessment.

damage assessment↗

NASA NTRS2013

New Approaches in Reusable Booster System Life Cycle Cost Modeling

This paper presents the results of a 2012 life cycle cost (LCC) study of hybrid Reusable Booster Systems (RBS) conducted by NASA Kennedy Space Center (KSC) and the Air Force Research Laboratory (AFRL). The work included the creation of a new cost estimating model and an LCC analysis, building on past work where applicable, but emphasizing the integration of new approaches in life cycle cost estimation. Specifically, the inclusion of industry processes/practices and indirect costs were a new and significant part of the analysis. The focus of LCC estimation has traditionally been from the perspective of technology, design characteristics, and related factors such as reliability. Technology has informed the cost related support to decision makers interested in risk and budget insight. This traditional emphasis on technology occurs even though it is well established that complex aerospace systems costs are mostly about indirect costs, with likely only partial influence in these indirect costs being due to the more visible technology products. Organizational considerations, processes/practices, and indirect costs are traditionally derived ("wrapped") only by relationship to tangible product characteristics. This traditional approach works well as long as it is understood that no significant changes, and by relation no significant improvements, are being pursued in the area of either the government acquisition or industry?s indirect costs. In this sense then, most launch systems cost models ignore most costs. The alternative was implemented in this LCC study, whereby the approach considered technology and process/practices in balance, with as much detail for one as the other. This RBS LCC study has avoided point-designs, for now, instead emphasizing exploring the trade-space of potential technology advances joined with potential process/practice advances. Given the range of decisions, and all their combinations, it was necessary to create a model of the original model and use genetic algorithms to explore results. A strong business case occurs when viable paths are identified for an affordable up-front investment, and these paths can credibly achieve affordable, responsive operations, characterized by smaller direct touch labor efforts at the wing level from flight to flight. The results supporting this approach, its potential, and its conclusions are presented here.

Zapata, Edgar↗

NASA NTRS2013

New Approaches in Reuseable Booster System Life Cycle Cost Modeling

Zapata, Edgar↗

NASA NTRS1984

Missions/Planning Panel

A panel discussion was held to develop a viewpoint of space power technology needs and state of readiness for future mission scenarios. Among the points made in the discussion, it was agreed that missions, particularly the far term ones, do serve to drive technology; however, as the missions become nearer term, issues of schedule and cost severely limit the willingness to accept risk. There are, in fact, no rewards to a mission manager for introducing new technology. Mission downscaling is the usual response to technology limitations. All panelists agreed that there exists a serious gap between when technologists feel their job is done and what mission managers need for decision. Typically a two to three year engineering development gap exists. It is essential to take technologies to the engineering model level and conduct a flight demonstration to close this gap. All agreed that increased effort should be made to achieve stronger interactions between planners and technologists and that workshops like the present one are a step in the right direction. Technologists need mission credibility and vice versa.

Fordyce, J. S.↗

NASA NTRS1984

Getting Mental Models and Computer Models to Cooperate

A qualitative theory of supervisory control is outlined wherein the mental models of one or more human operators are related to the knowledge representations within automatic controllers (observers, estimators) and operator decision aids (expert systems, advice-givers). Methods of quantifying knowledge and the calibration of one knowledge representation to another (human, computer, or objective truth) are discussed. Ongoing experiments in the use of decision aids for exploring one's own objective function or exploring system constraints and control strategies are described.

Sheridan, T. B.↗

NASA NTRS1993

Far-infrared line images of dwarf galaxies

Irregular dwarf galaxies are about ten times more widespread in the universe than regular spiral galaxies. They are characterized by a relatively low metallicity, i.e., lower abundance of the heavier elements (metals) with respect to hydrogen than in the solar neighborhood. These heavier elements in the form of molecules, atoms, or ions, which have radiative transitions in the infrared play a decisive role in the energy balance of the ISM and thereby for the formation of stars. Dwarf galaxies are thus model cases for the physical conditions in the early phase of the universe. Large Magellanic Cloud: 30 Doradus. The two nearest dwarf galaxies are the Magellanic clouds at a distance approximately 50 kpc. The LMC contains 30 Dor, a region with young, extremely massive stars which strongly interact with the surrounding ISM on account of their stellar winds and intense UV radiation. 30 Dor is the brightest object in the LMC at almost all wavelengths.

Poglitsch, A.↗

NASA NTRS2003

Archetypes for Organisational Safety

We propose a framework using system dynamics to model the dynamic behavior of organizations in accident analysis. Most current accident analysis techniques are event-based and do not adequately capture the dynamic complexity and non-linear interactions that characterize accidents in complex systems. In this paper we propose a set of system safety archetypes that model common safety culture flaws in organizations, i.e., the dynamic behaviour of organizations that often leads to accidents. As accident analysis and investigation tools, the archetypes can be used to develop dynamic models that describe the systemic and organizational factors contributing to the accident. The archetypes help clarify why safety-related decisions do not always result in the desired behavior, and how independent decisions in different parts of the organization can combine to impact safety.

Marais, Karen↗

NASA NTRS2010

Space Shuttle Probabilistic Risk Assessment (SPRA) Iteration 3.2

The Shuttle is a very reliable vehicle in comparison with other launch systems. Much of the risk posed by Shuttle operations is related to fundamental aspects of the spacecraft design and the environments in which it operates. It is unlikely that significant design improvements can be implemented to address these risks prior to the end of the Shuttle program. The model will continue to be used to identify possible emerging risk drivers and allow management to make risk-informed decisions on future missions. Potential uses of the SPRA in the future include: - Calculate risk impact of various mission contingencies (e.g. late inspection, crew rescue, etc.). - Assessing the risk impact of various trade studies (e.g. flow control valves). - Support risk analysis on mission specific events, such as in flight anomalies. - Serve as a guiding star and data source for future NASA programs.

Boyer, Roger L.↗

NASA NTRSDate not supplied

In-Time Safety Assessment & Risk Prediction for Unmanned Aerial Systems

One of the critical challenges in emerging autonomous systems is timely mitigation of hazards encountered during operation which may not be known or accounted for at the time of design. Efficient execution of unmanned systems therefore demands a paradigm shift from scheduled periodic maintenance to predictive risk analysis that includes condition-based-monitoring, real-time reliability assessment and hazard mitigation. Particularly, the state-of-health parameters needs to be computed at the component level, unit level as well as the integrated system level. While in the former two levels, the physics of health propagation may be based on underlying electro-mechanical properties, system level prognostics often relies on data-driven models. Further, uncertainty from model, measurements and input sources should be accurately quantified to generate meaningful prediction results that can be fed into reliable decision making processes. Finally, the expected risk and time to failure has to be computed based on the current state-of-health of the overall system. This talk presents a conceptual design of such an in-time safety assurance approach for unmanned aerial vehicles (UAV) operating at low altitudes near and over populated areas. Typical in-flight hazard incidents include unplanned detour, proximity to obstacles, mid-flight component faults, limited battery life and poor quality of GPS measurements. Safety assessment therefore comprises trajectory generation and re-plan, battery RUL computation, distributed fault diagnostics and uncertainty management of predicted trajectory based on GPS measurement noise. The entire monitoring framework will be demonstrated on simulated as well as real UAV flight experiments conducted at the NASA Langley Research Center. This tutorial will therefore guide the audience through a step-by-step tracking of an autonomous system with focus on in-time risk prediction in the presence of unforeseen hazards and uncertain environment.

diagnostics↗