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At least 235 records · Page 13

Rotorcraft Health Management Issues and Challenges

This paper presents an overview of health management issues and challenges that are specific to rotorcraft. Rotorcraft form a unique subset of air vehicles in that their propulsion system is used not only for propulsion, but also serves as the primary source of lift and maneuvering of the vehicle. No other air vehicle relies on the propulsion system to provide these functions through a transmission system with single critical load paths without duplication or redundancy. As such, health management of the power train is a critical and unique part of any rotorcraft health management system. This paper focuses specifically on the issues and challenges related to the dynamic mechanical components in the main power train. This includes the transmission and main rotor mechanisms. This paper will review standard practices used for rotorcraft health management, lessons learned from fielded trials, and future challenges.

Zakrajsek, James J.↗

The Lunar Environment: Determining the Health Effects of Exposure to Moon Dusts

The moon's surface is covered with a thin layer of fine, charged, reactive dust capable of layer of fine, charged, reactive dust capable of capable of entering habitats and vehicle compartments, where it can result in crewmember health problems. NASA formed the Lunar Airborne Dust Toxicity Advisory Group (LADTAG) to study the effects of exposure to Lunar Dust on human health. To date, no scientifically defensible toxicological studies have been performed on lunar dusts, specifically the determination of exposure limits and their affect on human health. The multi-center LADTAG (Lunar Airborne Dust Toxicology center LADTAG (Lunar Airborne Dust Toxicology Advisory Group) was formed in response to the Office of the Chief Health and Medical Office s (OCHMO) request to develop recommendations for defining risk (OCHMO) request to develop recommendations for defining risk defining risk criteria for human lunar dust exposure.

Khan-Mayberry, Noreen↗

Behavioral Health Program Element

The project goal is to develop behavioral health prevention and maintenance system for continued crew health, safety, and performance for exploration missions. The basic scope includes a) Operationally-relevant research related to clinical cognitive and behavioral health of crewmembers; b) Ground-based studies using analog environments (Antarctic, NEEMO, simulations, and other testbeds; c) ISS studies (ISSMP) focusing on operational issues related to behavioral health outcomes and standards; d) Technology development activities for monitoring and diagnostic tools; and e) Cross-disciplinary research (e.g., human factors and habitability research, skeletal muscle, radiation).

Leveton, Lauren B.↗

Space Life Sciences at NASA: Spaceflight Health Policy and Standards

In January 2005, the President proposed a new initiative, the Vision for Space Exploration. To accomplish the goals within the vision for space exploration, physicians and researchers at Johnson Space Center are establishing spaceflight health standards. These standards include fitness for duty criteria (FFD), permissible exposure limits (PELs), and permissible outcome limits (POLs). POLs delineate an acceptable maximum decrement or change in a physiological or behavioral parameter, as the result of exposure to the space environment. For example cardiovascular fitness for duty standards might be a measurable clinical parameter minimum that allows successful performance of all required duties. An example of a permissible exposure limit for radiation might be the quantifiable limit of exposure over a given length of time (e.g. life time radiation exposure). An example of a permissible outcome limit might be the length of microgravity exposure that would minimize bone loss. The purpose of spaceflight health standards is to promote operational and vehicle design requirements, aid in medical decision making during space missions, and guide the development of countermeasures. Standards will be based on scientific and clinical evidence including research findings, lessons learned from previous space missions, studies conducted in space analog environments, current standards of medical practices, risk management data, and expert recommendations. To focus the research community on the needs for exploration missions, NASA has developed the Bioastronautics Roadmap. The Bioastronautics Roadmap, NASA's approach to identification of risks to human space flight, revised baseline was released in February 2005. This document was reviewed by the Institute of Medicine in November 2004 and the final report was received in October 2005. The roadmap defines the most important research and operational needs that will be used to set policy, standards (define acceptable risk), and implement an overall Risk Management and Analysis process. Currently NASA is drafting spaceflight health standards for neurosensory alterations, space radiation exposure, behavioral health, muscle atrophy, cardiovascular fitness, immunological compromise, bone demineralization, and nutrition.

Davis, Jeffrey R.↗

Integration for Airborne Dust Prediction Systems and Vegetation Phenology to Track Pollen for Asthma Alerts in Public Health Decision Support Systems

The objective of the program is to assess the feasibility of combining a dust transport model with MODIS derived phenology to study pollen transport for integration with a public health decision support system. The use of pollen information has specifically be identified as a critical need by the New Mexico State Health department for inclusion in the Environmental Public Health Tracking (EPHT) program. Material and methods: Pollen can be transported great distances. Local observations of plan phenology may be consistent with the timing and source of pollen collected by pollen sampling instruments. The Dust REgional Atmospheric Model (DREAM) is an integrated modeling system designed to accurately describe the dust cycle in the atmosphere. The dust modules of the entire system incorporate the state of the art parameterization of all the major phases of the atmospheric dust life such as production, diffusion, advection, and removal. These modules also include effects of the particles size distribution on aerosol dispersion. The model was modified to use pollen sources instead of dust. Pollen release was estimated based on satellite-derived phenology of key plan species and vegetation communities. The MODIS surface reflectance product (MOD09) provided information on the start of the plant growing season, growth stage, and pollen release. The resulting deterministic model is useful for predicting and simulating pollen emission and downwind concentration to study details of phenology and meteorology and their dependencies. The proposed linkage in this project provided critical information on the location timing and modeled transport of pollen directly to the EPHT> This information is useful to support the centers for disease control and prevention (CDC)'s National EPHT and the state of New Mexico environmental public health decision support for asthma and allergies alerts.

Luvall, J. C.↗

Integrated System Health Management: Foundational Concepts, Approach, and Implementation.

Implementation of integrated system health management (ISHM) capability is fundamentally linked to the management of data, information, and knowledge (DIaK) with the purposeful objective of determining the health of a system. It is akin to having a team of experts who are all individually and collectively observing and analyzing a complex system, and communicating effectively with each other in order to arrive to an accurate and reliable assessment of its health. We present concepts, procedures, and a specific approach as a foundation for implementing a credible ISHM capability. The capability stresses integration of DIaK from all elements of a system. The intent is also to make possible implementation of on-board ISHM capability, in contrast to a remote capability. The information presented is the result of many years of research, development, and maturation of technologies, and of prototype implementations in operational systems (rocket engine test facilities). The paper will address the following topics: 1. ISHM Model of a system 2. Detection of anomaly indicators. 3. Determination and confirmation of anomalies. 4. Diagnostic of causes and determination of effects. 5. Consistency checking cycle. 6. Management of health information 7. User Interfaces 8. Example implementation ISHM has been defined from many perspectives. We define it as a capability that might be achieved by various approaches. We describe a specific approach that has been matured throughout many years of development, and pilot implementations. ISHM is a capability that is achieved by integrating data, information, and knowledge (DIaK) that might be distributed throughout the system elements (which inherently implies capability to manage DIaK associated with distributed sub-systems). DIaK must be available to any element of a system at the right time and in accordance with a meaningful context. ISHM Functional Capability Level (FCL) is measured by how well a system performs the following functions: (1) detect anomalies, (2) diagnose causes, (3) predict future anomalies/failures, and (4) provide the user with an integrated awareness about the condition of every element in the system and guide user decisions.

Figueroa, Fernando↗

Developing Crew Health Care and Habitability Systems for the Exploration Vision

This paper will discuss the specific mission architectures associated with the NASA Exploration Vision and review the challenges and drivers associated with developing crew health care and habitability systems to manage human system risks. Crew health care systems must be provided to manage crew health within acceptable limits, as well as respond to medical contingencies that may occur during exploration missions. Habitability systems must enable crew performance for the tasks necessary to support the missions. During the summer of 2005, NASA defined its exploration architecture including blueprints for missions to the moon and to Mars. These mission architectures require research and technology development to focus on the operational risks associated with each mission, as well as the risks to long term astronaut health. This paper will review the highest priority risks associated with the various missions and discuss NASA s strategies and plans for performing the research and technology development necessary to manage the risks to acceptable levels.

Laurini, Kathy↗

Integration of Dust Prediction Systems and Vegetation Phenology to Track Pollen for Asthma Alerts in Public Health

Initial efforts to develop a deterministic model for predicting and simulating pollen release and downwind concentration to study dependencies of phenology on meteorology will be discussed. The development of a real-time, rapid response pollen release and transport system as a component of the New Mexico Environmental Public Health Tracking System (EPHTS), is based on meteorological models, NASA Earth science results (ESR), and an in-situ network of phenology cameras. The plan is to detect pollen release verified using ground based atmospheric pollen sampling within a few hours using daily MODIS daa in nearly real-time from Direct Broadcast, similar to the MODIS Rapid Response System for fire detection. As MODIS winds down, the NPOESS-VIIRS sensor will assume daily vegetation monitoring tasks. Also, advancements in geostationary satellites will allow 1km vegetation indices at 15-30 minute intervals. The pollen module in EPHTS will be used to: (1) support public health decisions for asthma and allergy alerts in New Mexico, Texas and Oklahoma; (2) augment the Centers for Disease Control and Prevention (CDC)'s Environmental Public Health Tracking Network (EPHTN); and (3) extend surveillance services to local healthcare providers subscribing to the Syndrome Reporting Information System (SYRIS). Previous studies in NASA's public health applications portfolios provide the infrastructure for this effort. The team is confident that NASA and NOAA ESR data, combined into a verified and validated dust model will yield groundbreaking results using the modified dust model to transport pollen. The growing ESR/health infrastructure is based on results from a rapid prototype scoping effort for pollen detection and simulation carried out by the principal investigators.

Luvall, Jeffrey↗

Integration of Airborne Aerosol Prediction Systems and Vegetation Phenology to Track Pollen for Asthma Alerts in Public Health Decision Support Systems

The residual signal indicates that the pollen event may influence the seasonal signal to an extent that would allow detection, given accurate QA filtering and BRDF corrections. MODIS daily reflectances increased during the pollen season. The DREAM model (PREAM) was successfully modified for use with pollen and may provide 24-36 hour running pollen forecasts. Publicly available pollen forecasts are linked to general weather patterns and roughly-known species phenologies. These are too coarse for timely health interventions. PREAM addresses this key data gap so that targeting intervention measures can be determined temporally and geospatially. The New Mexico Department of Health (NMDOH) as part of its Environmental Public Health Tracking Network (EPHTN) would use PREAM a tool for alerting the public in advance of pollen bursts to intervene and reduce the health impact on asthma populations at risk.

Luvall, Jeffrey C.↗

Improving Public Health DSSs by Including Saharan Dust Forecasts Through Incorporation of NASA's GOCART Model Results

Approximately 2-3 billion metric tons of soil dust are estimated to be transported in the Earth's atmosphere each year. Global transport of desert dust is believed to play an important role in many geochemical, climatological, and environmental processes. This dust carries minerals and nutrients, but it has also been shown to carry pollutants and viable microorganisms capable of harming human, animal, plant, and ecosystem health. Saharan dust, which impacts the eastern United States (especially Florida and the southeast) and U.S. Territories in the Caribbean primarily during the summer months, has been linked to increases in respiratory illnesses in this region and has been shown to carry other human, animal, and plant pathogens. For these reasons, this candidate solution recommends integrating Saharan dust distribution and concentration forecasts from the NASA GOCART global dust cycle model into a public health DSS (decision support system), such as the CDC's (Centers for Disease Control and Prevention's) EPHTN (Environmental Public Health Tracking Network), for the eastern United States and Caribbean for early warning purposes regarding potential increases in respiratory illnesses or asthma attacks, potential disease outbreaks, or bioterrorism. This candidate solution pertains to the Public Health National Application but also has direct connections to Air Quality and Homeland Security. In addition, the GOCART model currently uses the NASA MODIS aerosol product as an input and uses meteorological forecasts from the NASA GEOS-DAS (Goddard Earth Observing System Data Assimilation System) GEOS-4 AGCM. In the future, VIIRS aerosol products and perhaps CALIOP aerosol products could be assimilated into the GOCART model to improve the results.

Berglund, Judith↗

Monitoring System for Storm Readiness and Recovery of Test Facilities: Integrated System Health Management (ISHM) Approach

Severe weather events are likely occurrences on the Mississippi Gulf Coast. It is important to rapidly diagnose and mitigate the effects of storms on Stennis Space Center's rocket engine test complex to avoid delays to critical test article programs, reduce costs, and maintain safety. An Integrated Systems Health Management (ISHM) approach and technologies are employed to integrate environmental (weather) monitoring, structural modeling, and the suite of available facility instrumentation to provide information for readiness before storms, rapid initial damage assessment to guide mitigation planning, and then support on-going assurance as repairs are effected and finally support recertification. The system is denominated Katrina Storm Monitoring System (KStorMS). Integrated Systems Health Management (ISHM) describes a comprehensive set of capabilities that provide insight into the behavior the health of a system. Knowing the status of a system allows decision makers to effectively plan and execute their mission. For example, early insight into component degradation and impending failures provides more time to develop work around strategies and more effectively plan for maintenance. Failures of system elements generally occur over time. Information extracted from sensor data, combined with system-wide knowledge bases and methods for information extraction and fusion, inference, and decision making, can be used to detect incipient failures. If failures do occur, it is critical to detect and isolate them, and suggest an appropriate course of action. ISHM enables determining the condition (health) of every element in a complex system-of-systems or SoS (detect anomalies, diagnose causes, predict future anomalies), and provide data, information, and knowledge (DIaK) to control systems for safe and effective operation. ISHM capability is achieved by using a wide range of technologies that enable anomaly detection, diagnostics, prognostics, and advise for control: (1) anomaly detection algorithms and strategies, (2) fusion of DIaK for anomaly detection (model-based, numerical, statistical, empirical, expert-based, qualitative, etc.), (3) diagnostics/prognostics strategies and methods, (4) user interface, (5) advanced control strategies, (6) integration architectures/frameworks, (7) embedding of intelligence. Many of these technologies are mature, and they are being used in the KStorMS. The paper will describe the design, implementation, and operation of the KStorMS; and discuss further evolution to support other needs such as condition-based maintenance (CBM).

Figueroa, Fernando↗

General Purpose Data-Driven Online System Health Monitoring with Applications to Space Operations

Modern space transportation and ground support system designs are becoming increasingly sophisticated and complex. Determining the health state of these systems using traditional parameter limit checking, or model-based or rule-based methods is becoming more difficult as the number of sensors and component interactions grows. Data-driven monitoring techniques have been developed to address these issues by analyzing system operations data to automatically characterize normal system behavior. System health can be monitored by comparing real-time operating data with these nominal characterizations, providing detection of anomalous data signatures indicative of system faults, failures, or precursors of significant failures. The Inductive Monitoring System (IMS) is a general purpose, data-driven system health monitoring software tool that has been successfully applied to several aerospace applications and is under evaluation for anomaly detection in vehicle and ground equipment for next generation launch systems. After an introduction to IMS application development, we discuss these NASA online monitoring applications, including the integration of IMS with complementary model-based and rule-based methods. Although the examples presented in this paper are from space operations applications, IMS is a general-purpose health-monitoring tool that is also applicable to power generation and transmission system monitoring.

Iverson, David L.↗

Crew Health Care System (CHeCS) Design Research, Documentations, and Evaluations

The Crew Health Care System (CHeCS) is a group within the Space Life Science Directorate (SLSD) that focuses on the overall health of astronauts by reinforcing the three divisions - the Environmental Maintenance System (EMS), the Countermeasures System (CMS), and the Health Maintenance System (HMS). This internship provided opportunity to gain knowledge, experience, and skills in CHeCS engineering and operations tasks. Various and differing tasks allowed for occasions to work independently, network to get things done, and show leadership abilities. Specific exercises included reviewing hardware certification, operations, and documentation within the ongoing Med Kit Redesign (MKR) project, and learning, writing, and working various common pieces of paperwork used in the engineering and design process. Another project focused on the distribution of various pieces of hardware to off-site research facilities with an interest in space flight health care. The main focus of this internship, though, was on a broad and encompassing understanding of the engineering process as time was spent looking at each individual step in a variety of settings and tasks.

CLement, Bethany M.↗

Potential Effects of Health Care Policy Decisions on Physician Availability

Many regions in America are experiencing downward trends in the number of practicing physicians and the number of available physician hours, resulting in a worrisome decrease in the availability of health care services. Recent changes in American health care legislation may induce a rapid change in the demand for health care services, which in turn will result in a new supply-demand equilibrium . In this paper we develop a system dynamics model linking physician availability to health care demand and profitability. We use this model to explore scenarios based on different initial conditions and describe possible outcomes for a range of different policy decisions.

Garcia, Christopher↗

Smart Sensors' Role in Integrated System Health Management

During the last decade, there has been a major effort in the aerospace industry to reduce the cost per pond of payload and become competitive in the international market. Competition from Europe, Japan, and China has reduced this cost to almost a third from 1990 to 2000. This cost has leveled in recent years to an average price of around $12,000/pound of payload. One of NASA's goals is to promote the development of technologies to reduce this cost by a factor of 10 or more Exploration of space, specially manned exploration missions, involves very complex launch and flight vehicles, associated ground support systems, and extensive human support during all phases of the mission. When considering the Space Shuttle Program, we can see that vehicle and ground support systems' processing, operation, and maintenance represent a large percentage of the program cost and time. Reducing operating, processing and maintenance costs will greatly reduce the cost of Exploration programs. The Integrated System Health Management (ISHM) concept is one of the technologies that will help reduce these operating, processing and maintenance costs. ISHM is an integrated health monitoring system applicable to both flight and ground systems. It automatically and autonomously acquires information from sensors and actuators and processes that information using the ISHM-embedded knowledge. As a result, it establishes the health of the system based on the acquired information and its prior knowledge. When this concept is fully implemented, ISHM systems shall be able to perform failure prediction and remediation before actual hard failures occurs, preventing its costly consequences. Data sources, sensors, and their associated data acquisition systems, constitute the foundation of the system. A smart sensing architecture is required to support the acquisition of reliable, high quality data, required by the ISHM. A thorough definition of the smart sensor architectures, their embedded diagnostic agents, and communication protocols need to be established and standardized to allow the embedding and exchange of health information among sensors and ISHM. This workshop is aimed to foster the exchange of ideas and lessons learned between government, industry and academia to aid in the establishment of ISHM (and smart sensors) standards and guidelines as well as to identify present technology gaps that will have to be overcome to successfully achieve this goal.

Perotti, Jose M.↗

Vehicle Health Management Communications Requirements for AeroMACS

As the development of standards for the aeronautical mobile airport communications system (AeroMACS) progresses, the process of identifying and quantifying appropriate uses for the system is progressing. In addition to defining important elements of AeroMACS standards, indentifying the systems uses impacts AeroMACS bandwidth requirements. Although an initial 59 MHz spectrum allocation for AeroMACS was established in 2007, the allocation may be inadequate; studies have indicated that 100 MHz or more of spectrum may be required to support airport surface communications. Hence additional spectrum allocations have been proposed. Vehicle health management (VHM) systems, which can produce large volumes of vehicle health data, were not considered in the original bandwidth requirements analyses, and are therefore of interest in supporting proposals for additional AeroMACS spectrum. VHM systems are an emerging development in air vehicle safety, and preliminary estimates of the amount of data that will be produced and transmitted off an aircraft, both in flight and on the ground, have been prepared based on estimates of data produced by on-board vehicle health sensors and initial concepts of data processing approaches. This allowed an initial estimate of VHM data transmission requirements for the airport surface. More recently, vehicle-level systems designed to process and analyze VHM data and draw conclusions on the current state of vehicle health have been undergoing testing and evaluation. These systems make use of vehicle system data that is mostly different from VHM data considered previously for airport surface transmission, and produce processed system outputs that will be also need to be archived, thus generating additional data load for AeroMACS. This paper provides an analysis of airport surface data transmission requirements resulting from the vehicle level reasoning systems, within the context of overall VHM data requirements.

Kerczewski, Robert J.↗

Using NASA Using Remote Sensing in Public Health Applications

The Public Health application area focuses on Earth science applications to public health and safety, particularly regarding infectious disease, emergency preparedness and response, and environmental health issues. The application explores issues of toxic and pathogenic exposure, as well as natural and man-made hazards and their effects, for risk characterization/mitigation and improvements to health and safety.

Estes, Sue↗

Constructing an Efficient Self-Tuning Aircraft Engine Model for Control and Health Management Applications

Self-tuning aircraft engine models can be applied for control and health management applications. The self-tuning feature of these models minimizes the mismatch between any given engine and the underlying engineering model describing an engine family. This paper provides details of the construction of a self-tuning engine model centered on a piecewise linear Kalman filter design. Starting from a nonlinear transient aerothermal model, a piecewise linear representation is first extracted. The linearization procedure creates a database of trim vectors and state-space matrices that are subsequently scheduled for interpolation based on engine operating point. A series of steady-state Kalman gains can next be constructed from a reduced-order form of the piecewise linear model. Reduction of the piecewise linear model to an observable dimension with respect to available sensed engine measurements can be achieved using either a subset or an optimal linear combination of "health" parameters, which describe engine performance. The resulting piecewise linear Kalman filter is then implemented for faster-than-real-time processing of sensed engine measurements, generating outputs appropriate for trending engine performance, estimating both measured and unmeasured parameters for control purposes, and performing on-board gas-path fault diagnostics. Computational efficiency is achieved by designing multidimensional interpolation algorithms that exploit the shared scheduling of multiple trim vectors and system matrices. An example application illustrates the accuracy of a self-tuning piecewise linear Kalman filter model when applied to a nonlinear turbofan engine simulation. Additional discussions focus on the issue of transient response accuracy and the advantages of a piecewise linear Kalman filter in the context of validation and verification. The techniques described provide a framework for constructing efficient self-tuning aircraft engine models from complex nonlinear simulations.Self-tuning aircraft engine models can be applied for control and health management applications. The self-tuning feature of these models minimizes the mismatch between any given engine and the underlying engineering model describing an engine family. This paper provides details of the construction of a self-tuning engine model centered on a piecewise linear Kalman filter design. Starting from a nonlinear transient aerothermal model, a piecewise linear representation is first extracted. The linearization procedure creates a database of trim vectors and state-space matrices that are subsequently scheduled for interpolation based on engine operating point. A series of steady-state Kalman gains can next be constructed from a reduced-order form of the piecewise linear model. Reduction of the piecewise linear model to an observable dimension with respect to available sensed engine measurements can be achieved using either a subset or an optimal linear combination of "health" parameters, which describe engine performance. The resulting piecewise linear Kalman filter is then implemented for faster-than-real-time processing of sensed engine measurements, generating outputs appropriate for trending engine performance, estimating both measured and unmeasured parameters for control purposes, and performing on-board gas-path fault diagnostics. Computational efficiency is achieved by designing multidimensional interpolation algorithms that exploit the shared scheduling of multiple trim vectors and system matrices. An example application illustrates the accuracy of a self-tuning piecewise linear Kalman filter model when applied to a nonlinear turbofan engine simulation. Additional discussions focus on the issue of transient response accuracy and the advantages of a piecewise linear Kalman filter in the context of validation and verification. The techniques described provide a framework for constructing efficient self-tuning aircraft engine models from complex nonlinear simulatns.

Armstrong, Jeffrey B.↗