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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Information Theoretic Measures for Visual Analytics: The Silver Ticket?

In the context of text-based analysis workflows, we propose that an effective analytic tool facilitates triage by a) enabling users to identify and set aside irrelevant content (i.e., reduce the complexity of information in a dataset) and b) develop a working mental model of which items are most relevant to the question at hand. This LDRD funded research developed a dataset that is enabling this team to evaluate propose normalized compression distance (NCD) as a task, user, and context-insensitive measure of categorization outcomes (Shannon entropy is reduced as order is imposed). Effective analytics tools help people impose order, reducing complexity in measurable ways. Our concept and research was documented in a paper accepted to the ACM conference "Beyond Time and Error: Novel Methods in Information Visualization Evaluation", part of the IEEE VisWeek Conference, Baltimore, MD, October 16-21, 2016. The paper is included as an appendix to this report.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Study of Neutron-Induced Stable and Radioactive Nuclides in a Post Detonation Urban Environment

In the event of a nuclear detonation in an urban environment, response time for triage by first responders, and forensic sample collection are of the utmost importance. When it comes to response planning, decision makers within the government need to have the most up-to-date information regarding several quantities of interest so that the maximum amount of lives can be saved. Quantities of interest in a post-detonation scenario include the spatial distribution of neutron-induced stable and radioactive isotopes in the environment, fallout patterns, blast and re damage zones [1]. The UMPRINDER toolkit is developed to calculate the prompt neutron-induced stable and radioactive isotopes in the surrounding environment in a nuclear forensics post-detonation scenario. The distribution of these isotopes in the environment can be used to provide guidance in determining best routes for first responders in order to minimize dose, debris sample collection routes for subsequent radiochemical analysis, and provide initial radionuclide inventories to fallout codes in order to improve fallout zone fidelity. Other methods have approached isotope transmutation on unstructured mesh for the fusion community concerning shutdown dose rates associated with fusion reactors. UMPRINDER is the first method to be focused on calculating some of the quantities of interest for the nuclear forensics and weapon effects communities.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2019

A Handheld Medical Diagnostic Device for Harsh Environments

Medical diagnostic capabilities for extreme environments, are currently limited in nature to single marker type assays. We propose to develop a handheld device for medical diagnostics in extreme environments that provide sensitive and specific detection of biomarkers with an emphasis initially on radiation exposure. Such a device will have multiple uses, and will be easily adaptable to many applications. For example, first responders, the battlefield, in low resource settings in developing countries facing emerging disease outbreaks, and during long-duration space flights. To this end, we will develop highly adaptable microfluidic devices (cards) for profiling different biomarkers with an emphasis on those related to radiation exposure. We will leverage the previous centrifugal separator work from LLNL and Sandia National Laboratory. The radiation exposure biomarker work at LLNL will provide a biological platform for demonstrating the utility of the device. We will develop a fluidic system using a pump-less mechanical method (centrifugal) to move, control, order and layer fluids in the platform. This decreases complexity, while enabling simultaneous cell separation and plasma generation for two uses: the first is differential blood cell counts and the second is biomarker assay panels. This work will be accomplished in three Aims: Aim 1) Test multiplex microfluidic cards and integrated reader. Aim 2) Demonstrate system capabilities to take and process blood samples for multi-endpoint analysis. Aim 3) Test multiplex detection based on measuring differential blood cell counts, while measuring plasma protein biomarkers. The proposed work addresses the mission research challenge of chemical and biological countermeasure in that our work aims to provide new research capabilities to respond to man-made or natural outbreaks of pandemic diseases in particular in low resource and triage environments.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Development of Direct Injection/Ionization Mass Spectrometry Methods for Whole Molecule Characterization

The objective of this work is to adapt ambient ionization mass spectrometry (AMS) techniques for the rapid analysis of intact uranium complexes, stable strontium, cerium, and explosive compounds. The methods used were “soft ionization” techniques, which facilitate the detection of whole molecule complexes. The soft ionization mass spectrometry (MS) techniques that were investigated include paper spray ionization (PSI), matrix-assisted ionization (MAI), electrospray ionization (ESI) and direct analysis in real time (DART). For the first time, PSI-MS methods were successfully developed for whole molecule uranium-containing analytes (uranyl acetate, uranyl nitrate, and uranyl-tributylphosphate complexes). This was also the first demonstration of uranium complex detection and characterization and one of the few examples of inorganic analysis using MAI techniques. Proof of concept experiments also putatively identified matrix-derived ions and ion complexes that have not previously been described in the literature. Additionally, PSI-MS on cotton swipe samples doped with a multi-element standard containing μg levels of U, Bi, Pb, Cd, Fe, and Zn were directly analyzed without purification, representing a major improvement over existing methods. Both PSI and MAI methods demonstrated limits of detection (LODs) in the 10 - 100’s ng for various uranyl species within a range of 10’s ppm - 100’s ppb, dependent on analytical method and analyte species. AMS methods were also developed for other inorganics, including Ce and Sr, and organic explosive residues to address specific challenges in environmental monitoring and forensics. Further refinement and qualification of the AMS techniques developed within this effort would lead to significant cost reduction and timeliness by facilitating the triage and queueing of samples for subsequent more sensitive and time-consuming analyses.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Innovative mercury treatment technology options for the liquid waste system at the Savannah River Site: scoping studies

The Savannah River Site (SRS) Liquid Waste System (LWS) contains liquids, salts and sludges that are currently being processed into final wasteforms for disposition, specifically, waste glass for sludges, solids and liquids containing high levels of radioactivity, and saltstone grout for low activity decontaminated liquid solutions. The LWS also contains approximately 60,000 kg of mercury present in the following physical and chemical forms, specifically: a) ionic inorganic mercury, organomercury (e.g., methylmercury), and other minor components found in LWS fluids b) mercury solids such as oxides, hydroxides, amalgams sulfides and sorbed mercury, c) accumulations of dense liquid elemental mercury, and d) vapor phase elemental and organomercury mercury found in tank headspace gas and in evaporators. An effective and proactive management strategy of the mercury present in the LWS is needed to support processing of LWS wastes into glass and saltstone. Sustainable processing of the LAWS to completion requires mercury removal from the LWS at a rate of approximately 2,900 kg/yr. This removal can be accomplished through existing mercury treatment systems or newly implemented LWS “purge points”. The chemical speciation of mercury has emerged as the key factor that controls mercury behavior in the LWS. For example, past studies demonstrated that mercury speciation is adversely impacting the performance of existing removal systems so that significant levels of mercury are recycled from the Defense Waste Processing Facility (DWPF) back to the tank farm. Consequently, mercury concentrations have slowly increased in the LWS tank fluids over time. The presence of organo-mercury has also been identified as the cause of increased mercury leaching from saltstone. In response to these challenges, the Department of Energy (DOE) Office of Environmental Management (EM-TD) Technology Development Program has supported a series of scoping studies predicated on manipulating or controlling mercury speciation and mercury behaviors within the constraints of LWS waste chemistry and safety conditions. The intent of these studies was to rapidly triage potential technology options and develop a technically based go / no go recommendation for further work. This composite report presents the results of three scoping studies: 1) advanced photooxidation processes, 2) chemical reduction, and 3) mercury getters.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Improving the Nomenclature Around Uncertainty [Slides]

This presentation finds that defining the marginal probability density function (PDF) for nuclear data is important. Additionally, the vocabulary of “means and covariances” and new GNDS 2.0 formats are limited to Gaussian (normal) representations— always incorrect—but clearly of practical significance when uncertainties are large (>40%). Finally, the Triage Solution: declare our current data as containing best estimate (mode) plus variance for a truncated normal or lognormal.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

NukeLM: Pre-Trained and Fine-Tuned Language Models for the Nuclear and Energy Domains

Natural language processing (NLP) tasks (text classification, named entity recognition, etc.) have seen amazing improvements over the last few years. This is due to models such as BERT that achieve deep knowledge transfer by using a large pre-trained model, then fine-tuning the model on specific tasks. The BERT architecture has shown even better performance on domain-specific tasks when the model is pre-trained using domain-relevant texts. Here, inspired by these recent advancements, we have developed NukeLM, a nuclear-domain BERT model pre-trained on 1.5 million abstracts from the DOE Office of Scientific and Technical Information (OSTI) database. This NukeLM model is then fine-tuned for the classification of research articles into either binary classes (related to the nuclear fuel cycle (NFC) or not) or multiple categories related to the subject of the article. We show that continued pre-training of a BERT-style architecture prior to fine-tuning results in greater performance in both article classification tasks. This information is critical for properly triaging manuscripts, a necessary task for better understanding citation networks that publish in the nuclear space and uncovering new areas of research in the nuclear (or nuclear relevant) domain.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2023

Performance Comparison of Object Detection Networks for Shrapnel Identification in Ultrasound Images

Ultrasound imaging is a critical tool for triaging and diagnosing subjects but only if images can be properly interpreted. Unfortunately, in remote or military medicine situations, the expertise to interpret images can be lacking. Machine-learning image interpretation models that are explainable to the end user and deployable in real time with ultrasound equipment have the potential to solve this problem. We have previously shown how a YOLOv3 (You Only Look Once) object detection algorithm can be used for tracking shrapnel, artery, vein, and nerve fiber bundle features in a tissue phantom. However, real-time implementation of an object detection model requires optimizing model inference time. Here, we compare the performance of five different object detection deep-learning models with varying architectures and trainable parameters to determine which model is most suitable for this shrapnel-tracking ultrasound image application. We used a dataset of more than 16,000 ultrasound images from gelatin tissue phantoms containing artery, vein, nerve fiber, and shrapnel features for training and evaluating each model. Every object detection model surpassed 0.85 mean average precision except for the detection transformer model. Overall, the YOLOv7tiny model had the higher mean average precision and quickest inference time, making it the obvious model choice for this ultrasound imaging application. Other object detection models were overfitting the data as was determined by lower testing performance compared with higher training performance. In summary, the YOLOv7tiny object detection model had the best mean average precision and inference time and was selected as optimal for this application. Next steps will implement this object detection algorithm for real-time applications, an important next step in translating AI models for emergency and military medicine.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

From Voxels to Knowledge: A Practical Guide to the Segmentation of Complex Electron Microscopy 3D-Data

Modern 3D electron microscopy approaches have recently allowed unprecedented insight into the 3D ultrastructural organization of cells and tissues, enabling the visualization of large macromolecular machines, such as adhesion complexes, as well as higher-order structures, such as the cytoskeleton and cellular organelles in their respective cell and tissue context. Given the inherent complexity of cellular volumes, it is essential to first extract the features of interest in order to allow visualization, quantification, and therefore comprehension of their 3D organization. Each data set is defined by distinct characteristics, e.g., signal-to-noise ratio, crispness (sharpness) of the data, heterogeneity of its features, crowdedness of features, presence or absence of characteristic shapes that allow for easy identification, and the percentage of the entire volume that a specific region of interest occupies. All these characteristics need to be considered when deciding on which approach to take for segmentation. The six different 3D ultrastructural data sets presented were obtained by three different imaging approaches: resin embedded stained electron tomography, focused ion beam- and serial block face- scanning electron microscopy (FIB-SEM, SBF-SEM) of mildly stained and heavily stained samples, respectively. For these data sets, four different segmentation approaches have been applied: (1) fully manual model building followed solely by visualization of the model, (2) manual tracing segmentation of the data followed by surface rendering, (3) semi-automated approaches followed by surface rendering, or (4) automated custom-designed segmentation algorithms followed by surface rendering and quantitative analysis. Depending on the combination of data set characteristics, it was found that typically one of these four categorical approaches outperforms the others, but depending on the exact sequence of criteria, more than one approach may be successful. Based on these data, we propose a triage scheme that categorizes both objective data set characteristics and subjective personal criteria for the analysis of the different data sets.

3D electron microscopy↗
DOE OSTI2026

Optimizing Optical Searches for Supermassive Black Hole Binaries in Active Galactic Nuclei Light Curves: Fourier versus Bayesian Periodicity Detection

Simulations predict that supermassive black hole binaries (SMBHBs) will exhibit periodic brightness variations that may exceed the stochastic variability intrinsic to active galactic nuclei (AGN). In this paper, we simulate SMBHBs with damped random walk (DRW) AGN variability and an added sinusoidal signal from the orbital motion, and test three methods—a generalized Lomb–Scargle periodogram (GLSP), a nested Bayesian sampler (NBS), and a weighted wavelet z-transform (or WWZ)—to determine which is best at recovering the periodicity. Our simulated light curves follow the properties of the Catalina Real-Time Transient Survey (or CRTS), Legacy Survey of Space and Time (LSST), and Zwicky Transient Facility (ZTF) to best inform current and future SMBHB searches. We map a broad range of parameter space and identify which DRW-only light curves best mimic periodicity and pass each method’s model selection. The NBS performs best at detecting periodicity and filtering out DRW-only light curves. Combined candidate selection with both the NBS and GLSP significantly reduces false-positive rates (FPRs) with marginal impact on true-positive rates (TPRs). With this joint model selection pipeline, we find the lowest FPRs in ZTF-like simulations and the highest detection rates in LSST-like simulations. Using a modified computation of the false-alarm probability with GLSP, we efficiently triage LSST AGN light curves (∼10 7 light curves in ∼10–30 hr) and achieve TPRs and FPRs of ∼40% and ∼0.5%, respectively.

Banaszak, Sebastian M. [Vanderbilt Univ., Nashvill↗
DOE OSTI2017

Soda Pop: A Time-Series Clustering, Alarming and Disease Forecasting Application

To introduce Soda Pop, an R/Shiny application designed to be a disease agnostic time-series clustering, alarming, and forecasting tool to assist in disease surveillance “triage, analysis and reporting” workflows within the Biosurveillance Ecosystem (BSVE). In this poster, we highlight the new capabilities that are brought to the BSVE by Soda Pop with an emphasis on the impact of methodological decisions. The Biosurveillance Ecosystem (BSVE) is a biological and chemical threat surveillance system sponsored by the Defense Threat Reduction Agency (DTRA). BSVE is intended to be user-friendly, multi-agency, cooperative, modular and threat agnostic platform for biosurveillance. In BSVE, a web-based workbench presents the analyst with applications (apps) developed by various DTRA funded researchers, which are deployed on-demand in the cloud(e.g., Amazon Web Services). These apps aim to address emerging needs and refine capabilities to enable early warning of chemical and biological threats for multiple users across local, state, and federal agencies. Soda Pop is an app developed by Pacific Northwest National Laboratory (PNNL) to meet the current needs of the BSVE for early warning and detection of disease outbreaks. Aimed for use bya diverse set of analysts, the application is agnostic to data source and spatial scale enabling it to be generalizable across many diseases and locations. To achieve this, we placed a particular emphasis on clustering and alerting of disease signals within Soda Pop without strong prior assumptions on the nature of observed diseased counts. Although designed to be agnostic to the data source, Soda Pop was initially developed and tested on data summarizing Influenza-Like Illness in military hospitals from collaboration with the Armed Forces Health Surveillance Branch. Currently, the data incorporated also includes the CDC’s National Notifiable Diseases Surveillance System(NNDSS) tables and the WHO’s Influenza A/B Influenza Data(Flunet). These data sources are now present in BSVE’s Postgres data storage for direct access. Soda Pop is designed to automate time-series tasks of data summarization, exploration, clustering, alarming and forecasting. Built as an R/Shiny application, Soda Pop is founded on the powerful statistical tool R.. Where applicable, Soda Pop facilitates nonparametric seasonal decomposition of time-series; hierarchical agglomerative clustering across reporting areas and between diseases within reporting areas; and a variety of alarming techniques including Exponential Weighted Moving Average alarms and Early Aberration Detection. Soda Pop embeds these techniques within a user-interface designed to enhance an analyst’s understanding of emerging trends in their data and enables the inclusion of its graphical elements into their dossier for further tracking and reporting. The ultimate goal of this software is to facilitate the discovery of unknown disease signals along with increasing the speed of detection of unusual patterns within these signals. Soda Pop organizes common statistical disease surveillance tasks in a manner integrated with BSVE data source inputs and outputs. The app analyzes time-series disease data and supports a robust set of clustering and alarming routines that avoid strong assumptions on the nature of observed disease counts. This attribute allows for flexibility in the data source, spatial scale, and disease types making it useful to a wide range of analysts.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1991

KSC off-runway contingency operation - Mode 7

The possibility of a mishap during a space shuttle landing at Kennedy Space Center (KSC) dictates the need for plans to rescue astronauts from areas other than the Shuttle Landing Facility (SLF). All shuttle landings are unpowered, gliding flight maneuvers, and a deviation from the planned flight profile could result in a shuttle landing or crashing somewhere other than the SLF runway. The geography of the Kennedy Space Center makes helicopter airlifting the only universal means of transportation for the rescue crew. This rescue crew is composed of KSC contractor fire-rescuemen who would ride to the crash scene on USAF HH-3 helicopters. These crews are provided with personal protective suits and training in shallow water, swamp, and dry land rescues. They aid the egress of the crew to a safe area for helicopter pickup and subsequent triage and medevac.

Maples, Arthur↗
NASA NTRS1994

Emergency medical services

When NASA was established in 1958, it was known that space flight would require efforts beyond those of NASA to ensure the health and safety of our astronauts. On 10 Aug. 1958, a Secretary of Defense memorandum was signed that assigned the first Department of Defense (DOD) Manager to provide support to NASA for Project Mercury. This established a chain of command through the Joint Chiefs of Staff to the Secretary of Defense. The current charter is dated 19 Mar. 1986 and assigns the DOD Manager responsibilities to the Commander and Chief, US Space Command. The DOD Managers charter has many support areas and among them are recovery of astronauts and medical support. Today these efforts support the Space Shuttle and Space Station Programs. Briefly, the program works with each organization tasking the other through a requirements document. Level of care, communications, and recovery requirements are established; NASA and the DOD provide the capability to meet them. NASA is also responsible for the specialized training and equipment needed to meet these requirements. A Shuttle launch a KSC requires an Emergency Medical Services (EMS) coordinator on console to facilitate communications, ensure proper coverage, and coordinate with area hospitals. A contingent of NASA medical personnel are assembled to provide triage and medical support capabilities. The DOD provides medical evacuation (MEDEVAC) helicopters with surgeons and pararescue specialists (PJ's) or emergency medical technicians (EMT's). Each helicopter is equipped with at least one doctor and one PJ/EMT per astronaut crew member. Transoceanic abort landing (TAL) sites and end of mission (EOM) sites have similar structures, with TAL sites utilizing fixed wingg aircraft for MEDEVAC. The DOD also supports contingency planning for the support and return of crew members from the Space Station Freedom. Much of this support has been directed at the recovery of crew members following the landing of an Assured Crew Return Vehicle.

Billica, Roger↗
NASA NTRS1994

Quantitative 3-D imaging topogrammetry for telemedicine applications

The technology to reliably transmit high-resolution visual imagery over short to medium distances in real time has led to the serious considerations of the use of telemedicine, telepresence, and telerobotics in the delivery of health care. These concepts may involve, and evolve toward: consultation from remote expert teaching centers; diagnosis; triage; real-time remote advice to the surgeon; and real-time remote surgical instrument manipulation (telerobotics with virtual reality). Further extrapolation leads to teledesign and telereplication of spare surgical parts through quantitative teleimaging of 3-D surfaces tied to CAD/CAM devices and an artificially intelligent archival data base of 'normal' shapes. The ability to generate 'topogrames' or 3-D surface numerical tables of coordinate values capable of creating computer-generated virtual holographic-like displays, machine part replication, and statistical diagnostic shape assessment is critical to the progression of telemedicine. Any virtual reality simulation will remain in 'video-game' realm until realistic dimensional and spatial relational inputs from real measurements in vivo during surgeries are added to an ever-growing statistical data archive. The challenges of managing and interpreting this 3-D data base, which would include radiographic and surface quantitative data, are considerable. As technology drives toward dynamic and continuous 3-D surface measurements, presenting millions of X, Y, Z data points per second of flexing, stretching, moving human organs, the knowledge base and interpretive capabilities of 'brilliant robots' to work as a surgeon's tireless assistants becomes imaginable. The brilliant robot would 'see' what the surgeon sees--and more, for the robot could quantify its 3-D sensing and would 'see' in a wider spectral range than humans, and could zoom its 'eyes' from the macro world to long-distance microscopy. Unerring robot hands could rapidly perform machine-aided suturing with precision micro-sewing machines, splice neural connections with laser welds, micro-bore through constricted vessels, and computer combine ultrasound, microradiography, and 3-D mini-borescopes to quickly assess and trace vascular problems in situ. The spatial relationships between organs, robotic arms, and end-effector diagnostic, manipulative, and surgical instruments would be constantly monitored by the robot 'brain' using inputs from its multiple 3-D quantitative 'eyes' remote sensing, as well as by contact and proximity force measuring devices. Methods to create accurate and quantitative 3-D topograms at continuous video data rates are described.

Altschuler, Bruce R.↗
NASA NTRS2001

Biomarkers of exposure and dose: state of the art

Biomarkers provide methods to measure changes in biological systems and to relate them to environmental insults and disease processes. Biomarkers can be classified as markers of exposure and dose, markers of sensitivity, and markers of disease. It is important that the differences and applications of the various types of biomarkers be clearly understood. The military is primarily interested in early biomarkers of exposure and dose that do not require high levels of sensitivity but can be used to rapidly triage war fighters under combat or terrorist conditions and determine which, if any, require medical attention. Biomarkers of long-term radiation risk represent the second area of interest for the military. Biomarkers of risk require high sensitivity and specificity for the disease and insult but do not require rapid data turnaround. Biomarkers will help provide information for quick command decisions in the field, characterise long-term troop risks and identify early stages of radiation-induced diseases. This information provides major positive reassurances about individual exposures and risk that will minimise the physical and psychological impact of wartime radiation exposures.

Review, Tutorial↗
NASA NTRS2007

Terrain Adaptive Navigation for Mars Rovers

A navigation system for Mars rovers in very rough terrain has been designed, implemented, and tested on a research rover in Mars analog terrain. This navigation system consists of several technologies that are integrated to increase the capabilities compared to current rover navigation algorithms. These technologies include: goodness maps and terrain triage, terrain classification, remote slip prediction, path planning, high-fidelity traversability analysis (HFTA), and slip-compensated path following. The focus of this paper is not on the component technologies, but rather on the integration of these components. Results from the onboard integration of several of the key technologies described here are shown. Additionally, the results from independent demonstrations of several of these technologies are shown. Future work will include the demonstration of the entire integrated system described here.

traversabiity analysis↗
NASA NTRS2006

Chemical Diversity along the Traverse of the Rover Spirit at Gusev Crater

The Alpha-Particle-X-ray Spectrometer (APXS) is part of the in situ payload of the Mars Exploration Rovers. It has determined the chemical composition of soils and rocks along the nearly 6 km long traverse of the rover Spirit. The measuring method a combination of PIXE and XRF using Cm244 sources - allowed the unambiguous identification of elemental compositions with high precision. Besides sample triage and quantification of saltforming elements as indicators for aqueous alteration, the APXS also delivered important constraints to mineralogy intruments (i.e., Mossbauer (MB), MiniTES, Pancam) on minerals and rock types. The mineralogy instruments on the other hand provided constraints on minerals used for APXS normative calculations and, e.g. allowed the attribution of S to sulfate, instead of sulfide or elemental sulfur. This abstract gives an updated overview of the data obtained up to our current rover position on sol 720 at the eastern base of the Columbia Hills. We will emphasize elemental correlations that imply the presence of certain minerals that can not be identified by the MER mineralogy instruments.

Gellert, R.↗
NASA NTRS2005

Kennedy Space Center (KSC) Mishap Response Plan

KSC Medical Operations, in exercising the KSC Psychological Triage Plan, provided crewmember family support following notification of the Columbia accident. KSC Medical Operations also provided field support in working with FEMA and EPA to assure adequate occupational medicine and environmental health care of KSC workers. In addition, the development of policy and procedures for handling and clearing biohazardous debris material in the KSC reconstruction hangar was prepared and implemented.

Scarpa, Philip↗