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All sourcesNASA NTRSDOE OSTI
NASA NTRS2019

Recommendation for a Medical System Concept of Operations for Gateway Missions

NASA’s exploration missions to cis-lunar space will establish a permanent gateway to future transport missions to Mars. These missions mandate a significant paradigm change for mission planning, spacecraft design, human systems integration, and in-flight medical care due to constraints on mass, volume, power, resupply, and medical evacuation capability. These constraints require medical system development to be tightly integrated with mission and habitat design to provide a sufficient medical infrastructure and enable mission success. This concept of operations provides a vision of medical care needs that will be used to guide the development of a medical system for the cis-lunar Gateway Habitat. This medical system will serve as the precursor to what is implemented in future exploration missions to Mars. This concept of operations documents an overview of the stakeholder needs and system goals of a medical system and provides examples of the types of activities for which the system will be used during the mission. This concept of operations informs the ExMC systems engineering effort to define the Gateway Habitat Medical System by documenting the medical activities and capabilities relevant to Gateway missions, as identified by the ExMC clinician community. In addition, this concept of operations will inform the subsequent systems engineering process of developing technical requirements, system architectures, interfaces, and verification and validation approaches for the medical system. This document supports the closure of ExMC Gap Med01: We do not have a concept of operations for medical care during exploration missions, corresponding to the ExMC-managed human system risk: Risk of Adverse Health Outcomes & Decrements in Performance due to Inflight Medical Conditions.

Rubin, David↗
NASA NTRS2004

Propulsion Integrated Vehicle Health Management Technology Experiment (PITEX) Conducted

The Propulsion Integrated Vehicle Health Management (IVHM) Technology Experiment (PITEX) is a continuing NASA effort being conducted cooperatively by the NASA Glenn Research Center, the NASA Ames Research Center, and the NASA Kennedy Space Center. It was a key element of a Space Launch Initiative risk-reduction task performed by the Northrop Grumman Corporation in El Segundo, California. PITEX's main objectives are the continued maturation of diagnostic technologies that are relevant to second generation reusable launch vehicle (RLV) subsystems and the assessment of the real-time performance of the PITEX diagnostic solution. The PITEX effort has considerable legacy in the NASA IVHM Technology Experiment for X-vehicles (NITEX) that was selected to fly on the X-34 subscale RLV that was being developed by Orbital Sciences Corporation. NITEX, funded through the Future-X Program Office, was to advance the technology-readiness level of selected IVHM technologies within a flight environment and to begin the transition of these technologies from experimental status into RLV baseline designs. The experiment was to perform realtime fault detection and isolation and suggest potential recovery actions for the X-34 main propulsion system (MPS) during all mission phases by using a combination of system-level analysis and detailed diagnostic algorithms.

Maul, William A.↗
NASA NTRS2025

NASA Open Science Data Repository: Open Science for Life in Space

Space biology and health data are critical for the success of deep space missions and sustainable human presence off-world. At the core of effectively managing biomedical risks is the commitment to open science principles, which ensure that data are findable, accessible, interoperable, reusable, reproducible and maximally open. The 2021 integration of the Ames Life Sciences Data Archive with GeneLab to establish the NASA Open Science Data Repository significantly enhanced access to a wide range of life sciences, biomedical-clinical, and mission telemetry data alongside existing ‘omics data from GeneLab. This paper describes the new database, its architecture, and new data streams supporting diverse data types and enhancing data submission, retrieval, and analysis. Features include the Biological Data Management Environment for improved data submission, a new user interface, controlled data access, an enhanced API, and comprehensive public visualization tools for environmental telemetry, radiation dosimetry data, and ‘omics analyses. By fostering global collaboration through its Analysis Working Groups and training programs, the Open Science Data Repository promotes widespread engagement in space biology, ensuring transparency and inclusivity in research. It supports the global scientific community in advancing our understanding of spaceflight's impact on biological systems, ensuring humans will thrive in future deep space missions.

OSDR↗
NASA NTRS2017

Understanding the International Space Station Crew Perspective following Long-Duration Missions through Data Analytics & Visualization of Crew Feedback

The International Space Station (ISS) first became a home and research laboratory for NASA and International Partner crewmembers over 16 years ago. Each ISS mission lasts approximately 6 months and consists of three to six crewmembers. After returning to Earth, most crewmembers participate in an extensive series of 30+ debriefs intended to further understand life onboard ISS and allow crews to reflect on their experiences. Examples of debrief data collected include ISS crew feedback about sleep, dining, payload science, scheduling and time planning, health & safety, and maintenance. The Flight Crew Integration (FCI) Operational Habitability (OpsHab) team, based at Johnson Space Center (JSC), is a small group of Human Factors engineers and one stenographer that has worked collaboratively with the NASA Astronaut office and ISS Program to collect, maintain, disseminate and analyze this data. The database provides an exceptional and unique resource for understanding the "crew perspective" on long duration space missions. Data is formatted and categorized to allow for ease of search, reporting, and ultimately trending, in order to understand lessons learned, recurring issues and efficiencies gained over time. Recently, the FCI OpsHab team began collaborating with the NASA JSC Knowledge Management team to provide analytical analysis and visualization of these over 75,000 crew comments in order to better ascertain the crew's perspective on long duration spaceflight and gain insight on changes over time. In this initial phase of study, a text mining framework was used to cluster similar comments and develop measures of similarity useful for identifying relevant topics affecting crew health or performance, locating similar comments when a particular issue or item of operational interest is identified, and providing search capabilities to identify information pertinent to future spaceflight systems and processes for things like procedure development and training. In addition, the comments were scored for sentiment using a polarity scoring algorithm to identify both positive and negative comments for particular groups and clusters, allowing the team to make analytically informed decisions regarding future hardware and operating procedures. The use of polarity scoring with time series analysis was used to provide insight into how crew health and habitability is changing throughout various spaceflight increments or the station lifecycle as a whole. Finally, a visualization framework was developed to address the needs of the end users to search for and analyze comments by user, category or mission. This paper will discuss how the use of an analytical framework in conjunction with the current human interface, improved the understanding of crew perspective and shortened the time for analysis allowing for more informed decisions and rapid development of improvements. These methods are significantly optimizing the way that this valuable data can be assessed and applied to current and future spaceflight design and development. This collaboration allows the FCI OpsHab team to effectively analyze and share data in a more automated and timely fashion. Trends are no longer derived manually and can be illustrated effectively and accurately with these evolving techniques to an ever growing group of human spaceflight end users.

Bryant, Cody↗
DOE OSTI2013

Deep vadose zone remediation: technical and policy challenges, opportunities, and progress in achieving cleanup endpoints

Current requirements for site remediation and closure are standards-based and are often overly conservative, costly, and in some cases, technically impractical. Use of risk-informed alternate endpoints provides a means to achieve remediation goals that are permitted by regulations and are protective of human health and the environment. Alternate endpoints enable the establishment of a path for cleanup that may include intermediate remedial milestones and transition points and/or regulatory alternatives to standards-based remediation. A framework is presented that is centered around developing and refining conceptual models in conjunction with assessing risks and potential endpoints as part of a system-based assessment that integrates site data with scientific understanding of processes that control the distribution and transport of contaminants in the subsurface and pathways to receptors. This system-based assessment and subsequent implementation of the remediation strategy with appropriate monitoring are targeted at providing a holistic approach to addressing risks to human health and the environment. This holistic approach also enables effective predictive analysis of contaminant behavior to provide defensible criteria and data for making long-term decisions. Developing and implementing an alternate endpoint-based approach for remediation and waste site closure presents a number of challenges and opportunities. Categories of these challenges include scientific and technical, regulatory, institutional, and budget and resource allocation issues. Opportunities exist for developing and implementing systems-based approaches with respect to supportive characterization, monitoring, predictive modeling, and remediation approaches. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRSDate not supplied

Market Survey 2020: Commercial Clinical Decision Support Systems and Wellness Tools

For long-duration, deep space exploration missions, current methods for managing and supporting crew health and medical conditions will be unsuitable. Communication and data transmission lags will necessitate the use of a sophisticated clinical decision support system (CDSS) that will tailor diagnosis and treatment guidance that is context-sensitive for anticipated astronaut health, wellness, and medical conditions. A variety of clinical decision support (CDS) and wellness tools (WT) are currently available in the commercial market and a broad-brush survey of this market can provide an initial impression of the current state of the art which, in turn, can inform the roadmap of NASA deep space CDSS development and associated requirements. Such a survey was undertaken during the first six months of 2020 using directed convenience sampling to obtain information provided by vendors on their websites; both commercially available CDS and WT (such as those used to track and monitor nutrition, exercise, and sleep) were included. Areas assessed were item type (e.g., software/application, device); primary purpose of the item (e.g., diagnostic support, nutrition tracking); additional purposes (if any); reported features, capabilities, and functionality; setting of use (e.g., inpatient, outpatient); intended user (e.g., clinician, patient); location and sources of data/information used or produced by the item; integration with patient electronic health record (EHR); compliance with interoperability ontologies and standards (e.g., Health Level 7 [HL7], Systematized Nomenclature of Medicine – Clinical Terminology [SNOMED-CT]); and whether the item is knowledge-based (derived from research findings) or non-knowledge-based (derived through artificial intelligence, machine learning, advanced probability and statistics), among others. Ninety-seven (97) vendor websites describing 196 CDS and 73 WT (269 total) were reviewed and coded. The primary purpose of the majority of CDS reviewed is diagnosis or diagnosis/treatment/drug decision support—targeted for clinician use— and the primary purpose of the majority of WT reviewed is the monitoring of different health metrics, most often through the use of a biosensor device (e.g., blood pressure)—targeted for patient use. Very few CDS or WT appear to comply with major international interoperability standards or can be integrated with a patient’s EHR data. None consider contextual factors, such as conditions of the physical environment (e.g., CO2 levels). The majority of CDS and WT reviewed are non-knowledge, cloud- or web-based applications or software. Forty-three (43) major findings were identified and the implications those findings have for NASA will be discussed. Example major findings include: CDS-WT capabilities range from diagnosis to treatment applications, CDS-WT may be wearable or non-wearable and are technologically advanced and only a few CDS-WT tools referenced compliance to ensure interoperability, among other findings. Recommendations will also be offered that will help to address ExMC Gap, Medical-701: Enhance medical capabilities within an exploration medical system.

market survey↗
DOE OSTI2021

Clinical knowledge extraction via sparse embedding regression (KESER) with multi-center large scale electronic health record data

The increasing availability of electronic health record (EHR) systems has created enormous potential for translational research. However, it is difficult to know all the relevant codes related to a phenotype due to the large number of codes available. Traditional data mining approaches often require the use of patient-level data, which hinders the ability to share data across institutions. In this project, we demonstrate that multi-center large-scale code embeddings can be used to efficiently identify relevant features related to a disease of interest. We constructed large-scale code embeddings for a wide range of codified concepts from EHRs from two large medical centers. We developed knowledge extraction via sparse embedding regression (KESER) for feature selection and integrative network analysis. We evaluated the quality of the code embeddings and assessed the performance of KESER in feature selection for eight diseases. Besides, we developed an integrated clinical knowledge map combining embedding data from both institutions. The features selected by KESER were comprehensive compared to lists of codified data generated by domain experts. Features identified via KESER resulted in comparable performance to those built upon features selected manually or with patient-level data. The knowledge map created using an integrative analysis identified disease-disease and disease-drug pairs more accurately compared to those identified using single institution data. Analysis of code embeddings via KESER can effectively reveal clinical knowledge and infer relatedness among codified concepts. KESER bypasses the need for patient-level data in individual analyses providing a significant advance in enabling multi-center studies using EHR data.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
NASA NTRS2007

Organization, Management and Function of International Space Station (ISS) Multilateral Medical Operations

Long duration crews have inhabited the ISS since November of 2000. The favorable medical outcomes of its missions can be largely attributed to sustained collective efforts of all ISS Partners medical organizations. In-flight medical monitoring and support, although crucial, is just a component of the ISS system of Joint Medical Operations. The goal of this work is to review the principles, design, and function of the multilateral medical support of the ISS Program. The governing documents, which describe the relationships among all ISS partner medical organizations, were evaluated, followed by analysis of the roles, responsibilities, and decision-making processes of the ISS medical boards, panels, and working groups. The degree of integration of the medical support system was evaluated by reviewing the multiple levels of the status reviews and mission assurance activities carried out throughout the last six years. The Integrated Medical Group, consisting of physicians and other essential personnel in the mission control centers represents the front-line medical support of the ISS. Data from their day-to-day activities are presented weekly at the Space Medicine Operations Team (SMOT), where known or potential concerns are addressed by an international group of physicians. A broader status review is conducted monthly to project the state of crew health and medical support for the following month, and to determine measures to return to nominal state. Finally, a comprehensive readiness review is conducted during preparations for each ISS mission. The Multilateral Medical Policy Board (MMPB) issues medical policy decisions and oversees all health and medical matters. The Multilateral Space Medicine Board (MSMB) certifies crewmembers and visitors for training and space flight to the Station, and physicians to practice space medicine for the ISS. The Multilateral Medical Operations Panel (MMOP) develops medical requirements, defines and supervises implementation of operational countermeasures, environmental monitoring, medical care, and emergency medical services. MMOP assures the medical readiness of the Station for each subsequent mission or critical event. All boards and panels have functioned effectively and without interruptions even in various challenging circumstances. Based on the experience of the authors, consensus has prevailed as the primary nature of decisions made by all ISS medical groups, at all levels. The six first years of piloted operation have demonstrated the ability of the ISS medical authority groups and the medical infrastructure to implement medical policies and requirements, effectively interface with non-medical groups, and maintain the health and productivity of the crew in an integrated, multilaterally coordinated fashion. The medical support system appears to be mature and ready for further expansion of all Partners roles, and for the anticipated increase in the size of ISS crews.

Duncan, James M.↗
DOE OSTI2017

Site Environmental Report for 2016

Lawrence Berkeley National Laboratory (LBNL, Berkeley Lab) is a multi-program scientific facility operated by the University of California (UC) for the U.S. Department of Energy (DOE). Berkeley Lab’s research is focused on the physical, biological, environmental, and computational sciences with the objective of delivering scientific knowledge and discoveries pertinent to DOE’s mission. This annual report describes environmental protection activities and potential impacts resulting from LBNL operations conducted in 2016. The format and content of this report satisfy the requirements of both DOE Order 231.1B Admin Chg 1, Environment, Safety, and Health Reporting, and the operating contract between UC and DOE (DOE Contract No. DE-AC02-05CH11231, also known as Contract 31). Activities are planned and conducted with full regard to protecting employees, the public, and the environment, as well as complying with all applicable environmental, safety, and health laws and regulations. Berkeley Lab implements an Environmental Management System (EMS) to oversee these compliance activities and improve overall environmental performance while maintaining operational capability and sustaining its overall mission. The effectiveness of the EMS and environmental programs is reviewed annually as part of the operating contract’s performance evaluation process. For fiscal year (FY) 2016, which began October 1, 2015, and ended September 30, 2016, the EMS was given a performance rating of A minus for its management of environmental activities (on a scale from A plus as the highest grade to F as the lowest). The measurement and rating system was developed jointly by Berkeley Lab, UC, and DOE. The FY 2016 rating was based on how Berkeley Lab met the objective in DOE’s FY 2017 Performance Evaluation and Measurement Plan (Appendix B in Contract 31, Section J) of providing an efficient and effective EMS. To support this rating, Berkeley Lab prepared a list of projects completed during the performance period that achieved reduced environmental impacts. The EMS was also graded through the federal Office of Management and Budget’s EMS Annual Report Data, in which elements of the International Organization for Standardization (ISO) 14001 standard are rated and the degree of integration between the EMS and Berkeley Lab’s sustainable practices is measured. Overall scores fall into one of three categories: green (highest), yellow (middle), or red (lowest). For FY 2016, Berkeley Lab received a score of green, as described in more detail in Chapter 2. An overview of environmental protection and restoration programs is provided (Chapter 3), including information about compliance activities, operating permits, and regulatory agency inspections that occurred during 2016. Six minor violations issued during these inspections are discussed, one of which was rescinded in 2017. This report also includes information on environmental monitoring performed in 2016 (Chapter 4). The results of these monitoring activities confirmed that groundwater cleanup actions continue to show improving conditions, and all emissions and discharges from LBNL operations were within environmental compliance release limits with the exception of some stormwater discharges. While most stormwater discharges measured throughout the LBNL site fall within acceptable levels established by the state's stormwater permit, iron and aluminum exceeded permitted levels. Berkeley Lab is aggressively implementing controls to reduce iron and aluminum discharge levels. The controls include construction of asphaltic berms to restrain and filter runoff to storm drains, and installation of filtration units in storm drain basins to absorb metal contaminants. The radiological dose assessments (Chapter 5) performed in 2016 concluded that the maximum dose to a hypothetical resident from Berkeley Lab’s airborne radionuclide releases was approximately 0.12% of the DOE and U.S. Environmental Protection Agency annual limit of 10 millirem per year (mrem/year); the dose from all radiation sources at Berkeley Lab was approximately 0.1% of the average natural background radiation dose of 310 mrem/yr in the United States, and about 0.4% of the DOE annual limit of 100 mrem/yr from all sources.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2020

A Generic Software Architecture for Prognostics

Prognostics is a systems engineering discipline focused on predicting end-of-life of components and systems. As a relatively new and emerging technology, there are few fielded implementations of prognostics, due in part to practitioners perceiving a large hurdle in developing the models, algorithms, architecture, and integration pieces. As a result, no open software frameworks for applying prognostics currently exist. This paper introduces the Generic Software Architecture for Prognostics (GSAP), an open-source, cross-platform, object-oriented software framework and support library for creating prognostics applications. GSAP was designed to make prognostics more accessible and enable faster adoption and implementation by industry, by reducing the effort and investment required to develop, test, and deploy prognostics. This paper describes the requirements, design, and testing of GSAP. Additionally, a detailed case study involving battery prognostics demonstrates its use.

Prognostics and Health Management (PHM)↗
DOE OSTI2018

Site Environmental Report for 2017

Lawrence Berkeley National Laboratory (LBNL, Berkeley Lab) is a multi-program scientific facility operated by the University of California (UC) for the U.S. Department of Energy (DOE). Berkeley Lab’s research is focused on the physical, biological, environmental, and computational sciences with the objective of delivering scientific knowledge and discoveries pertinent to DOE’s mission. This annual report describes environmental protection activities and potential impacts resulting from LBNL operations conducted in 2017. The format and content of this report satisfy the requirements of both DOE Order 231.1B, Administrative Change 1 (Environment, Safety, and Health Reporting) and the operating contract between UC and DOE (DOE Contract No. DE-AC02-05CH11231, also known as Contract 31). Activities are planned and conducted with full regard to protecting employees, the public, and the environment, as well as complying with all applicable environmental, safety, and health laws and regulations. Berkeley Lab implements an Environmental Management System (EMS) to oversee these compliance activities and continually improve overall environmental performance while maintaining operational capability and sustaining its overall mission. The effectiveness of the EMS and environmental programs is reviewed annually as part of the performance evaluation process of Contract 31. For fiscal year (FY) 2017, which began October 1, 2016, and ended September 30, 2017, the EMS was given a performance rating of B plus for its management of environmental activities (on a scale from A plus as the highest grade to F as the lowest). The measurement and rating system was developed jointly by Berkeley Lab, UC, and DOE. The FY 2017 rating was based on how Berkeley Lab met the objective in DOE’s FY 2017 Performance Evaluation and Measurement Plan (Appendix B in Contract 31, Section J) of providing an efficient and effective EMS. Six significant accomplishments, which ranged from effective teaming on projects and with regulatory agencies to improved program assessment approaches, were factors in the rating. The EMS was also graded through the federal Office of Management and Budget’s annual EMS performance metrics, in which a reporting scorecard rates elements of the International Organization for Standardization (ISO) 14001 standard and the degree of integration between the EMS and Berkeley Lab’s sustainable practices. Overall scores fall into one of three categories: green (highest), yellow (middle), or red (lowest). For FY 2017, Berkeley Lab received a score of green, as described in more detail in Chapter 2. An overview of environmental protection and restoration programs is provided, including information about compliance activities, operating permits, and regulatory agency inspections that occurred during 2017. Thirteen minor violations issued during City of Berkeley inspections of above and underground storage tanks, treatment units, and hazardous waste storage areas are discussed in this chapter. This report also includes information on environmental monitoring performed in 2017. The results of these monitoring activities confirmed that groundwater cleanup actions continue to show improving conditions, and all emissions and discharges from LBNL operations were within environmental compliance release limits, with the exception of some stormwater discharges. Most stormwater discharges measured throughout the LBNL site fall within acceptable levels established by the state’s stormwater permit; however, iron and aluminum exceeded Numeric Action Levels. To reduce iron and aluminum discharge levels, Berkeley Lab is aggressively implementing controls such as construction of asphaltic berms and check dams to restrain and filter runoff to storm drains, and installation of filtration units in storm drain basins to collect sediment and absorb metal contaminants. The radiological dose assessments performed in 2017 concluded that the maximum potential dose to a hypothetical resident from Berkeley Lab’s airborne radionuclide releases was approximately 0.1% of the DOE and U.S. Environmental Protection Agency annual limit of 10 millirem per year (mrem/yr); the potential dose from all radiation sources at Berkeley Lab was approximately 0.06% of the average natural background radiation dose of 310 mrem/yr in the United States, and about 0.2% of the DOE annual limit of 100 mrem/yr from all sources.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1990

A report on SHARP (Spacecraft Health Automated Reasoning Prototype) and the Voyager Neptune encounter

The development and application of the Spacecraft Health Automated Reasoning Prototype (SHARP) for the operations of the telecommunications systems and link analysis functions in Voyager mission operations are presented. An overview is provided of the design and functional description of the SHARP system as it was applied to Voyager. Some of the current problems and motivations for automation in real-time mission operations are discussed, as are the specific solutions that SHARP provides. The application of SHARP to Voyager telecommunications had the goal of being a proof-of-capability demonstration of artificial intelligence as applied to the problem of real-time monitoring functions in planetary mission operations. AS part of achieving this central goal, the SHARP application effort was also required to address the issue of the design of an appropriate software system architecture for a ground-based, highly automated spacecraft monitoring system for mission operations, including methods for: (1) embedding a knowledge-based expert system for fault detection, isolation, and recovery within this architecture; (2) acquiring, managing, and fusing the multiple sources of information used by operations personnel; and (3) providing information-rich displays to human operators who need to exercise the capabilities of the automated system. In this regard, SHARP has provided an excellent example of how advanced artificial intelligence techniques can be smoothly integrated with a variety of conventionally programmed software modules, as well as guidance and solutions for many questions about automation in mission operations.

Martin, R. G.↗
DOE OSTI2024

Prognostic model and failure mechanisms of steam generators in Sodium-Cooled fast reactors

This paper presents a prognostic model for sodium-cooled fast reactor (SFR) steam generators (SGs). Here, the purpose of the model is to estimate the remaining useful life of SFR SGs and thus to support the decision-making of autonomous control. SFR SGs are of great interest for plant integrity due to their harsh operation environment. They operate at higher temperatures and higher coolant-to-steam pressure differences than those of current light water reactors (LWR). The severity of the SFR SG failure consequences, which include water-sodium contact, is another reason. Understanding its failure mechanisms is important for the development of its prognostic model. Based on our literature review and physics-based analysis, we concluded that creep would be a dominant degradation mode of SFR SGs due to SFR’s high-temperature and high-pressure environment. Thus, creep is the focus of the prognostic model. Various other failure modes were also investigated in this study. The mechanical fatigue due to flow-induced vibration is usually observed in early developmental phases and would not be an important issue during normal operation. The thermal fatigue due to thermal stripping is occasionally observed in other components in SFRs but does not affect SG integrity. Pure water stress corrosive crack, fretting, and so on are commonly observed in LWR SGs but are significantly less important in SFR SGs because of the high temperatures, high pressure differences, and chemical properties of liquid sodium. Based on these investigations, a prognostic model focusing on creep failures was developed. It estimates the failure probability profile by sampling the Larson-Miller parameter (LMP) and temperature and associated uncertainties through Monte Carlo methods. Two case studies were presented. The first one demonstrated the model’s capability to calculate the failure probability for a new specimen within a given time. If the tube is working under temperatures of 500C ± 3 and pressures of 15.2 MPa, which leads to LMP of 20,100 ± 50, the failure probabilities within 50, 70, and 90 years are approximately 0.1 %, 3.2 %, and 17.5 %. The second demonstrated how adjusting the workload can help to protect the integrity of the component. For an old tube reaching 99 % of its lifespan, continuing to run at temperatures of 500C ± 3 and LMP of 20,100 ± 50 leads to a failure probability of about 29.0 % within a year. If the temperature is reduced by 5C, the failure probability can be reduced to 2.5 %, and, if the pressure is also reduced such that the LMP is increased by 100, the failure probability can further be reduced to 0.12 %.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2025

Machine Learning Models for Mapping Groundwater Pollution Risk: Advancing Water Security and Sustainable Development Goals in Georgia, USA

The widespread use of pesticides, such as atrazine and malathion, in agricultural systems raises significant concerns regarding the contamination of groundwater, which serves as a critical resource for drinking water. This study applies machine learning techniques to predict the concentrations of atrazine and malathion in groundwater across Georgia, USA, using 2019 data. A Random Forest classifier was employed to integrate various environmental and demographic factors, including pesticide application rates, precipitation, lithology, and population density, to predict pesticide contamination in groundwater. The models demonstrated high training accuracies of 100% and moderate average testing accuracy of 55% for atrazine and 60% for malathion across five iterations. The low test accuracy of the model, ranging from 50% to 75%, is likely due to overfitting, which can be attributed to the small dataset size and the complex nature of pesticide-contamination patterns, making it challenging for the model to generalize to unseen data. Feature importance analysis revealed that average pesticide usage emerged as the most influential factor for atrazine, while aquifer lithology and precipitation played crucial roles in both models. These results provide valuable insights into the dynamics of pesticide contamination, highlighting areas at greater risk of contamination. The findings underscore the importance of integrating environmental, geological, and agricultural variables for more effective groundwater management and sustainable agricultural practices, contributing to the protection of water resources and public health.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2022

An Advanced Open-Source Platform for Air Quality Analysis, Visualization, and Prediction

Ambient air pollution is the largest environmental health risk factor, leading to several million premature deaths globally per year. The challenge of combating poor air quality is exacerbated by growing urban populations, changing emissions, and a warming climate. While there have been many advances monitoring and modeling of atmospheric composition, reflected in the dramatic increase in archived Earth Observations, there is no single measurement or method that alone can provide an accurate depiction of the entire atmosphere. The rapidly growing collections of observational and modeling data require us to be smarter about what data to include, and how such data is used. In recent years, NASA has invested significantly in advancing the concepts for Analytics Collaborative Framework (ACF) [5] and New Observing Strategies (NOS) [4] to tackle our software infrastructure need for harmonized data management and dynamic acquisition of diverse measurements for on-demand, interactive, multivariate analysis, and access [3]. It is not enough to have a big data, standalone analytics solution; it is critical that we start integrating data from remote sensing, modeling, and in-situ networks in a harmonized manner that enables timely and data-driven decision-making for air quality management. This work presents the design and development of an Air Quality Analytics Collaborative Framework (AQ ACF), as part of NASA’s Advanced Information Systems Technology (AIST) effort, to establish a data, machine-learning, and numerically driven platform for air quality analysis, visualization, and prediction.

Liu, Qian↗
DOE OSTI2019

Site Environmental Report for 2018

Lawrence Berkeley National Laboratory (LBNL, Berkeley Lab) is a multi-program scientific facility operated by the University of California (UC) for the U.S. Department of Energy (DOE). Berkeley Lab’s research is focused on the physical, biological, environmental, and computational sciences, with the objective of delivering scientific knowledge and discoveries pertinent to DOE’s mission. This annual report describes environmental protection activities and potential impacts resulting from LBNL operations conducted in 2018. The format and content of this report satisfy the requirements of both DOE Order 231.1B, Administrative Change 1 (Environment, Safety, and Health Reporting) and the operating contract between UC and DOE (DOE Contract No. DE-AC02-05CH11231, also known as Contract 31). LBNL activities are planned and conducted with full regard to protecting employees, the public, and the environment, as well as complying with all applicable environmental, safety, and health laws and regulations. As presented in Chapter 2, Berkeley Lab implements an Environmental Management System (EMS) to oversee environmental compliance activities and continually improve overall environmental performance while maintaining operational capability and sustaining its overall mission. The effectiveness of the EMS and environmental programs is reviewed annually as part of the performance evaluation process of Contract 31. For fiscal year (FY) 2018, which began October 1, 2017, and ended September 30, 2018, the EMS was given a performance rating of B plus for its management of environmental activities (on a scale from A plus as the highest grade, to F as the lowest). The measurement and rating system was developed jointly by Berkeley Lab, UC, and DOE. The FY 2018 rating was based on how Berkeley Lab met the objective in DOE’s FY 2018 Performance Evaluation and Measurement Plan (Appendix B in Contract 31, Section J) of providing an efficient and effective EMS. Six significant accomplishments, which ranged from effective teaming on projects and with regulatory agencies to improved program assessment approaches, were factors in the rating. The EMS was also graded through the federal Office of Management and Budget’s annual EMS performance metrics, in which a reporting scorecard rates elements of the International Organization for Standardization (ISO) 14001 standard and the degree of integration between the EMS and Berkeley Lab’s sustainable practices. Overall scores fall into one of three categories: green (highest), yellow (middle), or red (lowest). For FY 2018, Berkeley Lab received a score of green. A week-long formal conformity audit of the EMS was conducted at the end of July by a qualified external party, as is required every three years. The audit team found that Berkeley Lab’s EMS continues to conform to the ISO standard with no major nonconformance. An overview of environmental protection and restoration programs is provided in Chapter 3, including information about compliance activities, operating permits, and regulatory agency inspections and audits that occurred during 2018. Twenty-one minor violations and two Class II violations were issued during agency inspections of programs governing aboveground and underground storage tanks, hazardous waste treatment units, hazardous waste storage areas, hazardous materials management, and wastewater, stormwater, and air emission sources. This report also includes information on environmental monitoring performed in 2018 (Chapter 4). The results of these monitoring activities confirmed that groundwater cleanup actions have been effective in reducing concentrations of volatile organic compounds (VOCs) in the groundwater, although concentrations appear to be reaching asymptotic levels in some areas. Site groundwater plumes are stable or are attenuating, and VOCs are not migrating off site. All emissions and discharges from LBNL operations were within environmental compliance release limits except oxides of nitrogen and carbon monoxide from boilers (under 5 million BTUs) from Buildings 2, 66, and 88. The radiological dose assessments (Chapter 5) performed in 2018 concluded that the maximum potential dose to a hypothetical resident from Berkeley Lab’s airborne radionuclide releases was approximately 0.04% of the DOE and U.S. Environmental Protection Agency annual limit of 10 millirem per year (mrem/yr); the potential dose from all radiation sources at Berkeley Lab was approximately 0.15% of the average natural background radiation dose of 310 mrem/yr in the United States, and about 0.5% of the DOE annual limit of 100 mrem/yr from all sources.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1993

Earthbound applications for NASA's physician workstation

The dream of a space probe to Mars or an astronaut colony on the moon persists. Despite years of setbacks and delays, NASA continues to lay the foundation for a new frontier in space. The necessity of a self contained health maintenance facility is an integral part of this stellar venture. As a subsystem of this health maintenance facility, the physician or astronaut workstation was envisioned as the vehicle of interface between the computer resources of the space station and the care provider. Our efforts to define and build this interface have resulted in a series of programs which can now be tested and refined using earth-based applications. The modules which have dual-use application from the NASA workstation include: patient scheduling and master patient index, pharmacy, laboratory, medical library, problem list/progress notes, and digital medical records. Our current plan is to develop these tools as objects that can be assembled in a variety of configurations. This will allow the technology to be used by the private sector where each doctor can select the starting point of his outpatient office system and add modules as he makes progress in system integration and training.

NASA Discipline Number 70-30↗
DOE OSTI2016

The Medical Science DMZ

Objective We describe use cases and an institutional reference architecture for maintaining high-capacity, data-intensive network flows (e.g., 10, 40, 100 Gbpsþ) in a scientific, medical context while still adhering to security and privacy laws and regulations. Materials and Methods High-end networking, packet filter firewalls, network intrusion detection systems. Results We describe a “Medical Science DMZ” concept as an option for secure, high-volume transport of large, sensitive data sets between research institutions over national research networks. Discussion The exponentially increasing amounts of “omics” data, the rapid increase of high-quality imaging, and other rapidly growing clinical data sets have resulted in the rise of biomedical research “big data.” The storage, analysis, and network resources required to process these data and integrate them into patient diagnoses and treatments have grown to scales that strain the capabilities of academic health centers. Some data are not generated locally and cannot be sustained locally, and shared data repositories such as those provided by the National Library of Medicine, the National Cancer Institute, and international partners such as the European Bioinformatics Institute are rapidly growing. The ability to store and compute using these data must therefore be addressed by a combination of local, national, and industry resources that exchange large data sets. Maintaining data-intensive flows that comply with HIPAA and other regulations presents a new challenge for biomedical research. Recognizing this, we describe a strategy that marries performance and security by borrowing from and redefining the concept of a “Science DMZ”—a framework that is used in physical sciences and engineering research to manage high-capacity data flows. Conclusion By implementing a Medical Science DMZ architecture, biomedical researchers can leverage the scale provided by high-performance computer and cloud storage facilities and national high-speed research networks while preserving privacy and meeting regulatory requirements.

97 MATHEMATICS AND COMPUTING↗