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At least 631 records · Page 35

Programmable intrusion detection for distributed energy resources in cyber–physical networked microgrids

We present a programmable intrusion detection method is presented to identify the malicious attacks to distributed energy resources (DERs) in the cyber-physical networked microgrids. The proposed method injects small programmable signals into the system and uses the response to identify abnormal conditions. Because of the low or even zero inertia induced by integrations of DER power-electronic-interfaces, microgrids have very limited resilience capability; and thus, being sensitive to attacks. One microgrid's malfunction caused by attacks can easily propagate to its neighboring systems when several microgrids are connected, leading to catastrophic electricity supply failures. Through the presented method, malicious intrusions can be effectively detected, located, and defended for securing microgrids. Theoretical derivations are provided to define the programmable detection rules. The detection rule is easy and flexible to update, making it difficult for attack actors to gain the knowledge of the detection rules, in order to avoid being detected. Numerical results on a cyber-physical networked microgrids system show that the proposed method is effective and efficient in precisely locating intrusion attacks to the microgrids system.

42 ENGINEERING↗

Fully Automated Detection of Cloud and Aerosol Layers in the CALIPSO Lidar Measurements

Accurate knowledge of the vertical and horizontal extent of clouds and aerosols in the earth s atmosphere is critical in assessing the planet s radiation budget and for advancing human understanding of climate change issues. To retrieve this fundamental information from the elastic backscatter lidar data acquired during the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) mission, a selective, iterated boundary location (SIBYL) algorithm has been developed and deployed. SIBYL accomplishes its goals by integrating an adaptive context-sensitive profile scanner into an iterated multiresolution spatial averaging scheme. This paper provides an in-depth overview of the architecture and performance of the SIBYL algorithm. It begins with a brief review of the theory of target detection in noise-contaminated signals, and an enumeration of the practical constraints levied on the retrieval scheme by the design of the lidar hardware, the geometry of a space-based remote sensing platform, and the spatial variability of the measurement targets. Detailed descriptions are then provided for both the adaptive threshold algorithm used to detect features of interest within individual lidar profiles and the fully automated multiresolution averaging engine within which this profile scanner functions. The resulting fusion of profile scanner and averaging engine is specifically designed to optimize the trade-offs between the widely varying signal-to-noise ratio of the measurements and the disparate spatial resolutions of the detection targets. Throughout the paper, specific algorithm performance details are illustrated using examples drawn from the existing CALIPSO dataset. Overall performance is established by comparisons to existing layer height distributions obtained by other airborne and space-based lidars.

Vaughan, Mark A.↗

Model-Based Systems Engineering, Real-Time Operations, and Autonomy

Model-Based Systems Engineering has been enabled by the development of the SysML language and software tools to create systems models. Systems models described in SysML incorporate frames (Diagrams) that represent behaviors (activities, sequences, state machines, use cases), requirements, and structure (definitions, internal structure, parametric formulation, and packaging). The SysML models are, in turn, used by applications to do analysis and studies of the designs and operational capabilities. These uses of the model are based on simulations, and do not include hardware. This paper presents a software environment and processes that enables more comprehensive systems models for MBSE, and use of these rich models for real-time operations. The paper describes a software platform that enables creation of comprehensive models, beyond what is now possible with SysML and related software tools, called the NASA Platform for Autonomous Systems (NPAS). The platform encapsulates a paradigm and infrastructure for creating systems models with complexity levels comparable to the ones handled by SysML software tools, but with additional fidelity that includes detailed design diagrams encompassing sensors, components, and design topologies. Furthermore, NPAS enables incorporation of data, information, and knowledge (DIaK) to implement autonomy and Integrated System Health Management (ISHM) and the inherent integration of content encompassing SysML structure and behavior diagrams throughout the NPAS modelAnd lastly, the NPAS models are used in real-time operations, taking advantage of the fidelity and complexity encompassed in the models in order to implement “thinking” ISHM and/or autonomous operations. . Incorporation of SysML model content into an NPAS model is briefly discussed.

MBSE↗

NASA Planetary Protection Program Overview and Update

NASA has an integrated planetary protection strategy that leverages COSPAR Policy guide-lines, workshops, scientific consensus, partnerships and international working groups to develop policy and implementation guidelines. The Oÿce of Safety and Mission Assurance, which in-cludes NASA’s Oÿce of Planetary Protection, depends on these activities to support NASA’s missions in the assurance of crew safety and mission success while protecting the public and planetary environment from harmful contamination. This report will detail the overall planetary protection policy development perspective to sup-port NASA’s upcoming mission opportunities for exploration to include crewed Mars and sam-ple return missions. NASA continues to evolve its strategies, policies, and standards. NASA’s support in the COSPAR workshop series on Refining Planetary Protection Requirements for Crewed Missions to Mars have resulted in a NASA interim directive and paved the way for the development of NASA planetary protection roadmaps. These Agency level roadmaps address technology development and testing required to fill knowledge gaps for developing responsive policy guidelines and quantitative technical standards. In addition to workshops and tech-nology management strategies, NASA is also leveraging the National Academies of Science, Engineering, and Medicine’s Committee of Planetary Protection to serve as a source of advice on planetary protection measures. Finally, the report will include how the Oÿce of Safety and Mission Assurance is incorporating planetary protection into existing and new multi-agency partnerships.

Frank Groen↗

Web-Based Tools for Data-Informed Remedy Optimization: Software Theory and User Guide

This report documents the development and application of two web-based decision-support tools for pump-and-treat (P&T) groundwater remediation systems: PTOLEMY (Pump-and-Treat Optimized Location Evaluation to Maximize Yields) and OPTIMA (Optimization for Pump-and-Treat Implementation, Management, & Assessment). These tools enhance remedy design and management by leveraging advanced computational methods – specifically deep learning and multi-objective optimization – within a user-friendly platform. By integrating data-driven models with established hydrogeological knowledge, PTOLEMY and OPTIMA enable more efficient evaluation of well placement and operational strategies, helping site managers balance multiple remediation objectives under complex conditions. Both tools are implemented as modules within the SOCRATES (Suite Of Comprehensive Rapid Analysis Tools for Environmental Sites) web platform, which provides data access, visualization, and analytics to support remedy optimization across sites in the U.S. Department of Energy Office of Environmental Management complex. PTOLEMY is a rapid screening module designed to identify promising locations for new extraction wells. It employs a multi-channel three-dimensional convolutional neural network (MC3D-CNN) trained on high-fidelity simulation data to predict the relative performance (in terms of contaminant mass recovery) of potential well sites. Through an interactive web interface, PTOLEMY visualizes the probability of high performance across a site, highlighting areas where an extraction well is likely to yield above-threshold contaminant removal over a multi-year period. PTOLEMY’s map-based displays and exportable results support transparent communication of screening analyses. By focusing attention on the most favorable candidate locations, the tool augments traditional engineering judgment and physics-based modeling, providing a data informed basis for subsequent detailed evaluations. OPTIMA is a multi objective optimization module designed to find wellfield layouts and operating schedules that meet various cleanup goals. It quickly evaluates thousands of candidate setups – combinations of well locations, timing, and rates – and returns a small set of best trade-off options for comparison. At its core, OPTIMA uses a U-Net-based surrogate model – a deep-learning emulator of a groundwater flow and transport simulator – to dramatically accelerate scenario evaluations. Coupling this fast surrogate with the NSGA-II (Non-dominated Sorting Genetic Algorithm II) evolutionary algorithm, OPTIMA explores a wide decision space of well locations and schedules to identify Pareto-optimal solutions that trade off key objectives (e.g., minimizing cleanup time, maximizing contaminant mass removal, and minimizing plume extent). The tool outputs a family of optimal configurations and visualizes their trade-offs (Pareto frontiers of cleanup metrics and maps of optimized well placements). Site managers can use these results to understand the range of viable strategies and to select candidate designs for more detailed verification. OPTIMA is currently under active development and not yet fully released; this guide provides early documentation to support planning and gather user feedback.

54 ENVIRONMENTAL SCIENCES↗

Assessment Environment for Complex Systems Software Guide

This Software Guide (SG) describes the software developed to test the Assessment Environment for Complex Systems (AECS) by the West Virginia High Technology Consortium (WVHTC) Foundation's Mission Systems Group (MSG) for the National Aeronautics and Space Administration (NASA) Aeronautics Research Mission Directorate (ARMD). This software is referred to as the AECS Test Project throughout the remainder of this document. AECS provides a framework for developing, simulating, testing, and analyzing modern avionics systems within an Integrated Modular Avionics (IMA) architecture. The purpose of the AECS Test Project is twofold. First, it provides a means to test the AECS hardware and system developed by MSG. Second, it provides an example project upon which future AECS research may be based. This Software Guide fully describes building, installing, and executing the AECS Test Project as well as its architecture and design. The design of the AECS hardware is described in the AECS Hardware Guide. Instructions on how to configure, build and use the AECS are described in the User's Guide. Sample AECS software, developed by the WVHTC Foundation, is presented in the AECS Software Guide. The AECS Hardware Guide, AECS User's Guide, and AECS Software Guide are authored by MSG. The requirements set forth for AECS are presented in the Statement of Work for the Assessment Environment for Complex Systems authored by NASA Dryden Flight Research Center (DFRC). The intended audience for this document includes software engineers, hardware engineers, project managers, and quality assurance personnel from WVHTC Foundation (the suppliers of the software), NASA (the customer), and future researchers (users of the software). Readers are assumed to have general knowledge in the field of real-time, embedded computer software development.

tests↗

Imagine Moving Off the Planet

Moving off the planet will be a defining moment of this century as landing on the Moon was in the last. For that to happen for humans to go where humans cannot go-- simulation is the sole solution. NASA supports simulation for life-cycle activities: design, analysis, test, checkout, operations, review and training. We contemplate time spans of a century and more, teams dispersed to different planets and the need for systems that endure or adapt as missions, teams and technology change. Without imagination such goals are impossible. But with imagination we can go outside our present perception of reality to think about and take action on what has been, is and, especially, what might be. Consciously maturing an imagined, possibly workable, idea through framing it to optimization to design, and building the product provides us with a new approach to innovation and simulation fidelity. We address options, analyze, test and make improvements in how we think and work. Each step includes increasingly exact information about costs, schedule, who will be needed, where, when and how. NASA i integrating such thinking into its Exploration Product Realization Hierarchy for simulation and analysis, test and verification, and stimulus response goals. Technically NASA follows a timeline of studies, analysis, definition, design, development and operations with concurrent documentation. We have matched this Product Realization Hierarchy with a continuum from image to realization that incorporates commitment, current and needed research and communication to ensure superior and creative problem solving as well as advances in simulation. One result is a new approach to collaborative systems. Another is a distributed observer network prototyped using game engine technology bringing advanced 3-D simulation of a simulation to the desktop enabling people to develop shared consensus of its meaning. Much of the value of simulation comes from developing in people their ability to make good decisions and reflexes supporting impressive achievement. Synthesizing imagination systematically into our work - and thus our success - is a challenge. NASA engineers have inventive minds, and the task is determining how best to enable them to devise the simulation and other innovations that will make a story so clear and so intellectually sound that people can carry out the mission for 50-100 years. This demands skills and knowledge traditionally under-respected and under-represented in technology organizations. But we are beginning to see that the process encourages efficiency and enables us to attain more effective results. We have to elicit imaginative, intelligent and effective ways to make better use than ever of the minds we have and will have available. We have to accept the challenge to accomplish tasks among dispersed interdisciplinary teams who must overcome changing priorities and technology, time and distance in order to maximize interactivity and innovation as never before. Attention to the process of innovation is a practical means to increase the efficiency of our intelligence. We have an obligation to reexamine and improve the process by which we approach and exercise innovation as we accept the charge to move off the planet.

Elfrey, Priscilla R.↗

Droplet Entrainment in Steam Supply System of Water-Cooled Small Modular Reactors: Experiment and Modeling Approaches

Droplet entrainment in steam-flow is a prominent phenomenon that needs adequate safety and risk analysis of postulated transient and accident scenarios—including experimental investigation and representative modeling and simulation (M&S)—for small modular reactor (SMR) system design and demonstration. This study identifies knowledge gaps by evaluating experimental and computational fluid dynamics modeling approaches to support early-stage reactor system design, testing, and model evaluation. Previous studies reported in the literature for steam-flow entrainment primarily focused on gigawatt capacity pressurized water reactor (PWR) systems. However, entrainment phenomena are even more prominent for PWR-type SMRs due to their more compact integrated designs, which need further research and development. To fill the research gaps, this study provides insight by specifying the phenomena of interest by leveraging the lessons learned from past research, adopting advanced M&S techniques and advanced instrumentation and control. The findings and recommendations are applicable for evaluating steam-flow entrainment models and for designing integral effect test and separate effect test facilities for gaining reactor design approvals.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Physics-Guided Deep Learning for Complex System Health Management and Decision Making

The landscape of complex engineered systems is rapidly evolving, from smart manufacturing facilities to next-generation transportation vehicles. As these systems become increasingly sophisticated and interconnected, the need for advanced health management systems grows ever more critical. These systems must go beyond simple monitoring, actively predicting potential failures before they occur. This paradigm shift from fixed maintenance schedules to condition-based predictions is key to optimizing system performance, enhancing safety, and paving the way for autonomous decision-making across various industries. Whether in industrial processes, energy systems, or advanced transportation, the ability to anticipate and prevent failures is becoming a cornerstone of operational excellence. To accurately predict the future health of any complex system, knowledge of its current health state and future operational conditions is essential. Recent advancements in data-driven algorithms have generated growing interest in artificial intelligence for industrial applications. However, the limitations of pure data-driven methods, particularly in industries where data acquisition is costly and limited, have become apparent. This has led to a focus on blending physics with data-driven algorithms, mitigating the drawbacks of both approaches while emphasizing their respective advantages. This research proposes a novel framework for integrating physics-based performance models with deep learning algorithms for the prognostics of complex safety-critical systems. In this approach, physics-based models serve as a blueprint, capturing fundamental system behaviors, while deep learning algorithms, leveraging real-world sensor data, fill in gaps and identify subtle patterns indicative of potential problems. This hybrid methodology, utilizing techniques such as Physics-Informed Neural Networks (PINNs), offers a powerful solution for predicting system health. By fusing domain knowledge with data-driven insights, this approach promises more accurate, adaptable, and reliable models for health prediction. The resulting framework is versatile, applicable across various sectors including aerospace, manufacturing, and energy systems, ultimately contributing to safer, more efficient operations in our increasingly complex technological landscape.

Diagnostics↗

Comprehensive framework for data-driven model form discovery of the closure laws in thermal-hydraulics codes

The two-phase two-fluid model is a basis of many thermal-hydraulics codes used in design, licensing, and safety considerations of nuclear power plants. Thermal-hydraulics codes rely on the closure laws to close the system of conservation equations and describe the interactions between phases. These laws, derived from years of experimental investigations, are semi-empirical correlations that lack generality and have a limited range of applicability. Increase of computational power, availability of new experiments, and development of high-fidelity simulations has increased the number of validation data. The discrepancies between the code predictions and the validation data are a great source of knowledge. Missing physics that are not included in the model but are important for the considered phenomena can be discovered by propagating the information from the experimental results through the model. Furthermore, physics-discovered data-driven model form (P3DM) methodology integrates available integral effect tests and separate effects tests to determine the necessary corrections to the model form of the closure laws. In contrast to existing calibration techniques, the methodology modifies the functional form of the closure laws. Based on the functional form of the correction, the missing physics that were not included in the original model can be discovered. The methodology provides the alternative to the machine learning approach, in which the model is discovered in the form of the intractable black-box relation. In this work, the methodology was applied to the CTF subchannel code to improve the prediction of the two-phase flow phenomena.

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Salient Characteristics for Terrestrial Analog Engineering Test Sites

The use of terrestrial analog sites is an essential component of the development process for systems that are planned for lunar and planetary surfaces. These sites can also be valuable for training personnel who are expected to operate those systems. The fact that the site is an integral element, capable of influencing data and impacting test results, must not be overlooked. For tests performed in analog environments to be truly valid it is essential that the relevant characteristics of the employed sites be thoroughly understood. It is also critical that a comparative evaluation be made to assess the similarity of the analog sites to target planetary sites. Examples of relevant characteristics include terrain, soil properties, meteorology, geologic features, biological history, and remoteness. The importance of each of the characteristics varies with the type of extraterrestrial activity to be conducted. As a result, a site that is ideal for one purpose may be totally inadequate for another. It may also be appropriate to utilize multiple sites of increasing fidelity as the development process evolves. For example, early in the development process, the use of lower-fidelity sites may be elected - especially if they are available for a lower cost. Later, it may be necessary to employ higher-fidelity sites to capture greater realism, even if there is an associated increased cost. Finally, when interpreting the results of field tests, it is necessary to understand the sensitivity of the results to the relevant conditions. Knowledge of characteristics and sensitivity of results is particularly important when using field test results to validate analytical model predictions. This is especially true for activities that involve physical interaction with the site. Examples would include tests of rovers or other vehicles and associated trafficability modeling, spacesuit mobility tests, and tests associated with system deployment operations.

Watson, J.K.↗

Metabolites Annotations and Genes Integrated (MAGI) v1.0

With the benefit of hindsight, it is easy to see that the readout of the human genome, spectacular milestone that it was, represents only the beginning of the "omics" information explosion. The technical side of the 'omics explosion--enabling researchers to efficiently readout terabytes of information spelling out whole genomes, transcriptomes, proteomes and metabolomes, does not per se provide a clear picture of how life works. Nor does it show us how we can engineer biology to solve the grand challenges of the 21st century: feeding 10 billion people with declining per capita supplies of arable land and clean water, sustaining biological diversity and slowing the increase in greenhouse gas formation, primarily carbon dioxide and methane. The 2017-063 invention--Metabolites and Genes Integration Technology--proposes an integrated approach to correcting and connecting the dots of the 'omics explosion: linking genes to proteins, proteins to pathways, pathways to biochemical reactions and metabolites. The '063 invention is potentially transformational in that it can generate testable hypotheses across thousands of genes to predict their chemical and metabolic products. It can also do the reverse; i.e., starting from chemical and metabolic products it can generate testable hypotheses about which genes and pathways those molecules are linked to. Since we know that genomic, transcriptomic, proteomic and metabolomic databases are chock full or erroneous information, MAGI also has the unique benefit of correcting these errors through its own independent pathway of bidirectional hypothesis generation (genes=>proteins=>metabolites + metabolites=>proteins=>genes). Perfectly amenable to high-throughput hypothesis generation and experimentation, MAGI can transform our understanding of human, animal, plant and microbial biology over several decades, laying the essential knowledge foundation to addressing the grand scientific challenges of the 21st century.

Bowen, Benjamin↗

Geologic hydrogen: a review of resource potential, subsurface dynamics, exploration, production, transportation, and research opportunities

Hydrogen is a versatile resource with critical roles in decarbonization, industrial manufacturing, and energy integration. However, most hydrogen today is produced from fossil fuels, resulting in high emissions and energy consumption. Although low-carbon hydrogen production methods, such as steam methane reforming with carbon capture and renewable-powered electrolysis, are advancing, their high costs hinder large-scale deployment. Identifying alternative pathways for producing low-cost, low-emission hydrogen is therefore essential. Geologic hydrogen, referring to natural and stimulated hydrogen generated in the Earth's subsurface, has attracted growing attention as a potential source of sustainable, economically viable, and environmentally favorable hydrogen. This paper provides a comprehensive review of geologic hydrogen, covering its resource potential, origins, migration and trapping mechanisms, exploration techniques, production strategies, and pipeline transportation. It also identifies key knowledge gaps and proposes a roadmap for future research. The review indicates that geologic hydrogen has vast resource potential and can leverage existing subsurface technologies and geophysical exploration methods. However, major challenges persist, including uncertain hydrogen generation rates, limited understanding and control of serpentinization processes, costly transportation infrastructure, the lack of validated techno-economic analysis, and potential social and environmental issues. As the field is still in its early stages, progress will require interdisciplinary collaboration spanning geoscience, engineering, economics, environmental science, and policy and regulation.

42 ENGINEERING↗

Comments on Control of Wave Energy Converters

The main objective of this letter is to consolidate the knowledge about the dynamics and control of oscillating-body wave energy converters (WECs). A number of studies have shown that control systems strongly affect power absorption; however, there remains a need for a concise and integrated explanation of the theoretical and practical implications that control can have on both performance and the broader WEC design process. This short letter attempts to fill this gap by presenting a discussion on the key practical aspects concerning the dynamics and control of oscillating-body WEC. In particular, the focus is on the choice of control models and a simple causal control scheme suitable for real-time implementation. To conclude, consideration is given to the effect of the power takeoff (PTO) on the maximization of electrical power, thus leading to the derivation of useful conditions for the control co-design of the PTO system.

42 ENGINEERING↗

2015 Space Radiation Standing Review Panel

The 2015 Space Radiation Standing Review Panel (from here on referred to as the SRP) met for a site visit in Houston, TX on December 8 - 9, 2015. The SRP met with representatives from the Space Radiation Element and members of the Human Research Program (HRP) to review the updated research plan for the Risk of Radiation Carcinogenesis Cancer Risk. The SRP also reviewed the newly revised Evidence Reports for the Risk of Acute Radiation Syndromes Due to Solar Particle Events (SPEs) (Acute Risk), the Risk of Acute (In-flight) and Late Central Nervous System Effects from Radiation Exposure (CNS Risk), and the Risk of Cardiovascular Disease and Other Degenerative Tissue Effects from Radiation (Degen Risk), as well as a status update on these Risks. The SRP would like to commend Dr. Simonsen, Dr. Huff, Dr. Nelson, and Dr. Patel for their detailed presentations. The Space Radiation Element did a great job presenting a very large volume of material. The SRP considers it to be a strong program that is well-organized, well-coordinated and generates valuable data. The SRP commended the tissue sharing protocols, working groups, systems biology analysis, and standardization of models. In several of the discussed areas the SRP suggested improvements of the research plans in the future. These include the following: It is important that the team has expanded efforts examining immunology and inflammation as important components of the space radiation biological response. This is an overarching and important focus that is likely to apply to all aspects of the program including acute, CVD, CNS, cancer and others. Given that the area of immunology/inflammation is highly complex (and especially so as it relates to radiation), it warrants the expansion of investigators expertise in immunology and inflammation to work with the individual research projects and also the NASA Specialized Center of Research (NSCORs). Historical data on radiation injury to be entered into the Watson “big data” study must be used with caution. The general scientific issues of reproducibility, details of experimental methods and data analysis from preclinical and basic research laboratories have been raised broadly over the last few years (not specific to this work) and indicate that caution must be applied in the ways these data are used. This pertains to preclinical data and also to phase 3 clinical trials in radiation oncology and medical oncology. Of course, appropriate use and analysis of these “big-data” sets also offer the potential of pinpointing limitations and extracting remaining useful information. Emphasis should be placed on the latter possibility. A key target is risk reduction from radiation exposure. Progress of the entire space program, now moving towards the Mars mission, requires timely answers to key components of human risk, which are known to be complex. Periodic review of progress should be conducted with additional resources directed into achieving critical milestones. Turning the long red bars to yellow and green (or for some risks such as CNS possibly to grey) must be high priority. That such progress will require new science and not engineering means that it should be viewed in a knowledge-based light. The technology-based aspects of engineering issues are certainly as important, however, science and knowledge-based problems are solved in a different way than engineering. Timelines for engineering are more predictable, while for science, progress can be methodical with occasional major incremental findings that can rapidly change the rate of progress. As opportunities for rapid incremental changes arise, periodic enhancement of investment is strongly recommended to enable such new knowledge to be quickly and efficiently exploited. Collaborations and linkages with National Institute of Allergy and Infectious Diseases (NIAID), the Biomedical Advanced Research and Development Authority (BARDA) and the Department of Defense (DoD) are in place and more are encouraged, where possible, with the radiation injury and medical countermeasure studies. This could include utilizing some of their animal model testing contracts to facilitate obtaining results using common platforms. Such approach will facilitate the comparison of results among laboratories, and will facilitate and accelerate the development of medical countermeasures. It is particularly noteworthy that the NASA Space Radiation Element is reaching out to the Multidisciplinary European Low Dose Initiative (MELODI) platform coordinating low dose radiation risk research, and to other international agencies that are studying low dose radiation effects in an effort to fill the void generated by the cancelation of the Department of Energy (DOE) low dose radiation program. While NASA is working actively with NIAID and BARDA to integrate their relevant findings of radiation mitigator investigations to NASA programs, the committee notes its disappointment that the United States currently lacks a dedicated low dose radiation program with clear mechanistic orientation and aimed at the quantification and mitigation of human radiation risk on Earth. This void gives to the NASA Space Radiation Program Element special societal value, but also makes its overall design more challenging.

Steinberg, Susan↗

Unlocking large compressive strains in thin active elastocaloric layers

Elastocaloric cooling attracts broad interest and rapidly growing attention due to its potential for high efficiency and low environmental impact. While it is common knowledge that triggering reversible entropy and temperature changes with stress applied in compression prevents rapid failures of materials, realizing this regime in elastocaloric systems is highly challenging because nearly all geometries suited for efficient heat transfer are prone to buckling even under modest loads. This work describes a concept of a novel composite, where an active NiTi layer is embedded into a polymer support structure such that the elastocaloric material is entirely in compression when the assembly is subjected to bending. The active layer achieves 8.1 K temperature change at 2.5% compressive strain without buckling. After 10,000 cycles at 2% compressive strain, the composite maintains mechanical integrity without degradation of the elastocaloric effect. The results demonstrate that NiTi and, potentially, other elastocalorically active materials in geometries previously thought impossible can be successfully implemented in regenerative cooling systems operating in compression.

42 ENGINEERING↗

Integrated System Health Management: Pilot Operational Implementation in a Rocket Engine Test Stand

This paper describes a credible implementation of integrated system health management (ISHM) capability, as a pilot operational system. Important core elements that make possible fielding and evolution of ISHM capability have been validated in a rocket engine test stand, encompassing all phases of operation: stand-by, pre-test, test, and post-test. The core elements include an architecture (hardware/software) for ISHM, gateways for streaming real-time data from the data acquisition system into the ISHM system, automated configuration management employing transducer electronic data sheets (TEDS?s) adhering to the IEEE 1451.4 Standard for Smart Sensors and Actuators, broadcasting and capture of sensor measurements and health information adhering to the IEEE 1451.1 Standard for Smart Sensors and Actuators, user interfaces for management of redlines/bluelines, and establishment of a health assessment database system (HADS) and browser for extensive post-test analysis. The ISHM system was installed in the Test Control Room, where test operators were exposed to the capability. All functionalities of the pilot implementation were validated during testing and in post-test data streaming through the ISHM system. The implementation enabled significant improvements in awareness about the status of the test stand, and events and their causes/consequences. The architecture and software elements embody a systems engineering, knowledge-based approach; in conjunction with object-oriented environments. These qualities are permitting systematic augmentation of the capability and scaling to encompass other subsystems.

Figueroa, Fernando↗

NASA Education Recommendation Report - Education Design Team 2011

NASA people are passionate about their work. NASA's missions are exciting to learners of all ages. And since its creation in 1958, NASA's people have been passionate about sharing their inspiring discoveries, research and exploration with students and educators. In May 2010, NASA administration chartered an Education Design Team composed of 12 members chosen from the Office of Education, NASA's Mission Directorates and Centers for their depth of knowledge and education expertise, and directed them to evaluate the Agency's program in the context of current trends in education. By improving NASA's educational offerings, he was confident that the Agency can play a leading role in inspiring student interest in science, technology, engineering and mathematics (STEM) as few other organizations can. Through its unique workforce, facilities, research and innovations, NASA can expand its efforts to engage underserved and underrepresented communities in science and mathematics. Through the Agency's STEM education efforts and science and exploration missions, NASA can help the United States successfully compete, prosper and be secure in the 21st century global community. After several months of intense effort, including meeting with education experts; reviewing Administration policies, congressional direction and education research; and seeking input from those passionate about education at NASA, the Education Design Team made six recommendations to improve the impact of NASA's Education Program: (1) Focus the NASA Education Program to improve its impact on areas of greatest national need (2) Identify and strategically manage NASA Education partnerships (3) Participate in National and State STEM Education policy discussions (4) Establish a structure to allow the Office of Education, Centers and Mission Directorates to implement a strategically integrated portfolio (5) Expand the charter of the Education Coordinating Committee to enable deliberate Education Program design (6) Improve communication to inspire learners

Pengra, Trish↗