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At least 487 records · Page 27

Supportability to 'Mars...and beyond'

The development of a 'front-end' Integrated Logistics Support (ILS) strategic concept and a Supportability Index Model (SIM) for incorporation into future SEI engineering efforts is discussed. The ILS objectives and support strategy are examined. The SIM mission phases, which evaluates those items determined to be the most crucial for each mission phase in terms of a measure of supportability effectiveness, are summarized and the SIM data development and initial model results are reviewed.

Thurman, Loren A.↗

National Campaign (NC)-1 Strategic Conflict Management Simulation (X4) Final Report

Urban Air Mobility (UAM) enables highly automated, cooperative, passenger or cargo-carrying air transportation services in and around urban areas. UAM is a subset of the Advanced Air Mobility (AAM) concept under development by the National Aeronautics and Space Administration (NASA), the Federal Aviation Administration (FAA), and industry. The Strategic Conflict Management (SCM) Simulation, dubbed “X4”, was conducted between July 2021 and June 2022 by NASA with the FAA and industry to evolve the Provider of Services for UAM (PSU) that will be needed to ensure initial UAM operations can scale in the National Airspace System (NAS). The FAA UAM Concept of Operations (ConOps) v1 [1] served as an initial guiding document for the X4 airspace management system design to ensure the architecture supports testing of services provided by third-party service providers. To that end, the X4 architecture leveraged concepts and technologies developed for Unmanned Aircraft System (UAS) Traffic Management (UTM) while also developing and testing new capabilities and services needed for UAM. The architecture included an initial prototype of the FAA-Industry Exchange Protocol (FIDXP), third-party services such as the PSUs, and Discovery and Synchronization Service (DSS), and other new services such as Demand-Capacity Balancing (DCB) to facilitate UAM strategic conflict management. During X4, NASA led discussions and collaborated with seven industry airspace partners to develop initial airspace management concepts for UAM that drove what would be tested and evaluated during the simulations. The initial capabilities defined for PSU leveraged UTM UAS Service Supplier (USS) as a starting point and evolved to meet UAM requirements. These discussions were also an opportunity for NASA to collaborate with industry to develop a set of initial Community-Based Rules (CBRs). These CBRs enabled how UAM traffic would be cooperatively managed among UAM operators. The collaborative, iterative process of developing CBRs with industry during X4 provided insight into the challenges involved and identified the need for a suitable and effective forum for future CBR development. In parallel with these discussions, NASA conducted a series of seven software sprints and two collaborative simulations with the airspace partners that built up in complexity. Over the course of the year, all seven partners successfully completed all the sprints by demonstrating the required capabilities. They also participated in the two collaborative simulations to demonstrate how multiple PSUs could work together in a collaborative, more complex environment with higher traffic density. The X4 simulation accomplished NASA's objectives and helped advance the development of the seven participating PSUs. The lessons learned provided insight into key elements of the UAM Notional Architecture from the FAA ConOps v1 [1] and UTM technologies when applied to UAM: - Having a Concept of Use (ConUse) defined prior to the activity would accelerate the time and effort from concept development to testing. - While the UAM Notional Architecture provided a starting point for a federated architecture that support services provided by third-party providers, the USS and PSU differed in their capability definitions for operational intent submission and sharing, conformance monitoring, airspace authorization, strategic conflict management, airspace constraints and dynamic replanning. - While existing DSS developed for UTM provided a way for PSU and other UAM services (such as DCB) to discover relevant operations from each other, additional complexity and challenges were found during X4 testing and illuminated the need for a more suitable solution for UAM. Industry can leverage the results of this demonstration to accelerate UAM requirements, CBRs, and standards development. The FAA and other government municipalities and agencies will be able to leverage results to inform future policies and identify additional gaps that require further analysis, moving toward operationalization of UAM.

Urban Air Mobility↗

SMC: SCENIC Model Control

NASAs Space Communications and Navigation (SCaN) program manages three active networks: the Near Earth Network, the Space Network, and the Deep Space Network. These networks simultaneously support NASA missions and provide communications services to customers worldwide. To efficiently manage these resources and their capabilities, a team of student interns at the NASA Glenn Research Center is developing a distributed system to model the SCaN networks. Once complete, the system shall provide a platform that enables users to perform capacity modeling of current and prospective missions with finer-grained control of information between several simulation and modeling tools. This will enable the SCaN program to access a holistic view of its networks and simulate the effects of modifications in order to provide NASA with decisional information. The development of this capacity modeling system is managed by NASAs Strategic Center for Education, Networking, Integration, and Communication (SCENIC). Three primary third-party software tools offer their unique abilities in different stages of the simulation process. MagicDraw provides UMLSysML modeling, AGIs Systems Tool Kit simulates the physical transmission parameters and de-conflicts scheduled communication, and Riverbed Modeler (formerly OPNET) simulates communication protocols and packet-based networking. SCENIC developers are building custom software extensions to integrate these components in an end-to-end space communications modeling platform. A central control module acts as the hub for report-based messaging between client wrappers. Backend databases provide information related to mission parameters and ground station configurations, while the end user defines scenario-specific attributes for the model. The eight SCENIC interns are working under the direction of their mentors to complete an initial version of this capacity modeling system during the summer of 2015. The intern team is composed of four students in Computer Science, two in Computer Engineering, one in Electrical Engineering, and one studying Space Systems Engineering.

Simulation↗

Space station evolution: Planning for the future

The need for permanently manned presence in space has been recognized by the United States and its international partners for many years. The development of this capability was delayed due to the concurrent recognition that reusable earth-to-orbit transportation was also needed and should be developed first. While the decision to go ahead with a permanently manned Space Station was on hold, requirements for the use of the Station were accumulating as ground-based research and the data from unmanned spacecraft sparked the imagination of both scientists and entrepreneurs. Thus, by the time of the Space Station implementation decision in the early 1980's, a variety of disciplines, with a variety of requirements, needed to be accommodated on one Space Station. Additional future requirements could be forecast for advanced missions that were still in the early planning stages. The logical response was the development of a multi-purpose Space Station with the ability to evolve on-orbit to new capabilities as required by user needs and national or international decisions, i.e., to build an evolutionary Space Station. Planning for evolution is conducted in parallel with the design and development of the baseline Space Station. Evolution planning is a strategic management process to facilitate change and protect future decisions. The objective is not to forecast the future, but to understand the future options and the implications of these on today's decisions. The major actions required now are: (1) the incorporation of evolution provisions (hooks and scars) in the baseline Space Station; and (2) the initiation of an evolution advanced development program.

Diaz, Alphonso V.↗

2040 Vision: A Roadmap for Integrated, Multiscale Materials and System Modeling and Simulation

Over the last few decades, advances in high-performance computing, new materials characterization methods, and, more recently, an emphasis on integrated computational materials engineering (ICME) and additive manufacturing have been a catalyst for multiscale modeling and simulation-based design of materials and structures in the aerospace industry. While these advances have driven significant progress in the development of aerospace components and systems, that progress has been limited by persistent technology and infrastructure challenges that must be overcome to realize the full potential of integrated materials and systems design and simulation modeling throughout the supply chain. As a result, NASA's Transformational Tools and Technology (TTT) Project sponsored a study (performed by a team led by Pratt & Whitney) to define the potential 25-year future state required for integrated multiscale modeling of materials and systems (e.g., load-bearing structures) to accelerate the pace and reduce the expense of innovation in future aerospace and aeronautical systems. This talk will describe the findings of this 2040 Vision study (e.g., the 2040 vision state; the required interdependent core technical work areas, Key Element (KE); associated critical gaps and actions to close those gaps; and major recommendations). This roadmap is a community consensus document and is a result of over 450 professionals input obtain via: i) four society workshops (AIAA, NAFEMS, and two TMS), ii) community-wide survey, and iii) the establishment of 9 expert panels (one per key element) consisting on average 10 non-team members from academia, government and industry to review, update content, and prioritize gaps and actions. It is NASA's hope and desire that this roadmap provides the strategic guidance to both public and private research and development decision makers to make the proposed 2040 vision state a reality and thereby provide a significant advancement in the United States global competitiveness.

Multiscale Modeling↗

Accelerating Next-Generation Cybersecurity R&D Using AI Workflows: BADGER Project Development

The Broadband Automation for Distributed Grid Efficiency and Resilience (BADGER) project aligns with national strategic priorities for integrating emerging wireless technologies and advancing AI-driven security. As critical infrastructure modernizes toward increasingly software-defined and interconnected systems, the ability to leverage 5G/NextG networks and AI-enabled control becomes essential. This report outlines work at the National Laboratory of the Rockies (NLR) to develop a NextG-native security architecture powered by AI-RAN concepts and evaluate workflows that enable efficient and reliable architectures. Together, these efforts position the laboratory to accelerate innovation while directly supporting national security and resilience objectives.

5G/6G↗

Final Technical Report

The Department of Energy is interested in technologies that support the sustainable production of fuels, chemicals, and other bioproducts from plant biomass, to offset the nation’s reliance on fossil resources. The plant cell wall of energy crops provides the largest reservoir of raw materials for bioproducts. However, the widespread use of plant cell walls is hampered by their complexity and resistance to breakdown. To improve the productivity and cost-effectiveness of using energy crops to generate bioproducts, the fundamental problem of deconstructing plant cell walls must be addressed. This project developed and evaluated an innovative genetic modification technology to produce strategically designed enzymes that specifically accumulate in the plant cell wall. The resulting enzyme-engineered energy crops are expected to grow normally under natural conditions but break down more quickly and easily under high temperature during the production of biobased products. As such, this plant cell wall targeting enzyme engineering effort will reduce the cost of plant cell wall deconstruction and ultimately improve the economics of bioproducts. The overall objective of this project is to develop and evaluate the in-planta enzyme engineering technology to reduce lignocellulose deconstruction cost. The concept was first validated using tobacco plant, a model plant system that is typically used in lab testing for initial concept validation. Then the enzyme optimization was validated using switchgrass, the energy crop to be used to produce bioproducts. There are three specific objectives in this Phase I project: (1) validate the enzyme optimization concept using tobacco plant, a model plant system. (2) validate the enzyme optimization concept using switchgrass. (3) techno-economic analysis (TEA) for further scale-up application. By the end of this project, in-planta enzyme engineering was validated in both tobacco and switchgrass plants, with improved enzyme activity and saccharification efficiency. The in-planta enzyme engineering in Tabacco didn’t have a significant impact on plant growth and development. Transgenic tobacco plants with in-planta cellulose degrading enzymes showed higher biomass digestibility than wild type. Gene construction and transformation in switchgrass was much longer than expected, which delayed the research progress. Besides, in-planta engineering of lignin degrading enzyme is more challenging than cellulose degrading enzyme, in terms of expression detection. Expression of lignin degrading enzyme and cellulose degrading enzyme improved biomass yield and saccharification efficiency of switchgrass, respectively. It is promising to express both genes in switchgrass for optimized overall performance. According to the results of TEA, switchgrass biomass production cost is mainly attributed to by fertility and harvesting. Biomass production profit can increase up to 10-fold depending on biomass price. The PHA production profit is also sensitive to the biomass price. The proposed technology could potentially reduce the biomass deconstruction cost from 33% to 9% of PHA revenue, making the biomass-based PHA competitive to petroleum-based polymers even in case of relatively high biomass price of biomass. Therefore, cultivation of the genetically engineered self-deconstruction switchgrass for Polyhydroxyalkanoate (PHA) production could benefit switchgrass grower and PHA producer with attractive profits for both sectors. This new enzyme optimization approach will be beneficial for bioindustries that use energy crops as feedstocks. It will improve the economic viability of converting energy crops to renewable products that support a sustainable society and helps address the Nation’s long-term strategic needs for renewable products and reduction of reliance on fossil resources.

42 ENGINEERING↗

The Analysis of the Contribution of Human Factors to the In-Flight Loss of Control Accidents

In-flight loss of control (LOC) is currently the leading cause of fatal accidents based on various commercial aircraft accident statistics. As the Next Generation Air Transportation System (NextGen) emerges, new contributing factors leading to LOC are anticipated. The NASA Aviation Safety Program (AvSP), along with other aviation agencies and communities are actively developing safety products to mitigate the LOC risk. This paper discusses the approach used to construct a generic integrated LOC accident framework (LOCAF) model based on a detailed review of LOC accidents over the past two decades. The LOCAF model is comprised of causal factors from the domain of human factors, aircraft system component failures, and atmospheric environment. The multiple interdependent causal factors are expressed in an Object-Oriented Bayesian belief network. In addition to predicting the likelihood of LOC accident occurrence, the system-level integrated LOCAF model is able to evaluate the impact of new safety technology products developed in AvSP. This provides valuable information to decision makers in strategizing NASA's aviation safety technology portfolio. The focus of this paper is on the analysis of human causal factors in the model, including the contributions from flight crew and maintenance workers. The Human Factors Analysis and Classification System (HFACS) taxonomy was used to develop human related causal factors. The preliminary results from the baseline LOCAF model are also presented.

Ancel, Ersin↗

Integrating in situ environmental covariates in an American lobster catch model to improve impact assessment

The installation and operation of floating offshore wind power is an integral component of societal transition to renewable energy generation where fixed bottom offshore wind is not possible. However, it will cause unique ecosystem changes. To disentangle the effects of offshore wind installations from the concurrent effects of climate change and the fishing practices on commercially significant resources, we must develop detailed characterizations of the resources before development occurs. In the Gulf of Maine, American lobster is the most commercially and culturally important fishery. At the time of writing, this is the largest fishery by value in North America. Our understanding of baseline localized parameters (such as catch per trap at the spatial scale of individual turbines) should be informed by relationships to environmental, biological, and survey-specific functional drivers of catch. A more mechanistic understanding of catch will allow for strategic adjustments to Post- Deployment fishery responses and ultimately, the development of research- and commercial-scale floating offshore wind development. Here, we used survey data from the New England Aqua Ventus Pre-Construction Commercial Trapping Survey to develop Generalized Additive Models describing seasonal catch per trap for legal and sublegal lobsters. We found fall catch to be nearly twice that of spring. Bottom temperature dynamics could be used to predict catch, and the Fall survey was associated with a warmer temperature regime. By using analytical tools that incorporate environmental heterogeneity, we developed monitoring methods from preconstruction baseline data that will be applicable over the post-construction operating period of an offshore wind farm.

BACI↗

Technology Investment Agendas to Expand Human Space Futures

The paper develops four alternative core-technology advancement specifications, one for each of the four strategic goal options for government investment in human space flight. Already discussed in the literature, these are: Explore Mars; Settle the Moon; accelerate commercial development of Space Passenger Travel; and enable industrial scale-up of Space Solar Power for Earth. In the case of the Explore Mars goal, the paper starts with the contemporary NASA accounting of ?55 Mars-enabling technologies. The analysis decomposes that technology agenda into technologies applicable only to the Explore Mars goal, versus those applicable more broadly to the other three options. Salient technology needs of all four options are then elaborated to a comparable level of detail. The comparison differentiates how technologies or major developments that may seem the same at the level of budget lines or headlines (e.g., heavy-lift Earth launch) would in fact diverge widely if developed in the service of one or another of the HSF goals. The paper concludes that the explicit choice of human space flight goal matters greatly; an expensive portfolio of challenging technologies would not only enable a particular option, it would foreclose the others. Technologies essential to enable human exploration of Mars cannot prepare interchangeably for alternative futures; they would not allow us to choose later to Settle the Moon, unleash robust growth of Space Passenger Travel industries, or help the transition to a post-petroleum future with Space Solar Power for Earth. The paper concludes that a decades-long decision in the U.S.--whether made consciously or by default--to focus technology investment toward achieving human exploration of Mars someday would effectively preclude the alternative goals in our lifetime.

human space flight↗

NASA's Physics of the Cosmos and Cosmic Origins Technology Development Programs

NASA's Physics of the Cosmos (PCOS) and Cosmic Origins (COR) Program Offices, established in 2011, reside at the NASA Goddard Space Flight Center (GSFC). The offices serve as the implementation arm for the Astrophysics Division at NASA Headquarters. We present an overview of the programs' technology development activities and technology investment portfolio, funded by NASA's Strategic Astrophysics Technology (SAT) program. We currently fund 19 technology advancements to enable future PCOS and COR missions to help answer the questions "How did our universe begin and evolve?" and "How did galaxies, stars, and planets come to be?" We discuss the process for addressing community-provided technology gaps and Technology Management Board (TMB)-vetted prioritization and investment recommendations that inform the SAT program. The process improves the transparency and relevance of our technology investments, provides the community a voice in the process, and promotes targeted external technology investments by defining needs and identifying customers. The programs' goal is to promote and support technology development needed to enable missions envisioned by the National Research Council's (NRC) "New Worlds, New Horizons in Astronomy and Astrophysics" (NWNH) Decadal Survey report [1] and the Astrophysics Implementation Plan (AIP) [2]. These include technology development for dark energy, gravitational waves, X-ray and inflation probe science, and a 4m-class UV/optical telescope to conduct imaging and spectroscopy studies, as a post-Hubble observatory with significantly improved sensitivity and capability.

Technology Management Board (TMB)↗

Crew workload-management strategies - A critical factor in system performance

This paper reviews the philosophy and goals of the NASA/USAF Strategic Behavior/Workload Management Program. The philosophical foundation of the program is based on the assumption that an improved understanding of pilot strategies will clarify the complex and inconsistent relationships observed among objective task demands and measures of system performance and pilot workload. The goals are to: (1) develop operationally relevant figures of merit for performance, (2) quantify the effects of strategic behaviors on system performance and pilot workload, (3) identify evaluation criteria for workload measures, and (4) develop methods of improving pilots' abilities to manage workload extremes.

Hart, Sandra G.↗

A Technology Plan for Enabling Commercial Space Business

The National Aeronautics and Space Administration's (NASA) Advanced Space Transportation Program is a customer driven, focused technology program that supports the NASA Strategic Plan and considers future commercial space business projections. The initial cycle of the Advanced Space Transportation Program implementation planning was conducted from December 1995 through February 1996 and represented increased NASA emphasis on broad base technology development with the goal of dramatic reductions in the cost of space transportation. The second planning cycle, conducted in January and February 1997, updated the program implementation plan based on changes in the external environment, increased maturity of advanced concept studies, and current technology assessments. The program has taken a business-like approach to technology development with a balanced portfolio of near, medium, and long-term strategic targets. Strategic targets are influenced by Earth science, space science, and exploration objectives as well as commercial space markets. Commercial space markets include those that would be enhanced by lower cost transportation as well as potential markets resulting in major increases in space business induced by reductions in transportation cost. The program plan addresses earth-to-orbit space launch, earth orbit operations and deep space systems. It also addresses all critical transportation system elements; including structures, thermal protection systems, propulsion, avionics, and operations. As these technologies are matured, integrated technology flight experiments such as the X-33 and X-34 flight demonstrator programs support near-term (one to five years) development or operational decisions. The Advanced Space Transportation Program and the flight demonstrator programs combine business planning, ground-based technology demonstrations and flight demonstrations that will permit industry and NASA to commit to revolutionary new space transportation systems beginning at the turn of the century and continuing far into the future.

Lyles, Garry M.↗

NASA Laboratory Analysis for Manned Exploration Missions

The Exploration Laboratory Analysis (ELA) project supports the Exploration Medical Capability Element under the NASA Human Research Program. ELA instrumentation is identified as an essential capability for future exploration missions to diagnose and treat evidence-based medical conditions. However, mission architecture limits the medical equipment, consumables, and procedures that will be available to treat medical conditions during human exploration missions. Allocated resources such as mass, power, volume, and crew time must be used efficiently to optimize the delivery of in-flight medical care. Although commercial instruments can provide the blood and urine based measurements required for exploration missions, these commercial-off-the-shelf devices are prohibitive for deployment in the space environment. The objective of the ELA project is to close the technology gap of current minimally invasive laboratory capabilities and analytical measurements in a manner that the mission architecture constraints impose on exploration missions. Besides micro gravity and radiation tolerances, other principal issues that generally fail to meet NASA requirements include excessive mass, volume, power and consumables, and nominal reagent shelf-life. Though manned exploration missions will not occur for nearly a decade, NASA has already taken strides towards meeting the development of ELA medical diagnostics by developing mission requirements and concepts of operations that are coupled with strategic investments and partnerships towards meeting these challenges. This paper focuses on the remote environment, its challenges, biomedical diagnostics requirements and candidate technologies that may lead to successful blood/urine chemistry and biomolecular measurements in future space exploration missions. SUMMARY The NASA Exploration Laboratory Analysis project seeks to develop capability to diagnose anticipated space exploration medical conditions on future manned missions. To achieve this goal, NASA will leverage existing point-of-care technology to provide clinical laboratory measurements in space. This approach will place the project on a path to minimize sample, reagent consumption, mass, volume and power. For successful use in the space environment, NASA specific conditions such as micro gravity and radiation, for example, will also need to be addressed.

Exploration Medical Capability↗

Resilient information and inference networks under mixed-trust sensing

With ubiquitous digitization, sensing, and computational intelligence deployed in increasingly more and broader domains, including critical infrastructure, potentially misleading and destabilizing effects of multimodal anomalies and adversarial behavior are growing in importance. Here, we develop randomized and reinforcement learning-based strategies for strategically recruiting and utilizing deployed (and, thus, vulnerable and potentially faulty and/or compromised) nodes from information and inference networks, while defending against adversaries that attempt to misguide assessments of inferred variables. Recognizing that, besides communication and other costs, sampling from any observable node can either provide true data or dangerously expose our inference to misinformation (without being easily distinguishable what actually happens), the proposed strategies proceed by progressively recruiting nodes and cautiously scaling their information contribution based on assumed, or, in our reinforcement learning approach, intelligently weighed trustworthiness, with the learning approach also considering network-wide, threat-inclusive risk/value tradeoffs. While avoiding the hardware, communication, analytical and computational burden of explicit redundancy, the proposed defensive schemes enable on-the-fly assessments of underlying processes, and system-wide situational awareness with demonstrable resilience against adversarial activities.

97 - MATHEMATICS AND COMPUTING↗

A unified catalogue-level reanalysis of stage-III cosmic shear surveys

ABSTRACT Cosmological parameter constraints from recent galaxy imaging surveys are reaching percent-level accuracy on the effective amplitude of the lensing signal, S8. The upcoming Legacy Survey of Space and Time (LSST) of the Vera C. Rubin Observatory will produce subpercent level measurements of cosmological parameters, providing a milestone test of the ΛCDM model. To supply guidance to the upcoming LSST analysis, it is important to understand thoroughly the results from different recent galaxy imaging surveys and assess their consistencies. In this work, we perform a unified catalogue-level reanalysis of three cosmic shear data sets: the first year data from the Dark Energy Survey (DES-Y1), the 1000 deg2 data set from the Kilo-Degree Survey (KiDS-1000), and the first year data from the Hyper Suprime-Cam Subaru Strategic Program (HSC-Y1). We utilize a pipeline developed and rigorously tested by the LSST Dark Energy Science Collaboration to perform the reanalysis and assess the robustness of the results to analysis choices. We find the S8 constraint to be robust to two different small-scale modelling approaches, and varying choices of cosmological priors. Our unified analysis allows the consistency of the surveys to be rigorously tested, and we find the three surveys to be statistically consistent. Due to the partially overlapping footprint, we model the cross-covariance between KiDS-1000 and HSC-Y1 approximately when combining all three data sets, resulting in a 1.6–1.9 per cent constraint on S8 given different assumptions on the cross-covariance.

79 ASTRONOMY AND ASTROPHYSICS↗

Geothermal Energy R&D: An Overview of the U.S. Department of Energy’s Geothermal Technologies Office

Geothermal energy can provide answers to many of America’s essential energy questions. The United States has tremendous geothermal resources, as illustrated by the results of the DOE GeoVision analysis, but technical and non-technical barriers have historically stood in the way of widespread deployment of geothermal energy. The U.S. Department of Energy’s Geothermal Technologies Office within the Office of Energy Efficiency and Renewable Energy has invested more than $470 million in research and development (R&D) since 2015 to meet its three strategic goals: (1) unlock the potential of enhanced geothermal systems, (2) advance technologies to increase geothermal energy on the U.S. electricity grid, and (3) support R&D to expand geothermal energy opportunities throughout the United States. Here, we describe many of those R&D initiatives and outlines future directions in geothermal research.

energy storage systems↗

Artificial Intelligence Strategy and Implementation [Slides]

LANL strategic activities for AI center on this goal: accelerate development of AI-enabled capabilities for science and security, with focus on developing and applying mission-relevant core AI technologies, creating an AI workforce pipeline and training opportunities, and building AI partnerships and community.

42 ENGINEERING↗