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

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At least 541 records · Page 30

Envisioning U.S. Climate Predictions and Projections to Meet New Challenges

In the face of a changing climate, the understanding, predictions, and projections of natural and human systems are increasingly crucial to prepare and cope with extremes and cascading hazards, determine unexpected feedbacks and potential tipping points, inform long-term adaptation strategies, and guide mitigation approaches. Increasingly complex socio-economic systems require enhanced predictive information to support advanced practices. Such new predictive challenges drive the need to fully capitalize on ambitious scientific and technological opportunities. These include the unrealized potential for very high-resolution modeling of global-to-local Earth system processes across timescales, reduction of model biases, enhanced integration of human systems and the Earth Systems, better quantification of predictability and uncertainties; expedited science-to-service pathways, and co-production of actionable information with stakeholders. Enabling technological opportunities include exascale computing, advanced data storage, novel observations and powerful data analytics, including artificial intelligence and machine learning. Looking to generate community discussions on how to accelerate progress on U.S. climate predictions and projections, representatives of Federally-funded U.S. modeling groups outline here perspectives on a six-pillar national approach grounded in climate science that builds on the strengths of the U.S. modeling community and agency goals. This calls for an unprecedented level of coordination to capitalize on transformative opportunities, augmenting and complementing current modeling center capabilities and plans to support agency missions. Tangible outcomes include projections with horizontal spatial resolutions finer than 10 km, representing extremes and associated risks in greater detail, reduced model errors, better predictability estimates, and more customized projections to support next generation climate services.

54 ENVIRONMENTAL SCIENCES↗

A Hybrid Dynamic/Steady-State Tool With Protection Simulation for Cascading-Outage Analysis of Extreme Events in Power Systems

The bulk electric power grid is subject to vulnerabilities from component outages, which in certain combinations (extreme events) might lead to cascading outages. Some of these outages can be severe enough to trigger brownouts and blackouts. Much is known about mitigating the first few failures near the beginning of a cascade, but there are few established methods and tools for directly analyzing the risks of cascading component outages over a longer time scale. Current power system tools have limited ability to perform detailed and accurate cascading-outage analysis, which could be computationally intensive. The Dynamic Contingency Analysis Tool (DCAT) enables power system planning engineers to more realistically assess the consequences of extreme contingencies and potential cascading events across their systems and interconnections. DCAT has several unique features: (i) detailed hybrid dynamic and steady-state analysis of power systems to mimic real-world cascading outages, (ii) detailed modeling of protection systems embedded in the dynamic simulation, (iii) simulation of corrective action after transients, (iv) simulation of islanding , and (v) high-performance computing capability to simulate a large number of contingencies in a reasonable time. DCAT outputs will help find technically sound solutions to reduce the risk of cascading outages. This paper provides details of DCAT methodology and shows its capabilities with extreme events on real-world cases.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Forecasting the Impact of an 1859-calibre Superstorm on Satellite Resources

We have assembled a database of operational satellites in orbit as of 2004, and have developed a series of simple models to assess the economic impacts to this resource caused by various scenarios of superstorm events possible during the next sunspot cycle between 2010 and 2014. Despite the apparent robustness of our satellite assets against the kinds of storms we have encountered during the satellite era, our models suggest a potential economic loss exceeding $10(exp 11) for satellite replacement and lost profitability caused by a once a century single storm similar to the 1859 superstorm. From a combination of power system and attitude control system (the most vulnerable) failures, we estimate that 80 satellites (LEO, MEO, GEO) may be disabled as a consequence of a superstorm event. Additional consequences may include the failure of many of the GPS, GLONASS and Galileo satellite systems in MEO. Approximately 98 LEO satellites that normally would not have re-entered for many decades, may prematurely de-orbit in ca 2021 as a result of the temporarily increased atmospheric drag caused by the superstorm event occurring in 2012. The $10(exp 11) International Space Station may lose at least 15 kilometers of altitude, placing it in critical need for re-boosting by an amount that is potentially outside the range of typical Space Shuttle operations during the previous solar maximum in ca 2000, and at a time when NASA plans to decommission the Space Shuttle. Several LEO satellites will unexpectedly be placed on orbits that enter the ISS zone of avoidance, requiring some action by ground personnel and ISS astronauts to avoid close encounters. Radiation effects on astronauts have also been considered and could include a range of possibilities from acute radiation sickness for astronauts inside spacecraft, to near-lethal doses during EVAs. The specifics depends very sensitively on the spectral hardness of the accompanying SPE event. Currently, the ability to forecast extreme particle events and coronal mass ejections, or predict their fluences and geo-severity in the 24-hrs prior to the event, appears to be no better than 50/50. If the events of the 1859 superstorm serve as a guide, the scope of a contemporary superstorm will most certainly be an awesome event, but one that the vast majority of our other satellite resources may reasonably be expected to survive.

Odenwald, Sten↗

Spacecraft Water Impurity Monitor, a System for Water Quality Analysis on Exploration Missions Beyond Low Earth Orbit

Exploration missions beyond low-earth-orbit (LEO) will require advanced instrumentation to monitor water quality. Traveling beyond LEO means the transfer of water samples to an Earth-based laboratory for detailed analysis is not feasible. Detailed analysis of water composition during exploration is still necessary, because having the capability to determine the specific organic chemical causing a change in total organic carbon (TOC) or the specific metal or ionic species causing a change in conductivity has the potential to inform the crew health and system management decisions. On a new vehicle such as a lunar or Mars surface habitat or a Mars transit vehicle, finding “new” impurities not seen on ISS should be expected. The key is to identify the impurity so the correct action can be taken. On ISS we can measure TOC, conductivity, and other physical properties but do not have the capability for detailed analysis using vehicle instrumentation. This is acceptable because ISS can send samples down to Earth for further analysis and obtain the detailed composition. The Spacecraft Water Impurity Monitor (SWIM) will provide detailed water quality analysis for missions in which sample down mass is not available. SWIM is a system comprising organic and inorganic analysis modules. For organic chemicals, a gas chromatograph mass spectrometer (GCMS) detects and identifies organic impurities. For inorganic species, a capillary electrophoresis capacitively coupled contactless conductivity detection (CE-C4D) system as well as ion specific electrodes detect and identify metal ions and other inorganic salts / acids. The SWIM technology demonstration project has completed a System Requirements Review (SRR) to finalize detection requirements and is currently working to refine vehicle interface requirements for a future technology demonstration. The project also has begun preliminary flight design activities for the core analyzers in the instrument suite.

Water Monitoring↗

Spacecraft Water Impurity Monitor, a System for Water Quality Analysis on Exploration Missions Beyond Low Earth Orbit

Exploration missions beyond low-earth-orbit (LEO) will require advanced instrumentation to monitor water quality. Traveling beyond LEO means the transfer of water samples to an Earth-based laboratory for detailed analysis is not feasible. Detailed analysis of water composition during exploration is still necessary, because having the capability to determine the specific organic chemical causing a change in total organic carbon (TOC) or the specific metal or ionic species causing a change in conductivity has the potential to inform the crew health and system management decisions. On a new vehicle such as a lunar or Mars surface habitat or a Mars transit vehicle, finding “new” impurities not seen on ISS should be expected. The key is to identify the impurity so the correct action can be taken. On ISS we can measure TOC, conductivity, and other physical properties but do not have the capability for detailed analysis using vehicle instrumentation. This is acceptable because ISS can send samples down to Earth for further analysis and obtain the detailed composition. The Spacecraft Water Impurity Monitor (SWIM) will provide detailed water quality analysis for missions in which sample down mass is not available. SWIM is a system comprising organic and inorganic analysis modules. For organic chemicals, a gas chromatograph mass spectrometer (GCMS) detects and identifies organic impurities. For inorganic species, a capillary electrophoresis capacitively coupled contactless conductivity detection (CE-C4D) system as well as ion specific electrodes detect and identify metal ions and other inorganic salts / acids. The SWIM technology demonstration project has completed a System Requirements Review (SRR) to finalize detection requirements and is currently working to refine vehicle interface requirements for a future technology demonstration. The project also has begun preliminary flight design activities for the core analyzers in the instrument suite.

Water Monitoring↗

Understanding and Modeling Pooled Rideshare Acceptance: Influential Factors, Preferred User Experiences, and Implications

This dissertation explores factors influencing pooled rideshare (PR) adoption to provide actionable insights for transportation network companies (TNCs) and policymakers. PR allows travelers to share rides with unknown passengers, offering benefits such as cost reduction and congestion relief. However, adoption remains limited due to safety concerns, privacy issues, and trust in rideshare platforms. A national U.S. survey with 5,385 respondents examined transportation preferences and barriers to PR adoption. Exploratory and confirmatory factor analyses identified five key factors influencing PR consideration—safety, service experience, privacy, traffic/environment, and time/cost. Second factor analyses examined ways to optimize PR experiences, revealing four factors—comfort/ease of use, convenience, vehicle technology/accessibility, and passenger safety. Privacy concerns, for instance, using regression analysis, were found to reduce the likelihood of PR adoption by 77%, and convenience had the potential to increase it by 156%. The Pooled Rideshare Acceptance Model (PRAM), based on the Technology Acceptance Model, assessed the impact of these factors using the Structural Equation Model (SEM). Privacy, safety, trust, and convenience had a large effect (Cohen's f2 > 0.35) on PR acceptance, while multigroup analyses (PRAMMA) explored 16 demographic variables such as gender, generation, and income, emphasizing the need for tailored strategies. Based on all the statistical analysis and workshops using descriptive statistics, 95 actionable recommendations were made from the riders' perspective. Findings highlight the importance of customized services, user experience improvements, and policy interventions to enhance PR adoption. This dissertation provides a roadmap for future research and policy development, ensuring evidence-based, practical strategies to improve PR services in the U.S. and beyond.

Gangadharaiah, Rakesh↗

A simulation study of active feedback supression of dynamic response in helicopter rotor blades

A parameter study is presented for active feedback control applied to a helicopter rotor blade during forward flight. The study was performed on an electromechanical apparatus which included a mechanical model rotor blade and electronic analog simulation of interaction between blade deflections and aerodynamic loading. Blade response parameters were obtained for simulated vortex impinging at the blade tip at one pulse per revolution, and for a pulse which traveled from the blade tip toward its root. Results show that the response in a 1 - 10-per-rev frequency band is diminished by the feedback action, but at the same time responses at frequencies above 10-per-rev become increasingly more prominent with increased feedback amplitude, and can even lead to instability at certain levels. It appears that the latter behavior results from limitations of the laboratory simulation apparatus, rather than genuine potential behavior for a prototype helicopter.

Kana, D. D.↗

Flare stars and solar bursts - High resolution in time and frequency

Coronal loops on the sun and nearby stars are studied using observations at 20-cm wavelength with high resolution in time and frequency. Observations of the dwarf M star AD Leonis with high time resolution led to the discovery of a quasi-periodic train of circularly polarized spikes with a mean periodicity of 32 + or - 5 ms and a total duration of 150 ms. Observations at closely spaced wavelengths using the VLA revealed a narrow-band structure in solar bursts and in the slowly varying radiation of the dwarf M star YZ Canis Minoris. This narrow-band emission may be attributed to electron-cyclotron maser radiation. Maser action at the second or first harmonic of the gyrofrequency implies magnetic field strengths of 250 and 500 G, respectively. Hence, observations with high resolution in time and frequency suggest coherent processs in the coronas of the sun and dwarf M stars. It is noted that the scientific potential suggested by the present data can be realized by the development of a solar-stellar synthesis radiotelescope. This instrument would be dedicated to solar and stellar observations with high angular, temporal, and frequency resolution.

Lang, K. R.↗

Virtual Machine Language 2.1

VML (Virtual Machine Language) is an advanced computing environment that allows spacecraft to operate using mechanisms ranging from simple, time-oriented sequencing to advanced, multicomponent reactive systems. VML has developed in four evolutionary stages. VML 0 is a core execution capability providing multi-threaded command execution, integer data types, and rudimentary branching. VML 1 added named parameterized procedures, extensive polymorphism, data typing, branching, looping issuance of commands using run-time parameters, and named global variables. VML 2 added for loops, data verification, telemetry reaction, and an open flight adaptation architecture. VML 2.1 contains major advances in control flow capabilities for executable state machines. On the resource requirements front, VML 2.1 features a reduced memory footprint in order to fit more capability into modestly sized flight processors, and endian-neutral data access for compatibility with Intel little-endian processors. Sequence packaging has been improved with object-oriented programming constructs and the use of implicit (rather than explicit) time tags on statements. Sequence event detection has been significantly enhanced with multi-variable waiting, which allows a sequence to detect and react to conditions defined by complex expressions with multiple global variables. This multi-variable waiting serves as the basis for implementing parallel rule checking, which in turn, makes possible executable state machines. The new state machine feature in VML 2.1 allows the creation of sophisticated autonomous reactive systems without the need to develop expensive flight software. Users specify named states and transitions, along with the truth conditions required, before taking transitions. Transitions with the same signal name allow separate state machines to coordinate actions: the conditions distributed across all state machines necessary to arm a particular signal are evaluated, and once found true, that signal is raised. The selected signal then causes all identically named transitions in all present state machines to be taken simultaneously. VML 2.1 has relevance to all potential space missions, both manned and unmanned. It was under consideration for use on Orion.

Riedel, Joseph E.↗

A Science-Focused Artificial Intelligence (AI) Responding in Real-Time to New Information: Capability Demonstration for Ocean World Missions

Introduction: Artificial intelligence (AI) has long been considered a potential mechanism to explore increasingly challenging environments, including those with extreme temperatures and pressures, limited communication capabilities, or those with demanding terrain. We posit that missions in extreme environments could deploy an onboard AI focused on science observations and goals in order to augment a traditional concept(s) of operations (ConOps). An onboard AI capability could perform functions such as data analysis in order to make high-level decisions, including prioritized data transmission for analysis by ground-based teams or autonomously-guided follow-on analyses that maximize science return. Such a capability would empower missions to respond to scientific data of interest in real-time; a mission could make observations and perform a preliminary analysis to alert ground-based scientists to an observation of interest, enabling an informed, rapid response from Earth-based teams. Enceladus Case Study for Onboard AI: We are developing an onboard AI capability for real-time telemetry response that formulates and carries-out informed decisions in service to established mission goals, enabling increased science return of a mission. We focus our AI development for use on a constellation of SmallSats orbiting Enceladus. Our Enceladus case study tests autonomous decision-making capabilities in scenarios with complex orbital dynamics, plume ejecta, extreme cold environments, power restrictions, and a requirement to maximize science return for a potential positive detection of life, while critically evaluating the potential for false positives. Telemetry includes simulated scientific data, spacecraft onboard operational data (e.g., position, velocity, and rotation), and engineering hardware performance data. Enceladus SmallSat Constellation. Our constellation includes eight SmallSat spacecraft in an 8:35 resonant orbit-based formation, leveraging Saturn’s gravitational forces to maintain stable orbits with global coverage around Enceladus. To our knowledge, we simulate the first stable configuration of multiple spacecraft in closed orbits around Enceladus, using a full ephemeris force model (Russell and Lara, 2009). Each spacecraft’s orbit will precess, causing an eastward ground track shift (from an orbiter’s perspective) of each spacecraft for each orbit. However, all spacecraft return to their original positions relative to Enceladus after eight Enceladus revolutions around Saturn. We model communication pathways between SmallSats to understand how information would need to be transmitted across the constellation to enable AI-driven decision-making and resource allocation across the fleet. Capability Demonstration. Our simulated capability demonstration inputs position, velocity, and rotation telemetry from our Enceladus-focused constellation simulations, and mass spectrometry data collected from abiotic and biotic laboratory-analog ocean world experiments (Theiling et al., 2018; Theiling, 2021; Da Poian et al., 2023). Data from these experiments are used to simulate MS measurements and different scenarios of science observations for onboard analysis performed on each of the eight spacecraft. For these demonstrations, we integrate 24 machine learning (ML) algorithms into an onboard intelligence as a ‘knowledge base’, including algorithms evaluating data quality and those predicting (with % confidence) gas composition, ocean aqueous chemistry, and whether the sample was influenced by microbial life. The onboard AI capability is designed to use the knowledge base to come to a consensus-based decision in the interpretation of the observed data in order to request additional action outside of a pre-defined ConOps. Requested actions could include e.g., prioritized downlink to Earth (for analysis by ground-based teams) or follow-on analyses performed across the constellation. The spacecraft’s intelligent onboard planner must then determine whether sufficient resources (e.g., time, power, etc.) are available and weigh the request with mission priorities. In our simulation, the constellation is able to identify potential biosignatures using onboard ML algorithms, evaluate the confidence of that prediction, and perform follow-on analyses across the fleet to confirm the detection, in order to best prepare a transmission of these data to Earth-based teams.

astrobiology↗

Pharmacology Risk Report

It seems very likely that the actions of administered drugs on crewmembers during spaceflight are different than they are on Earth, but even after more than 40 years of spaceflight experience, the answers to most questions about medication use during missions remain unanswered. Use of medications with insufficient knowledge about their actual activities may result in inadequate treatment and may even reduce performance and well-being in particular circumstances. There is evidence that this has already occurred during and immediately after spaceflights. The spaceflight pharmaceutical activity knowledge base must be improved to enable flight surgeons and crewmembers to make better decisions about using pharmaceuticals inflight. The spaceflight environment induces changes in human physiology, and these changes have been the subject of much study over the past few decades. These studies are confounded by the small number of potential subjects, as well by the inability to separate the different stressors of spaceflight (radiation exposure from microgravity, for example). In every physiological system, the details of spaceflight-induced physiological changes are not well understood. Despite this fact, crewmembers are treated with pharmaceuticals to reduce or prevent medical problems, with insufficient information as to drug function on their altered physiological systems. There are two major concerns about pharmaceutical use in the unusual environment of spaceflight. The actions of pharmaceuticals on physiology altered by a spaceflight environment are currently assumed to be the same as the actions in terrestrial use. This has yet to be established. The wide range of physiological systems altered by spaceflight and the degree of change experienced in some of them make it very likely that alterations in pharmaceutical action will be seen. As the duration of missions lengthens to include more distant exploration, it becomes more likely that problems will be encountered. Secondly, the integrity of stored pharmaceuticals must be established to ensure that adequate amounts of active compounds are available in each dose and that degradation to toxic compounds is minimized. This risk is also dependent on mission duration, since longer missions will require that drugs be stored much longer than their usual terrestrial shelf-lives.

Source record↗

Improving Efficacy and Safety of Pharmacological Treatment Through Precision Health and Pharmacogenomics

INTRODUCTION: Future spaceflight will require increased crew medical autonomy as exploration class missions expand in duration and distance from Earth, especially for Mars missions. As mission duration increases, it will be essential to have appropriate amounts of effective medication to ensure the maintenance of crew health and performance. Conversely, mass and volume constraints will become more severe as future spaceflight expands beyond low Earth orbit, where resupply is difficult or becomes impossible. These constraints thus convey an urgency to tailor medications for individual crewmembers and further examine appropriate dosing regimens. BACKGROUND: Precision Health is an exciting area of medicine focused on maintaining an individual’s health and performance through in-depth understanding of an individual’s unique clinical and environmental history, genetic makeup, and molecular profiles. This approach can be adapted to better predict, monitor, and address physiological responses to the spaceflight environment. A subset of this field is pharmacogenomics (PGX), the study of how the expressed genome impacts drug responses with the goal of prescribing the right dose of the right drug at the right time. Specifically, PGX testing provides valuable information on an individual’s precise allelic variations to guide physicians in making informed decisions on drug choice and dosing to avoid adverse events and maximize efficacy. The study goal was to identify which current space pharmacy drugs could be evaluated using PGX testing and to understand the potential impact on the health and wellness of the astronaut population. Additionally, we sought to evaluate clinically available FDA-approved PGX testing solutions to better understand its applicability. METHODS: A complete list of drugs on the ISS was analyzed for risk and likelihood of drug failure and PGX actionability. This analysis encompassed both astronauts’ personal medications, including supplements and over the counter drugs (n=151) contained in the ISS medical accessory kit (IMAK), and ISS MedKit formulary medications (n=95). Duplicate medications and different formulations were removed, which resulted in a total of 157 drugs used in the subsequent analysis. A 5x5 risk assessment table was produced by examining the likelihood of drug failure compared to the consequence of drug failure (LxC). Likelihood of individual drug failure was defined by whether existing processes are sufficient to prevent ineffective treatment or impactful side effect events, as ranked from 1 (very low, can easily be prevented) to 5 (very high, cannot be prevented) during a Mars mission. In contrast, the consequence of drug failure was defined by impact to safety, schedule, cost, or technical criteria and ranked from 1 (very low) to 5 (very high). An assessment of PGX reference laboratories is currently underway to evaluate sample requirements, benefit analysis (cost vs. utility of allele variant analysis), relevance to inflight medication usage, quality of reporting in enabling clinical application, and ease of integration into electronic medical records. RESULTS: Risk assessments (LxC 5x5 table) indicated 128 medications were in the green zone where risk is acceptable, with the remaining 29 of the medications in the yellow or red zone driven predominantly due to drug failure or safety concerns. We found that current PGX testing results could impact 21% of the total medications in the ISS MedKit and IMAK; of these, 9 medications currently have direct clinically actionable guidance available. Results of the clinical PGX solution evaluations as related to these medications will be presented. CONCLUSION: PGX testing has demonstrated clear benefits in terrestrial medicine and clinical environments for the selection of proper medications, avoiding adverse drug reactions, and maximizing drug efficacy. We propose that similar benefits would be bestowed on the astronaut and commercial spaceflight passenger population by performing preemptive preflight PGX testing to reduce risk of mission failure due to ineffective or toxic medications, improve drug efficacy, and further open the door to countermeasure research. For example, PGX results could allow tailoring of specific medications at optimal doses more precisely to each individual astronaut, particularly in areas of space motion sickness, sleep aids, and analgesics. An additional benefit is that PGX results could provide information for better planning of the components of a space pharmacy for deep space missions to be more effective and efficient in the utilization of limited pharmaceutical resources. Finally, while PGX testing of the astronaut corps is not currently conducted, this approach could provide immediate impact in support of mission success by reducing risks, optimizing astronaut performance, and providing valuable insights into long-term astronaut health. Such advancements in clinical decision making are important next steps in building dynamic individual risk profiles for astronauts, increasing selection of the best treatment choice, and providing tailored countermeasures for individual crewmembers.

Pharmacogenomics↗

Northwest Colorado Local Energy Analysis: October 2025 Results

The U.S. Department of Energy's (DOE) Communities Local Energy Action Program (Communities LEAP) provided customized technical assistance to the Northwest Colorado region to assist in developing strategies that facilitate long-term economic benefits through locally driven energy planning and development. The region sought technical assistance to model alternatives energy projects in response to the expected retirement of coal-fired powers plant and associated coal mines by 2030. Northwest Colorado faces a potential economic gap due to the loss of tax revenue, labor income, and jobs within the region due to the impending closure of the Craig and Hayden Power Stations and related mining operations at Trapper and Colowyo mines.

08 HYDROGEN↗

Agent Based Modeling of Air Carrier Behavior for Evaluation of Technology Equipage and Adoption

As part of ongoing research, the National Aeronautics and Space Administration (NASA) and LMI developed a research framework to assist policymakers in identifying impacts on the U.S. air transportation system (ATS) of potential policies and technology related to the implementation of the Next Generation Air Transportation System (NextGen). This framework, called the Air Transportation System Evolutionary Simulation (ATS-EVOS), integrates multiple models into a single process flow to best simulate responses by U.S. commercial airlines and other ATS stakeholders to NextGen-related policies, and in turn, how those responses impact the ATS. Development of this framework required NASA and LMI to create an agent-based model of airline and passenger behavior. This Airline Evolutionary Simulation (AIRLINE-EVOS) models airline decisions about tactical airfare and schedule adjustments, and strategic decisions related to fleet assignments, market prices, and equipage. AIRLINE-EVOS models its own heterogeneous population of passenger agents that interact with airlines; this interaction allows the model to simulate the cycle of action-reaction as airlines compete with each other and engage passengers. We validated a baseline configuration of AIRLINE-EVOS against Airline Origin and Destination Survey (DB1B) data and subject matter expert opinion, and we verified the ATS-EVOS framework and agent behavior logic through scenario-based experiments. These experiments demonstrated AIRLINE-EVOS's capabilities in responding to an input price shock in fuel prices, and to equipage challenges in a series of analyses based on potential incentive policies for best equipped best served, optimal-wind routing, and traffic management initiative exemption concepts..

Horio, Brant M.↗

Current NASA space station planning

Design considerations, trials, and actions both taken and necessary in the future which lead to the establishment of a space station by NASA are reviewed. Human performance on board Skylab demonstrated the feasibility and benefits of continuous operation of a space station. The manned orbital systems concept (MOSC) program, keeping in close contact with potential users, resulted in station requirements which included support for 720 day missions, up to four specialists per payload, 8-10 kW power, a 230 x 200 n mi altitude orbit, orbit change capability of 28.5 deg, all attitude orientation, and stability to within 1,100,000 g. Although the concept will not be funded, it provides a guide for incremental growth of a manned station from previously unmanned science platforms. Initiation of hardware development is projected for 1984-85. The agencies, both domestic and international, and missions for which the station will be built, are discussed.

Culbertson, P. E.↗

Direct-To Tool for En Route Controllers

This paper describes a new automation tool for en route air traffic controllers, called the Direct-To Tool. The Tool is designed to reduce the time of flight and fuel consumption for aircraft flying in en route airspace. It provides each controller with the identities of aircraft in his/her sector, which can reduce their time en route by bypassing dog-legged route segments and flying "direct to" a waypoint closer to the destination airport. The Tool uses its build-in conflict probing capability to determine if the improved route is free of conflicts with other aircraft. The Tool's graphical computer interface enables the controller to enter a direct-to clearance by a simple point and click action. Because of its low workload and convenience, this method is strongly favored by controllers The Tool has been running since January with live radar data received at NASA from the Fort Worth Air Route Traffic Control Center. For aircraft operating in the Fort Worth Center, the Tool has the potential to save in excess of 500,000 in-flight minutes per year. A provisional patent application for this Tool has been filed. A field task in planned for the last quarter of this year.

Erzberger, Heinz↗

Ice-Ridge Pile Up and the Genesis of Martian "Shorelines"

Unique geomorphologic features such as basin terraces exhibiting topographic continuity have been found within several Martian craters as shown in Viking, MOC, and THEMIS images. These features, showing similarity to terrestrial shorelines, have been mapped and cataloged with significant effort [1]. Currently, open wave action on the surface of paleolakes has been hypothesized as the geomorphologic agent responsible for the generation of these features [2]. As consequence, feature interpretations, including shorelines, wave-cut benches, and bars are, befittingly, lacustrine. Because such interpretations and their formation mechanisms have profound implications for the climate and potential biological history of Mars, confidence is crucial. The insight acquired through linked quantitative modeling of geomorphologic agents and processes is key to accurately interpreting these features. In this vein, recent studies [3,4] involving the water wave energy in theoretical open water basins on Mars show minimal erosional effects due to water waves under Martian conditions. Consequently, sub-glacial lake flattens the surface, produces a local velocity increase over the lake, and creates a deviation of the ice flow from the main flow direction [11]. These consequences of ice flow are observed at Lake Vostok, Antarctica an excellent Martian analogue [11]. Martian observations include reticulate terrain exhibiting sharp inter-connected ridges speculated to reflect the deposition and reworking of ice blocks at the periphery of ice-covered lakes throughout Hellas [12]. Our model determines to what extent ice, a terrestrial geomorphologic agent, can alter the Martian landscape. Method: We study the evolution of crater ice plugs as the formation mechanism of surface features frequently identified as shorelines. In particular, we perform model integrations involving parameters such as ice slope and purity, atmospheric pressure and temperature, crater shape and composition, and an energy balance between solar flux, geothermal flux, latent heat, and ablation. Our ultimate goal is to understand how an intracrater ice plug could create the observed shoreline features and how these

Barnhart, C. J.↗

AEGIS: Autonomous Entity Global Intelligence System for Urban Air Mobility

This paper presents a global intelligence system that synthesizes aerial vehicles’ real-time physical data, planned actions, and historical behavior into engineered data frames representing the collective state of the airspace and suitable for efficient machine learning consumption. These data frames are then learnt by a deep neural net to build a prediction model that estimates the expected evolution path of the current state, thereby identifying potential future conflicts. This approach lends itself to an automated early warning system that the aerial vehicles can implement onboard with a suitable edge computing module more efficiently and effectively than non-AI methods, and eventually take preventive or corrective measures towards self/collaborative resolution of the issues. Contrary to a centralized early warning system where all vehicles’ task-space eventually converges to a global optimum state, the presented distributed global intelligence system brings in a balance between local utility functions of each vehicle and the global operating framework. This contributes to effectively handle the potential massive scaling in urban air mobility in the near future.

Artificial Intelligence↗