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At least 631 records · Page 35

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NASA NTRS2018

Aircraft Capability Management

This presentation presents an overview of work performed at NASA Ames Research Center in 2017. The work concerns the analysis of current aircraft system management displays, and the initial development of an interface for providing information about aircraft system status. The new interface proposes a shift away from current aircraft system alerting interfaces that report the status of physical components, and towards displaying the implications of degradations on mission capability. The proposed interface describes these component failures in terms of operational consequences of aircraft system degradations. The research activity was an effort to examine the utility of different representations of complex systems and operating environments to support real-time decision making of off-nominal situations. A specific focus was to develop representations that provide better integrated information to allow pilots to more easily reason about the operational consequences of the off-nominal situations. The work is also seen as a pathway to autonomy, as information is integrated and understood in a form that automated responses could be developed for the off-nominal situations in the future.

airplane capabilities↗

DOE OSTI2025

Data-driven emulation of modal aerosol microphysics via neural operator-based modeling

The complexity and the small characteristic scales of aerosol microphysical processes pose a big challenge for accurate and efficient Earth system simulations at regional and global scales. In this work, we construct and evaluate a surrogate model: the aerosol deep operator network (ADON), a physics-inspired dual-net architecture for emulating the aerosol microphysics parameterization suite in the version 2 of the Energy Earth System Model (E3SMv2). The current version of the surrogate model is trained on a dataset comprising 9.8 million samples obtained from a global E3SMv2 simulation with the horizontal resolution of about one degree under cloud-free conditions. Incorporating domain spatial and temporal coordinates, as well as principle components extracted from training data, the dual-net surrogate model effectively captures the intricate representations of aerosol and the relationship with atmospheric state variables, achieving an R-squared score over $$95.7\%$$ for all the lognormal aerosol modes in the extrapolated regime. The validated model provides feature importance of input variables and their impact on the predictive capacity of the surrogate model in relation to the E3SM. The computational cost of online inference time deployed on CPUs and GPUs with lower precisions highlights ADON’s efficiency and potential in robust predictive modeling for large-scale Earth system computations.

Bai, Zhe↗

NASA NTRS2018

Determining Thermal Capabilities for External Transfer Operations on the International Space Station

External transfers on the International Space Station (ISS) have a degree of difficulty caused by the severity of the radiative thermal environment and the complexity of the operational choreography to perform the installation and activation of the hardware. These transfers can be performed robotically, by astronauts during an Extra Vehicular Activity (EVA - spacewalk), or combination of robotic/crew operations. Robotic transfers may include capability to intermittently power the hardware; while the hardware remains unpowered for EVA operations. Robotic transfers can be staged to occur in a favorable thermal environment, though typically take longer than a transfer by crew during an EVA where the hardware may not be robotically compatible. The hardware is under passive thermal control, use of optics/multi-layer insulation/heaters, while being transferred from/to a visiting vehicle, airlock, stowage platform, or external ISS structure and may include additional design components, such as removable protective blankets, to meet the transfer requirements. Thermal analysis must be performed to determine the capability of the hardware being transferred to provide the Mission Control team the products necessary to plan and execute the operation while establishing an awareness for any contingency response. An overview of the thermal aspects in planning these types of transfer operations, the analytical approaches and assumptions, and examples of results are provided in this paper.

Thermal↗

NASA NTRS2022

NASA System-Wide Safety Wildland Firefighting Operations Workshop Report

On March 9-11, 2022, NASA’s System-Wide Safety Wildland Firefighting Operations Workshop engaged the broader wildland firefighting management ecosystem in a safety-oriented discussion via a virtual platform. This enabled a better understanding of how NASA and community expertise can be leveraged in the safe development of current and future firefighting systems and operations. The goals of the workshop were to: (1) identify and prioritize the top safety-oriented risks, gaps in capabilities, and emerging technologies to enhance wildland firefighting for both near-term and far-term concepts, with a specific focus on aviation operations and (2) engage the stakeholder community in defining emergent safety-oriented scope, roles, responsibilities, and procedures for agents undergoing increasingly complex wildland firefighting operations in information-rich, but uncertain environments. Workshop participants were solicited from wildland firefighting stakeholders across government, industry, and academia. All levels of government were engaged, as NASA sought attendees from federal, state, local, and tribal government agencies. Industry participants from traditional wildland firefighting domains such as data visualization and equipment manufacturers were invited, and corporate attendees from novel application domains such as aerial robotics and autonomous systems were present as well. The top three findings were as follows: (1) Enhancing situation awareness is a safety priority, especially in the use of aerial assets; (2) Timely access to information along with data fusion and integrated displays will enhance safety-critical decision-making both inside and outside aviation contexts; and (3) Tailorable standards and common operating pictures in the field will enhance inter-agency cooperation in the wildland firefighting lifecycle and enable the optimal use of limited resources such as aerial assets. The workshop helped inform NASA of the relevant safety-related wildland firefighting concerns and aided the broader ecosystem in understanding the potential safety-oriented role NASA might play in this community. Increased engagement with crucial governmental stakeholders (e.g., U.S. Forest Service, CAL FIRE, etc.) along with industry partners in cutting- edge information -centric domains is a fundamental next step. Additionally, the workshop findings will help define the first of a series of operationally challenging demonstrations, held in concert with strategic ecosystem partners, known as the Safety Demonstrator Series for NASA’s System-Wide Safety project. The first demonstration is set in the wildland firefighting application domain and will: (1) examine high risk operational scenarios to reduce their overall risk via services, functions or capabilities that act as risk mitigators (or transfer that risk to automated systems better able to tolerate it) and (2) explore novel tools and technologies that will enhance safety margins by enabling non-traditional or neoteric operational paradigms.

wildland firefighting↗

NASA NTRSDate not supplied

Initial Analysis of Digitally Enabled Cooperative Operations in Class D Terminal Airspace

The primary contribution of this paper is an initial analysis of integrating digitally enabled cooperative operations (or digital operations for short) with Visual Flight Rules (VFR) and Instrument Flight Rules (IFR) operations in the terminal airspace around a Class D airport, specifically around Fort Worth Alliance airport (KAFW). Enabled by connected digital technologies and automated information exchange, digital operations as envisioned would utilize cooperative practices and operator-responsible separation to ensure safety. In the present study, three conflict management configurations for digital operations were analyzed: 1) centralized with a single instance of a conflict management service to model a scenario with only one fleet operator conducting digital operations or all fleet operators utilizing the same service, 2) federated with two different instances to model a scenario with two different fleet operators conducting digital operations, and 3) fully distributed with a different instance for each digital operation. In simulations in which recorded tracks for VFR and IFR operations were played back and digital operations were modeled that would nominally arrive at KAFW once every 20 minutes (given no conflict resolution maneuvers), there were one or fewer losses of separation (LOS) across the three conflict management configurations. The same result was seen in simulations in which digital operations would nominally arrive at KAFW once every 10 minutes. However, in simulations in which digital operations would nominally arrive at KAFW once every 5 minutes, the number of LOS ranged between six and ten. This highlights the need for follow-on research to investigate the extent to which additional capabilities for digital operations, such as complexity management and/or flow organization, may be needed.

digitally enabled cooperative operations↗

DOE OSTI2023

Modeling, analysis, and optimization of complex nuclear processes and facilities via computational methods: The HALEU process case study

Improving and adapting industrial systems to timely meet changing programmatic and market demands is an important goal to achieve, including when operating and maintaining complex nuclear processes and facilities. However, changes to these complex systems are costly, particularly when they are already in place and bounded to stringent requirements and constraints such as when handling radioactive material and contaminated equipment. These conditions often exist when treating spent nuclear fuel remotely within shielded nuclear radiation chambers, commonly referred as hot cells, to condition nuclear material and/or fabricate products for utilization in other nuclear enterprises such as in the manufacture of advanced nuclear fuel. The illustrative case considered here is the production of high assay low enriched uranium (HALEU) products supporting the deployment of advanced nuclear reactors. For the HALEU program, resources invested were and are being systematically analyzed so that these investments are maximized in a facility that is nearly 60 years old. A methodology that has effectively enabled optimized and improvements in the Spent Fuel Treatment (SFT) program, and consequently the HALEU program, involves discrete event simulation as addressed in this article. Here, the quantification of multiple productivity metrics, including material processing rates, cycle times, bottlenecks, number of material transfers as well as equipment, workstation, and material handling utilization, has resulted in a myriad of diverse discoveries and data-informed decisions regarding process layout and constituent, labor levels and schedules, selection of new process units, storage needs, and other critical process configurations. This article describes such a computational capability being applied for decision-making, illustrates its application to an actual process and program, provides illustrative results, and argues how computational methods for the modeling, analysis, and optimization of complex processes and facilities does lead to informed decisions derived from data and not only from intuition.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

NASA NTRS2000

Lessons Learned on Operating and Preparing Operations for a Technology Mission from the Perspective of the Earth Observing-1 Mission

The New Millennium Program's first Earth-observing mission (EO-1) is a technology validation mission. It is managed by the NASA Goddard Space Flight Center in Greenbelt, Maryland and is scheduled for launch in the summer of 2000. The purpose of this mission is to flight-validate revolutionary technologies that will contribute to the reduction of cost and increase of capabilities for future land imaging missions. In the EO-1 mission, there are five instrument, five spacecraft, and three supporting technologies to flight-validate during a year of operations. EO-1 operations and the accompanying ground system were intended to be simple in order to maintain low operational costs. For purposes of formulating operations, it was initially modeled as a small science mission. However, it quickly evolved into a more complex mission due to the difficulties in effectively integrating all of the validation plans of the individual technologies. As a consequence, more operational support was required to confidently complete the on-orbit validation of the new technologies. This paper will outline the issues and lessons learned applicable to future technology validation missions. Examples of some of these include the following: (1) operational complexity encountered in integrating all of the validation plans into a coherent operational plan, (2) initial desire to run single shift operations subsequently growing to 6 "around-the-clock" operations, (3) managing changes in the technologies that ultimately affected operations, (4) necessity for better team communications within the project to offset the effects of change on the Ground System Developers, Operations Engineers, Integration and Test Engineers, S/C Subsystem Engineers, and Scientists, and (5) the need for a more experienced Flight Operations Team to achieve the necessary operational flexibility. The discussion will conclude by providing several cost comparisons for developing operations from previous missions to EO-1 and discuss some details that might be done differently for future technology validation missions.

Mandl, Dan↗

NASA NTRS1992

Reducing the complexity of software systems - A strategic software perspective

The results of a combined management and technical initiative aimed at reducing the size and complexity associated with developing operations planning, scheduling, and resource management software systems are presented. The initiative has produced operations concepts, functional requirements, system architectures, a comprehensive lexicon, and software tools to revolutionize the traditional software technology and development practices for planning, scheduling, and resource management systems used in space operations control centers. Examples of technology and practices to reduce complexity include a method for projecting design consequences from an operations concept, a universal architecture for heuristic algorithms, an object-oriented framework for describing large classes of problems that parametrically adapt to all domain peculiarities, the identification of general approaches which respond to changes with minimum impact on systems implementations, and a management structure for prototyping to minimize the risks of ill-conceived designs.

Hornstein, Rhoda S.↗

NASA NTRS2007

Autonomous Payload Operations Onboard the International Space Station

Operating the International Space Station (ISS) involves many complex crew tended, ground operated and combined systems. Over the life of the ISS program, it has become evident that by having automated and autonomous systems on board, more can be accomplished and at the same time reduce the workload of the crew and ground operators. Engineers at the National Aeronautics and Space Administration's (NASA) Marshall Space Flight Center in Huntsville Alabama, working in collaboration with The Charles Stark Draper Laboratory have developed an autonomous software system that uses the Timeliner User Interface Language and expert logic to continuously monitor ISS payload systems, issue commands and signal ground operators as required. This paper describes the development history of the system, its concept of operation and components. The paper also discusses the testing process as well as the facilities used to develop the system. The paper concludes with a description of future enhancement plans for use on the ISS as well as potential applications to Lunar and Mars exploration systems.

Stetson, Howard K.↗

DOE OSTI2022

Deep Learning Based Frequency Stability Assessment in Power Grid with High Renewables

Frequency stability assessment is one critical aspect of power system security assessment. Traditional N-1 screening method is based on the simulations of a few typical daily and seasonal operation scenarios. However, the increasing integration of inverter-based renewables and the retirement of conventional synchronous generators result in decreasing system inertia and growing complexity of system operating conditions. Selecting a few typical operation scenarios cannot cover all operating conditions, and the time-domain simulation of all operation conditions requires tremendous time. This paper proposes a more efficient frequency stability assessment method based on deep learning. The affinity propagation clustering algorithm is used to divide the dataset into different clusters, so the selected dataset for training can cover the diversified operating conditions as much as possible. Also, feature normalization is applied to both the training dataset and testing dataset in order to remove any unnecessary bias. Especially, trained model based on full dataset normalization has bounded error in the prediction. The case study on the reduced 240-bus WECC system demonstrates that the proposed method can predict accurate frequency nadir with limited training dataset. The deep learning model using the revised feature normalization can predict more accurate frequency nadir than that using the traditional feature normalization and has very small maximum prediction error.

affinity propagation↗

NASA NTRS2001

Robust Strategy for Rocket Engine Health Monitoring

Monitoring the health of rocket engine systems is essentially a two-phase process. The acquisition phase involves sensing physical conditions at selected locations, converting physical inputs to electrical signals, conditioning the signals as appropriate to establish scale or filter interference, and recording results in a form that is easy to interpret. The inference phase involves analysis of results from the acquisition phase, comparison of analysis results to established health measures, and assessment of health indications. A variety of analytical tools may be employed in the inference phase of health monitoring. These tools can be separated into three broad categories: statistical, rule based, and model based. Statistical methods can provide excellent comparative measures of engine operating health. They require well-characterized data from an ensemble of "typical" engines, or "golden" data from a specific test assumed to define the operating norm in order to establish reliable comparative measures. Statistical methods are generally suitable for real-time health monitoring because they do not deal with the physical complexities of engine operation. The utility of statistical methods in rocket engine health monitoring is hindered by practical limits on the quantity and quality of available data. This is due to the difficulty and high cost of data acquisition, the limited number of available test engines, and the problem of simulating flight conditions in ground test facilities. In addition, statistical methods incur a penalty for disregarding flow complexity and are therefore limited in their ability to define performance shift causality. Rule based methods infer the health state of the engine system based on comparison of individual measurements or combinations of measurements with defined health norms or rules. This does not mean that rule based methods are necessarily simple. Although binary yes-no health assessment can sometimes be established by relatively simple rules, the causality assignment needed for refined health monitoring often requires an exceptionally complex rule base involving complicated logical maps. Structuring the rule system to be clear and unambiguous can be difficult, and the expert input required to maintain a large logic network and associated rule base can be prohibitive.

Santi, L. Michael↗

NASA NTRSDate not supplied

Initial Analysis of Digitally Enabled Cooperative Operations in Class D Terminal Airspace

digitally enabled cooperative operations, digital ↗

NASA NTRSDate not supplied

Hardware-in-the-Loop Simulation of Modular Antenna Assembly

Robots are playing an increasing role in space exploration and in-space servicing. Robotic arms are good for performing in-space tasks such as modular assembly. The SPIDER arm (SPace Infrastructure Dexterous Robot) of the OSAM-1 mission represents an example of a system that can perform modular antenna assembly tasks in environmental conditions that would be dangerous for astronauts. One of the WVRTC activities is to perform independent verification and validation of the SPIDER assembly operations. Space robotic systems adopting large manipulators such as the SPIDER arm are complex to test and verify under normal 1-G conditions. Our work involves proof-of-principle testing of a hardware-inthe-loop (HIL) simulator operating in 1-g conditions, which replicates the motion of the space robot end-effector under the same geometric, kinematic and dynamic conditions, and in response to externally applied forces from its space environment. In particular, our software simulates in real-time the robot dynamics inclusive of flexibility, an important aspect in case of a long robotic arms operating in 0-G conditions. For example, the same oscillatory motions of the space manipulator’s end-effector can be mimicked on ground through our industrial manipulator, allowing us to test the feasibility of complex operation such as assembling modular components.

Robotic Assembly↗

DOE OSTI2023

Front-End Engineering Design for Carbon Capture from Shell's Deer Park Chemical Complex (Final Scientific/Technical Report)

This is the final scientific/technical report for a Front-End Engineering and Design (FEED) whose objective was to separate and capture over 820,000 tonnes per year (tpy) CO2 emissions from the commercially operated Shell Chemicals Complex located in Deer Park, Texas, USA reducing the overall facility CO2 emissions by 95% while providing energy transition jobs in a commercial area with a high concentration of refinery and chemical facilities producing CO2 emissions. The emission sources at the facility that were in scope were a total of Sixteen Furnaces – 8 OP3 furnaces and 8 OP3/HT2 Furnaces. Other minor sources were out of scope.

01 COAL, LIGNITE, AND PEAT↗

NASA NTRS2026

Hydrology Copilot: A Cloud-Native Ai System for Hydrological Data Analysis

The emergence of AI-driven Earth observation systems promises to broaden access to petabyte-scale geospatial data beyond domain specialists. However, translating this vision into operational scientific infrastructure requires addressing fundamental challenges in data virtualization, code transparency, and domain-specific reasoning. We present Hydrology Copilot, a cloud-native AI framework for natural-language-driven analysis of Earth observation data. To demonstrate operational capabilities at scale, we implement the system using NASA's North American Land Data Assimilation System version 3 (NLDAS-3), which provides surface meteorological forcing and land-surface model output across North and Central America at 1-km resolution, from which drought diagnostics are derived. The system integrates five core contributions: (1) scalable data virtualization using Kerchunk-based cloud optimized access, achieving a 1.5 to 4.6 times improvement in I/O latency across benchmark queries spanning regional single-day extractions (4.6 times speedup) to continental monthly aggregations (1.5 times speedup); (2) transparent code generation through Microsoft Azure AI Foundry agents that expose executable Python workflows for scientific verification; (3) persistent conversational memory enabling multi-turn analytical discourse across sessions; (4) intelligent query validation that enforces dataset boundaries and resolves ambiguous requests before execution; and (5) a multi-agent architecture coordinating query parsing, code generation, and visualization. We evaluate the system through drought-monitoring workflows, demonstrating reliable code generation, accurate results validated against reference computations and the operational U.S. Drought Monitor, and efficient operation across increasingly complex tasks. By bridging natural-language interfaces with rigorous hydrological analysis, Hydrology Copilot advances beyond proof-of-concept demonstrations to provide a deployable framework for operational Earth science applications.

Data virtualization↗

NASA NTRS1992

In-space assembly-servicing requirements

A method for developing the requirements for in-space assembly, servicing, and checkout of proposed Mars space transfer vehicles is discussed. Required in-space operations and functions are identified in relation to various Earth to Orbit (ETO) vehicles by looking at the manifesting options of baseline Mars Space Transfer Vehicles (STV). Each operation is then reduced to a minimum complexity state resulting in a set of operational primitive functions. These primitive functions are used to assess the trade-offs between robotic, telerobotic, and EVA operations. The study demonstrates that the complexity of the in-space operations remains stable with ETO vehicle size, and therefore the functions, and ultimately the infrastructure required to support proposed missions, are relatively unaffected by varying the ETO vehicle size within the range considered for this study.

Cockrell, Charles E.↗

NASA NTRS1993

In-space assembly-servicing requirements

A method for developing the requirements for in-space assembly, servicing, and checkout of the proposed Mars space transfer vehicles is discussed. Required in-space operations and functions are identified in relation to various Earth to Orbit (ETO) vehicles by looking at the manifesting options of baseline Mars Space Transfer Vehicles (STV). Each operation is then reduced to a minimum complexity state resulting in a set of operational primitive functions. These primitive functions are used to assess the tradeoffs between robotic, telerobotic, and EVA operations. The study demonstrates that the complexity of the in-space operations remains stable with ETO vehicle size, and therefore the functions, and ultimately the infrastructure required to support proposed missions, are relatively unaffected by varying the ETO vehicle size within the range considered for this study.

Cockrell, Charles E.↗

NASA NTRS2010

The Deep Space Network Advanced Systems Program

The deep space network (DSN)--with its three complexes in Goldstone, California, Madrid, Spain, and Canberra, Australia--provides the resources to track and communicate with planetary and deep space missions. Each complex consists of an array of capabilities for tracking probes almost anywhere in the solar system. A number of innovative hardware, software and procedural tools are used for day-to-day operations at DSN complexes as well as at the network control at the Jet Propulsion Laboratory (JPL). Systems and technologies employed by the network include large-aperture antennas (34-m and 70-m), cryogenically cooled receivers, high-power transmitters, stable frequency and timing distribution assemblies, modulation and coding schemes, spacecraft transponders, radiometric tracking techniques, etc. The DSN operates at multiple frequencies, including the 2-GHz band, the 7/8-GHz band, and the 32/34-GHz band.

tracking↗