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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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Multifidelity deep operator networks for data-driven and physics-informed problems

Operator learning for complex nonlinear systems is increasingly common in modeling multi-physics and multi-scale systems. However, training such high-dimensional operators requires a large amount of expensive, high-fidelity data, either from experiments or simulations. In this work, we present a composite Deep Operator Network (DeepONet) for learning using two datasets with different levels of fidelity to accurately learn complex operators when sufficient high-fidelity data is not available. Additionally, we demonstrate that the presence of low-fidelity data can improve the predictions of physics-informed learning with DeepONets. We demonstrate the new multi-fidelity training in diverse examples, including modeling of the ice-sheet dynamics of the Humboldt glacier, Greenland, using two different fidelity models and also using the same physical model at two different resolutions.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1983

Matrix differentiation formulas

A compact differentiation technique (without using indexes) is developed for scalar functions that depend on complex matrix arguments which are combined by operations of complex conjugation, transposition, addition, multiplication, matrix inversion and taking the direct product. The differentiation apparatus is developed in order to simplify the solution of extremum problems of scalar functions of matrix arguments.

Usikov, D. A.↗
NASA NTRSDate not supplied

MAGE: Alleviating Uncertainty in Real-Time Decision-Making as a Function of Problem Complexity

In this paper, we discuss a critical aspect of uncertainty in the operation of complex systems, such as the future air traffic: the ability of agents in the system to arrive at satisfactory decisions and the attendant actions as a function of problem complexity. Intuitively, when the problem complexity is manageable, given an appropriate decision problem formulation and solution tools, an agent (computational or human) has no trouble arriving at a solution that yields good outcomes for the agent and the system. Growing problem complexity results in progressively larger computational problems that may yield suboptimal solutions or even be intractable within required time limits or at all. We propose a measurable representation of complexity in terms of problem tractability and quality of solutions. We also propose a computational scheme, MAGE (Monitor, Anticipate, Guide, Evolve), for detecting approaching transitions from efficient decision-making states to inefficient to unsafe ones, so that operations based on decision-making can be reconfigured to forestall unfavorable transitions, returning to efficient modes when complexity diminishes. Maintaining tractable complexity reduces the uncertainty in the outcomes of decision-making. We describe the general scheme, an outline of MAGE applied to managing airspace complexity, and initial examples of investigating the tractability of problem-solving schemes.

complexity management↗
NASA NTRS1990

Method for concurrent execution of primitive operations by dynamically assigning operations based upon computational marked graph and availability of data

Computationally complex primitive operations of an algorithm are executed concurrently in a plurality of functional units under the control of an assignment manager. The algorithm is preferably defined as a computationally marked graph contianing data status edges (paths) corresponding to each of the data flow edges. The assignment manager assigns primitive operations to the functional units and monitors completion of the primitive operations to determine data availability using the computational marked graph of the algorithm. All data accessing of the primitive operations is performed by the functional units independently of the assignment manager.

Stoughton, John W.↗
NASA NTRS2015

SimSup's Loop: A Control Theory Approach to Spacecraft Operator Training

Immersive simulation is a staple of training for many complex system operators, including astronauts and ground operators of spacecraft. However, while much has been written about simulators, simulation facilities, and operator certification programs, the topic of how one develops simulation scenarios to train a spacecraft operator is relatively understated in the literature. In this paper, an approach is presented for using control theory as the basis for developing the immersive simulation scenarios for a spacecraft operator training program. The operator is effectively modeled as a high level controller of lower level hardware and software control loops that affect a select set of system state variables. Simulation scenarios are derived from a STAMP-based hazard analysis of the operator's high and low level control loops. The immersive simulation aspect of the overall training program is characterized by selecting a set of scenarios that expose the operator to the various inadequate control actions that stem from control flaws and inadequate control executions in the different sections of the typical control loop. Results from the application of this approach to the Lunar Atmosphere and Dust Environment Explorer (LADEE) mission are provided through an analysis of the simulation scenarios used for operator training and the actual anomalies that occurred during the mission. The simulation scenarios and inflight anomalies are mapped to specific control flaws and inadequate control executions in the different sections of the typical control loop to illustrate the characteristics of anomalies arising from the different sections of the typical control loop (and why it is important for operators to have exposure to these characteristics). Additionally, similarities between the simulation scenarios and inflight anomalies are highlighted to make the case that the simulation scenarios prepared the operators for the mission.

LADEE↗
NASA NTRS2023

Monitoring Airspace Complexity and Determining Contributing Factors

The national airspace has evolved over many years to accommodate increased traffic demand while simultaneously maintaining air travel as one of the safest forms of transportation. One of the reasons for this success is the ability of the air traffic control system and the operators to adapt and accommodate to situations that routinely disrupt normal operations. These situations may include: adverse weather, delays, early arrivals, equipment outages, and other factors that are outside the operators’ ability to control. These factors can lead to states where automation is unable to properly handle these issues, and therefore air traffic controllers and pilots have to intervene — ultimately increasing communication between operators resulting in higher workload. As controller workload increases to handle sub-optimal operating conditions, complexity increases. This is because, under these conditions humans are required to make tactical decisions in response to external factors. This results in a departure from the original strategic plan where operations would be more efficiently managed. Human operators manage airspace complexity under rigid regulations but in a constantly changing environment. The airspace is divided into sectors and the number of aircraft assigned to each controller is limited for safe handling. Some prior studies devised airspace complexity metrics in commercial aviation and related these metrics to controller workload. The upper bounds on the system load are pre-determined. Such bounds on complexity make for a safe system, but the system cannot scale and adapt to autonomous, dense, and heterogeneous traffic — including the many types of Unmanned Aerial Vehicles (UAVs) envisioned to be added to the operations. We hypothesize that, as traffic density and heterogeneity grow, and other key metrics change, there will be phase transitions at which the way traffic should be managed changes significantly. We offer a method for in-time detection of contributing factors that lead to phase transitions, characterized by increased complexity. To the best of our knowledge, there is no tool similar to ours that identifies such contributing factors or precursor patterns.

Precursor↗
NASA NTRS1975

Safety management of a complex R&D ground operating system

Report discusses safety program implementation for large R&D operating system. Analytical techniques are defined and suggested as tools for identifying potential hazards and determining means to effectively control or eliminate hazards.

Connors, J.↗
NASA NTRS2005

Cognitive Performance in Operational Environments

Optimal cognition during complex and sustained operations is a critical component for success in current and future military operations. "Cognitive Performance, Judgment, and Decision-making" (CPJD) is a newly organized U.S. Army Medical Research and Materiel Command research program focused on sustaining operational effectiveness of Future Force Warriors by developing paradigms through which militarily-relevant, higher-order cognitive performance, judgment, and decision-making can be assessed and sustained in individuals, small teams, and leaders of network-centric fighting units. CPJD evaluates the impact of stressors intrinsic to military operational environments (e.g., sleep deprivation, workload, fatigue, temperature extremes, altitude, environmental/physiological disruption) on military performance, evaluates noninvasive automated methods for monitoring and predicting cognitive performance, and investigates pharmaceutical strategies (e.g., stimulant countermeasures, hypnotics) to mitigate performance decrements. This manuscript describes the CPJD program, discusses the metrics utilized to relate militarily applied research findings to academic research, and discusses how the simulated combat capabilities of a synthetic battle laboratory may facilitate future cognitive performance research.

Russo, Michael↗
NASA NTRS1989

Design challenges for space bioreactors

The design of bioreactors for operation under conditions of microgravity presents problems and challenges. Absence of a significant body force such as gravity can have profound consequences for interfacial phenomena. Marangoni convection can no longer be overlooked. Many speculations on the advantages and benefits of microgravity can be found in the literature. Initial bioreactor research considerations for space applications had little regard for the suitability of the designs for conditions of microgravity. Bioreactors can be classified in terms of their function and type of operation. The complex interaction of parameters leading to optimal design and operation of a bioreactor is illustrated by the JSC mammalian cell culture system. The design of a bioreactor is strongly dependent upon its intended use as a production unit for cell mass and/or biologicals or as a research reactor for the study of cell growth and function. Therefore a variety of bioreactor configurations are presented in rapid summary. Following this, a rationale is presented for not attempting to derive key design parameters such as the oxygen transfer coefficient from ground-based data. A set of themes/objectives for flight experiments to develop the expertise for design of space bioreactors is then proposed for discussion. These experiments, carried out systematically, will provide a database from which engineering tools for space bioreactor design will be derived.

Seshan, P. K.↗
DOE OSTI2023

Operation Optimization Using Reinforcement Learning with Integrated Artificial Reasoning Framework

In large and complex systems, operational decision-making requires a systematic analysis with a vast amount of data from both process parameters and component status monitoring. In this paper, we present an integrated artificial reasoning approach for system state transition models that can help operational decision-making with explainable and traceable reasoning. The integrated artificial reasoning framework is a physics-based approach of defining the system structure in a Bayesian network, so we leveraged it in a Markov decision process (MDP) for finding optimal operational solutions. In our proposed framework, the MDP is implemented on a dynamic Bayesian network (DBN), which represents causalities in a system. The multilevel flow modeling was utilized in order to extract these causalities in a more efficient and objective manner. Since multilevel flow modeling is based on the fundamental energy and mass conservation laws, the target system is decomposed into several mass, energy, and information structures, which serve as the basis for a DBN. The MDP consists of the processes of finding a solution for the Bellman equation, which can be derived from the conditional probability equations of the constructed DBN. System operators can capture stochastic system dynamics as multiple subsystem state transitions based on their physical relations and uncertainties coming from the component degradation process or random failures. We analyzed a simplified example system to illustrate finding an optimal operational policy with this approach.

Kim, Junyung↗
NASA NTRSDate not supplied

Modeling Distributed Situation Awareness in Resilience-based Design of Complex Systems

Human operators play a major role in the resilience of complex systems–while human error is one of the biggest contributors to hazardous events, operators additionally play a critical role in mitigating hazardous events. A key factor underlying this operator resilience is situation awareness–the ability of operators to understand their environment and each other to achieve desired system functions. In contrast to situation awareness-related accident models in the literature, which are largely conceptual in nature, this work proposes the use of a dynamic simulation framework to concretely model both the effects of situation awareness-related human errors and situation awareness-related hazard-mitigating properties using the distributed situation awareness theory. This work then presents specialized model constructs to enable agents’ individual perceptions of the system state and transactions with other agents (and thus distributed situation awareness) to be represented in simulation. To demonstrate this framework, it is then adapted to an aircraft taxiway case study, where it is used to model aircraft conflicts due to lack of vision and poor communications from the air traffic controller. This demonstration shows the potential of using simulation models to rigorously understand situation awareness-related human errors and thus inform the design of resilience.

Resilience Modeling↗
NASA NTRS2015

Mini-Stamp as a Micro-Display for At-A-Glance Subsystem Information for DSN Links

Operators of the Deep Space Network (DSN) attend to numerous tasks with the overall goal of providing continuous support for the world's deep space missions. This high-stakes operations environment requires operators to understand the state of the Deep Space Network and predict what will happen next. Under the Follow-the-Sun initiative which requires remote operations of the highly complex telecommunications equipment, operators will need to remain aware of the state of the entire network rather than just their own facility, and transitioning fluidly between periods of low activity and periods of high demand. I designed a micro-display for operators to see, at a glance, the state of a Deep Space Network support including its subsystems. Using in-depth user-centered and participatory design techniques to identify information requirements, I designed what I called a Postage Stamp (NTR-49720) for individual operators to be able to maintain awareness of their own assigned supports. However, under Follow the Sun, operators must remain aware of all supports. The area occupied by the Postage Stamp must shrink to allow operators to see the state of the entire system, e.g., via a Big Board posted prominently in the operations room. Micro-displays are tools for mental model re-alignment, helping operators to keep their mental models of how the system works and behaves aligned with the changing state of the complex system. Data-driven micro-displays such as the Postage Stamp and Mini-Stamp display information about the system in a consistent way. Like a traffic light, the format of the micro-display never changes: the operator always knows where to look to find a specific piece of information. The Mini-Stamp always looks like the Mini-Stamp, and all of its data fields always lie in the same place on the micro-display. Real-time data flows through the Mini-Stamp to provide information to the operator.

Holloway, Alexandra↗
DOE OSTI2023

Digital Twins for Nuclear Power Plants and Facilities

The nuclear digital twin (DT) is the virtual representation of a nuclear energy system across its lifecycle. The nuclear DT uses real-time information and other data sources to improve the process of design, licensing, construction, security, O&M, decommissioning, and waste disposal. By leveraging the knowledge base and experience from the past 40 years of LWR operation, the nuclear DT is helping to accelerate the development and deployment of advanced nuclear technology in areas of passive safety, new fuel forms, instrumentation, and reactor control. For the currently operating nuclear fleet, DTs are reducing the operational risks, increasing plant availability, increasing energy capability, and reducing electricity production costs. For advanced fission and fusion reactors, DTs are being used to design for passive safety and built-in security-by-design. Rapidly deployable small modular reactor (SMR) and microreactor designs compatible with modular construction techniques and advanced manufacturing will be the new normal, reducing the need for large capital expenditures and compressing construction schedules. In addition, lower operational and maintenance costs will be realized by reducing the complexity of operations, staffing needs, and maintenance-related activities.

Kropaczek, Dave↗
NASA NTRSDate not supplied

DeepONet-Assisted Optimization of Surface Topography for Transition Delay in a Mach 4.5 Boundary Layer

We use deep learning, an ensemble variational technique (EnVar), and direct numerical simulations(DNS) to design an optimal topography for a two-dimensional roughness element that delays the on-set of laminar-turbulent transition in a Mach 4.5 flat-plate boundary layer. Deep operator networks (DeepONets), which have the known ability to learn complex nonlinear operators within dynamical systems, are used for machine learning. For the baseline configuration of a smooth flat plate, the second-mode waves at the DNS inflow cause a quick nonlinear breakdown of the high-speed boundary layer within the computational domain. Results reported in the present study validate the ability of DeepONets to model the transition delay via a given topography of the roughness element. The computing cost to optimize the rough-ness element for minimal skin-friction drag is substantially lowered by the DeepONets-based reduced-order model. In comparison to the baseline method of EnVar optimization based on DNS alone, the DeepONets-based EnVar optimizer is able to delay transition past the outflow boundary of the computational domain while utilizing almost 5–6 times fewer DNS.

Machine Learning↗
NASA NTRS1995

Mode Transitions in Glass Cockpit Aircraft: Results of a Field Study

One consequence of increased levels of automation in complex control systems is the presence of modes. A mode is a particular configuration of a control system that defines how human command inputs are interpreted. In complex systems, modes also often determine a specific allocation of control authority between the human and automated systems. Even in simple static devices (e.g., electronic watches, word processors), the presence of modes has been found to cause problems in either-the acquisition or production of skilled performance. Many of these problems arise due to the fact that the selection of a mode causes device behavior to be mediated by hidden internal state information. For these simple systems, many of these interaction problems can be solved by the design of appropriate feedback to communicate internal state information to the human operator. In complex dynamic systems, however, the design issues associated with modes seem to trancend the problem of merely communicating internal state information via displayed feedback. In complex supervisory control systems (e.g., aircraft, spacecraft, military command and control), a key function of modes is the selection of a particular configuration of control authority between the human operator and automated control systems. One mode may result in full manual control, another may result in a mix of manual and automatic control, while a third may result in full automatic control over the entire system. The human operator selects an appropriate mode as a function of current goals, operating conditions, and operating procedures. Thus, the operator is put in a position of essentially trying to control two coupled dynamic systems: the target system itself, and also a highly complex suite of automation controlling the target system. From a historical perspective, it should probably not come as a surprise that very little information is available to guide the design of mode-oriented control systems. The topic of function allocation (i.e., the proper division of control authority among human and computer) has a long history in human-machine systems research. Although this research has produced some relevant guidelines, a design approach capable of defining appropriate allocations of control function between the human and automation is not yet available. As a result, the function allocation decision itself has been allocated to the operator, to be performed in real-time, in the operation of mode-oriented control systems. A variety of documented aircraft accidents and incidents suggest that the real-time selection and monitoring of control modes is a weak link in the effective operation of complex supervisory control systems. Research in human-machine systems and human-computer interaction has barely scraped the surface of the problem of understanding how operators manage this task.The purpose of this paper is to present the results of a field study which examined how operators manage mode selection in a complex supervisory control system. Data on mode engagements using the Boeing B757/767 auto-flight system were collected during approach and descent into four major airports in the East Coast of the United States. Protocols documenting mode selection, automatic mode changes, pilot actions, quantitative records of flight-path variables, and verbal reports during and after mode engagements were collected by an observer from the jumpseat. Observations were conducted on two typical trips between three airports. Each trip was be replicated 11 times, which yielded a total of 22 trips and 66 legs on which data were collected. All data collected concerned the same flight numbers, and therefore, the same time of day, same type of aircraft, and identical operational environments (e.g., ATC facilities, weather patterns, traffic flow etc.)

Degani, Asaf↗
NASA NTRS1985

Shuttle near-field environmental impacts - Conclusions and observations for launching at other locations

Near field and far field environmental monitoring activities extending from the first launch of the Space Shuttle at the Kennedy Space Center have provided a database from which conclusions can now be drawn for short term, acute effects of launch and, to a lesser degree, long term cumulative effects on the natural environment. Data for the first 15 launches of the Space Shuttle from Kennedy Space Center Pad 39A are analyzed for statistical significance and reduced to graphical presentations of individual and collective disposition isopleths, summarization of observed environmental impacts (e.g., vegetation damage, fish kills), and supporting data from specialized experiments and laboratory analyses. Conclusions are drawn with regard to the near field environment at Pad A, the effects on the lagoonal complex, and the relationships of these data and conclusions to upcoming operations at Complex 39 Pad B where the environment is significantly different. The paper concludes with a subjective evaluation of the likely impacts at Vandenberg Space Launch Complex 6 for the first Shuttle launch next year.

Koller, A. M., Jr.↗
NASA NTRS1997

Mars Pathfinder Rover-Lewis Research Center Technology Experiments Program

An overview of NASA's Mars Pathfinder Program is given and the development and role of three technology experiments from NASA's Lewis Research Center and carried on the Mars Pathfinder rover is described. Two recent missions to Mars were developed and managed by the Jet Propulsion Laboratory, and launched late last year: Mars Global Surveyor in November 1996 and Mars Pathfinder in December 1996. Mars Global Surveyor is an orbiter which will survey the planet with a number of different instruments, and will arrive in September 1997, and Mars Pathfinder which consists of a lander and a small rover, landing on Mars July 4, 1997. These are the first two missions of the Mars Exploration Program consisting of a ten year series of small robotic martian probes to be launched every 26 months. The Pathfinder rover will perform a number of technology and operational experiments which will provide the engineering information necessary to design and operate more complex, scientifically oriented surface missions involving roving vehicles and other machinery operating in the martian environment. Because of its expertise in space power systems and technologies, space mechanisms and tribology, Lewis Research Center was asked by the Jet Propulsion Laboratory, which is heading the Mars Pathfinder Program, to contribute three experiments concerning the effects of the martian environment on surface solar power systems and the abrasive qualities of the Mars surface material. In addition, rover static charging was investigated and a static discharge system of several fine Tungsten points was developed and fixed to the rover. These experiments and current findings are described herein.

Stevenson, Steven M.↗
NASA NTRS1968

Assembly, checkout, and operation optimization analysis technique for complex systems

Computerized simulation model of a launch vehicle/ground support equipment system optimizes assembly, checkout, and operation of the system. The model is used to determine performance parameters in three phases or modes - /1/ systems optimization techniques, /2/ operation analysis methodology, and /3/ systems effectiveness analysis technique.

Source record↗