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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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NASA NTRS1995

An Open Simulation System Model for Scientific Applications

A model for a generic and open environment for running multi-code or multi-application simulations - called the open Simulation System Model (OSSM) - is proposed and defined. This model attempts to meet the requirements of complex systems like the Numerical Propulsion Simulator System (NPSS). OSSM places no restrictions on the types of applications that can be integrated at any state of its evolution. This includes applications of different disciplines, fidelities, etc. An implementation strategy is proposed that starts with a basic prototype, and evolves over time to accommodate an increasing number of applications. Potential (standard) software is also identified which may aid in the design and implementation of the system.

Williams, Anthony D.↗

NASA NTRS2017

Mission Assurance: A Model-Based Approach

The purpose of Safety and Mission Assurance (SMA) at NASA’s Jet Propulsion Laboratory is to ensure mission safety and success. As the complexity of technical systems increases, the tools, processes, and infrastructure used to facilitate SMA activities must evolve. A transition from a document-centric approach to a data-driven, model-based architecture is critical in allowing SMA efforts to grapple with complex system designs. This work describes how a sample subset of existing SMA processes can be executed in a model-based environment, while also describing ways in which a model-based architecture can further augment SMA efforts. One key aspect is supporting the complex interplay between the different SMA processes and the systems engineering effort to provide additional insight into the system from an SMA perspective. The proposed architecture for model-based mission assurance provides an avenue for assuring mission safety and success in increasingly complex systems.

Schreiner, Samuel S.↗

NASA NTRS1993

Simulating Orbital Operations Of Spacecraft

Orbital Operations Simulator, OOS, computer program developed to implement mathematical models of complex outer-space vehicular systems and be "testbed" for new flight software. Has multi-vehicular-simulation capability to model on-orbit proximity and docking operations. Version 1.0, with its Prepare Processor and User Interface Shell designed to be true multivehicle dynamic simulator with capability to change mathematical models of spacecraft subsystems easily. Written in K & R standard C, LEX, and YACC languages and operates under System V shell.

Edwards, Carter↗

NASA NTRS2001

Multiagent Work Practice Simulation: Progress and Challenges

Modeling and simulating complex human-system interactions requires going beyond formal procedures and information flows to analyze how people interact with each other. Such work practices include conversations, modes of communication, informal assistance, impromptu meetings, workarounds, and so on. To make these social processes visible, we have developed a multiagent simulation tool, called Brahms, for modeling the activities of people belonging to multiple groups, situated in a physical environment (geographic regions, buildings, transport vehicles, etc.) consisting of tools, documents, and a computer system. We are finding many useful applications of Brahms for system requirements analysis, instruction, implementing software agents, and as a workbench for relating cognitive and social theories of human behavior. Many challenges remain for representing work practices, including modeling: memory over multiple days, scheduled activities combining physical objects, groups, and locations on a timeline (such as a Space Shuttle mission), habitat vehicles with trajectories (such as the Shuttle), agent movement in 3D space (e.g., inside the International Space Station), agent posture and line of sight, coupled movements (such as carrying objects), and learning (mimicry, forming habits, detecting repetition, etc.).

Clancey, William J.↗

NASA NTRS2002

Multiagent Work Practice Simulation: Progress and Challenges

Modeling and simulating complex human-system interactions requires going beyond formal procedures and information flows to analyze how people interact with each other. Such work practices include conversations, modes of communication, informal assistance, impromptu meetings, workarounds, and so on. To make these social processes visible, we have developed a multiagent simulation tool, called Brahms, for modeling the activities of people belonging to multiple groups, situated in a physical environment (geographic regions, buildings, transport vehicles, etc.) consisting of tools, documents, and computer systems. We are finding many useful applications of Brahms for system requirements analysis, instruction, implementing software agents, and as a workbench for relating cognitive and social theories of human behavior. Many challenges remain for representing work practices, including modeling: memory over multiple days, scheduled activities combining physical objects, groups, and locations on a timeline (such as a Space Shuttle mission), habitat vehicles with trajectories (such as the Shuttle), agent movement in 3d space (e.g., inside the International Space Station), agent posture and line of sight, coupled movements (such as carrying objects), and learning (mimicry, forming habits, detecting repetition, etc.).

Clancey, William J.↗

NASA NTRS1976

The formulation of simulation models of aeronautical systems

Recent developments in formula-manipulation compilers have led to a significant reduction in the time spent in formulating models of complex multi-degrees-of-freedom dynamical systems. MACSYMA, a computer system that can be used to perform symbolic manipulations in an interactive mode, is applied to the problem of formulating models of aeronautical systems for simulation studies. An example demonstrates that once the procedure is established, the formulation and modification of the models can be reduced to a series of routine computer operations.

Howard, J. C.↗

NASA NTRS1990

Crew workload strategies in advanced cockpits

Many methods of measuring and predicting operator workload have been developed that provide useful information in the design, evaluation, and operation of complex systems and which aid in developing models of human attention and performance. However, the relationships between such measures, imposed task demands, and measures of performance remain complex and even contradictory. It appears that we have ignored an important factor: people do not passively translate task demands into performance. Rather, they actively manage their time, resources, and effort to achieve an acceptable level of performance while maintaining a comfortable level of workload. While such adaptive, creative, and strategic behaviors are the primary reason that human operators remain an essential component of all advanced man-machine systems, they also result in individual differences in the way people respond to the same task demands and inconsistent relationships among measures. Finally, we are able to measure workload and performance, but interpreting such measures remains difficult; it is still not clear how much workload is too much or too little nor the consequences of suboptimal workload on system performance and the mental, physical, and emotional well-being of the human operators. The rationale and philosophy of a program of research developed to address these issues will be reviewed and contrasted to traditional methods of defining, measuring, and predicting human operator workload. Viewgraphs are given.

Hart, Sandra G.↗

NASA NTRS2020

Prognostics for Systems Health Management - Model and Hybrid Based Approaches. Where are We Heading?

To facilitate and solve the prediction problem, awareness of the current state and health of the system is key, since it is necessary to perform condition-based system health predictions. To accurately predict the future state of any system, it is required to possess knowledge of its current health state and future operational conditional. In case of next generation electric aircrafts, computing remaining flying time is safety-critical, since an aircraft that runs out of power (battery charge) while in the air will eventually lose control leading to catastrophe. In order to tackle and solve the prediction problem, it is essential to have awareness of the current health state of the system, especially since it is necessary to perform condition-based predictions. To be able to predict the future state of the system, it is also required to possess knowledge of the current and future operational conditions and flight profiles for accurate estimation of end-of-discharge (EOD) for the batteries. Similar framework can be implemented to other complex systems and subsystems. Our research approach is to develop a system level health monitoring safety indicator which runs estimation and prediction algorithms to estimate remaining useful life predictions at system, subsystem swell as component levels. Given models of the current and future system behavior, a general approach of model-based prognostics is discussed as a solution to the prediction problem and further for decision making. Data driven prognostics approaches have been equally used with good results in the past, where respective approaches have their own challenges to tackle. This limits their applicability to complex real-world domains: (a) high complexity or incompleteness of physics-based models and (b) limited representativeness of the training dataset for data-driven models. With the advent of internet of things for data collection and increased use of ML algorithms, hybrid approaches are the next avenue to reduce the challenges and achieve better results. An hybrid framework for fusing information from physics-based performance models along with deep learning algorithms for prognostics of complex safety critical systems is presented. In this framework, we use physics-based performance models to infer unobservable model parameters related to the system's components health solving a calibration problem.

Prognostics↗

NASA NTRS1975

Application of a new criterion for modeling systems

A new criterion is proposed for modeling systems which promises to be useful in deciding how complex a model should be. The criterion is based on the expected model response error instead of the error in fitting the data used for estimating the model parameters. The new criterion also does not require withholding data to be used exclusively for testing. There remains, however, the difficulty of testing a large number of candidate models that correspond to the combinations of terms used in the dynamic equations. A computational approach is suggested which greatly reduces the computations required in searching for the best model. In the suggested approach the gradient of the response with respect to the model coefficients is held fixed and numerous combinations of terms are assessed. After determining the most promising candidate model, the gradient is updated and the process is repeated. This procedure gives greater assurance that the best model is selected and does not rely on the analyst's judgement.

Taylor, L. W., Jr.↗

NASA NTRS2005

Uncertainty Modeling for Robustness Analysis of Control Upset Prevention and Recovery Systems

Formal robustness analysis of aircraft control upset prevention and recovery systems could play an important role in their validation and ultimate certification. Such systems (developed for failure detection, identification, and reconfiguration, as well as upset recovery) need to be evaluated over broad regions of the flight envelope and under extreme flight conditions, and should include various sources of uncertainty. However, formulation of linear fractional transformation (LFT) models for representing system uncertainty can be very difficult for complex parameter-dependent systems. This paper describes a preliminary LFT modeling software tool which uses a matrix-based computational approach that can be directly applied to parametric uncertainty problems involving multivariate matrix polynomial dependencies. Several examples are presented (including an F-16 at an extreme flight condition, a missile model, and a generic example with numerous crossproduct terms), and comparisons are given with other LFT modeling tools that are currently available. The LFT modeling method and preliminary software tool presented in this paper are shown to compare favorably with these methods.

Belcastro, Christine M.↗

NASA NTRS1979

Monitoring and decision making by people in man machine systems

The analysis of human monitoring and decision making behavior as well as its modeling are described. Classic and optimal control theoretical, monitoring models are surveyed. The relationship between attention allocation and eye movements is discussed. As an example of applications, the evaluation of predictor displays by means of the optimal control model is explained. Fault detection involving continuous signals and decision making behavior of a human operator engaged in fault diagnosis during different operation and maintenance situations are illustrated. Computer aided decision making is considered as a queueing problem. It is shown to what extent computer aids can be based on the state of human activity as measured by psychophysiological quantities. Finally, management information systems for different application areas are mentioned. The possibilities of mathematical modeling of human behavior in complex man machine systems are also critically assessed.

Johannsen, G.↗

NASA NTRSDate not supplied

Using the System Complexity Metric (SCM) to Compare CO2 Removal Systems

A fundamental cause of difficulty in large engineering projects is their inherent complexity. An impression of complexity occurs if a system is simply difficult to understand, where there is no obvious mental model that correctly predicts its behavior. Higher system complexity is usually associated with higher cost and higher failure rate. Complexity is perceived if a system has many diverse components, multiple interactions and feedback loops, transients and dynamic behavior, and unanticipated failure modes. Identifying and removing these signs of complexity should improve performance and reduce the cost and failure rate. Complexity can be directly measured by the number of components and their interactions. The System Complexity Metric (SCM) is defined as the sum of the number of parts in a system, N, plus the number of the one-way interconnections between them, I. SCM = N + I. The SCM is easily determined by direct inspection of the system block diagram. SCM can be used to compare systems and to guide their redesign to reduce cost and failure rate. Carbon dioxide removal systems are analyzed using SCM, cost, and failure rate. As in previous work, cost is directly proportional to SCM and that failure rate increases as a power of SCM for large differences in SCM. The SCM ranking of carbon dioxide removal systems is the same as their ranking in detailed analysis and practice.

Harry W. Jones↗

NASA NTRSDate not supplied

Using the System Complexity Metric (SCM) to Compare CO2 Reduction Systems

A fundamental cause of difficulty in large engineering projects is their inherent complexity. An impression of complexity occurs if a system is simply difficult to understand, where there is no obvious mental model that correctly predicts its behavior. Higher system complexity is usually associated with higher cost and higher failure rate. Complexity is perceived if a system has many diverse components, multiple interactions and feedback loops, transients and dynamic behavior, and unanticipated failure modes. Identifying and removing these signs of complexity should improve performance and reduce the cost and failure rate. Complexity can be directly measured by the number of components and their interactions. The System Complexity Metric (SCM) is defined as the sum of the number of parts in a system, N, plus the number of the one-way interconnections between them, I. SCM = N + I. The SCM is easily determined by direct inspection of the system block diagram. SCM can be used to compare systems and to guide their redesign to reduce cost and failure rate. Carbon dioxide reduction systems are analyzed using SCM, cost, and failure rate. As in previous work, cost is directly proportional to SCM and that failure rate increases as a power of SCM for large differences in SCM. The SCM ranking of carbon dioxide reduction systems is the same as their ranking in detailed analysis and practice.

Harry W. Jones↗

NASA NTRSDate not supplied

AgMIP Local, National and Global Assessments of Food System Challenges in A Changing Climate

Food systems connect a diverse network of stakeholders around the world, with complex dynamics governing production, processing, transportation, trade and consumption of food products. Extreme conditions can disrupt multiple components of the food system, with systemic connections providing structure that can both buffer and exacerbate risks. Climate change is shifting current practices in agricultural production and the broader food system, encouraging shifts toward more diverse value chains capable of drawing from multiple food producing regions to reduce the chance that an entire value chain be subject to simultaneous impacts. The IPCC Working Group I report assessed that heat waves, fires, floods and severe storms are becoming more pronounced and widespread with each degree of global warming, increasing food system risk. Food system disruptions can also come from outside the climate system, including from viral outbreaks, geopolitical conflict and socioeconomic changes. This presentation will highlight how the Agricultural Model Intercomparison and Improvement Project (AgMIP) develops modeling approaches that connect climate, biophysical and socioeconomic models in order to capture complex responses of the food system and potential interventions by diverse stakeholders in the public and private sectors. Models are applied on a range of scales that match decision contexts. These include households in specific agricultural production regions (e.g., within a country), national-level policymakers considering policies, sustainability and development priorities for a country’s agricultural sector, and global food market models that balance production and consumption around the world with competition for land, water, energy and sustainability priorities. Models are capable of capturing many important responses, but further development is needed to represent key systemic risks and the possibility for additional interventions beyond the farm gate. Improved food system models will provide important insights into our society’s ability to cope with climate change, as well as our ability to identify agricultural adaptation and mitigation opportunities to reduce overall risk.

Food systems↗

NASA NTRS2005

Achieving control and interoperability through unified model-based systems and software engineering

Control and interoperation of complex systems is one of the most difficult challenges facing NASA's Exploration Systems Mission Directorate. An integrated but diverse array of vehicles, habitats, and supporting facilities, evolving over the long course of the enterprise, must perform ever more complex tasks while moving steadily away from the sphere of ground support and intervention.

control↗

NASA NTRSDate not supplied

Noise Reduction Trajectory Analysis of a Supersonic Business Jet using Novel Optimization Tools

Proposals to reduce airport noise during takeoff and landing for supersonic aircraft using methods such as variable noise reduction systems add complexity to conceptual flight models. To better optimize these takeoff and landing profiles for noise certification, new modeling methods are explored in this paper with the end goal of more effectively determining the sensitivities of airframe, propulsion, and mission design variables on overall airport noise. Takeoff and landing trajectories are modeled for a notional supersonic business jet concept developed by NASA for use in environmental impact studies conducted by the International Civil Aviation Organization. Optimization tools capable of gradient-based optimal control and collocation solving methods are examined with the aim of achieving faster solutions in a more comprehensive design space. The benefits and limitations of these new methods are compared with existing methods used in previous studies of the airplane concept. It is found that the new modeling methods match closely when compared with existing tools for a standard takeoff and landing case, with a cumulative effective perceived noise difference of 0.1 EPNdB. Comparisons between takeoff trajectories with a variable noise reduction system match within 0.8 EPNdB and 1.3 EPNdB, due to highlighted differences in the modeling approaches.

supersonic↗

NASA NTRS2018

Evaluating the Assumptions in an Empirical Jet-Surface Interaction Noise Model

A set of empirical jet-surface interaction noise models, developed for single-stream round nozzles exhausting over a simple surface in a static ambient, are evaluated for use in more realistic applications that include multi-stream nozzle systems, multi-plane surface geometries, and a flight-stream. The simple-single-stream models have several advantages when used in system-level noise studies: they are robust, they are quickly computed, and they are generally applicable to a wide range of configurations. However, these models require simplifying assumptions when applied to more complex jet exhaust systems; for example, previous work on multi-stream jets used an empirical formula to compute a single-stream equivalent jet potential core length that could be used to predict the noise using simple-single-stream jet-surface interaction models. This paper considers the effect of flight and multi-plane surfaces using a similar approach: introducing assumptions to simplify the complex system, applying the simple-single-stream models, and evaluating the uncertainty.

Jet Noise↗

NASA NTRS2018

Evaluating the Assumptions in an Empirical Jet-Surface Interaction Noise Model

A set of empirical jet-surface interaction noise models, developed for single-stream round nozzles exhausting over a simple surface in a static ambient, are evaluated for use in more realistic applications that include multi-stream nozzle systems, multi-plane surface geometries, and a flight-steam. The simple-single-stream models have several advantages when used in system-level noise studies: they are robust, they are quickly computed, and they are generally applicable to a wide range of configurations. However, these models require simplifying assumptions when applied to more complex jet exhaust systems; for example, previous work on multi-stream jets used an empirical formula to compute a single-stream equivalent jet potential core length that could be used to predict the noise using simple-single-stream jet-surface interaction models. This paper considers the effect of flight and multi-plane surfaces using a similar approach: introducing assumptions to simplify the complex system, applying the simple-single-stream models, and evaluating the uncertainty.

Jet Noise↗