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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 649 records · Page 36
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Simulation Studies for an Urban Air Mobility Aircraft using Hardware-In-Loop Experiments

Urban Air Mobility seeks to transport passengers, deliver cargo, and provide emergency medical transportation in major metropolitan areas. This will be accomplished with distributed electric powered vertical takeoff and landing aircraft vehicles. The low specific energy of the current generation lithium-ion battery packs limit the operational range of the electric aircraft. Limited range impacts safety by reducing the amount of time available for analyzing the potential impact of errors and failures and responding to them, and for flying to an alternative landing area or returning to the base. It is therefore critical to understand the impact of flight and environmental conditions on the onboard lithium-ion battery pack’s health. With this as the motivation, the procedure for evaluating the performance of battery packs in a laboratory setting and the results obtained using this procedure on battery packs subject to power draw characteristics of a simulated flight of a NASA conceptual quadrotor aircraft model are described. The fully charged battery is allowed to discharge at specific C-rates based on the power draw profile during the experiment, and the current and voltages are recorded as a function of time. Observed results under different operating conditions and mission profiles are discussed.

UAM↗
NASA NTRSDate not supplied

Supportability Concepts for Crewed Deep Space Exploration

Supportability—defined as the set of system characteristics that influence the logistics and support required to enable safe and effective operations—will be a much larger driver of mass, risk, and crew time for future human space exploration due to the more challenging mission context. For Mars, systems must operate in a logistically isolated environment for much longer durations than previous missions, which results in a higher probability of system failure and therefore an increased need for maintenance or contingency options. Mars missions also lack access to quick aborts, which increases the consequences of an unrecoverable system failure. Together, this higher likelihood and consequence of failure results in an increase in supportability-related risk. Supportability analysis is an important part of systems development that helps designers better understand the impacts of system and mission decisions on risk, mass, and crew time. The real-world processes that drive maintenance requirements and other supportability-related characteristics are probabilistic, and therefore they require different conceptual approaches and models than are used for more deterministic aspects of space systems. This paper provides an overview of supportability analysis, addresses key concepts, and provides examples of how supportability analysis can be incorporated into system development. Specifically, system supportability involves stochastic processes, and therefore must be evaluated using probabilistic models. These models can be used to perform sensitivity analysis even if system characteristics are not yet fully defined. Failure rates cannot be measured directly, but tests provide valuable data that can help refine those estimates. Human spaceflight architectures are complex, and exhibit coupled behavior that should be examined with integrated systems analysis that includes an assessment of supportability.

Supportability↗
NASA NTRSDate not supplied

Supportability Concepts for Crewed Deep Space Exploration

Supportability—defined as the set of system characteristics that influence the logistics and support required to enable safe and effective operations—will be a much larger driver of mass, risk, and crew time for future human space exploration due to the more challenging mission context. For Mars, systems must operate in a logistically isolated environment for much longer durations than previous missions, which results in a higher probability of system failure and therefore an increased need for maintenance or contingency options. Mars missions also lack access to quick aborts, which increases the consequences of an unrecoverable system failure. Together, this higher likelihood and consequence of failure results in an increase in supportability-related risk. Supportability analysis is an important part of systems development that helps designers better understand the impacts of system and mission decisions on risk, mass, and crew time. The real-world processes that drive maintenance requirements and other supportability-related characteristics are probabilistic, and therefore they require different conceptual approaches and models than are used for more deterministic aspects of space systems. This paper provides an overview of supportability analysis, addresses key concepts, and provides examples of how supportability analysis can be incorporated into system development. Specifically, system supportability involves stochastic processes, and therefore must be evaluated using probabilistic models. These models can be used to perform sensitivity analysis even if system characteristics are not yet fully defined. Failure rates cannot be measured directly, but tests provide valuable data that can help refine those estimates. Human spaceflight architectures are complex, and exhibit coupled behavior that should be examined with integrated systems analysis that includes an assessment of supportability.

Supportability↗
NASA NTRS2024

Sizing and Performance Analysis of a MW-Class Electrified Aircraft Propulsion (EAP) System for a Parallel Hybrid Turboprop Concept

Aircraft electrification has emerged as a pivotal research and development focus in the 21st century, gaining international momentum as a strategic approach to curtail fuel consumption and emissions in the civil aviation sector. Through the Electrified Powertrain Flight Demonstration (EPFD) project, NASA is collaborating with industry partners to develop and demonstrate Megawatt (MW) class Electrified Aircraft Propulsion (EAP) systems using regional turboprops, as well as single-aisle commercial transports. With the rapid emergence of novel EAP concepts, current efforts are focused on developing the capabilities to evaluate the impacts of electrification on vehicle-level performance. This requires parametric modeling at the conceptual design stage, using uncertainty propagation techniques to account for the high variability in EAP system architecture. This paper details an integrated approach to parametric sizing of multi-MW EAP systems in a large turboprop freighter concept with a parallel hybrid configuration. The primary goal is to assess vehicle-level performance sensitivities, such as range and fuel burn reduction, to variations in electrical system component-level performance metrics, including specific power, efficiency, and energy density, based on near-term EAP technology levels.

electrified aircraft propulsion↗
NASA NTRS1988

A flexible computer aid for conceptual design based on constraint propagation and component-modeling

The Rubber Airplane program, which combines two symbolic processing techniques with a component-based database of design knowledge, is proposed as a computer aid for conceptual design. Using object-oriented programming, programs are organized around the objects and behavior to be simulated, and using constraint propagation, declarative statements designate mathematical relationships among all the equation variables. It is found that the additional level of organizational structure resulting from the arrangement of the design information in terms of design components provides greater flexibility and convenience.

Kolb, Mark A.↗
NASA NTRS1994

Computer-aided operations engineering with integrated models of systems and operations

CONFIG 3 is a prototype software tool that supports integrated conceptual design evaluation from early in the product life cycle, by supporting isolated or integrated modeling, simulation, and analysis of the function, structure, behavior, failures and operation of system designs. Integration and reuse of models is supported in an object-oriented environment providing capabilities for graph analysis and discrete event simulation. Integration is supported among diverse modeling approaches (component view, configuration or flow path view, and procedure view) and diverse simulation and analysis approaches. Support is provided for integrated engineering in diverse design domains, including mechanical and electro-mechanical systems, distributed computer systems, and chemical processing and transport systems. CONFIG supports abstracted qualitative and symbolic modeling, for early conceptual design. System models are component structure models with operating modes, with embedded time-related behavior models. CONFIG supports failure modeling and modeling of state or configuration changes that result in dynamic changes in dependencies among components. Operations and procedure models are activity structure models that interact with system models. CONFIG is designed to support evaluation of system operability, diagnosability and fault tolerance, and analysis of the development of system effects of problems over time, including faults, failures, and procedural or environmental difficulties.

Malin, Jane T.↗
NASA NTRS1997

Meta-Modeling: A Knowledge-Based Approach to Facilitating Model Construction and Reuse

In this paper, we introduce a new modeling approach called meta-modeling and illustrate its practical applicability to the construction of physically-based ecosystem process models. As a critical adjunct to modeling codes meta-modeling requires explicit specification of certain background information related to the construction and conceptual underpinnings of a model. This information formalizes the heretofore tacit relationship between the mathematical modeling code and the underlying real-world phenomena being investigated, and gives insight into the process by which the model was constructed. We show how the explicit availability of such information can make models more understandable and reusable and less subject to misinterpretation. In particular, background information enables potential users to better interpret an implemented ecosystem model without direct assistance from the model author. Additionally, we show how the discipline involved in specifying background information leads to improved management of model complexity and fewer implementation errors. We illustrate the meta-modeling approach in the context of the Scientists' Intelligent Graphical Modeling Assistant (SIGMA) a new model construction environment. As the user constructs a model using SIGMA the system adds appropriate background information that ties the executable model to the underlying physical phenomena under investigation. Not only does this information improve the understandability of the final model it also serves to reduce the overall time and programming expertise necessary to initially build and subsequently modify models. Furthermore, SIGMA's use of background knowledge helps eliminate coding errors resulting from scientific and dimensional inconsistencies that are otherwise difficult to avoid when building complex models. As a. demonstration of SIGMA's utility, the system was used to reimplement and extend a well-known forest ecosystem dynamics model: Forest-BGC.

Keller, Richard M.↗
NASA NTRS1987

A conceptual framework for intelligent real-time information processing

By combining artificial intelligence concepts with the human information processing model of Rasmussen, a conceptual framework was developed for real time artificial intelligence systems which provides a foundation for system organization, control and validation. The approach is based on the description of system processing terms of an abstraction hierarchy of states of knowledge. The states of knowledge are organized along one dimension which corresponds to the extent to which the concepts are expressed in terms of the system inouts or in terms of the system response. Thus organized, the useful states form a generally triangular shape with the sensors and effectors forming the lower two vertices and the full evaluated set of courses of action the apex. Within the triangle boundaries are numerous processing paths which shortcut the detailed processing, by connecting incomplete levels of analysis to partially defined responses. Shortcuts at different levels of abstraction include reflexes, sensory motor control, rule based behavior, and satisficing. This approach was used in the design of a real time tactical decision aiding system, and in defining an intelligent aiding system for transport pilots.

Schudy, Robert↗
DOE OSTI2024

Emergent temperature sensitivity of soil organic carbon driven by mineral associations

Abstract Soil organic matter decomposition and its interactions with climate depend on whether the organic matter is associated with soil minerals. However, data limitations have hindered global-scale analyses of mineral-associated and particulate soil organic carbon pools and their benchmarking in Earth system models used to estimate carbon cycle–climate feedbacks. Here we analyse observationally derived global estimates of soil carbon pools to quantify their relative proportions and compute their climatological temperature sensitivities as the decline in carbon with increasing temperature. We find that the climatological temperature sensitivity of particulate carbon is on average 28% higher than that of mineral-associated carbon, and up to 53% higher in cool climates. Moreover, the distribution of carbon between these underlying soil carbon pools drives the emergent climatological temperature sensitivity of bulk soil carbon stocks. However, global models vary widely in their predictions of soil carbon pool distributions. We show that the global proportion of model pools that are conceptually similar to mineral-protected carbon ranges from 16 to 85% across Earth system models from the Coupled Model Intercomparison Project Phase 6 and offline land models, with implications for bulk soil carbon ages and ecosystem responsiveness. To improve projections of carbon cycle–climate feedbacks, it is imperative to assess underlying soil carbon pools to accurately predict the distribution and vulnerability of soil carbon.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Validation of theory-based models for the control of plasma currents in W7-X divertor plasmas

A theory-based model for the control of plasma currents for steady-state operation in W7-X is proposed and intended for model-based plasma control. The conceptual outline implies the strength of physics-based models: it offer approaches applicable to future conditions of fusion devices or next-step machines. The application at extrapolated settings is related to the validity range of the theory model. Therefore, the predictive power of theory-based control models could be larger than for data-driven approaches and limitations can be predicted from the validity range for the prediction of bootstrap currents in W7-X. The model predicts the L/R response when density or heating power is changed. The model is based on neoclassical bootstrap current calculations and validated for different discharge conditions. While the model was found to be broadly applicable for conducted electron-cyclotron-heated discharges in W7-X, limits were found for cases when the polarization of the electron cyclotron heating was changed from X2 to O2-heating. The validity assessment attempts to quantify the potential of the derived model for model-based control in the operational space (density, heating power) of W7-X.

neoclassical modelling↗
DOE OSTI2025

Toward equitable environmental exposure modeling through convergence of data, open, and citizen sciences: an example of air pollution exposure modeling amidst increasing wildfire smoke

Exposure modeling is critical in environmental epidemiology and human health but may face challenges (e.g., skewed data, unequal error, context-insensitive validation, and computational demands). Modeling decisions reflect the intended use of the models and the values that modelers prioritize. We aimed to provide a conceptual framework and machine learning (ML) modeling protocols that address these issues. With 500m-gridded hourly PM 2.5 and O 3 levels in Illinois before, during, and after the 2023 Canadian wildfire season as a motivating example, we conducted modeling experiments to evaluate modeling methods, guided by three domains we propose based on theories of science: 1) Data Diversity, leveraging open and citizen science data to enhance inclusivity, parsimony, and representativeness; 2) Equitable Accuracy, ensuring fairly distributed uncertainties across subpopulations; and 3) Sustainable Modeling, balancing accuracy with reducing computational demands to promote accessibility for under-resourced researchers. Here, we found that ML with publicly available data can achieve high accuracy. Depending on methods, performance may vary substantially, even with identical input data. Large but skewed data may reduce performance. Misuse of cross-validation protocols can underestimate prediction error; although we observed R 2 s of ∼98 %, the modeled estimates varied significantly, indicating the need for careful model validation. By using new modeling protocols including representativeness-considered training and validation data and a new loss function, we achieved high agreement between estimates and ground-based measurements (e.g., R 2 = ∼90 % for PM 2.5 ; ∼80 % for O 3 ), equally distributed errors across sociodemographic strata and urban–rural divides, and reduction in computation time—from several weeks or months to a few days.

Exposure assessment↗
NASA NTRS1990

Designing a training tool for imaging mental models

The training process can be conceptualized as the student acquiring an evolutionary sequence of classification-problem solving mental models. For example a physician learns (1) classification systems for patient symptoms, diagnostic procedures, diseases, and therapeutic interventions and (2) interrelationships among these classifications (e.g., how to use diagnostic procedures to collect data about a patient's symptoms in order to identify the disease so that therapeutic measures can be taken. This project developed functional specifications for a computer-based tool, Mental Link, that allows the evaluative imaging of such mental models. The fundamental design approach underlying this representational medium is traversal of virtual cognition space. Typically intangible cognitive entities and links among them are visible as a three-dimensional web that represents a knowledge structure. The tool has a high degree of flexibility and customizability to allow extension to other types of uses, such a front-end to an intelligent tutoring system, knowledge base, hypermedia system, or semantic network.

Dede, Christopher J.↗
DOE OSTI2020

Iodine Waste Form Corrosion: PNNL Summary Testing Report

A test method to correlate the laboratory corrosion behavior of iodine-containing waste forms (IWFs) to a conceptual long-term corrosion models is required. Several candidate methods have been evaluated previously, and each method presents unique challenges and limitations. Dynamic leach tests have emerged as the preferred candidate test method to evaluate IWFs and parameterize an eventual long-term corrosion model. This report was prepared in support of this effort to define the test suite to evaluate the corrosion of IWFs, with the goal of defining and parameterizing a conceptual long-term corrosion model. A review was presented highlighting the high degree of variability between the IWF corrosion data that is available in the literature and the need for a standardized test suite. The targeted test suite is composed of a single interval screening test, a dynamic leach test, and post-test solid characterization of the monolithic IWF samples. The data presented serves two purposes: to expand the range of IWFs evaluated with the test suite to assess method variability and to further understand the corrosion of IWFs to best inform conceptual long-term corrosion model development. A series of IWF types were included in the testing, including hot isostatically pressed Ag-mordenite, silver functionalized silica-based aerogels, iodosodalites (hot isostatic pressing, sintered, glass bonded ceramic), iodoapatite, tellurite glass and glass composite materials.

42 ENGINEERING↗
NASA NTRS1996

Geometric Model for a Parametric Study of the Blended-Wing-Body Airplane

A parametric model is presented for the blended-wing-body airplane, one concept being proposed for the next generation of large subsonic transports. The model is defined in terms of a small set of parameters which facilitates analysis and optimization during the conceptual design process. The model is generated from a preliminary CAD geometry. From this geometry, airfoil cross sections are cut at selected locations and fitted with analytic curves. The airfoils are then used as boundaries for surfaces defined as the solution of partial differential equations. Both the airfoil curves and the surfaces are generated with free parameters selected to give a good representation of the original geometry. The original surface is compared with the parametric model, and solutions of the Euler equations for compressible flow are computed for both geometries. The parametric model is a good approximation of the CAD model and the computed solutions are qualitatively similar. An optimal NURBS approximation is constructed and can be used by a CAD model for further refinement or modification of the original geometry.

Mastin, C. Wayne↗
NASA NTRS1999

UML and Model Checking

UML use cases conceptually identify function points or major requirements that a software system must satisfy. Sequence diagrams expand each use case to show in temporal sequence a more detailed notion of intended system behavior.

UML Model Checking software system real-time inter↗
NASA NTRS2009

Decomposition of the Mean Squared Error and NSE Performance Criteria: Implications for Improving Hydrological Modelling

The mean squared error (MSE) and the related normalization, the Nash-Sutcliffe efficiency (NSE), are the two criteria most widely used for calibration and evaluation of hydrological models with observed data. Here, we present a diagnostically interesting decomposition of NSE (and hence MSE), which facilitates analysis of the relative importance of its different components in the context of hydrological modelling, and show how model calibration problems can arise due to interactions among these components. The analysis is illustrated by calibrating a simple conceptual precipitation-runoff model to daily data for a number of Austrian basins having a broad range of hydro-meteorological characteristics. Evaluation of the results clearly demonstrates the problems that can be associated with any calibration based on the NSE (or MSE) criterion. While we propose and test an alternative criterion that can help to reduce model calibration problems, the primary purpose of this study is not to present an improved measure of model performance. Instead, we seek to show that there are systematic problems inherent with any optimization based on formulations related to the MSE. The analysis and results have implications to the manner in which we calibrate and evaluate environmental models; we discuss these and suggest possible ways forward that may move us towards an improved and diagnostically meaningful approach to model performance evaluation and identification.

Gupta, Hoshin V.↗