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Results for “Qualitative representation”

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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

A CFD Framework for Film Boiling and Quenching in Cryogenic Chilldown

Tests of cryogenic chilldown in a vertical stainless-steel tube are simulated using computational fluid dynamics (CFD). Subcooled liquid nitrogen enters a room-temperature tube at one end, resulting in film boiling and eventual quenching of the tube walls. A CFDbased modeling framework employing the mixture multiphase model was developed to simulate this chilldown process and was applied to validate it against experimental data. Extensive sensitivity studies have been performed to create a consistent modeling framework, and a range of test conditions are simulated to assess the modeling capability. The importance of the rewetting temperature and its relation to the foam limit temperature is discussed and considered in the CFD framework. The presented results demonstrate a qualitatively consistent representation of the film boiling and quenching regime. However, the quantitative accuracy of the simulations varies with the test conditions. In addition, simulated distributions of the vapor volume fraction are presented, but the current lack of experimental volume fraction data prevents comparisons.

Computational Fluid Dynamics↗
NASA NTRS1987

Qualitative and temporal reasoning in engine behavior analysis

Numerical simulation models, engine experts, and experimental data are used to generate qualitative and temporal representations of abnormal engine behavior. Engine parameters monitored during operation are used to generate qualitative and temporal representations of actual engine behavior. Similarities between the representations of failure scenarios and the actual engine behavior are used to diagnose fault conditions which have already occurred, or are about to occur; to increase the surveillance by the monitoring system of relevant engine parameters; and to predict likely future engine behavior.

Dietz, W. E.↗
DOE OSTI2022

Qualitative trend analysis based on a mixed-integer representation

Shape constrained spline fitting is a useful method to impose prior knowledge onto flexible semi-parametric models during parameter estimation. Most typically, the function shape is imposed through order restrictions on the regression coefficients. The intended shape is considered known or selected based on heuristic rules. In this study, we present a method to estimate the optimal set of order restrictions to segment a univariate data series into episodes with distinct shapes. This is also known as the qualitative trend analysis (QTA) problem. The obtained solution uses a trade-off between lack-of-fit and model complexity. Further, our practical implementation takes inspiration from the generalized order restricted information criterion (GORIC) for inequality-constrained model selection. From this, one learns (a) that QTA can be formulated as a mixed-integer quadratic program (MIQP) and (b) that the newly proposed mixed order restricted information criterion (MORIC) enables optimal segmentation. This is illustrated through didactic case studies.

42 ENGINEERING↗
NASA NTRS1981

Stereographic observations from geosynchronous satellites - An important new tool for the atmospheric sciences

Observations of cloud geometry using scan-synchronized stereo geostationary satellites having images with horizontal spatial resolution of approximately 0.5 km, and temporal resolution of up to 3 min are presented. The stereo does not require a cloud with known emissivity to be in equilibrium with an atmosphere with a known vertical temperature profile. It is shown that absolute accuracies of about 0.5 km are possible. Qualitative and quantitative representations of atmospheric dynamics were shown by remapping, display, and stereo image analysis on an interactive computer/imaging system. Applications of stereo observations include: (1) cloud top height contours of severe thunderstorms and hurricanes, (2) cloud top and base height estimates for cloud-wind height assignment, (3) cloud growth measurements for severe thunderstorm over-shooting towers, (4) atmospheric temperature from stereo heights and infrared cloud top temperatures, and (5) cloud emissivity estimation. Recommendations are given for future improvements in stereo observations, including a third GOES satellite, operational scan synchronization of all GOES satellites and better resolution sensors.

Hasler, A. F.↗
NASA NTRS1988

A design and implementation methodology for diagnostic systems

A methodology for design and implementation of diagnostic systems is presented. Also discussed are the advantages of embedding a diagnostic system in a host system environment. The methodology utilizes an architecture for diagnostic system development that is hierarchical and makes use of object-oriented representation techniques. Additionally, qualitative models are used to describe the host system components and their behavior. The methodology architecture includes a diagnostic engine that utilizes a combination of heuristic knowledge to control the sequence of diagnostic reasoning. The methodology provides an integrated approach to development of diagnostic system requirements that is more rigorous than standard systems engineering techniques. The advantages of using this methodology during various life cycle phases of the host systems (e.g., National Aerospace Plane (NASP)) include: the capability to analyze diagnostic instrumentation requirements during the host system design phase, a ready software architecture for implementation of diagnostics in the host system, and the opportunity to analyze instrumentation for failure coverage in safety critical host system operations.

Williams, Linda J. F.↗
DOE OSTI2021

Latent map Gaussian processes for mixed variable metamodeling

Gaussian processes (GPs) are ubiquitously used in sciences and engineering as metamodels. Standard GPs, however, can only handle numerical or quantitative variables. Here we introduce latent map Gaussian processes (LMGPs) that inherit the attractive properties of GPs and are also applicable to mixed data which have both quantitative and qualitative inputs. The core idea behind LMGPs is to learn a continuous, low-dimensional latent space or manifold which encodes all qualitative inputs. To learn this manifold, we first assign a unique prior vector representation to each combination of qualitative inputs. We then use a low-rank linear map to project these priors on a manifold that characterizes the posterior representations. As the posteriors are quantitative, they can be directly used in any standard correlation function such as the Gaussian or Matern. Hence, the optimal map and the corresponding manifold, along with other hyperparameters of the correlation function, can be systematically learned via maximum likelihood estimation. Through a wide range of analytic and real-world examples, we demonstrate the advantages of LMGPs over state-of-the-art methods in terms of accuracy and versatility. In particular, we show that LMGPs can handle variable-length inputs, have an explainable neural network interpretation, and provide insights into how qualitative inputs affect the response or interact with each other. We also employ LMGPs in Bayesian optimization and illustrate that they can discover optimal compound compositions more efficiently than conventional methods that convert compositions to qualitative variables via manual featurization.

42 ENGINEERING↗
DOE OSTI2025

Cartesian equivariant representations for learning and understanding molecular orbitals

Qualitative and quantitative orbital properties such as bonding/antibonding character, localization, and orbital energies are critical to how chemists understand reactivity, catalysis, and excited-state behavior. Despite this, representations of orbitals in deep learning models have been very underdeveloped relative to representations of molecular geometries and Hamiltonians. Here, we apply state-of-the-art equivariant deep learning architectures to the task of assigning global labels to orbitals, namely energies characterizations, given the molecular coefficients from Hartree–Fock or density functional theory. The architecture we have developed, the Cartesian Equivariant Orbital Network (CEONET), shows how molecular orbital coefficients are readily featurized as equivariant node features common to all graph-based machine-learned potentials. We find that CEONET performs well at predicting difficult quantitative labels such as the orbital energy and orbital entropy. Furthermore, we find that the CEONET representation provides an intuitive latent space for differentiating orbital character for the qualitative assignment of e.g. bonding or antibonding character. In addition to providing a useful representation for further integrating deep learning with electronic structure theory, we expect CEONET to be useful for automatizing and interpreting the results of advanced electronic structure methods such as complete active space self-consistent field theory. In particular, the ability of CEONET to infer multireference character via the orbital entropy paves the way toward the machine-learned selection of active spaces.

chemical reactions↗
NASA NTRS1985

Viscoplastic constitutive relationships with dependence on thermomechanical history

Experimental evidence of thermomechanical history dependence in the cyclic hardening behavior of some common high-temperature structural alloys is presented with special emphasis on dynamic metallurgical changes. The inadequacy of formulating nonisothermal constitutive equations solely on the basis of isothermal testing is discussed. A representation of thermoviscoplasticity is proposed that qualitatively accounts for the observed hereditary behavior. This is achieved by formulating the scalar evolutionary equation in an established viscoplasticity theory to reflect thermomechanical path dependence. To assess the importance of accounting for thermomechanical history dependence in practical structural analyses, two qualitative models are specified: (1) formulated as if based entirely on isothermal information; (2) to reflect thermomechanical path dependence using the proposed thermoviscoplastic representation. Predictions of the two models are compared and the impact the calculated differences in deformation behavior may have on subsequent lifetime predictions is discussed.

Robinson, D. N.↗
NASA NTRS1992

Proceedings of the Workshop on Change of Representation and Problem Reformulation

The proceedings of the third Workshop on Change of representation and Problem Reformulation is presented. In contrast to the first two workshops, this workshop was focused on analytic or knowledge-based approaches, as opposed to statistical or empirical approaches called 'constructive induction'. The organizing committee believes that there is a potential for combining analytic and inductive approaches at a future date. However, it became apparent at the previous two workshops that the communities pursuing these different approaches are currently interested in largely non-overlapping issues. The constructive induction community has been holding its own workshops, principally in conjunction with the machine learning conference. While this workshop is more focused on analytic approaches, the organizing committee has made an effort to include more application domains. We have greatly expanded from the origins in the machine learning community. Participants in this workshop come from the full spectrum of AI application domains including planning, qualitative physics, software engineering, knowledge representation, and machine learning.

Lowry, Michael R.↗
NASA NTRS1973

A qualitative study of the complete set of solutions of the differential equation of motion of a test particle in the equatorial plane of the Kerr gravitational field

A study is made of the mathematical solution of the differential equation of motion of a test particle in the equatorial plane of the Kerr gravitational field, using S (Schwarzschild-like) coordinates. A qualitative solution of this equation leads to the conclusion that there can only be 25 different types of orbits. For each value of a, the results are presented in a master diagram for which h and e are the parameters. A master diagram divides the h, e parameter space into regions such that at each point within one of these regions the types of admissible orbits are qualitatively the same. A pictorial representation of the physical orbits in the r, phi plane is also given.

Montgomery, H. E.↗
NASA NTRS2009

Presentation Extensions of the SOAP

A set of extensions of the Satellite Orbit Analysis Program (SOAP) enables simultaneous and/or sequential presentation of information from multiple sources. SOAP is used in the aerospace community as a means of collaborative visualization and analysis of data on planned spacecraft missions. The following definitions of terms also describe the display modalities of SOAP as now extended: In SOAP terminology, View signifies an animated three-dimensional (3D) scene, two-dimensional still image, plot of numerical data, or any other visible display derived from a computational simulation or other data source; a) "Viewport" signifies a rectangular portion of a computer-display window containing a view; b) "Palette" signifies a collection of one or more viewports configured for simultaneous (split-screen) display in the same window; c) "Slide" signifies a palette with a beginning and ending time and an animation time step; and d) "Presentation" signifies a prescribed sequence of slides. For example, multiple 3D views from different locations can be crafted for simultaneous display and combined with numerical plots and other representations of data for both qualitative and quantitative analysis. The resulting sets of views can be temporally sequenced to convey visual impressions of a sequence of events for a planned mission.

Carnright, Robert↗
NASA NTRS1993

Combining qualitative and quantitative spatial and temporal information in a hierarchical structure: Approximate reasoning for plan execution monitoring

The problem of plan generation (PG) and the problem of plan execution monitoring (PEM), including updating, queries, and resource-bounded replanning, have different reasoning and representation requirements. PEM requires the integration of qualitative and quantitative information. PEM is the receiving of data about the world in which a plan or agent is executing. The problem is to quickly determine the relevance of the data, the consistency of the data with respect to the expected effects, and if execution should continue. Only spatial and temporal aspects of the plan are addressed for relevance in this work. Current temporal reasoning systems are deficient in computational aspects or expressiveness. This work presents a hybrid qualitative and quantitative system that is fully expressive in its assertion language while offering certain computational efficiencies. In order to proceed, methods incorporating approximate reasoning using hierarchies, notions of locality, constraint expansion, and absolute parameters need be used and are shown to be useful for the anytime nature of PEM.

Hoebel, Louis J.↗
NASA NTRS1985

Thermomechanical cyclic hardening behavior of Hastelloy-X

Experimental evidence of thermomechanical history dependence on the cyclic hardening behavior of a representative combustor liner material Hastelloy-X is presented, along with a discussion about the relevant concept of thermomechanical path dependence. Based on the experimental results, a discussion is given on the inadequacy of formulating nonisothermal constitutive equations solely on the basis of isothermal testing. Finally, the essence of a mathematical representation of thermoviscoplasticity is presented that qualitatively accounts for the observed hereditary behavior. This is achieved by formulating the scaler evolutionary equation in an established viscoplastic theory to reflect thermomechanical path dependence. Although the necessary nonisothermal tests for further quantifying the thermoviscoplastic model have been identified, such data are not yet available.

Bartolotta, P. A.↗
NASA NTRS1992

Transition region modeling for compressible flow

The ongoing effort at NASA Langley Research Center aimed at developing transitional zone models for Reynolds-averaged Navier-Stokes calculations is described. Results from three models that we have examined - two zero-equation models and a two-equation model of the k-omega type - are presented for high-speed flows. The use of analytical and computational tools to provide guidance and to provide the transitional flow-field data bases necessary to develop such models is discussed. Some results from validation of these tools are given; qualitative comparisons between modeled and theoretical/computational representations of the transitional zone are provided.

Chang, C.-L.↗
NASA NTRS1989

Qualitative mechanism models and the rationalization of procedures

A qualitative, cluster-based approach to the representation of hydraulic systems is described and its potential for generating and explaining procedures is demonstrated. Many ideas are formalized and implemented as part of an interactive, computer-based system. The system allows for designing, displaying, and reasoning about hydraulic systems. The interactive system has an interface consisting of three windows: a design/control window, a cluster window, and a diagnosis/plan window. A qualitative mechanism model for the ORS (Orbital Refueling System) is presented to coordinate with ongoing research on this system being conducted at NASA Ames Research Center.

Farley, Arthur M.↗
NASA NTRS1992

Using qualitative maps to direct reactive robots

The principal advantage of mobile robots is that they are able to go to specific locations to perform useful tasks rather than have the tasks brought to them. It is important therefore that the robot be used to reach desired locations efficiently and reliably. A mobile robot whose environment extends significantly beyond its sensory horizon must maintain a representation of the environment, a map, in order to attain these efficiency and reliability requirements. We believe that qualitative mapping methods provide useful and robust representation schemes and that such maps may be used to direct the actions of a reactively controlled robot. In this paper we describe our experience in employing qualitative maps to direct, through the selection of desired control strategies, a reactive-behavior based robot. This mapping capability represents the development of one aspect of a successful deliberative/reactive hybrid control architecture.

Bertin, Randolph↗
DOE OSTI2023

Use of machine learning to analyze chemistry card sort tasks

Education researchers are deeply interested in understanding the way students organize their knowledge. Card sort tasks, which require students to group concepts, are one mechanism to infer a student’s organizational strategy. However, the limited resolution of card sort tasks means they necessarily miss some of the nuance in a student’s strategy. Here in this work, we propose new machine learning strategies that leverage a potentially richer source of student thinking: free-form written language justifications associated with student sorts. Using data from a university chemistry card sort task, we use vectorized representations of language and unsupervised learning techniques to generate qualitatively interpretable clusters, which can provide unique insight in how students organize their knowledge. We compared these to machine learning analysis of the students’ sorts themselves. Machine learning-generated clusters revealed different organizational strategies than those built into the task; for example, sorts by difficulty or even discipline. There were also many more categories generated by machine learning for what we would identify as more novice-like sorts and justifications than originally built into the task, suggesting students’ organizational strategies converge when they become more expert-like. Finally, we learned that categories generated by machine learning for students’ justifications did not always match the categories for their sorts, and these cases highlight the need for future research on students’ organizational strategies, both manually and aided by machine learning. In sum, the use of machine learning to analyze results from a card sort task has helped us gain a more nuanced understanding of students’ expertise, and demonstrates a promising tool to add to existing analytic methods for card sorts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1988

A knowledge-based approach to identification and adaptation in dynamical systems control

Artificial intelligence techniques are applied to the problems of model form and parameter identification of large-scale dynamic systems. The object-oriented knowledge representation is discussed in the context of causal modeling and qualitative reasoning. Structured sets of rules are used for implementing qualitative component simulations, for catching qualitative discrepancies and quantitative bound violations, and for making reconfiguration and control decisions that affect the physical system. These decisions are executed by backward-chaining through a knowledge base of control action tasks. This approach was implemented for two examples: a triple quadrupole mass spectrometer and a two-phase thermal testbed. Results of tests with both of these systems demonstrate that the software replicates some or most of the functionality of a human operator, thereby reducing the need for a human-in-the-loop in the lower levels of control of these complex systems.

Glass, B. J.↗