SEARCH · Search NASA

Results for “Knowledge Modeling”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 307 records · Page 17

All sources NASA NTRS DOE OSTI

NASA NTRSDate not supplied

Understanding the Impact of Unobservable Variables on the Performance of Predictive Models: The Need for Feature Space Partitioning and Fusion

When developing predictive models over a dataset, the model is globally optimized across the entire feature space to learn a decision boundary. However, when unobservable variables—which cannot be measured or estimated—interact with the observable variables, this can negatively impact the optimization applied to the decision boundary since the data samples introduced by unobservable variables may have little to no association with the applied global optimization. This, consequently, penalizes the entire decision boundary and model performance. This paper examines some of the detrimental effects of unobservable variables, particularly their role in creating new modes in the distribution of observable variables and reducing the separability of class distributions. Such challenges result in skewed or warped decision boundaries and decreased accuracy of model predictions, particularly for interpretable models like logistic regression and decision trees. Through two illustrative case examples, we highlight the need to address the challenges imposed by unobservable variables. We propose a strategy to mitigate these challenges by creating local regions within the feature space through partitioning. This enables the optimization of local models within the regions to overcome the impact of unobservability in different feature space localities. Research into a more sophisticated partitioning strategy and where the partition should be relative to the sample of interest is left as future work. Through the analysis of the impact of unobservability and the development of a partitioning method, we demonstrate the clear need for a partitioning strategy that integrates knowledge from multiple local models to estimate risk factors using information fusion. Thus, we establish the foundation and motivation for using partitioning and information fusion to overcome the effects of unobservability in predictive models. Formal fusion methods, such as Dempster-Shafer theory, can better leverage the information from local regions to improve the performance of interpretable predictive models in the presence of unobservable variables.

Time Series Data↗

NASA NTRS1998

Some Formal Aspects of Human-Machine Interaction

While automated control systems such as autopilots and medical devices are introduced at a rapid pace, it is widely recognized that user interaction with these machines is problematic (Abbott, Slotte, & Stimson, 1996). One factor commonly cited in the literature is the discrepancy between the machine's behavior and the user's expectations. Design guidelines to reduce this discrepancy focus on two elements: (1) improvement of the "feedback" about what the automation is actually doing, and (2) improvement of the user's "mental model" of the automation (Norman, 1990; Sarter and Woods, 1995). This presentation describes a methodology for investigating these two elements via a formal (Le., mathematical) approach. The method involves two representations: (1) a finite state model of the machine's behavior (2) a finite state model of the user's knowledge and expectations about the machine's behavior. In the analysis phase we compare these two models and identify discrepancies. Such discrepancies can be compensated by augmenting the display and/or the user's model. A taxonomy of these discrepancies will be discussed using examples from automated Eight control systems of modern "glass cockpit" jetliners.

Degani, Asaf↗

NASA NTRS2003

Measurement and evaluation of the radiative properties of a thin solid fuel

Accurate modeling of combustion systems requires knowledge of the radiative properties of the system. Gas phase properties are well known, but detailed knowledge of surface properties is limited. Recent work has provided spectrally resolved data for some solid fuels, but only for the unburned material at room temperature, and for limited sets of previously burned and quenched samples. Due to lack of knowledge of the spectrally resolved properties at elevated temperatures, as well as processing limitations in the modeling effort, graybody values are typically used for the fuels surface radiative properties. However, the spectrally resolved properties for the fuels at room temperature can be used to give a first-order correction for temperature effects on the graybody values. Figure 1 shows a sample of the spectrally resolved emittance/absorptance for a thin solid fuel of the type commonly used in combustion studies, from approximately 2 to 20 microns. This plot clearly shows a strong spectral dependence across the entire range. By definition, the emittance is the ratio of the emitted energy to that of a blackbody at the same temperature. Therefore, to determine a graybody emittance for this material, the spectrally resolved data must be applied to a blackbody curve. The total area under the resulting curve is ratioed to the total area under the blackbody curve to yield the answer. Due to the asymmetry of the spectrally resolved emittance and the changing shape of the blackbody curve as the temperature increases, the relative importance of the emittance value at any given wavelength will change as a function of temperature. Therefore, the graybody emittance value for a given material will change as a function of temperature even if the spectral dependence of the radiative properties remains unchanged. This is demonstrated in Figures 2 and 3, which are plots of the spectrally resolved emittance for KimWipes (shown in Figure 1) multiplied by the blackbody curves for 300 K (Figure 2) and 800 K (Figure 3). Each figure also shows the blackbody curve for that temperature. Ratioing the areas under the curve for each of these figures give a graybody emittance of 0.64 at 300 K, and 0.46 at 800 K. It is recognized that materials undergoing pyrolysis will change in composition as they heat up, and that the radiative properties of the materials may have inherent temperature dependence. Both of these effects will contribute to changes in the radiative characteristics of a given material, and are not accounted for here. However, this paper demonstrates the temperature dependence of graybody radiative properties, and provides a method for a first-order correction (for temperature) to the graybody values if the spectrally resolved properties are known.

Pettegrew, Richard↗

NASA NTRS2023

CME Propagation Through the Heliosphere: Status and Future of Observations and Model Development

The ISWAT (International Space Weather Action Teams) heliosphere clusters H1 and H2 have a focus on interplanetary space and its characteristics, especially on the large-scale co-rotating and transient structures impacting Earth. Solar wind stream interaction regions, generated by the interaction between high-speed solar wind originating in large-scale open coronal magnetic fields and slower solar wind from closed magnetic fields, are regions of compressed plasma and magnetic field followed by high-speed streams that recur at the ~27 day solar rotation period. Short-term reconfigurations of the lower coronal magnetic field generate flare emissions and provide the energy to accelerate enormous amounts of magnetised plasma and particles in the form of coronal mass ejections into interplanetary space. The dynamic interplay between these phenomena changes the configuration of interplanetary space on various temporal and spatial scales which in turn influences the propagation of individual structures. While considerable efforts have been made to model the solar wind, we outline the limitations arising from the rather large uncertainties in parameters inferred from observations that make reliable predictions of the structures impacting Earth difficult. Moreover, the increased complexity of interplanetary space as solar activity rises in cycle 25 is likely to pose a challenge to these models. Combining observational and modeling expertise will extend our knowledge of the relationship between these different phenomena and the underlying physical processes, leading to improved models and scientific understanding and more-reliable space-weather forecasting. The current paper summarizes the efforts and progress achieved in recent years, identifies open questions, and gives an outlook for the next 5–10 years. It acts as basis for updating the existing COSPAR roadmap by Schrijver et al. (2015), as well as providing a useful and practical guide for peer-users and the next generation of space weather scientists.

Space weather↗

NASA NTRS1992

Reuse: A knowledge-based approach

This paper describes our research in automating the reuse process through the use of application domain models. Application domain models are explicit formal representations of the application knowledge necessary to understand, specify, and generate application programs. Furthermore, they provide a unified repository for the operational structure, rules, policies, and constraints of a specific application area. In our approach, domain models are expressed in terms of a transaction-based meta-modeling language. This paper has described in detail the creation and maintenance of hierarchical structures. These structures are created through a process that includes reverse engineering of data models with supplementary enhancement from application experts. Source code is also reverse engineered but is not a major source of domain model instantiation at this time. In the second phase of the software synthesis process, program specifications are interactively synthesized from an instantiated domain model. These specifications are currently integrated into a manual programming process but will eventually be used to derive executable code with mechanically assisted transformations. This research is performed within the context of programming-in-the-large types of systems. Although our goals are ambitious, we are implementing the synthesis system in an incremental manner through which we can realize tangible results. The client/server architecture is capable of supporting 16 simultaneous X/Motif users and tens of thousands of attributes and classes. Domain models have been partially synthesized from five different application areas. As additional domain models are synthesized and additional knowledge is gathered, we will inevitably add to and modify our representation. However, our current experience indicates that it will scale and expand to meet our modeling needs.

Iscoe, Neil↗

NASA NTRS1995

Modeling the vestibulo-ocular reflex of the squirrel monkey during eccentric rotation and roll tilt

Model simulations of the squirrel monkey vestibulo-ocular reflex (VOR) are presented for two motion paradigms: constant velocity eccentric rotation and roll tilt about a naso-occipital axis. The model represents the implementation of three hypotheses: the "internal model" hypothesis, the "gravito-inertial force (GIF) resolution" hypothesis, and the "compensatory VOR" hypothesis. The internal model hypothesis is based on the idea that the nervous system knows the dynamics of the sensory systems and implements this knowledge as an internal dynamic model. The GIF resolution hypothesis is based on the idea that the nervous system knows that gravity minus linear acceleration equals GIF and implements this knowledge by resolving the otolith measurement of GIF into central estimates of gravity and linear acceleration, such that the central estimate of gravity minus the central estimate of acceleration equals the otolith measurement of GIF. The compensatory VOR hypothesis is based on the idea that the VOR compensates for the central estimates of angular velocity and linear velocity, which sum in a near-linear manner. During constant velocity eccentric rotation, the model correctly predicts that: (1) the peak horizontal response is greater while "facing-motion" than with "back-to-motion"; (2) the axis of eye rotation shifts toward alignment with GIF; and (3) a continuous vertical response, slow phase downward, exists prior to deceleration. The model also correctly predicts that a torsional response during the roll rotation is the only velocity response observed during roll rotations about a naso-occipital axis. The success of this model in predicting the observed experimental responses suggests that the model captures the essence of the complex sensory interactions engendered by eccentric rotation and roll tilt.

NASA Discipline Neuroscience↗

NASA NTRS1991

Design and Analysis Tools for Concurrent Blackboard Systems

A blackboard system consists of a set of knowledge sources, a blackboard data structure, and a control strategy used to activate the knowledge sources. The blackboard model of problem solving is best described by Dr. H. Penny Nii of the Stanford University AI Laboratory: "A Blackboard System can be viewed as a collection of intelligent agents who are gathered around a blackboard, looking at pieces of information written on it, thinking about the current state of the solution, and writing their conclusions on the blackboard as they generate them. " The blackboard is a centralized global data structure, often partitioned in a hierarchical manner, used to represent the problem domain. The blackboard is also used to allow inter-knowledge source communication and acts as a shared memory visible to all of the knowledge sources. A knowledge source is a highly specialized, highly independent process that takes inputs from the blackboard data structure, performs a computation, and places the results of the computation in the blackboard data structure. This design allows for an opportunistic control strategy. The opportunistic problem-solving technique allows a knowledge source to contribute towards the solution of the current problem without knowing which of the other knowledge sources will use the information. The use of opportunistic problem-solving allows the data transfers on the blackboard to determine which processes are active at a given time. Designing and developing blackboard systems is a difficult process. The designer is trying to balance several conflicting goals and achieve a high degree of concurrent knowledge source execution while maintaining both knowledge and semantic consistency on the blackboard. Blackboard systems have not attained their apparent potential because there are no established tools or methods to guide in their construction or analyze their performance.

McManus, John W.↗

NASA NTRS1992

Constraints on cosmic ray propagation in the galaxy

The goal was to derive a more detailed picture of magnetohydrodynamic turbulence in the interstellar medium and its effects on cosmic ray propagation. To do so, radio astronomical observations (scattering and Faraday rotation) were combined with knowledge of solar system spacecraft observations of MHD turbulence, simulations of wave propagation, and modeling of the galactic distribution to improve the knowledge. A more sophisticated model was developed for the galactic distribution of electron density turbulence. Faraday rotation measure data was analyzed to constrain magnetic field fluctuations in the ISM. VLBI observations were acquired of compact sources behind the supernova remnant CTA1. Simple calculations were made about the energies of the turbulence assuming a direct link between electron density and magnetic field variations. A simulation is outlined of cosmic ray propagation through the galaxy using the above results.

Cordes, James M.↗

NASA NTRS1987

LTE modeling of inhomogeneous chromospheric structure using high-resolution limb observations

The paper discusses considerations relevant to LTE modeling of rough atmospheres. Particular attention is given to the application of recent high-resolution observations of the solar limb in the far-infrared and radio continuum to the modeling of chromospheric spicules. It is explained how the continuum limb observations can be combined with morphological knowledge of spicule structure to model the physical conditions in chromospheric spicules. This discussion forms the basis for a chromospheric model presented in a parallel publication based on observations ranging from 100 microns to 2.6 mm.

Lindsey, C.↗

NASA NTRSDate not supplied

AI Foundation Models for Science: An Open Collaborative Initiative

Foundation Models (FMs), AI models designed to replace task-specific models, are increasingly being recognized for their versatility across numerous downstream applications. These models, trained using self-supervised techniques on any type of sequence data, circumvent the need for large annotated datasets, a major bottleneck in traditional AI model development. FMs can be applied to downstream tasks using few-shot learning and fine-tuning, significantly reducing the need for large labeled training datasets and computational resources. However, the development of FMs requires substantial resources, including access to data and compute power, expertise in the latest models, and specialized scientific knowledge for systematic evaluation. It is challenging for a single group to possess all these capabilities. To address this, NASA IMPACT has initiated an open collaborative effort, leveraging partnerships with the private sector and other groups within and outside NASA, to jointly build FMs. The overarching goal is to develop a consistent and collaborative approach to building FMs for high-value science datasets. This initiative has fostered collaboration within NASA and with external partners, including IBM Research, Clark University, DOE’s ORNL, ESA, and USGS. The effort focuses on identifying key datasets with a wide range of downstream applications, pretraining and building FMs using modified transformer architectures, evaluating compute infrastructure needs, and sharing models, pretraining and fine-tuning code, and data with the community. Furthermore, it aims to train the Earth science community to fine-tune these models for various downstream applications. Our initial effort resulted in the creation of a 100 million parameter HLS Geospatial Model within six months, which was released on HuggingFace. We are now expanding our scope to include data from weather and climate models and investigating multimodal models. We invite those interested in participating in this effort to join us by sharing their use cases, expertise, or data.

Rahul Ramachandran↗

NASA NTRS2015

Ocean Heat and Carbon Uptake in Transient Climate Change: Identifying Model Uncertainty

Global warming on decadal and centennial timescales is mediated and ameliorated by the oceansequestering heat and carbon into its interior. Transient climate change is a function of the efficiency by whichanthropogenic heat and carbon are transported away from the surface into the ocean interior (Hansen et al. 1985).Gregory and Mitchell (1997) and Raper et al. (2002) were the first to identify the importance of the ocean heat uptakeefficiency in transient climate change. Observational estimates (Schwartz 2012) and inferences from coupledatmosphere-ocean general circulation models (AOGCMs; Gregory and Forster 2008; Marotzke et al. 2015), suggest thatocean heat uptake efficiency on decadal timescales lies in the range 0.5-1.5 W/sq m/K and is thus comparable to theclimate feedback parameter (Murphy et al. 2009). Moreover, the ocean not only plays a key role in setting the timing ofwarming but also its regional patterns (Marshall et al. 2014), which is crucial to our understanding of regional climate,carbon and heat uptake, and sea-level change. This short communication is based on a presentation given by A.Romanou at a recent workshop, Oceans Carbon and Heat Uptake: Uncertainties and Metrics, co-hosted by US CLIVARand OCB. As briefly reviewed below, we have incomplete but growing knowledge of how ocean models used in climatechange projections sequester heat and carbon into the interior. To understand and thence reduce errors and biases inthe ocean component of coupled models, as well as elucidate the key mechanisms at work, in the final section we outlinea proposed model intercomparison project named FAFMIP. In FAFMIP, coupled integrations would be carried out withprescribed overrides of wind stress and freshwater and heat fluxes acting at the sea surface.

periodic variations↗

NASA NTRS1993

Expanding the KATE toolbox

KATE (Knowledge-based Autonomous Test Engineer) is a model-based software system developed in the Artificial Intelligence Laboratory at the Kennedy Space Center for monitoring, fault detection, and control of launch vehicles and ground support systems. In order to bring KATE to the level of performance, functionality, and integratability needed for firing room applications, efforts are underway to implement KATE in the C++ programming language using an X-windows interface. Two programs which were designed and added to the collection of tools which comprise the KATE toolbox are described. The first tool, called the schematic viewer, gives the KATE user the capability to view digitized schematic drawings in the KATE environment. The second tool, called the model editor, gives the KATE model builder a tool for creating and editing knowledge base files. Design and implementation issues having to do with these two tools are discussed. It will be useful to anyone maintaining or extending either the schematic viewer or the model editor.

Thomas, Stan J.↗

NASA NTRS1993

Effects of free-stream turbulence on boundary-layer transition

Traditional methods for the prediction of the transition location rest either on lump parameters like the momentum thickness or on N factors obtained from the approximate linear stability characteristics of the flow. These methods account for the effects of the disturbance environment by empirical correlation with observed transition locations. We have developed a highly efficient and accurate approach to stability analysis and transition simulation based on parabolized stability equations (PSE). Here we present a first application of this approach to realistic problems of practical interest. We study the effects of the turbulence level on transition and heat transfer in flows over flat plates, curved plates, and the stator blade of a gas-turbine model. We discuss the formulation of an input model for the PSE analysis in the light of the present knowledge of receptivity mechanisms. The input model is used to compute transition locations for various configurations and flow conditions. The results compare favorably with experimental data.

Herbert, TH.↗

NASA NTRS2017

Coupled Data Assimilation for Integrated Earth System Analysis and Prediction: Goals, Challenges, and Recommendations

The purpose of this report is to identify fundamental issues for coupled data assimilation (CDA), such as gaps in science and limitations in forecasting systems, in order to provide guidance to the World Meteorological Organization (WMO) on how to facilitate more rapid progress internationally. Coupled Earth system modeling provides the opportunity to extend skillful atmospheric forecasts beyond the traditional two-week barrier by extracting skill from low-frequency state components such as the land, ocean, and sea ice. More generally, coupled models are needed to support seamless prediction systems that span timescales from weather, subseasonal to seasonal (S2S), multiyear, and decadal. Therefore, initialization methods are needed for coupled Earth system models, either applied to each individual component (called Weakly Coupled Data Assimilation - WCDA) or applied the coupled Earth system model as a whole (called Strongly Coupled Data Assimilation - SCDA). Using CDA, in which model forecasts and potentially the state estimation are performed jointly, each model domain benefits from observations in other domains either directly using error covariance information known at the time of the analysis (SCDA), or indirectly through flux interactions at the model boundaries (WCDA). Because the non-atmospheric domains are generally under-observed compared to the atmosphere, CDA provides a significant advantage over single-domain analyses. Next, we provide a synopsis of goals, challenges, and recommendations to advance CDA: Goals: (a) Extend predictive skill beyond the current capability of NWP (e.g. as demonstrated by improving forecast skill scores), (b) produce physically consistent initial conditions for coupled numerical prediction systems and reanalyses (including consistent fluxes at the domain interfaces), (c) make best use of existing observations by allowing observations from each domain to influence and improve the full earth system analysis, (d) develop a robust observation-based identification and understanding of mechanisms that determine the variability of weather and climate, (e) identify critical weaknesses in coupled models and the earth observing system, (f) generate full-field estimates of unobserved or sparsely observed variables, (g) improve the estimation of the external forcings causing changes to climate, (h) transition successes from idealized CDA experiments to real-world applications. Challenges: (a) Modeling at the interfaces between interacting components of coupled Earth system models may be inadequate for estimating uncertainty or error covariances between domains, (b) current data assimilation methods may be insufficient to simultaneously analyze domains containing multiple spatiotemporal scales of interest, (c) there is no standardization of observation data or their delivery systems across domains, (d) the size and complexity of many large-scale coupled Earth system models makes it is difficult to accurately represent uncertainty due to model parameters and coupling parameters, (e) model errors lead to local biases that can transfer between the different Earth system components and lead to coupled model biases and long-term model drift, (e) information propagation across model components with different spatiotemporal scales is extremely complicated, and must be improved in current coupled modeling frameworks, (h) there is insufficient knowledge on how to represent evolving errors in non-atmospheric model components (e.g. as sea ice, land and ocean) on the timescales of NWP.

CDA↗

NASA NTRS2021

Empirical Model of 10 – 130 MeV Solar Energetic Particle Spectra at 1 AU Based on Coronal Mass Ejection Speed and Direction

We present a new empirical model to predict solar energetic particle (SEP) event integrated and peak intensity spectra between 10 and 130 MeV at 1 AU, based on multi-point spacecraft measurements from the Solar TErrestrial RElations Observatory (STEREO), the Geostationary Operational Environmental Satellites (GOES), and the Payload for Antimatter Matter Exploration and Light-nuclei Astrophysics (PAMELA) satellite experiment. The analyzed data sample includes 32 SEP events occurring between 2010 and 2014, with a statistically significant proton signal at energies in excess of a few tens of MeV, unambiguously recorded at three spacecraft locations. The spatial distributions of SEP intensities are reconstructed by assuming an energy-dependent 2D Gaussian functional form, and accounting for the correlation between the intensity and the speed of the parent coronal mass ejection (CME), and the magnetic-field-line connection angle. The CME measurements used are from the Space Weather Database Of Notifications, Knowledge, Information (DONKI). The model performance, including its extrapolations to lower/higher energies, is tested by comparing with the spectra of 20 SEP events not used to derive the model parameters. Despite the simplicity of the model, the observed and predicted event-integrated and peak intensities at Earth and at the STEREO spacecraft for these events show remarkable agreement, both in the spectral shapes and their absolute values.

Alessandro Bruno↗

NASA NTRS2002

A Statistical Comparison of PSC Model Simulations and POAM Observations

A better knowledge of PSC composition and formation mechanisms is important to better understand and predict stratospheric ozone depletion. Several past studies have attempted to compare modeling results with satellite observations. These comparisons have concentrated on case studies. In this paper we adopt a statistical approach. POAM PSC observations from several Arctic winters are categorized into Type Ia and Ib PSCs using a technique based on Strawa et al. The discrimination technique has been modified to employ the wavelengths dependence of the extinction signal at all wavelengths rather than only at 603 and 10 18 nm. Winter-long simulations for the 1999-2000 Arctic winter have been made using the IMPACT model. These simulations have been constrained by aircraft observations made during the SOLVE/THESEO 2000 campaign. A complete set of winter-long simulations was run for several different microphysical and PSC formation scenarios. The simulations give us perfect knowledge of PSC type (Ia, Ib, or II), composition, especially condensed phase HNO3 which is important for denitrification, and condensed phase H2O. Comparisons are made between the simulation and observation of PSC extinction at 1018 rim versus wavelength dependence, winter-long percentages of Ia and Ib occurrence, and temporal and altitude trends of the PSCs. These comparisons allow us to comment on how realistic some modeling scenarios are.

Strawa, A. W.↗

NASA NTRS1995

EXPECT: Explicit Representations for Flexible Acquisition

To create more powerful knowledge acquisition systems, we not only need better acquisition tools, but we need to change the architecture of the knowledge based systems we create so that their structure will provide better support for acquisition. Current acquisition tools permit users to modify factual knowledge but they provide limited support for modifying problem solving knowledge. In this paper, the authors argue that this limitation (and others) stem from the use of incomplete models of problem-solving knowledge and inflexible specification of the interdependencies between problem-solving and factual knowledge. We describe the EXPECT architecture which addresses these problems by providing an explicit representation for problem-solving knowledge and intent. Using this more explicit representation, EXPECT can automatically derive the interdependencies between problem-solving and factual knowledge. By deriving these interdependencies from the structure of the knowledge-based system itself EXPECT supports more flexible and powerful knowledge acquisition.

Swartout, BIll↗

NASA NTRS2017

Acoustic Model Testing Chronology

Scale models have been used for decades to replicate liftoff environments and in particular acoustics for launch vehicles. It is assumed, and analyses supports, that the key characteristics of noise generation, propagation, and measurement can be scaled. Over time significant insight was gained not just towards understanding the effects of thruster details, pad geometry, and sound mitigation but also to the physical processes involved. An overview of a selected set of scale model tests are compiled here to illustrate the variety of configurations that have been tested and the fundamental knowledge gained. The selected scale model tests are presented chronologically.

Nesman, Tom↗