Results for “Model error” — Page 87

NASA NTRSDate not supplied

Clifford Neural Operators on Atmospheric Data Influenced Partial Differential Equations

Mathematical representations of the atmosphere are key to forecasting and research tasks across Earth science. Numerically solving the underlying partial differential equations(PDEs) of the atmosphere, however, can be difficult and computationally expensive with numerous trade-offs between computing efficiency and accuracy. Utilizing neural net-works to learn approximations of the PDE solutions from the data can help us model complex phenomena more efficiently than traditional numerical schemes. Here, we have applied Clifford algebra-based neural operators for predicting atmospheric variables. Clifford Fourier neural operators are used with two different backbone architectures, ResNet and UNet, on custom data of U10, V10 and surface pressure as well as U500, V500 and Z500. Clifford Fourier neural operators, coupled with ResNet and UNet architectures, are applied to a key reanalysis dataset. Model performance is initially strong, but we observe increasing errors, resulting in the model becoming highly unstable.

Sujit Roy↗

NASA NTRS2011

Understanding Effective Diameter and Its Application to Terrestrial Radiation in Ice Clouds

The cloud property known as "effective diameter" or "effective radius", which in essence is the cloud particle size distribution (PSD) volume at bulk density divided by its projected area, is used extensively in atmospheric radiation transfer, climate modeling and remote sensing. This derives from the assumption that PSD optical properties can be uniquely described in terms of their effective diameter, D(sub e), and their cloud water content (CWC), henceforth referred to as the D(sub e)-CWC assumption. This study challenges this assumption, showing that while the D(sub e)-CWC assumption appears generally valid for liquid water clouds, it appears less valid for ice clouds in regions where (1) absorption is not primarily a function of either the PSD ice water content (IWC) or the PSD projected area, and (2) where wave resonance (i.e. photon tunneling) contributes significantly to absorption. These two regions often strongly coincide at terrestrial wavelengths when De less than ~60 m, which is where this D(sub e)-CWC assumption appears poorest. Treating optical properties solely in terms of D(sub e) and IWC may lead to errors up to 24%, 26% and 20% for terrestrial radiation in the window region regarding the absorption and extinction coefficients and the single scattering albedo, respectively. Outside the window region, errors may reach 33% and 42% regarding absorption and extinction. The magnitude and sign of these errors can change rapidly with wavelength, which may produce significant errors in climate modeling, remote sensing and other applications concerned with the wavelength dependence of radiation. Where the D(sub e)-CWC assumption breaks down, ice cloud optical properties appear to depend on D(sub e), IWC and the PSD shape. Optical property parameterizations in climate models and remote sensing algorithms based on historical PSD measurements may exhibit errors due to previously unknown PSD errors (i.e. the presence of ice artifacts due to the shattering of larger ice particles on the probe inlet tube during sampling). More recently developed cloud probes are designed to mitigate this shattering problem. Using realistic PSD shapes for a given temperature (and/or IWC) and cloud type may minimize errors associated with PSD shape in ice optics parameterizations and remote sensing algorithms. While this topic was investigated using two ice optics schemes (the Yang et al., 2005 database and the modified anomalous diffraction approximation, or MADA), a physical understanding of the limitations of the D(sub e)-IWC assumption was made possible by using MADA. MADA allows one to approximate the contribution of photon tunneling to absorption relative to other optical processes, which reveals that part of the error regarding the D(sub e)-IWC assumption can be associated with tunneling. By relating the remaining error to the radiation penetration depth in bulk ice (DELTA L) due to absorption, the domain where the D(sub e)-IWC assumption is weakest was described in terms of D(sub e) and DELTA L.

Mitchell, D. L.↗

DOE OSTI2025

Self-Supervised T-GCN for Detection of Disturbance and Propagation in Power Grid

Urban power systems increasingly rely on dense sensing to monitor grid reliability, yet disturbance labels are scarce and events are rare. We present a self-supervised spatio-temporal method that detects, localizes, and characterizes grid frequency disturbances across urban areas using only unlabeled data. Our approach trains a tiny Temporal Graph Convolutional Network (T-GCN) to forecast per-site frequency residuals (deviation from 60 Hz). The sensor graph is constructed directly from signals using pre-event Pearson correlation with a cross-correlation lag penalty without geocoding. At inference, node-level anomalies are the model's forecast errors; region-level alarms arise from connected components of high-score nodes. We estimate disturbance propagation by computing per-node arrival times (first persistent exceedance), then fit a planar or time-of-arrival model to obtain direction, speed, and an epicenter proxy. With only three real events collected at decisecond resolution across U.S. cities, we evaluate the T-GCN and report time-to-detect, footprint size, and propagation consistency. We further show that short-window embeddings from the T-GCN's hidden states enable few-shot event-vs-background recognition via a simple prototypical classifier. Despite minimal data and no labels, our system yields fast, spatially coherent detection and interpretable propagation maps, offering a practical, lightweight pathway to city-scale grid resilience analytics.

Niu, Haoran [ORNL] (ORCID:0000000155228297)↗

NASA NTRS1976

On the computational cost of approximating and recognizing noise-perturbed straight lines and quadratic arcs in the plane

Recognition of underlying straight lines and quadratic arcs in line drawings, and approximation of very noisy data by such line/curve segments, is addressed as a subproblem of the more general problem of optimum recognition of complicated line/curve drawings. Some specific algorithms are presented with extensions and interpretations for more complicated applications, and a data generation model is developed for the problem. Data are generated as a perturbation of a single underlying straight line or an elliptic or hyperbolic arc. Recursive estimation techniques, minimization of central processing unit time, decision making with controlled error probabilities, and modeling and recognition of pictures consisting of noisy curves are dealt with. Applications envisaged include: picture data compression, contour line representation in maps, intelligent data searches, and ballistic missile decoy tracking.

Cooper, D. B.↗

NASA NTRS2015

Jovian plasma modeling for mission design

The purpose of this report is to address uncertainties in the plasma models at Jupiter responsible for surface charging and to update the jovian plasma models using the most recent data available. The updated plasma environment models were then used to evaluate two proposed Europa mission designs for spacecraft charging effects using the Nascap-2k code. The original Divine/Garrett jovian plasma model (or "DG1", T. N. Divine and H. B. Garrett, "Charged particle distributions in Jupiter's magnetosphere," J. Geophys. Res., vol. 88, pp. 6889-6903,1983) has not been updated in 30 years, and there are known errors in the model. As an example, the cold ion plasma temperatures between approx.5 and 10 Jupiter radii (Rj) were found by the experimenters who originally published the data to have been underestimated by approx.2 shortly after publication of the original DG1 model. As knowledge of the plasma environment is critical to any evaluation of the surface charging at Jupiter, the original DG1 model needed to be updated to correct for this and other changes in our interpretation of the data so that charging levels could beproperly estimated using the Nascap-2k charging code. As an additional task, the Nascap-2k spacecraft charging tool has been adapted to incorporate the so-called Kappa plasma distribution function--an important component of the plasma model necessary to compute the particle fluxes between approx.5 keV and 100 keV (at the outset of this study,Nascap-2k did not directly incorporate this common representation of the plasma thus limiting the accuracy of our charging estimates). The updating of the DG1 model and its integration into the Nascap-2k design tool means that charging concerns can now be more efficiently evaluated and mitigated. (We note that, given the subsequent decision by the Europa project to utilize solar arrays for its baseline design, surface charging effects have becomeeven more of an issue for its mission design). The modifications and results of those modifications to the DG1 model to produce the new DG2 model presented here and the steps taken to integrate the DG2 predictions into Nascap-2k are described in this report.

Voyager 2↗

NASA NTRS2015

Jovian Plasma Modeling for Mission Design

The purpose of this report is to address uncertainties in the plasma models at Jupiter responsible for surface charging and to update the jovian plasma models using the most recent data available. The updated plasma environment models were then used to evaluate two proposed Europa mission designs for spacecraft charging effects using the Nascap-2k code. The original Divine/Garrett jovian plasma model (or "DG1", T. N. Divine and H. B. Garrett, "Charged particle distributions in Jupiter's magnetosphere," J. Geophys. Res., vol. 88, pp. 6889-6903,1983) has not been updated in 30 years, and there are known errors in the model. As an example, the cold ion plasma temperatures between approx.5 and 10 Jupiter radii (Rj) were found by the experimenters who originally published the data to have been underestimated by approx.2 shortly after publication of the original DG1 model. As knowledge of the plasma environment is critical to any evaluation of the surface charging at Jupiter, the original DG1 model needed to be updated to correct for this and other changes in our interpretation of the data so that charging levels could beproperly estimated using the Nascap-2k charging code. As an additional task, the Nascap-2k spacecraft charging tool has been adapted to incorporate the so-called Kappa plasma distribution function--an important component of the plasma model necessary to compute the particle fluxes between approx.5 keV and 100 keV (at the outset of this study,Nascap-2k did not directly incorporate this common representation of the plasma thus limiting the accuracy of our charging estimates). The updating of the DG1 model and its integration into the Nascap-2k design tool means that charging concerns can now be more efficiently evaluated and mitigated. (We note that, given the subsequent decision by the Europa project to utilize solar arrays for its baseline design, surface charging effects have becomeeven more of an issue for its mission design). The modifications and results of those modifications to the DG1 model to produce the new DG2 model presented here and the steps taken to integrate the DG2 predictions into Nascap-2k are described in this report

Garrett, Henry B.↗

NASA NTRS2024

Core Body Temperature Predictions Using Metabolic Energy Expenditure and Heart Rate During Simulated Extravehicular Activity

Long duration spaceflight missions will require crew to become more autonomous in conducting extravehicular activities (EVA) without direct communication with Mission Control for biomedical support. To enable such autonomy, we are developing a Crew State and Risk Model (CSRM) as a collection of key physiology domains that drive EVA crew capabilities and workloads. One model component of CSRM is human thermal regulation. In this paper, customized development of a baseline model to predict core body temperature is presented using physiology inputs of heart rate and metabolic rate. The model development dataset included a baseline study where participants (n=6, equal male and female) performed a 5-hour EVA in a two-part session while wearing a hybrid space suit simulator (HS3). The first session included an end-to-end EVA traversing 1500 meters to a geology site and traversing back to a habitat conducting geology, payload relocation, and maintenance operations every 500 meters. The second session included standalone tasks of a 2000-meter traverse followed by geology tasks. Thermal measures of core body temperature, local skin temperature, liquid cooling garment temperature, heart rate, and metabolic rate were collected through the test duration. Multiple regression was used to build a linear equation to predict core body temperature from inputs of heart rate and metabolic rate. Heat storage was calculated via predicted core body temperature plus LCG and skin temperatures. The model was tested against a dataset from a pressurized suited test (n=6, equal male and female) in the NASA Active Response Gravity Offload System (ARGOS) conducting similar end-to-end EVA and standalone tasks. Predicted error of the model against the raw test cases was 0.2±0.15 °C. The baseline prediction of core body temperature using heart rates and metabolic rates allows for simple real-time tracking from data collected in-flight to monitor crew consumables and thermal flight limits during EVA.

Bradley Hoffmann↗

NASA NTRS2007

A Reduced-Order Model For Zero-Mass Synthetic Jet Actuators

Accurate details of the general performance of fluid actuators is desirable over a range of flow conditions, within some predetermined error tolerance. Designers typically model actuators with different levels of fidelity depending on the acceptable level of error in each circumstance. Crude properties of the actuator (e.g., peak mass rate and frequency) may be sufficient for some designs, while detailed information is needed for other applications (e.g., multiple actuator interactions). This work attempts to address two primary objectives. The first objective is to develop a systematic methodology for approximating realistic 3-D fluid actuators, using quasi-1-D reduced-order models. Near full fidelity can be achieved with this approach at a fraction of the cost of full simulation and only a modest increase in cost relative to most actuator models used today. The second objective, which is a direct consequence of the first, is to determine the approximate magnitude of errors committed by actuator model approximations of various fidelities. This objective attempts to identify which model (ranging from simple orifice exit boundary conditions to full numerical simulations of the actuator) is appropriate for a given error tolerance.

Yamaleev, Nail K.↗

NASA NTRS1966

Error rate reduction of parity checked telemetry data by likelihood deletion strategy

Theoretical model and application of error rate reduction of parity checked telemetry data by likelihood deletion strategy

SPACE COMMUNICATION↗

DOE OSTI2020

Medium Energy Electron Flux in Earth's Outer Radiation Belt (MERLIN): A Machine Learning Model

The radiation belts of the Earth, filled with energetic electrons, comprise complex and dynamic systems that pose a significant threat to satellite operation. While various models of electron flux both for low and relativistic energies have been developed, the behavior of medium energy (120–600 keV) electrons, especially in the MEO region, remains poorly quantified. At these energies, electrons are driven by both convective and diffusive transport, and their prediction usually requires sophisticated 4D modeling codes. In this paper, we present an alternative approach using the Light Gradient Boosting (LightGBM) machine learning algorithm. The Medium Energy electRon fLux In Earth's outer radiatioN belt (MERLIN) model takes as input the satellite position, a combination of geomagnetic indices and solar wind parameters including the time history of velocity, and does not use persistence. MERLIN is trained on >15 years of the GPS electron flux data and tested on more than 1.5 years of measurements. Tenfold cross validation yields that the model predicts the MEO radiation environment well, both in terms of dynamics and amplitudes o f flux. Evaluation on the test set shows high correlation between the predicted and observed electron flux (0.8) and low values of absolute error. The MERLIN model can have wide space weather applications, providing information for the scientific community in the form of radiation belts reconstructions, as well as industry for satellite mission design, nowcast of the MEO environment, and surface charging analysis.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

IDAES-PSE 2.5.0 Release

The Institute for the Design of Advanced Energy Systems (IDAES) Integrated Platform is a versatile computational environment offering extensive process systems engineering (PSE) capabilities for optimizing the design and operation of complex, interacting technologies and systems. IDAES enables users to efficiently search vast, complex design spaces to discover the lowest cost, most environmentally sustainable solutions while supporting the full process modeling lifecycle, from conceptual design to dynamic optimization and control. The extensible, open platform empowers users to create models of novel processes and rapidly develop custom analyses, workflows, and end-user applications. IDAES-PSE 2.5.0 Release Highlights Upcoming Changes IDAES will be switching to the new Pyomo solver interface in the next release. Whilst this will hopefully be a smooth transition for most users, there are a few important changes to be aware of. The new solver interface uses a different version of the IPOPT writer (“ipopt_v2”) and thus any custom configuration options you might have set for IPOPT will not carry over and will need to be reset. By default, the new Pyomo linear presolver will be activated with ipopt_v2. Whilst are working to identify any bugs in the presolver, it is possible that some edge cases will remain. IDAES will begin deploying a new set of scaling tools and APIs over the next few releases that make use of the new solver writers. The old scaling tools and APIs will remain for backward compatibility but will begin to be deprecated. New Models, Tools and Features New diagnostics check for near-parallel variables and constraints. New diagnostics tools for identifying causes of infeasibility in models. New example for creating a custom model of a liquid-liquid extractor unit operation. Bug Fixes Fixed bug in Gibbs reactor that caused it to appear to have additional spurious degrees of freedom. Fixed bug in the Modular Property Framework that would cause errors when trying to use phase-based material balances with phase equilibria. Fixed bug in Modular Properties Framework that caused errors when initializing models with non-vapor-liquid phase equilibria. Testing and Robustness Deployed the IDAES Diagnostics Toolbox to confirm that there are no structural or numerical issues in the core model libraries. Additional robustness tests for core model, and some associated improvements in the converge tester class. Fixed a number of issues that were causing unexpected warnings to be emitted during testing. Deprecations and Removals Removed examples for RIPE tool which has not been supported for a number of releases.

AS↗

NASA NTRS1997

Geosat Data Assimilation with Application to the Eastern North Atlantic

An attempt is made to determine the three-dimensional ocean circulation from satellite altimeter measurements by assimilating Geosat sea surface height data into an eddy-resolving QuasiGeostrophic (QG) model of the eastern North Atlantic Ocean. Results are tested against independent information from hydrographic field observations and moored current meter data collected during the Geosat ERM. The comparison supports the concept of inferring aspects of the three-dimensional flow field from sea surface height observations by combining altimetric measurements with the dynamics of ocean circulation models. A Holland-type QG model with open boundaries is set up on a 2000 km X 2000 km domain of the eastern North Atlantic between 25 deg. and 45 deg. N, 32 deg. and 8 deg. W. By using a simple nudging technique, about two years of Geosat altimeter data are assimilated into the model every five days as space-time objective analyses on the model grid. The error information resulting from the analysis is used during the assimilation procedure to account for data uncertainties. Results show an intense eddy field, which in the surface layer interacts with a meandering Azores Front. Compared to Geosat, the model leads to smoothed fields that follow the observations. Model simulations are significantly correlated with hydrographic data from March 1988 and June 1989, both close to the surface and in the subsurface. Good agreement is also found between the model velocity fields and moored current meter data in the top two model layers. The agreement is visually weak in the bottom layer, although a coherence analysis reveals an agreement between the model simulation and current meter data over the full water column at periods exceeding 80 days.

Stammer, Detlef↗

NASA NTRS1979

Impact of cell size on inventory and mapping errors in a cellular geographic information system

The author has identified the following significant results. The effect of grid position was found insignificant for maps but highly significant for isolated mapping units. A modelable relationship between mapping error and cell size was observed for the map segment analyzed. Map data structure was also analyzed with an interboundary distance distribution approach. Map data structure and the impact of cell size on that structure were observed. The existence of a model allowing prediction of mapping error based on map structure was hypothesized and two generations of models were tested under simplifying assumptions.

Wehde, M. E.↗

NASA NTRS2000

Examination of Solar Cycle Statistical Model and New Prediction of Solar Cycle 23

Sunspot numbers in the current solar cycle 23 were estimated by using a statistical model with the accumulating cycle sunspot data based on the odd-even behavior of historical sunspot cycles from 1 to 22. Since cycle 23 has progressed and the accurate solar minimum occurrence has been defined, the statistical model is validated by comparing the previous prediction with the new measured sunspot number; the improved sunspot projection in short range of future time is made accordingly. The current cycle is expected to have a moderate level of activity. Errors of this model are shown to be self-correcting as cycle observations become available.

Kim, Myung-Hee Y.↗

NASA NTRS1979

The performance of a seasonal global climatic model

A seasonal global climatic model developed by Sellers is studied. Several changes are made to correct errors in the original model and to allow its use in a time dependent simulation mode. The major changes are in the infrared radiation formulation and in the size of the time steps. The seasonal cycles of surface temperature, wind, ice, snow, albedo, horizontal heat transport, and vertical flux of solar and infrared radiation are compared to recent observations. The seasonal cycle of temperature is fairly well reproduced, but has too small an amplitude in the Northern Hemisphere high latitudes. An overestimate of albedo at the poles is found, which is related to errors in some of the other variables. The sensitivity of the model to CO2 and solar constant (O) changes is summarized. Doubling the CO2 amount causes a 2.45 K increase in global average surface temperature (T). Increasing Q by 1% increases T by 3.14K. Decreasing 0 by 1% decreases T by 4.65K. An annual average version of the model is more sensitive to changes in Q than the model with the seasonal cycle.

Robock, A.↗

NASA NTRS2016

WFIRST/AFTA Coronograph Contrast Performance Sensitivity Studies: Simulation Versus Experiment

The WFIRST/AFTA 2.4 m space telescope currently under study includes a stellar coronagraph for the imaging and the spectral characterization of extrasolar planets. The coronagraph employs sequential deformable mirrors to compensate for phase and amplitude errors. Using the optical model of an Occulting Mask Coronagraph (OMC) testbed at the Jet Propulsion Laboratory, we have investigated through modeling and simulations the sensitivity of dark hole contrast in a Hybrid Lyot Coronagraph (HLC) for several error cases, including lateral and longitudinal translation errors of two deformable mirrors, DM1 and DM2, lateral and/or longitudinal translation errors of an occulting mask and a Lyot-Stop, clocking errors of DM1 and DM2, and the mismatch errors between the testbed and the model sensitivity matrices. We also investigated the effects of a control parameter, namely the actuator regularization factor, on the control efficiency and on the final contrast floor. We found several error cases which yield contrast results comparable to that observed on the HLC testbed. We present our findings in this paper.

Coronagraphy↗

NASA NTRS2016

WFIRST/AFTA coronograph contrast performance sensitivity studies: simulation versus experiment

The WFIRST/AFTA 2.4 m space telescope currently under study includes a stellar coronagraph for the imaging and the spectral characterization of extrasolar planets. The coronagraph employs sequential deformable mirrors to compensate for phase and amplitude errors. Using the optical model of an Occulting Mask Coronagraph (OMC) testbed at the Jet Propulsion Laboratory, we have investigated through modeling and simulations the sensitivity of dark hole contrast in a Hybrid Lyot Coronagraph (HLC) for several error cases, including lateral and longitudinal translation errors of two deformable mirrors, DM1 and DM2, lateral and/or longitudinal translation errors of an occulting mask and a Lyot-Stop, clocking errors of DM1 and DM2, and the mismatch errors between the testbed and the model sensitivity matrices. We also investigated the effects of a control parameter, namely the actuator regularization factor, on the control efficiency and on the final contrast floor. We found several error cases which yield contrast results comparable to that observed on the HLC testbed. We present our findings in this paper.

Nemati, Bijan↗

NASA NTRS2002

Finite Element A Posteriori Error Estimation for Heat Conduction

This research investigates residual-based a posteriori error estimates for finite element approximations of heat conduction in single-layer and multi-layered materials. The finite element approximation, based upon hierarchical modelling combined with p-version finite elements, is described with specific application to a two-dimensional, steady state, heat-conduction problem. Element error indicators are determined by solving an element equation for the error with the element residual as a source, and a global error estimate in the energy norm is computed by collecting the element contributions. Numerical results of the performance of the error estimate are presented by comparisons to the actual error. Two methods are discussed and compared for approximating the element boundary flux. The equilibrated flux method provides more accurate results for estimating the error than the average flux method. The error estimation is applied to multi-layered materials with a modification to the equilibrated flux method to approximate the discontinuous flux along a boundary at the material interfaces. A directional error indicator is developed which distinguishes between the hierarchical modeling error and the finite element error. Numerical results are presented for single-layered materials which show that the directional indicators accurately determine which contribution to the total error dominates.

Lang, Christapher G.↗