Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “model structural error”

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.

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

At least 1,225 records · Page 68
All sourcesNASA NTRSDOE OSTI
NASA NTRS2007

System Engineering the Space Infrared Interferometric Telescope (SPIRIT)

The Space Infrared Interferometric Telescope (SPIRIT) was designed to accomplish three scientific objectives: (1) learn how planetary systems form from protostellar disks and how they acquire their inhomogeneous chemical composition; (2) characterize the family of extrasolar planetary systems by imaging the structure in debris disks to understand how and where planets of different types form; and (3) learn how high-redshift galaxies formed and merged to form the present-day population of galaxies. SPIRIT will accomplish these objectives through infrared observations with a two aperture interferometric instrument. This paper gives an overview of SPIRIT design and operation, and how the three design cycle concept study was completed. The error budget for several key performance values allocates tolerances to all contributing factors, and a performance model of the spacecraft plus instrument system demonstrates meeting those allocations with margin.

Hyde, Tristram T.↗
NASA NTRS2019

A Systematic Approach to Isolating the Causes and Impacts of Climate Model Bias Employing Analysis Increments

One of the most promising approaches to isolating the causes and understanding the impacts of climate model formulation errors is through the utilization of information contained in short-term forecast errors. The underlying assumption being that by capturing the errors at the very early stages of growth (before nonlinearities develop), we should be able to associate those errors with specific deficiencies in the model's formulation of the relevant physical processes. Here, we provide an example of utilizing the long-term mean of the 6-hourly analysis increments (first guess forecast minus analysis) produced by MERRA-2 to correct the NASA/GEOS AGCM over well-defined regions, thereby allowing us to quantify how the reduced tendency errors in these regions manifest themselves both locally and remotely through large-scale teleconnections to reduce the model's climatological biases. We extend previous work (focused on boreal summer) to address the full annual cycle of model bias. A key result is the large seasonality of the errors over the Tibet region and their impacts on the Northern Hemisphere jet biases, and related precipitation and temperature biases over North American. Attempts to correct the phase and amplitude errors of the climatological boreal winter ridge over western North America (a likely key requirement for improving winter climate forecasts over North America) reveal a surprising complexity in the sources of the errors in what is otherwise manifest as a rather simple PNA-like bias structure.

Schubert, S.↗
NASA NTRSDate not supplied

Grid Refinement Techniques for the 𝜸-Re𝜽𝒕 Transition Model in FUN3D

There has been an increased focus on the overall accuracy and grid convergence of Reynolds-averaged Navier-Stokes (RANS)-based transition models from the recent AIAA and NATO-AVT workshops. Even though satisfactory grid convergence could be achieved for simple two-dimensional flow configurations, it required mesh counts that are substantially larger than those used in typical applications. In this paper, we focus our efforts on understanding how the grid resolution and topology influences the accuracy and convergence of results by studying the Schubauer and Skramstad flat-plate configuration and the NLF-0416 airfoil at an angle of attack equal to five degrees using FUN3D, a second-order finite-volume code. By focusing on these cases, we can analyze both natural and separation-induced transition scenarios. Multiple grid refinement strategies are investigated. First, we determine the relative effectiveness of zonal streamwise refinement in the transition region within structured grids as an alternative to the costly option of globally uniform refinement of a baseline grid. We also complement this zonal technique by globally varying the wall-normal resolution keeping the streamwise resolution fixed. The zonal streamwise refinement can accurately model natural transition in a flat-plate boundary layer and separation-induced transition, but struggles to accurately model natural transition in airfoil flows. A series of unstructured prismatic grids that have similar node counts and viscous wall spacings as the structured hexahedral grids are also tested, and they do not achieve grid convergence until an extremely fine resolution. Last, we employ adjoint-based unstructured grid adaptation in FUN3D to natural and separation-induced transition on the NLF-0416 airfoil. The adjoint-based refinement process converges to the same solution as the baseline family of structured grids, but leads to smaller errors on coarser grids.

Grid Adaptation↗
NASA NTRSDate not supplied

Grid Refinement Techniques for the 𝜸-Re 𝜽 𝒕 Transition Model in FUN3D

There has been an increased focus on the overall accuracy and grid convergence of Reynolds-averaged Navier-Stokes (RANS)-based transition models from the recent AIAA and NATO-AVT workshops. Even though satisfactory grid convergence could be achieved for simple two-dimensional flow configurations, it required mesh counts that are substantially larger than those used in typical applications. In this paper, we focus our efforts on understanding how the grid resolution and topology influences the accuracy and convergence of results by studying the Schubauer and Skramstad flat-plate configuration and the NLF-0416 airfoil at an angle of attack equal to five degrees using FUN3D, a second-order finite-volume code. By focusing on these cases, we can analyze both natural and separation-induced transition scenarios. Multiple grid refinement strategies are investigated. First, we determine the relative effectiveness of zonal streamwise refinement in the transition region within structured grids as an alternative to the costly option of globally uniform refinement of a baseline grid. We also complement this zonal technique by globally varying the wall-normal resolution keeping the streamwise resolution fixed. The zonal streamwise refinement can accurately model natural transition in a flat-plate boundary layer and separation-induced transition, but struggles to accurately model natural transition in airfoil flows. A series of unstructured prismatic grids that have similar node counts and viscous wall spacings as the structured hexahedral grids are also tested, and they do not achieve grid convergence until an extremely fine resolution. Last, we employ adjoint-based unstructured grid adaptation in FUN3D to natural and separation-induced transition on the NLF-0416 airfoil. The adjoint-based refinement process converges to the same solution as the baseline family of structured grids, but leads to smaller errors on coarser grids.

Grid Adaptation↗
DOE OSTI2019

van der Waals Correction to the Physisorption of Graphene on Metal Surfaces

Adsorption is a scientifically and technologically important interfacial phenomenon, which however presents challenges to conventional density functional theory (DFT) due to the long-range van der Waals (vdW) interactions. We have developed a model of long-range vdW correction for physisorption of graphene (G) on metals with the Lifshitz–Zaremba–Kohn second-order perturbation theory, by incorporating dipole- and quadrupole-surface interactions and screening effects. The physisorption energies calculated by the model between graphene and eight metal surfaces (Al, Ni, Co, Pd, Pt, Cu, Ag, and Au), and the adsorption energies for the same G/metal structures from self-consistent DFT PBE (Perdew–Burke–Ernzerhof) calculations, are obtained in a range of distances between G and the metal surfaces. The sum of these two parts is the total adsorption energy as a function of the distance, from which the equilibrium distance and the binding energy are determined simultaneously. The results show high accuracy, with the mean absolute error (MAE) of binding energy of 7 meV and the MAE of equilibrium distance of 0.2 Å, significantly improving upon other vdW methods. Here, the PBE + vdW binding energy curves give better fits to the random phase approximation curves around the equilibrium distances than do the curves of other methods considered here. The higher-order quadrupole-surface correction is important and accounts for about 30% of the total vdW correction.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Machine learning assisted prediction of the Young’s modulus of compositionally complex alloys

We identify compositionally complex alloys (CCAs) that offer exceptional mechanical properties for elevated temperature applications by employing machine learning (ML) in conjunction with rapid synthesis and testing of alloys for validation to accelerate alloy design. The advantages of this approach are scalability, rapidity, and reasonably accurate predictions. ML tools were implemented to predict Young’s modulus of refractory-based CCAs by employing different ML models. Our results, in conjunction with experimental validation, suggest that average valence electron concentration, the difference in atomic radius, a geometrical parameter λ and melting temperature of the alloys are the key features that determine the Young’s modulus of CCAs and refractory-based CCAs. The Gradient Boosting model provided the best predictive capabilities (mean absolute error of 6.15 GPa) among the models studied. Our approach integrates high-quality validation data from experiments, literature data for training machine-learning models, and feature selection based on physical insights. It opens a new avenue to optimize the desired materials property for different engineering applications.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Multiscale Physics of Atomic Nuclei from First Principles

Atomic nuclei exhibit multiple energy scales ranging from hundreds of MeV in binding energies to fractions of an MeV for low-lying collective excitations. As the limits of nuclear binding are approached near the neutron and proton drip lines, traditional shell structure starts to melt with an onset of deformation and an emergence of coexisting shapes. It is a long-standing challenge to describe this multiscale physics starting from nuclear forces with roots in quantum chromodynamics. Here, we achieve this within a unified and nonperturbative quantum many-body framework that captures both short- and long-range correlations starting from modern nucleon-nucleon and three-nucleon forces from chiral effective field theory. The short-range (dynamic) correlations which account for the bulk of the binding energy are included within a symmetry-breaking framework, while long-range (static) correlations (and fine details about the collective structure) are included by employing symmetry projection techniques. Our calculations accurately reproduce—within theoretical error bars—available experimental data for low-lying collective states and the electromagnetic quadrupole transitions in 20−30 Ne. In addition, we reveal coexisting spherical and deformed shapes in 30 Ne, which indicates the breakdown of the magic neutron number 𝑁 = 20 as the key nucleus 28 O is approached, and we predict that the drip line nuclei 32,34 Ne are strongly deformed and collective. By developing reduced-order models for symmetry-projected states, we perform a global sensitivity analysis and find that the subleading singlet 𝑆-wave contact and a pion-nucleon coupling strongly impact nuclear deformation in chiral effective field theory. The techniques developed in this work clarify how microscopic nuclear forces generate the multiscale physics of nuclei spanning collective phenomena as well as short-range correlations and allow one to capture emergent and dynamical phenomena in finite fermion systems such as atom clusters, molecules, and atomic nuclei.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2025

Online and Offline Data Quality Monitoring for the Mu2e Calorimeter

This thesis presents the design, implementation, and validation of a calorimeter Data Quality Monitoring (DQM) toolchain for the Mu2e experiment at Fermilab. Mu2e searches for charged lepton flavor violation via coherent muon-to-electron conversion in the field of an aluminum nucleus, $\mu^- Al \rightarrow e^-Al$, a process whose observation would constitute clear evidence of physics beyond the Standard Model. Achieving target sensitivity requires stringent control of detector performance and data integrity during acquisition, as subtle issues in readout configuration, data formatting, or electronics behavior can compromise reconstruction and bias downstream analyzes. To address these challenges, this work develops a multi-layer DQM approach spanning both raw data validation and reconstructed digi-level diagnostics. At the low level, a fragment analysis component performs word- and bit-field decoding of calorimeter readout blocks, enabling sanity checks of the expected structure and producing detailed error and integrity statistics useful for commissioning and troubleshooting. At the digi level, the CaloDigiDQM analyzer is implemented within the art framework and transforms each CaloDigiCollection into a structured hierarchy of ROOT histograms designed for fast drill-down diagnostics. The module generates coherent monitoring views at global, disk, board, and channel granularity, including occupancy, waveform-derived features (baseline, RMS, peak amplitude and position), and left-right sensor consistency metrics. Detector-aware channel-to-electronics mapping is performed through the conditions system (CaloDAQMap), ensuring that diagnostics remain aligned with hardware identifiers used in operations. For end-to-end testing without reliance on live DAQ data, a synthetic CaloDigi producer is developed to generate realistic waveforms with controlled noise and pulse shapes. The resulting system supports both offline ROOT-file production and online operation, including optional histogram streaming through otsdaq via ots::HistoSender. This toolchain provides a practical and scalable foundation for calorimeter commissioning and stable data collection, enabling early detection of anomalies and reducing operational risk for Mu2e.

Vakulenko, Mark [Drew U.] (ORCID:0009000276197818)↗
DOE OSTI2025

MIC-DP: A Scalable Correlation-Aware Differential Privacy Framework for High-Dimensional Data

Conventional differential privacy (DP) assumes record independence, limiting effectiveness on real-world datasets with temporal, spatial, or structural correlations. These dependencies undermine privacy guarantees and degrade utility in domains like healthcare, IoT, and smart city analytics. We propose Maximum Information Correlated Differential Privacy (MIC-DP), a novel framework that dynamically calibrates noise based on statistical dependencies. MIC-DP uses the Maximum Information Coefficient (MIC) to capture both linear and nonlinear correlations without explicit modeling, enabling adaptive sensitivity adjustment and improved privacy–utility trade-offs. Evaluations on healthcare (MIMIC), demographic (ACI), and synthetic datasets show that MIC-DP reduces mean absolute error (MAE) by up to 5.2% under strict privacy budgets (ϵ≤1), with aggregate utility improvements reaching 18% across datasets and evaluation metrics. MIC-DP provides formal (ϵ,δ)-privacy guarantees, scales efficiently with feature count, and supports deployment in moderate-scale, privacy-sensitive applications. Its tunable performance and runtime efficiency make MIC-DP suitable for privacy-sensitive applications where low-latency analytics and strong privacy guarantees must coexist. These results demonstrate MIC-DP’s effectiveness as a correlation-aware solution for practical DP.

Yang, Wenjun [Univ. of Washington, Tacoma, WA (Uni↗
DOE OSTI2022

Analysis of Integrated Vapor Transport Biases

Abstract High-fidelity analyses and forecasts of integrated vapor transport (VT) are central to the study of Earth’s hydrological cycle as well as high-impact phenomena such as monsoons and atmospheric rivers. The impact of the in-line analysis correction-based additive inflation (ACAI) on IVT biases and forecast errors is examined within the Navy Earth System Prediction Capability (Navy ESPC) global coupled system. The ACAI technique uses atmospheric analysis corrections from the data assimilation system to approximate model bias and as a representation of stochastic model error to simultaneously reduce systematic and random errors and improve ensemble performance. ACAI reduces the global average magnitude of the 7- and 14-day IVT bias by 16%–17% during Northern Hemisphere summer, reaching 70% reductions in some tropical regions. The global average IVT bias reduction is similar to the bias reduction for low-level wind speed bias and considerably smaller than the bias reduction in total precipitable water. The localized regions where ACAI increases IVT bias occur where the control IVT biases change sign and structure with increasing forecast lead time, such as the South Asian monsoon region. Substituting analyzed wind or moisture fields for the forecast fields when calculating the forecast IVT confirms that, on average, wind errors dominate the IVT error calculation in the tropics, although wind and moisture error contributions are comparable in the extratropics. The existence of regions where using either analyzed winds or analyzed moisture increases IVT bias or mean absolute error reveals areas with compensating errors.

Reynolds, Carolyn A.↗
DOE OSTI2021

Penalized ensemble Kalman filters for high dimensional non-linear systems

The ensemble Kalman filter (EnKF) is a data assimilation technique that uses an ensemble of models, updated with data, to track the time evolution of a usually non-linear system. It does so by using an empirical approximation to the well-known Kalman filter. However, its performance can suffer when the ensemble size is smaller than the state space, as is often necessary for computationally burdensome models. This scenario means that the empirical estimate of the state covariance is not full rank and possibly quite noisy. To solve this problem in this high dimensional regime, we propose a computationally fast and easy to implement algorithm called the penalized ensemble Kalman filter (PEnKF). Under certain conditions, it can be theoretically proven that the PEnKF will be accurate (the estimation error will converge to zero) despite having fewer ensemble members than state dimensions. Further, as contrasted to localization methods, the proposed approach learns the covariance structure associated with the dynamical system. These theoretical results are supported with simulations of several non-linear and high dimensional systems.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS1973

Specification of mesospheric density, pressure, and temperature by extrapolation

A procedure is presented which employs an extrapolation technique to obtain estimates of density, pressure, and temperature up to 90 km from 52 km data. The resulting errors are investigated. The procedure is combined with a special temperature interpolation method around the stratopause to produce such estimates at eight levels between 36 km and 90 km from North American sectional chart data at 5, 2, and 0.4 mb. Fifth charts were processed to obtain mean values and standard deviations at grid points for midseasonal months from 1964 to 1966. The mean values were compared with Groves' model, and internal consistency tests were performed upon the statistics. Through application of the extrapolation procedure, the atmospheric structure of a stratospheric warming event is studied.

Graves, M. E.↗
NASA NTRS1978

16-38 micron spectroscopy of NGC 7027

Medium-resolution spectroscopy of the planetary nebula NGC 7027 over the wavelength range from 16 to 38 microns is reported which was performed from NASA's Kuiper Airborne Observatory. It is found that within the errors, the spectrum is smooth and has the shape of a dilute 130-K blackbody but falls below that curve at the longer wavelengths. The absence of two theoretically predicted features in the 16-40-micron band, a forbidden fine-structure line of O IV at 25.91 microns and a broad emission feature in the 22-35-micron region due to carbonate materials, is discussed; a lower limit of 25,000 per cu cm is placed on the electron density in the ionized region. A simple model involving small graphite grains at a temperature around 90 K is proposed to explain the observed featureless continuum. This model is shown to require a dust mass of about 0.025 solar mass and a gas mass of approximately 1 solar mass, which imply that most of this mass would be associated with the molecular cloud surrounding the ionized region.

Mccarthy, J. F.↗
NASA NTRS1980

Radar image preprocessing

Standard image processing techniques are not applicable to radar images because of the coherent nature of the sensor. Therefore there is a need to develop preprocessing techniques for radar images which will then allow these standard methods to be applied. A random field model for radar image data is developed. This model describes the image data as the result of a multiplicative-convolved process. Standard techniques, those based on additive noise and homomorphic processing are not directly applicable to this class of sensor data. Therefore, a minimum mean square error (MMSE) filter was designed to treat this class of sensor data. The resulting filter was implemented in an adaptive format to account for changes in local statistics and edges. A radar image processing technique which provides the MMSE estimate inside homogeneous areas and tends to preserve edge structure was the result of this study. Digitally correlated Seasat-A synthetic aperture radar (SAR) imagery was used to test the technique.

Frost, V. S.↗
NASA NTRS1989

Error analysis of finite element solutions for postbuckled cylinders

A general method of error analysis and correction is investigated for the discrete finite-element results for cylindrical shell structures. The method for error analysis is an adaptation of the method of successive approximation. When applied to the equilibrium equations of shell theory, successive approximations derive an approximate continuous solution from the discrete finite-element results. The advantage of this continuous solution is that it contains continuous partial derivatives of an order higher than the basis functions of the finite-element solution. Preliminary numerical results are presented in this paper for the error analysis of finite-element results for a postbuckled stiffened cylindrical panel modeled by a general purpose shell code. Numerical results from the method have previously been reported for postbuckled stiffened plates. A procedure for correcting the continuous approximate solution by Newton's method is outlined.

Sistla, Rajaram↗
NASA NTRS2010

The Influence of Friction Stir Weld Tool Form and Welding Parameters on Weld Structure and Properties: Nugget Bulge in Self-Reacting Friction Stir Welds

Although friction stir welding (FSW) was patented in 1991, process development has been based upon trial and error and the literature still exhibits little understanding of the mechanisms determining weld structure and properties. New concepts emerging from a better understanding of these mechanisms enhance the ability of FSW engineers to think about the FSW process in new ways, inevitably leading to advances in the technology. A kinematic approach in which the FSW flow process is decomposed into several simple flow components has been found to explain the basic structural features of FSW welds and to relate them to tool geometry and process parameters. Using this modelling approach, this study reports on a correlation between the features of the weld nugget, process parameters, weld tool geometry, and weld strength. This correlation presents a way to select process parameters for a given tool geometry so as to optimize weld strength. It also provides clues that may ultimately explain why the weld strength varies within the sample population.

Schneider, Judy↗
DOE OSTI2017

The Mira-Titan Universe. II. Matter Power Spectrum Emulation

We introduce a new cosmic emulator for the matter power spectrum covering eight cosmological parameters. Targeted at optical surveys, the emulator provides accurate predictions out to a wavenumber k ~ 5Mpc -1 and redshift z ≤ 2. Besides covering the standard set of CDM parameters, massive neutrinos and a dynamical dark energy of state are included. The emulator is built on a sample set of 36 cosmological models, carefully chosen to provide accurate predictions over the wide and large parameter space. For each model, we have performed a high-resolution simulation, augmented with sixteen medium-resolution simulations and TimeRG perturbation theory results to provide accurate coverage of a wide k-range; the dataset generated as part of this project is more than 1.2Pbyte. With the current set of simulated models, we achieve an accuracy of approximately 4%. Because the sampling approach used here has established convergence and error-control properties, follow-on results with more than a hundred cosmological models will soon achieve ~1% accuracy. We compare our approach with other prediction schemes that are based on halo model ideas and remapping approaches. The new emulator code is publicly available.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1991

Experimental study of adaptive pointing and tracking for large flexible space structures

This paper describes an experimental study of adaptive pointing and tracking control for flexible spacecraft conducted on a complex ground experiment facility. The algorithm used in this study is based on a multivariable direct model reference adaptive control law. Several experimental validation studies were performed earlier using this algorithm for vibration damping and robust regulation, with excellent results. The current work extends previous studies by addressing the pointing and tracking problem. As is consistent with an adaptive control framework, the plant is assumed to be poorly known to the extent that only system level knowledge of its dynamics is available. Explicit bounds on the steady-state pointing error are derived as functions of the adaptive controller design parameters. It is shown that good tracking performance can be achieved in an experimental setting by adjusting adaptive controller design weightings according to the guidelines indicated by the analytical expressions for the error.

Boussalis, D.↗