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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.

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At least 955 records · Page 53
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

bnl/pub-Maffettone_2020_08

The application of the XCA package as first demonstrated in aXiv:2008.00283. ABSTRACT: The discovery of new structural and functional materials is driven by phase identification, often using X-ray diffraction (XRD). Automation has accelerated the rate of XRD measurements, greatly outpacing XRD analysis techniques that remain manual, time consuming, error prone, and impossible to scale. With the advent of autonomous robotic scientists or self-driving labs, contemporary techniques prohibit the integration of XRD. Here, we describe a computer program for the autonomous characterization of XRD data, driven by artificial intelligence (AI), for the discovery of new materials. Starting from structural databases, we train an ensemble model using a physically accurate synthetic dataset, which output probabilistic classifications --- rather than absolutes --- to overcome the overconfidence in traditional neural networks. This AI agent behaves as a companion to the researcher, improving accuracy and offering unprecedented time savings, and is demonstrated on a diverse set of organic and inorganic materials challenges. This innovation is directly applicable to inverse design approaches, robotic discovery systems, and can be immediately considered for other forms of characterization such as spectroscopy and the pair distribution function.

Maffettone, PhillipM [Brookhaven National Lab. (BN↗
DOE OSTI2018

Measuring the Viewing Angle of GW170817 with Electromagnetic and Gravitational Waves

The joint detection of gravitational waves (GWs) and electromagnetic (EM) radiation from the binary neutron star merger GW170817 ushered in a new era of multi-messenger astronomy. Joint GW–EM observations can be used to measure the parameters of the binary with better precision than either observation alone. Here, we use joint GW–EM observations to measure the viewing angle of GW170817, the angle between the binary's angular momentum and the line of sight. We combine a direct measurement of the distance to the host galaxy of GW170817 (NGC 4993) of 40.7 ± 2.36 Mpc with the Laser Interferometer Gravitational-wave Observatory (LIGO)/Virgo GW data and find that the viewing angle is ${32}_{-13}^{+10}\,\pm 1.7$ degrees (90% confidence, statistical, and systematic errors). We place a conservative lower limit on the viewing angle of ≥13°, which is robust to the choice of prior. This measurement provides a constraint on models of the prompt γ-ray and radio/X-ray afterglow emission associated with the merger; for example, it is consistent with the off-axis viewing angle inferred for a structured jet model. Lastly, we provide for the first time the full posterior samples from Bayesian parameter estimation of LIGO/Virgo data to enable further analysis by the community.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1976

Development of a methodology for classifying software errors

A mathematical formalization of the intuition behind classification of software errors is devised and then extended to a classification discipline: Every classification scheme should have an easily discernible mathematical structure and certain properties of the scheme should be decidable (although whether or not these properties hold is relative to the intended use of the scheme). Classification of errors then becomes an iterative process of generalization from actual errors to terms defining the errors together with adjustment of definitions according to the classification discipline. Alternatively, whenever possible, small scale models may be built to give more substance to the definitions. The classification discipline and the difficulties of definition are illustrated by examples of classification schemes from the literature and a new study of observed errors in published papers of programming methodologies.

Gerhart, S. L.↗
NASA NTRS1978

Structural design of a 64-meter low-cost antenna

The computer model of a 64 m ground antenna was generated by 1108 software. The reflector and alidade model was iteratively designed and analyzed by the JPL/IDEAS program, which minimized the distortion RMS with respect to the structural weight. Curves of values describing the optimizing processes are presented, functional aspects of the structural elements are defined, and detail descriptions of the design equations for stress calculations are included. Computed data used for calculating the RF boresight error and natural frequency answers are also included.

Katow, M. S.↗
NASA NTRS1984

Methods for analysis of cracks in three-dimensional solids

Analytical and numerical methods evaluating the stress-intensity factors for three-dimensional cracks in solids are presented, with reference to fatigue failure in aerospace structures. The exact solutions for embedded elliptical and circular cracks in infinite solids, and the approximate methods, including the finite-element, the boundary-integral equation, the line-spring models, and the mixed methods are discussed. Among the mixed methods, the superposition of analytical and finite element methods, the stress-difference, the discretization-error, the alternating, and the finite element-alternating methods are reviewed. Comparison of the stress-intensity factor solutions for some three-dimensional crack configurations showed good agreement. Thus, the choice of a particular method in evaluating the stress-intensity factor is limited only to the availability of resources and computer programs.

Raju, I. S.↗
NASA NTRS1996

Computer-Aided Process Model For Carbon/Phenolic Materials

Computer program implements thermochemical model of processing of carbon-fiber/phenolic-matrix composite materials into molded parts of various sizes and shapes. Directed toward improving fabrication of rocket-engine-nozzle parts, also used to optimize fabrication of other structural components, and material-property parameters changed to apply to other materials. Reduces costs by reducing amount of laboratory trial and error needed to optimize curing processes and to predict properties of cured parts.

Letson, Mischell A.↗
NASA NTRS2017

Analyzing the Operational Behavior of the Alignment and Phasing System of the Thirty Meter Telescope using SysML

The Alignment and Phasing System (APS) of the Thirty Meter Telescope (TMT) is responsible for positioning individual segments of the primary mirror, as well as the secondary and tertiary mirrors. Given its essential role, understanding the as-speci ed behavior and verifying related requirements is vital to the correct operation of the TMT. Analyzing the behavior of APS is challenging due to the variety of interactions with other subsystems. This paper presents results from developing an integrated system model that captures the structure, behavior, and requirements in a formal modeling language to enable automated veri cation using appropriate solvers. Speci cally, demonstrated and discussed are the results of applying a Systems Modeling Language (SysMLTM) based approach in which operational modes, behavior speci cations and use case scenarios are used for the purpose of verifying requirements on timing, power, and pointing error through system-level simulation using a single, integrated model.

Troy, Mitchell↗
NASA NTRS2020

Structural Model Tuning Tool: User's Reference Manual

This report presents an efficient approach for tuning finite element models to match the measured ground vibration test and static test data. Frequencies, mode shapes, total weight, location of the center of gravity, and static deformation computed from the finite element model are matched to the measured data. The model tuning procedure used in this work is based on solving an optimization problem in which the errors for the considered metrics, between the finite element prediction and the measured data, are minimized. Analytical sensitivity values of performance indices are computed using the NASTRAN-generated sensitivity values together with the in-house computer codes, which allow for faster computational time and the use of gradient-based optimizers. The method is applied to the Aerostructures Test Wing IV model. The study shows that the military standard and the National Aeronautics and Space Administration standard for comparing analytical and experimental modal data are all satisfied. The final finite element model correlates well with the test data. The flutter speed decreases by 8.91 percent after model tuning compared with the original Aerostructures Test Wing IV design.

Chan-gi Pak↗
NASA NTRSDate not supplied

A Model-Based Framework for NASA Science Mission Formulation

This paper details an effort to implement NASA systems engineering standards and practices using a Digital System Model (DSM), which we also refer to as the system architecture model (SAM). Creating a SAM at the beginning of a design effort helps systems engineer identify errors, inconsistencies, and miscommunications as early as possible. Such issues can then be resolved before it becomes costly and requires significant rework to do so. A pre-formulation SAM also enables advanced trade studies at the earliest stage of concept development. This results in “win-wins” where architecture changes can reduce cost without decreasing effectiveness, or increase effectiveness without increasing cost. SAMs also streamline the creation of project documentation and facilitate superior dialogue between science, engineering, and management stakeholders. Common artifacts such as Master Equipment Lists (MELs), Science Traceability Matrices (STMs), and Mission Traceability Matrices (MTMs), can be automatically maintained through requirements and structural models in the SAM. Key performance parameters (and changes to them) can be tied to simulations in the SAM, allowing far more rapid and extensive trade space exploration. As will be shown in this work, these advantages have been realized for the first time in an actual NASA Goddard Space Flight Center (GSFC) pre-phase A and phase A concept study. Modelbased design tools have been developed in a general, modular manner to maximize reuse on future programs. Focus is placed on structural and requirements architecture modeling. Data is ingested into the SAM from existing discipline model outputs (e.g. MS Excel spreadsheets) and used to update a SysML structural model. A mission requirements model is created within the SAM, containing mission specific as well as standard GSFC mission requirements. With the linked requirements model and structural model, automated compliance checking will be performed as mission parameters evolve without the need for discipline engineers to work directly with the SAM in SysML.

MBSE↗
DOE OSTI2026

The ballad of LLM agents: philosophical reasoning for chemistry

Large language models (LLMs) show remarkable potential for scientific reasoning but often produce unreliable or scientifically unactionable outputs when faced with multi-step logic, domain grounding, and interpretability challenges, especially in complex fields like chemistry and materials science. Here, we introduce a framework of philosophical reasoning agents, inspired by canonical thinkers such as Socrates, Descartes, Kant, and Hume, to guide LLM behavior via structured prompt engineering. These agents embody distinct reasoning paradigms (dialectical inquiry, deductive logic, rule-based judgment, and empirical validation) and are evaluated across multiple chemistry subdomains, physical, analytical, general, inorganic, and organic chemistry, using the ChemBench benchmark. Our agentic prompting approach yields substantial accuracy gains on open-ended numerical chemistry questions, with gains of +11.5 percentage points for GPT-4o with Hume, +4.5 percentage points for GPT-5 with Kant, and +21.8 percentage points for GPT-5.1 with Socrates at the strict 1% error threshold, relative to the corresponding base models. Beyond accuracy, we observe benchmark-level model–agent performance patterns, suggesting that different prompting styles interact differently with each base model. These findings demonstrate that embedding philosophy-of-science principles into multi-agent frameworks can improve and produce interpretable, adaptive, and domain-aligned scientific LLMs.

Harb, Hassan [Argonne National Laboratory (ANL), A↗
DOE OSTI2024

Active learning for SNAP interatomic potentials via Bayesian predictive uncertainty

Bayesian inference with a simple Gaussian error model is used to efficiently compute prediction variances for energies, forces, and stresses in the linear SNAP interatomic potential. Here, the prediction variance is shown to have a strong correlation with the absolute error over approximately 24 orders of magnitude. Using this prediction variance, an active learning algorithm is constructed to iteratively train a potential by selecting the structures with the most uncertain properties from a pool of candidate structures. The relative importance of the energy, force, and stress errors in the objective function is shown to have a strong impact upon the trajectory of their respective net error metrics when running the active learning algorithm. Batched training of different batch sizes is also tested against singular structure updates, and it is found that batches can be used to significantly reduce the number of retraining steps required with only minor impact on the active learning trajectory.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Data-driven modeling and control of an X-ray bimorph adaptive mirror

Adaptive X-ray mirrors are being adopted on high-coherent-flux synchrotron and X-ray free-electron laser beamlines where dynamic phase control and aberration compensation are necessary to preserve wavefront quality from source to sample, yet challenging to achieve. Additional difficulties arise from the inability to continuously probe the wavefront in this context, which demands methods of control that require little to no feedback. In this work, a data-driven approach to the control of adaptive X-ray optics with piezo-bimorph actuators is demonstrated. This approach approximates the non-linear system dynamics with a discrete-time model using random mirror shapes and interferometric measurements as training data. For mirrors of this type, prior states and voltage inputs affect the shape-change trajectory, and therefore must be included in the model. Without the need for assumed physical models of the mirror's behavior, the generality of the neural network structure accommodates drift, creep and hysteresis, and enables a control algorithm that achieves shape control and stability below 2 nm RMS. Using a prototype mirror and ex situ metrology, it is shown that the accuracy of our trained model enables open-loop shape control across a diverse set of states and that the control algorithm achieves shape error magnitudes that fall within diffraction-limited performance.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Convex Q-Learning in Continuous Time with Application to Dispatch of Distributed Energy Resources

Convex Q-learning is a recent approach to reinforcement learning, motivated by the possibility of a firmer theory for convergence, and the possibility of making use of greater a priori knowledge regarding policy or value function structure. This paper explores algorithm design in the continuous time domain, with a finite-horizon optimal control objective. The main contributions are (i) The new Q-ODE: a model-free characterization of the Hamilton-Jacobi-Bellman equation. (ii) A formulation of Convex Q-learning that avoids approximations appearing in prior work. The Bellman error used in the algorithm is defined by filtered measurements, which is necessary in the presence of measurement noise. (iii) Convex Q-learning with linear function approximation is a convex program. It is shown that the constraint region is bounded, subject to an exploration condition on the training input. (iv) The theory is illustrated in application to resource allocation for distributed energy resources, for which the theory is ideally suited.

Lu, Fan↗
DOE OSTI2017

Magellan/M2FS Spectroscopy of Galaxy Clusters: Stellar Population Model and Application to Abell 267

We report the results of a pilot program to use the Magellan/M2FS spectrograph to survey the galactic populations and internal kinematics of galaxy clusters. For this initial study, we present spectroscopic measurements for 223 quiescent galaxies observed along the line of sight of the galaxy cluster Abell 267 (z∼0.23). We develop a Bayesian method for modeling the integrated light from each galaxy as a simple stellar population, with free parameters that specify the redshift (v{sub los}/c) and characteristic age, metallicity ([Fe/H]), alpha-abundance ([α/Fe]), and internal velocity dispersion (σ{sub int}) for individual galaxies. Parameter estimates derived from our 1.5 hr observation of A267 have median random errors of σ{sub v{sub l{sub o{sub s}}}}=20 km s{sup −1}, σ{sub Age}=1.2 Gyr, σ{sub [Fe/H]}=0.11 dex, σ{sub [α/Fe]}=0.07 dex, and σ{sub σ{sub i{sub n{sub t}}}}=20 km s{sup −1}. In a companion paper, we use these results to model the structure and internal kinematics of A267.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1974

Measurement of density and porosity of lunar rocks based on samples of Luna 16 automatic lunar station

Three fragments of holocrystalline igneous rocks of the gabbro type, weighing 30 to 50 mg each, were investigated. The density of the fragments was established with a mercury pycnometer and was found to be 3.05 to 3.12 g/cu cm, with a relative error not more than 2 percent. The porosity was found for the difference between the volumes determined with the mercury and with the gas techniques; for all three samples together it was 13 percent, and the error of determination was 70 percent owing to the small volumes. It can be anticipated that the porosity of the rock in bulk will be higher than the value obtained based on small fragments. The porosity of lunar rocks can markedly affect the isostatic distribution of rocks and must be taken into account when developing models of lunar structure.

Volynets, V. F.↗
NASA NTRS1980

Digital preprocessing of SEASAT imagery

A model for radar image data is derived for use in developing enhancement techniques. This model describes the image data as the result of a multiplicative-convolved noise process. This information is then used to design a minimum mean square error (MMSE) filter. The resulting filter is implemented adaptively to change with local statistics. A radar image processing technique which provides the MMSE estimate inside homogeneous areas and tends to preserve edge structure is thus developed. This technique has been implemented and tested using digitally correlated SEASAT-A synthetic aperture radar (SAR) imagery.

Frost, V. S.↗
NASA NTRS1984

Maneuvering of large flexible space antennas using optimal discrete-time controllers

The problem of maneuvering large space structures is formulated as a discrete-time, finite-duration optimal regulator problem. Two methods are considered for minimizing the elastic motion during the maneuver. The methods are applied to retargetting maneuver of a large space antenna, and the results are compared with those obtained using bang-bang control. The optimal regulator designed using the model error sensitivity supression method gives the best performance.

Joshi, S. M.↗
NASA NTRS1989

Sensor failure detection using generalized parity relations for flexible structures

Analytical redundancy may be preferable to hardware redundancy in failure detection/isolation tasks for such large-scale systems as space structures. Generalized single-sensor parity relations are presently applied to this problem; they are noted to yield a very simple isolation logic, and their generation is found to be extremely rapid, even in the case of extremely complex systems, provided only that the eigenstructure of the system be known. Their implementation is, however, extremely sensitive to modeling errors and noise.

Mercadal, Mathieu↗