Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “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 1,171 records · Page 65
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Determination of transition metal ion distribution in cubic spinel Co{sub 1.5}Fe{sub 1.5}O{sub 4} using anomalous x-ray diffraction

We report anomalous x-ray diffraction studies on Co ferrite with composition Co{sub 1.5}Fe{sub 1.5}O{sub 4} to obtain the distribution of transition metal ions in tetrahedral and octahedral sites. We synthesize spinel oxide (Co{sub 1.5}Fe{sub 1.5}O{sub 4}) through co-precipitation and subsequent annealing route. The imaginary part (absorption) of the energy dependent anomalous form factor is measured and the real part is calculated theoretically through Kramers–Krönig transformation to analyze anomalous x-ray diffraction peak intensities. Fe and Co K-edge x-ray absorption near edge structure (XANES) spectra are used to estimate charge states of transition metals. Our analysis, within experimental errors, suggests 44% of the tetrahedral sites contain Co in +2 oxidation state and the rest 56% sites contain Fe in +2 and +3 oxidation states. Similarly, 47% of the octahedral sites contain Fe in +3 oxidation states, whereas, the rest of the sites contain Co in +2 and +3 oxidation states. While a distinct pre-edge feature in the Fe K-edge XANES is observed, Co pre-edge remains featureless. Implications of these results to magnetism are briefly discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Benchmarking machine learning strategies for phase-field problems

Abstract We present a comprehensive benchmarking framework for evaluating machine-learning approaches applied to phase-field problems. This framework focuses on four key analysis areas crucial for assessing the performance of such approaches in a systematic and structured way. Firstly, interpolation tasks are examined to identify trends in prediction accuracy and accumulation of error over simulation time. Secondly, extrapolation tasks are also evaluated according to the same metrics. Thirdly, the relationship between model performance and data requirements is investigated to understand the impact on predictions and robustness of these approaches. Finally, systematic errors are analyzed to identify specific events or inadvertent rare events triggering high errors. Quantitative metrics evaluating the local and global description of the microstructure evolution, along with other scalar metrics representative of phase-field problems, are used across these four analysis areas. This benchmarking framework provides a path to evaluate the effectiveness and limitations of machine-learning strategies applied to phase-field problems, ultimately facilitating their practical application.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Fault Modeling of Extreme Scale Applications Using Machine Learning

Faults are commonplace in large scale systems. These systems experience a variety of faults such as transient, permanent and intermittent. Multi-bit faults are typically not corrected by the hardware resulting in an error. Here, this paper attempts to answer an important question: Given a multi-bit fault in main memory, will it result in an application error — and hence a recovery algorithm should be invoked — or can it be safely ignored? We propose an application fault modeling methodology to answer this question. Given a fault signature (a set of attributes comprising of system and application state), we use machine learning to create a model which predicts whether a multibit permanent/transient main memory fault will likely result in error. We present the design elements such as the fault injection methodology for covering important data structures, the application and system attributes which should be used for learning the model, the supervised learning algorithms (and potentially ensembles), and important metrics. Lastly, we use three applications — NWChem, LULESH and SVM — as examples for demonstrating the effectiveness of the proposed fault modeling methodology.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Measuring the Error in Approximating the Sub-Level Set Topology of Sampled Scalar Data

This paper studies here the influence of the definition of neighborhoods and methods used for creating point connectivity on topological analysis of scalar functions. It is assumed that a scalar function is known only at a finite set of points with associated function values. In order to utilize topological approaches to analyze the scalar-valued point set, it is necessary to choose point neighborhoods and, usually, point connectivity to meaningfully determine critical-point behavior for the point set. Two distances are used to measure the difference in topology when different point neighborhoods and means to define connectivity are used: (i) the bottleneck distance for persistence diagrams and (ii) the distance between merge trees. Usually, these distances define how different scalar functions are with respect to their topology. These measures, when properly adapted to point sets coupled with a definition of neighborhood and connectivity, make it possible to understand how topological characteristics depend on connectivity. Noise is another aspect considered. Five types of neighborhoods and connectivity are discussed: (i) the Delaunay triangulation; (ii) the relative neighborhood graph; (iii) the Gabriel graph; (iv) the k-nearest-neighbor (KNN) neighborhood; and (v) the Vietoris–Rips complex. It is discussed in detail how topological characterizations depend on the chosen connectivity.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Osprey Framework v0.2.2

The Alpha Berkeley Framework is a software architecture for building agentic AI systems that coordinate multi-step workflows in scientific and industrial environments. It is based on a plan-first orchestration model, where natural language requests are translated into execution plans with explicit dependencies and optional human approval. The framework includes capability classification, which selects relevant tools on a per-task basis to keep orchestration efficient as the number of available tools grows. It incorporates task extraction methods that compress conversational context and integrate external resources such as databases, APIs, and knowledge bases into structured, machine-readable tasks. Execution is supported by modular services with checkpointing, artifact management, and error handling, allowing workflows to be paused, inspected, and resumed. The system is designed for deployment in production environments, supporting both local and containerized execution as well as integration with HPC clusters. Interfaces include command-line tools, browser-based workflows, and containerized services. The framework has been demonstrated in tutorial examples and deployed at the Advanced Light Source, where it coordinates accelerator control and analysis workflows.

Hellert, Thorsten [Lawrence Berkeley National Labo↗
DOE OSTI2026

OpenStudio®-MCP [SWR-26-035]

OpenStudio®-MCP is a Model Context Protocol (MCP) server that lets AI assistants perform building energy modeling through natural language. Rather than requiring users to learn the OpenStudio® SDK, EnergyPlus® scripting, or Ruby/Python automation, the server translates conversational requests into sequences of tool calls that create models, design HVAC systems, run simulations, and extract results — all within a single chat session. The server's 124 tools are organized into a skills architecture where each skill encapsulates a domain of building energy modeling (envelope, HVAC, loads, weather, simulation, results) behind typed, LLM-friendly interfaces. High-leverage operations like applying ASHRAE 90.1 baseline systems or generating standards-compliant typical buildings are exposed as single tool calls that internally wire dozens of OpenStudio® objects. Bundled measures from ComStock™ and Openstudio® -common-measures-gem are wrapped with dedicated tools and typed arguments rather than exposed through a generic measure interface, so AI models get consistent, error-resistant recipes without needing to discover measure arguments at runtime. A key design decision is structured results extraction: six SQL-based tools return surgical ~300–1,000 token responses (end-use breakdowns, envelope summaries, HVAC sizing, timeseries data) instead of requiring the AI to parse ~100K-token raw HTML reports, making iterative design exploration practical within context window limits. The codebase is designed as a reference implementation — explicit, well-commented, and modular — so that other simulation engines (EnergyPlus® standalone, TRNSYS, DOE-2) can use it as a template for building their own MCP servers.

Ball, Brian [National Laboratory of the Rockies (N↗
DOE OSTI2018

Data Evaluation of Actinide Cross Sections: 240 Am, 241 Am, and 242 Am

Evaluations for neutron-induced reactions on the isotopes 240 Am, 241 Am, and 242 Am were per formed by optimizing reaction-model calculations based on existing experimental data from both direct measurements and surrogate reactions. The evaluated data were based on results obtained from the LLNL reaction codes YAHFC and FRESCO using up-to-date nuclear models; including an improvement upon some previous treatments for inelastic processes. Nuclear reaction codes generated data for all relevant reaction channels, which were then translated into Generalized Nu clear Data Structure and LLNL’s Evaluated Neutron Data Libraries (ENDL). These data libraries were tested for potential errors and applied to verification and validation (V&V) tests suites where applicable for comparisons.

42 ENGINEERING↗
DOE OSTI2024

Accurate Ultrasonic Thickness Measurement for Arbitrary Time-Variant Thermal Profile

Ultrasonic thickness measurement of mechanical structures is one of the most popular and commonly used nondestructive methods for various kinds of process control and corrosion monitoring. With ultrasonic propagation speed being temperature-dependent, the thickness measurement can be performed reliably only when the thermal profile is completely known. Most conventional techniques assume the temperature of the test structure is uniform and at room temperature across its thickness. Such assumptions may lead to large errors in the thickness measurement, especially when there are significant temperature variations across the thickness. State-of-the-art techniques use external temperature measurements or implement iterative methods to compensate for the unknown thermal profiles. However, such techniques produce unsatisfactory results when the heat distribution is complex or varies rapidly with time. In this work, we propose a two-sensors technique, using both compressive and shear excitations, with a non-iterative rapid data processing method for accurate thickness measurement under arbitrary time-variant thermal profile. The independent behavior of shear and compressive waves is used to formulate a real-time thickness estimation technique. The developed technique is experimentally validated on a steel plate with fixed acoustic sensors. Test results show that the error in thickness estimation can be reduced by up to 98% compared to conventional thickness gauging methods.

36 MATERIALS SCIENCE↗
NASA NTRS1973

Currents in Florida lightning return strokes.

The transmission line return stroke model is used to derive individual current versus time wave forms from measured electric fields. A total of 98 strokes in 21 flashes at distances less than or equal to 10 km and 63 strokes in 18 flashes at distances between 10 and 32 km are analyzed for current wave shape and magnitude. For the closer strokes, return stroke velocity is also determined from the electric field wave forms. Eighteen detailed current and field wave forms and a statistical distribution of peak currents are presented. Return stroke channel currents are found to exhibit a sharp initial peak which currents measured in tall structures at the base of the lightning channel apparently do not exhibit. A complete discussion of errors is given.

Uman, M. A.↗
NASA NTRS1974

Carrier synchronization and detection of QASK signal sets

A carrier regeneration loop which generates highly coherent quadrature reference signals for quadrature amplitude-shift keying (QASK) demodulation is presented. The loop employs the principle of decision feedback and has a structure analogous to a decision feedback loop for quadriphase signals suggested earlier in the literature. The error probability performance of QASK is computed in the presence of the noisy carrier reference signals provided by the above loop. It is demonstrated that when the ratio of data rate to loop bandwidth is 50 or greater, then for all practical purposes, ideal QASK error probability performance is achieved.

Simon, M. K.↗
NASA NTRS1982

Documentation for the machine-readable version of the Uppsala general catalogue of galaxies

The machine-readable version of the catalog containing descriptions of galaxies, their surrounding areas, and position angles for flattened galaxies is described. In addition to the correction of several errors discovered in a previous computerized version, a few duplicate records were removed and the record structure was revised slightly to accommodate a large data value and to remove superfluous blanks.

Warren, W. H., Jr.↗
NASA NTRS1983

Deformable subreflector computed by geometric optics

Using a Cassegrainian geometry, the 64-meter antenna with its distorted paraboloidal reflecting surface is forced to produce a uniform phase wavefront by a pathlength-compensating subreflector. First, the computed distortion vectors at the joints or nodes of the main reflector structure supporting the surface panels are best fitted to a paraboloid. Second, the resulting residual distortion errors are used to determine a compensating subreflector surface by ray tracing using geometric optics principles. Third, the totally corrected subreflector surface is defined by the normal directions and distances to the surface of the original symmetric hyperboloid for the purpose of evaluation. Finally, contour maps of distortions of the paraboloid reflector and the compensating subreflector are presented. A field-measured check of the subreflector in focused position as computed by the described methodology is also presented for the antenna position at horizon look with the geometry at 45 degrees elevation.

Katow, M. S.↗
NASA NTRS1985

Compensator development and examination of performance and robustness

This research focuses on the development of compensators to control the mean square surface error of a wraprib antenna. The methodology is as follows: A model of appropriate size and structure is developed by looking at the convergence of functional gains for control and estimation. Then an LQG compensator is designed using this model. Finally, the compensator is simplified using balanced realization theory. In the conventional approach for compensator design, there is no mechanism for ensuring that the model is adequate for designing a compensator which will achieve the desired level of performance. It is shown here that both the model order and compensator order are directly related to the closed loop performance requirements for the system.

Source record↗
NASA NTRS1985

Recent Developments in Nonlinear Normal Mode Initialization

The importance of a balanced initial condition upon GLAS GCM forecasts and assimilation cycles was assessed. An effort to combine previous work on normal mode initialization at GLA is underway to develop an initialization process for the production version of the GLAS 4th order GCM. The major aspects of this work fall into two parts: vectorization of the linear projector code and the insertion of the mode projector and Machenhauer iteration algorithm into the full GLAS GCM. Memory and paging constraints place restrictions on the number of horizontal modes stored for initialization purposes, and on the manner in which they are stored. Only the first five vertical structures of the gravity modes are used. Differing phase and normalization conventions provided many elusive coding errors. A Machenhauer nonlinear normal mode initialization technique is used. This method entails the insertion of a modified version of the mode projector into the full GCM, and the modification of the GCM to allow for iterative calls to the projector.

Bloom, S. C.↗
NASA NTRS1987

Fine-scale motion in the central Orion nebula

The inner region of M42 has been mapped in the O III N1 forbidden line at an unprecedented combination of velocity and spatial resolution and photometric accuracy. Three separate velocity systems along the line of sight are identified. Differential mass flow is present in two of these systems. All three systems show random fluctuations in velocity well above their measurement errors. The point-by-point velocities are used to determine the diagnostic statistical parameter, the structure function. The random motions show correlation with spatial separation, as expected for turbulence; but comparison with the predictions of classical theory for nebular turbulence shows poor agreement. If Kolmogorov (1941, 1942) theory applies, then the energy must be input at many scales.

Castaneda, Hector O.↗
NASA NTRS1990

An optimal estimation approach for enhanced identification of large space structures

A very robust technique for the realization/identification of structural dynamic systems is presented. This methodology combines the eigensystem realization algorithm (ERA) and minimum model error (MME) techniques to develop an extremely robust algorithm able to distinguish modes whose amplitudes are small fractions of the noise amplitude. As the amplitude of the noise grows, the enhanced robustness of the combined ERA/MME algorithm becomes more significant. This is a result of the MME being able to produce simulated measurements of much greater accuracy than the original measurements, for input to the ERA. The new method was able to determine correct model order at noise levels many times higher than the original ERA for the realization problem in which the model order must be derived.

Mook, D. Joseph↗
NASA NTRS1991

Logic flowgraph methodology - A tool for modeling embedded systems

The logic flowgraph methodology (LFM), a method for modeling hardware in terms of its process parameters, has been extended to form an analytical tool for the analysis of integrated (hardware/software) embedded systems. In the software part of a given embedded system model, timing and the control flow among different software components are modeled by augmenting LFM with modified Petrinet structures. The objective of the use of such an augmented LFM model is to uncover possible errors and the potential for unanticipated software/hardware interactions. This is done by backtracking through the augmented LFM mode according to established procedures which allow the semiautomated construction of fault trees for any chosen state of the embedded system (top event). These fault trees, in turn, produce the possible combinations of lower-level states (events) that may lead to the top event.

Muthukumar, C. T.↗