Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “model diagnostics and development”

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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

The NASA Ames Aerothermodynamics Branch (Code TSA)

The NASA Ames Aerothermodynamics Branch provides NASA with integrated modeling, simulation, and test capabilities in the areas of aerothermodynamics, shock layer radiation, and entry system design. Our core capabilities include CFD simulation for entry vehicles at hypersonic velocities, including arc jet facility flow modeling and characterization; modeling and testing of shock layer kinetics and radiation; development of flow-field diagnostic techniques; and aero- and aerothermal testing via ballistic ranges. This presentation provides a brief technical introduction to the branches work and our capabilities in these areas.

Aerothermodynamics↗
NASA NTRS1992

The impact of dynamic data assimilation on the numerical simulations of the QE II cyclone and an analysis of the jet streak influencing the precyclogenetic environment

A mesoscale numerical model is combined with a dynamic data assimilation via Newtonian relaxation, or 'nudging', to provide initial conditions for subsequent simulations of the QE II cyclone. Both the nudging technique and the inclusion of supplementary data are shown to have a large positive impact on the simulation of the QE II cyclone during the initial phase of rapid cyclone development. Within the initial development period (from 1200 to 1800 UTC 9 September 1978), the dynamic assimilation of operational and bogus data yields a coherent two-layer divergence pattern that is not well defined in the model run using only the operational data and static initialization. Diagnostic analysis based on the simulations show that the initial development of the QE II storm between 0000 UTC 9 September and 0000 UTC 10 September was embedded within an indirect circulation of an intense 300-hPa jet streak, was related to baroclinic processes extending throughout a deep portion of the troposphere, and was associated with a classic two-layer mass-divergence profile expected for an extratropical cyclone.

Manobianco, John↗
DOE OSTI2020

Development of Prognostic Models Using Plant Asset Data

The recent growth of machine learning and artificial intelligence technologies provides opportunities for leveraging data-driven algorithms to address the problems of diagnostics and prognostics in the nuclear power industry. The use of machine learning and other statistical methods as prognostic models is of particular interest in the nuclear industry to accurately predict future equipment or plant state given a set of measurements. Such predictive capability will enable predictive assessment of component condition and remaining life and allow for condition-based predictive maintenance. The resulting optimization of maintenance scheduling and reduction in unnecessary maintenance activities will lower overall maintenance costs and improve the economics of nuclear power. This report discusses the various aspects of data processing and model development that are likely to influence the performance of prognostic models. Data from a boiling-water reactor was used to evaluate several prognostic models to identify key considerations for developing such models to predict data-driven plant state and equipment degradation condition. Preliminary results indicate the need for data sets that are relevant to the problem at hand and contain signatures that may be correlated to the prediction problem. Assuming such data exist, development of prognostic models using data-driven methods requires an understanding of the various sources of influence on the prediction accuracy (such as the model architecture, data preprocessing approaches, and potentially external factors influencing the equipment or plant system under assessment). Ongoing research is evaluating these factors in greater detail and examining techniques for calculating prediction uncertainty bounds.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
NASA NTRS1995

Some Progress in Large-Eddy Simulation using the 3-D Vortex Particle Method

This two-month visit at CTR was devoted to investigating possibilities in LES modeling in the context of the 3-D vortex particle method (=vortex element method, VEM) for unbounded flows. A dedicated code was developed for that purpose. Although O(N(sup 2)) and thus slow, it offers the advantage that it can easily be modified to try out many ideas on problems involving up to N approx. 10(exp 4) particles. Energy spectrums (which require O(N(sup 2)) operations per wavenumber) are also computed. Progress was realized in the following areas: particle redistribution schemes, relaxation schemes to maintain the solenoidal condition on the particle vorticity field, simple LES models and their VEM extension, possible new avenues in LES. Model problems that involve strong interaction between vortex tubes were computed, together with diagnostics: total vorticity, linear and angular impulse, energy and energy spectrum, enstrophy. More work is needed, however, especially regarding relaxation schemes and further validation and development of LES models for VEM. Finally, what works well will eventually have to be incorporated into the fast parallel tree code.

Winckelmans, G. S.↗
DOE OSTI2023

IDAES-PSE 2.2.0 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. New features in the 2.2 release include: DiagnosticsToolbox DiagnosticsToolbox (idaes.core.util.model_diagnostics. DiagnosticsToolbox is a new self-guiding toolbox for assisting with diagnosing modeling issues. The toolbox contains a wide range of tools for identifying common modeling issues and conveying these to the user, and more features will be added in the coming months. To try the new toolbox, use the following steps: from idaes.core.util import DiagnosticsToolbox Build an instance of your model Ensure your models has zero degrees of freedom (as best you can) dt = DiagnosticsToolbox(model) dt.report_structural_issues() Follow the prompts Deprecations DegeneracyHunter is being deprecated in favor of the new DiagnosticsToolbox. The features and capabilities of DegeneracyHunter will be moved over to the DiagnositcsToolbox in the coming months. Removal of usage of Pyomo's expr.current due to deprecation upstream. Removed support for radial basis functions in ALAMOpy as these did not work in the current implementation. Those wishing to use radial basis functions should use Pysmo instead. New Capabilities MSContactor model for unit operations involving mass transfer between 2 or more streams, such as membrane, solvent extraction and solids leaching operations. Other Improvements Improved formulation for solubility products with additional parameters for better scaling of terms Better backward compatibility, verification and robustness testing of core models and APIs Added support for Separator models without energy balances

DiagnosticsToolbox↗
DOE OSTI2023

Reconstruction of tokamak plasma safety factor profile using deep learning

Abstract The motional Stark effect (MSE) diagnostic has been a standard measurement for the magnetic field line pitch angle in tokamaks that are equipped with neutral beams. However, the MSE data are not always available due to experimental constraints, especially in future devices without neutral beams. Here we develop a deep-learning based model (SGTC-QR) that can reconstruct the safety factor profile without the MSE diagnostic to mimic the traditional equilibrium reconstruction with the MSE constraint. The model demonstrates promising performance, and the sub-millisecond inference time is compatible with the real-time plasma control system.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

The E3SM Diagnostics Package (E3SM Diags v2.7): a Python-based diagnostics package for Earth system model evaluation

Abstract. The E3SM Diagnostics Package (E3SM Diags) is a modern, Python-based Earth system model (ESM) evaluation tool (with Python module name e3sm_diags), developed to support the Department of Energy (DOE) Energy Exascale Earth System Model (E3SM). E3SM Diags provides a wide suite of tools for evaluating native E3SM output, as well as ESM data on regular latitude–longitude grids, including output from Coupled Model Intercomparison Project (CMIP) class models. E3SM Diags is modeled after the National Center for Atmospheric Research (NCAR) Atmosphere Model Working Group (AMWG, 2022) diagnostics package. In its version 1 release, E3SM Diags included a set of core essential diagnostics to evaluate the mean physical climate from model simulations. As of version 2.7, more process-oriented and phenomenon-based evaluation diagnostics have been implemented, such as analysis of the quasi-biennial oscillation (QBO), the El Niño–Southern Oscillation (ENSO), streamflow, the diurnal cycle of precipitation, tropical cyclones, ozone and aerosol properties. An in situ dataset from DOE's Atmospheric Radiation Measurement (ARM) program has been integrated into the package for evaluating the representation of simulated cloud and precipitation processes. This tool is designed with enough flexibility to allow for the addition of new observational datasets and new diagnostic algorithms. Additional features include customizable figures; streamlined installation, configuration and execution; and multiprocessing for fast computation. The package uses an up-to-date observational data repository maintained by its developers, where recent datasets are added to the repository as they become available. Finally, several applications for the E3SM Diags module were introduced to fit a diverse set of use cases from the scientific community.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Ohm’s Law, the Reconnection Rate, and Energy Conversion in Collisionless Magnetic Reconnection

Magnetic reconnection is a ubiquitous plasma process that transforms magnetic energy into particle energy during eruptive events throughout the universe. Reconnection not only converts energy during solar flares and geomagnetic substorms that drive space weather near Earth, but it may also play critical roles in the high energy emissions from the magnetospheres of neutron stars and black holes. In this review article, we focus on collisionless plasmas that are most relevant to reconnection in many space and astrophysical plasmas. Guided by first-principles kinetic simulations and spaceborne in-situ observations, we highlight the most recent progress in understanding this fundamental plasma process. We start by discussing the non-ideal electric field in the generalized Ohm’s law that breaks the frozen-in flux condition in ideal magnetohydrodynamics and allows magnetic reconnection to occur. We point out that this same reconnection electric field also plays an important role in sustaining the current and pressure in the current sheet and then discuss the determination of its magnitude (i.e., the reconnection rate), based on force balance and energy conservation. This approach to determining the reconnection rate is applied to kinetic current sheets with a wide variety of magnetic geometries, parameters, and background conditions. We also briefly review the key diagnostics and modeling of energy conversion around the reconnection diffusion region, seeking insights from recently developed theories. Finally, future prospects and open questions are discussed.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

IDAES-PSE 2.3.0 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.. New Features and Models • New diagnostics toolboxes and examples o Tutorial for using the DiagnosticsToolbox o Methods to identify potential evaluation errors in models o SVDToolbox for performing singular value decomposition analysis on models to identify possible degeneracies and poor scaling o DegeneracyHunter for identifying irreducible degenerate sets in models • Model for solid-liquid separation which takes two inputs (solid and liquid streams) and produces three outlets (solids, liquid entrained with solids and pure liquid) • Example of temperature swing adsorption in models_extra Deprecation Warnings • With the update to Pyomo 6.7.0, the plate heat exchanger model has begun failing tests on some CI platforms. If this is not addressed by the February release, this model may be removed due to failing tests. See #1294. Offers to help identify the cause and fix this issue are welcome. Improvements and bug fixes • Fixed oversight which precluded using Mixer and Separator models when inherent reactions were present in property package • Added reporting methods to the MSContactor model • Minor corrections in some examples where values were being fixed outside of declared variable bounds

DiagnosticsToolbox,IDAES,PSE,Process Systems Engin↗
NASA NTRS1987

Interactive plotting of NASTRAN data on microcomputers

A microcomputer based program has been developed to aid in the development of NASTRAN models. The program reads in the complete NASTRAN data deck, produces a diagnostic print file, and then allows the user to view the model in an interactive mode. The program runs on a wide variety of hardware by making use of the Virtual Device Interface.

Norton, Robert L.↗
NASA NTRS1986

A flight expert system (FLES) for on-board fault monitoring and diagnosis

The increasing complexity of modern aircraft creates a need for a larger number of caution and warning devices. But more alerts require more memorization and higher work loads for the pilot and tend to induce a higher probability of errors. Therefore, an architecture for a flight expert system (FLES) to assist pilots in monitoring, diagnosing and recovering from in-flight faults has been developed. A prototype of FLES has been implemented. A sensor simulation model was developed and employed to provide FLES with the airplane status information during the diagnostic process. The simulator is based partly on the Lockheed Advanced Concept System (ACS), a future generation airplane, and partly on the Boeing 737, an existing airplane. A distinction between two types of faults, maladjustments and malfunctions, has led us to take two approaches to fault diagnosis. These approaches are evident in two FLES subsystems: the flight phase monitor and the sensor interrupt handler. The specific problem addressed in these subsystems has been that of integrating information received from multiple sensors with domain knowledge in order to assess abnormal situations during airplane flight. This paper describes the reasons for handling malfunctions and maladjustments separately and the use of domain knowledge in the diagnosis of each.

Ali, M.↗
NASA NTRS1995

Modeling and simulation of a turbulent far wake

Work continued on two projects which had been started during previous years. Both projects involve calculations of the subsonic, turbulent far wake of a two-dimensional object at a Reynolds number of 1000 (based on wake momentum thickness). This flow was used as a test case for direct comparison of various turbulence models and a direct numerical simulations (DNS) of this flow were undertaken. In the turbulence model comparison studies, for any particular model tested, a unique self-similar solution was obtained far enough downstream, regardless of inlet conditions. Furthermore, different turbulence models led to different far-wake equilibrium solutions. No turbulence model could correctly predict all features of the turbulent far wake. For example, the spreading rate and turbulent shear stresses were underpredicted by all the standard models (both two-equation and full Reynolds stress models). In cases where a more correct spreading rate was achieved, it was at the expense of the turbulent kinetic energy, which was overpredicted. In general, the Algebraic Dissipation Rate Model of Gatski and Speziale, 1992, when added to any of the standard models, improved the results dramatically. Also, full Reynolds stress closure models did a much better job at predicting the shapes of both the mean and turbulence profiles, but the spreading rate was not significantly improved over that predicted by the simpler two-equation models. There are two main conclusions from these studies: First, in a comparison such as this, it is not enough to compare just one parameter, like the spreading rate. A good prediction for one parameter does not necessarily imply good predictions for all parameters in a flow. Second, since no turbulence model could correctly predict the turbulent far wake, much of the important physics of turbulent free shear flows is apparently lost by the assumptions inherent in today's methods of turbulence modeling; turbulence models must be improved. Direct simulations of this flow were begun last year in order to provide a data base through which some of the deficiencies of the existing turbulence models could be identified. Quantities such as the pressure-strain correlation, turbulent diffusion, and the dissipation rate tensor can be easily calculated from the DNS results, whereas these quantities are nearly impossible to measure experimentally. Improvements to existing turbulence models (and development of new models) require knowledge about flow quantities such as these. During this summer, diagnostics codes were written which will calculate the parameters mentioned above, along with other single-point and multi-point statistics. The DNS calculations are still in progress at the time of this writing. When these calculations are complete, the diagnostics codes will be applied so that the results can aid turbulence modelers. In addition, the results will show whether or not there exists a universal equilibrium turbulent far wake, independent of initial conditions.

Cimbala, John M.↗
NASA NTRS2003

Experiments And Model Development For The Investigation Of Sooting And Radiation Effects In Microgravity Droplet Combustion

This study involves flight experiments (for droplets between 1.5 to 5 mm) and supportive ground-based experiments, with concurrent numerical model development and validation. The experiments involve two fuels: n-heptane, and ethanol. The diagnostic measurements include light extinction for soot volume fraction, two-wavelength pyrometry and thin-filament pyrometry for temperature, spectral detection for OH chemiluminescence, broadband radiometry for flame emission, and thermophoretic sampling with subsequent transmission electron microscopy for soot aerosol property calculations.

Yozgatligil, Ahmet↗
DOE OSTI2024

Status of the Spallation Neutron Source beam test facility and progress of beam dynamics studies

The Spallation Neutron Source (SNS) Beam Test Facility (BTF) supports the study of beam dynamics in the front end of a high power LINAC. The BTF combines a replica of the SNS front end, including nearly-identical ion source, RFQ and MEBT, with extensive phase space diagnostics and a FODO transport line. Diagnostic capabilities include direct measurement of 6D phase space distribution and detection of halo distributions to a sensitivity of greater than one part-per-million. The goal of on-going BTF studies is to demonstrate accurate particle-in-cell modeling of halo growth and evolution by leveraging unprecedented accuracy in the description of the initial beam distribution. This work is motivated by operational experience at the SNS, which currently operates with beam loss that cannot be described by any model. This paper summarizes progress in the BTF beam study program as well as diagnostics development and recent upgrades to the beamline configuration.

Ruisard, Kiersten↗
NASA NTRS2012

Implementation of an Integrated On-Board Aircraft Engine Diagnostic Architecture

An on-board diagnostic architecture for aircraft turbofan engine performance trending, parameter estimation, and gas-path fault detection and isolation has been developed and evaluated in a simulation environment. The architecture incorporates two independent models: a realtime self-tuning performance model providing parameter estimates and a performance baseline model for diagnostic purposes reflecting long-term engine degradation trends. This architecture was evaluated using flight profiles generated from a nonlinear model with realistic fleet engine health degradation distributions and sensor noise. The architecture was found to produce acceptable estimates of engine health and unmeasured parameters, and the integrated diagnostic algorithms were able to perform correct fault isolation in approximately 70 percent of the tested cases

Armstrong, Jeffrey B.↗
NASA NTRS1999

Ion Thruster and Power Processor Developed for the Deep Space 1 Mission

The NASA Solar Electric Propulsion Technology Applications Readiness (NSTAR) Program has provided a single-string primary propulsion system to NASA's Deep Space 1 spacecraft. This spacecraft will carry about 81 kg of xenon propellant for the ion thruster, which can be throttled down from 2.3 to 0.5 kW as the spacecraft moves away from the Sun. The propellant load will provide about 20 months of propulsion at the one-half power throttle setpoint of 1.2 kW. This mission will validate the 2.5-kW ion propulsion system and will fly by the asteroid 1992 KD in 1999. If funding permits, Deep Space 1 also will encounter comets Wilson-Harrington and Borrelly in 2001. NASA Lewis Research Center's On-Board Propulsion Branch was responsible for the development of the 30-cm-diameter ion thruster, the 2.5-kW power processor unit (PPU), and the Digital Control and Interface Unit (DCIU) that controls the PPU/thruster/feed system and provides data and recovery from fault conditions. Lewis transferred the thruster and PPU technologies to the Hughes Electron Dynamics Division, which was selected to build two sets of flight thrusters, as well as the PPU's and DCIU's. Hughes subcontracted the DCIU development to Spectrum Astro Incorporated. The Jet Propulsion Laboratory (JPL) was primarily responsible for the NSTAR project management, thruster lifetests, the feed system, diagnostics, and the propulsion subsystem integration. A total of four engineering model thrusters and three breadboard PPU's were built, integrated, and tested. More than 50 development tests were conducted along with thruster design verification tests of 2000 and 1000 hours. In addition, an 8000-hr life demonstration test was successfully completed and demonstrated wear-rates consistent with full-power lifetimes in excess of 12,000 hours.

Sovey, James S.↗
NASA NTRS2009

Fault Diagnostics and Prognostics for Large Segmented SRMs

We report progress in development of the fault diagnostic and prognostic (FD&P) system for large segmented solid rocket motors (SRMs). The model includes the following main components: (i) 1D dynamical model of internal ballistics of SRMs; (ii) surface regression model for the propellant taking into account erosive burning; (iii) model of the propellant geometry; (iv) model of the nozzle ablation; (v) model of a hole burning through in the SRM steel case. The model is verified by comparison of the spatially resolved time traces of the flow parameters obtained in simulations with the results of the simulations obtained using high-fidelity 2D FLUENT model (developed by the third party). To develop FD&P system of a case breach fault for a large segmented rocket we notice [1] that the stationary zero-dimensional approximation for the nozzle stagnation pressure is surprisingly accurate even when stagnation pressure varies significantly in time during burning tail-off. This was also found to be true for the case breach fault [2]. These results allow us to use the FD&P developed in our earlier research [3]-[6] by substituting head stagnation pressure with nozzle stagnation pressure. The axial corrections to the value of the side thrust due to the mass addition are taken into account by solving a system of ODEs in spatial dimension.

Luchinsky, Dmitry↗
DOE OSTI2024

Radioimaging for real-time tracking of high-voltage breakdown

Development of a radioimaging diagnostic for high-voltage component reliability testing and electrical breakdown computational model validation is described. Radioimaging has its roots in radio astronomy, where aperture synthesis (also known as synthesis imaging) has been utilized for decades to image radio sources far from Earth. Radioimaging as described herein, in contrast, seeks to image radio sources in close proximity to its receivers (i.e., in a laboratory environment). Here it is shown that corona discharge, a non-destructive precursor to catastrophic (thermal) arc discharge, electromagnetically radiates strongly within a 250 kHz – 2.5 GHz bandwidth, and is readily detected and located by postprocessing the received radio signals. The ability of radioimaging to detect both corona and arc discharge (grouped together herein as high voltage breakdown or HVB) makes it a valuable tool for 100% HVB detection in materials, components, and devices, and has the ability to indicate electrical weakness (via corona detection) prior to a destructive arc discharge event. Radioimaging enables HVB to be located both internal and external to dielectric components under test in near-real-time, with multiple and/or extended HVB events located simultaneously. In contrast, existing non-destructive diagnostics (at the time of this writing) either indicate electrical breakdown without resolving failure locations (e.g., current, voltage, and chemical measurements), locate external HVB (e.g., high-speed optical and ultraviolet (UV) measurements or photography), or locate both external and internal HVB but with low fidelity (e.g., a single HVB source can be located by existing time-of-arrival (TOA) UHF or acoustic emissions). Radioimaging instead creates a sequence of high-fidelity images similar to an optical high-speed camera but at radiofrequencies (RF), and is not limited to two-dimensions. Moreover, radioimaging has already served one internal and two external industry customers, the results of which are detailed in this report. The radioimaging results described herein were part of a three-year effort funded by the Sandia Lab Directed Research and Development (LDRD) program within the Radiation, Electromagnetic, High Energy Density Science (REHEDS) investment area.

47 OTHER INSTRUMENTATION↗