Data-Driven Parsimonious Models for Virtual Diagnostics and Control
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Transfer learning for probabilistic localization of hidden cracks in concrete structures
Abstract The utility of discriminative supervised learning models built using multiple training-data sources is investigated for hidden crack localization in concrete. Feed-forward neural network (FFNN) is chosen as the model architecture, and transfer learning is used to assimilate the information obtained from different sources (computational physics simulations and laboratory experiments). The labeled training data consists of values of a damage index and the known locations of hidden cracks. The classification models need to learn how the presence of damage (hidden cracks) affects the damage index at different sensors for different test conditions. To this end, diagnostic FFNN models are built by sequentially adding and training new hidden layers to assimilate labeled information from computer models (different model geometries, test conditions, crack lengths, crack locations) and laboratory experiments on a plain cement slab. These transfer learning-based models are then used to localize damage in concrete specimens that reflect real-world conditions (i.e., specimens with steel reinforcement and randomly distributed aggregate). The actual damage state in these specimens is determined by extracting cores and performing petrographic studies on the extracted cores. The damage probability estimated by transfer learning-based models is compared with the petrographic damage rating index (DRI) to identify the most suitable approach to train the diagnostic models. The transfer learning-based diagnostic methodology shows promise and could be used in various structural health monitoring applications, where sufficient labeled data are typically not available from a single data source.
Miele, S.↗
Improving Reliability of Large Language Models for Nuclear Power Plant Diagnostics Technical Presentation
Large Language Models (LLMs) struggle out of the box when answering factually about detailed questions, especially in domains that are sparsely represented in their training data. This causes hallucinations and reduces reliability making it difficult for them to be used in practice. This work shows that using RAG techniques can improve factual accuracy and reliability, allowing for the application of LLMs in specialized areas, even when those areas that aren’t extensively covered in their initial training.
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
Diagnostic evaluation of numerical model simulations using the tendency equation
A procedure is proposed to expand the diagnostic capabilities of the pressure tendency equation of a primitive equation NWP model by computing the pressure tendency in physical coordinates. The advantages of isolating the density advection as a diagnostic tool to understand pressure changes is shown. By simple thermodynamic arguments it is demonstrated that in areas of synoptic-scale cyclonic development, the vertically integrated density advection is more than sufficient to explain the depletion of mass over a growing depression. Consequently, the joint contribution of the net divergence and vertical motion opposes the pressure fall. This is illustrated for a case of rapid cyclogenesis in southern South America.
Jusem, Juan C.↗
Transportation technology: Earth-to-orbit propulsion
The topics presented are covered in viewgraph form and include the following: (1) sensor autodiagnosis and autocalibration; (2) autodiagnostic and autocalibration program; (3) plume diagnostics; (4) plume diagnostics program; (5) failure modeling; (6) mass data storage and retrieval; (7) fiber optic instrumentation bus; (8) model based diagnostics; (9) safety monitoring system (SMS); (10) control and real time diagnostics; (11) current intelligent controls program; (12) augumented intelligent controls program; (13) current real time diagnostics program; (14) augumented RT diagnostics program; and (15) control and diagnostic system hardware.
Gorland, S.↗
An Overview of the NASA Aviation Safety Program Propulsion Health Monitoring Element
The NASA Aviation Safety Program (AvSP) has been initiated with aggressive goals to reduce the civil aviation accident rate, To meet these goals, several technology investment areas have been identified including a sub-element in propulsion health monitoring (PHM). Specific AvSP PHM objectives are to develop and validate propulsion system health monitoring technologies designed to prevent engine malfunctions from occurring in flight, and to mitigate detrimental effects in the event an in-flight malfunction does occur. A review of available propulsion system safety information was conducted to help prioritize PHM areas to focus on under the AvSP. It is noted that when a propulsion malfunction is involved in an aviation accident or incident, it is often a contributing factor rather than the sole cause for the event. Challenging aspects of the development and implementation of PHM technology such as cost, weight, robustness, and reliability are discussed. Specific technology plans are overviewed including vibration diagnostics, model-based controls and diagnostics, advanced instrumentation, and general aviation propulsion system health monitoring technology. Propulsion system health monitoring, in addition to engine design, inspection, maintenance, and pilot training and awareness, is intrinsic to enhancing aviation propulsion system safety.
Simon, Donald L.↗
A balanced diagnostic system compatible with a barotropic prognostic model
A system of diagnostic equations for the velocity field, or wind laws, for a barotropic primitive-equation model of large-scale atmospheric flow is derived. Attention is given to the classical balance equation and its ellipticity condition. Numerical solutions of the diagnostic system are presented, including examples of cases of the mixed elliptic-hyperbolic type and cases with non-zero divergence. Procedures for implementing such a system are outlined, along with a review of factors in using the technique for operational numerical weather prediction.
Ghil, M.↗
A Hybrid Neural Network-Genetic Algorithm Technique for Aircraft Engine Performance Diagnostics
In this paper, a model-based diagnostic method, which utilizes Neural Networks and Genetic Algorithms, is investigated. Neural networks are applied to estimate the engine internal health, and Genetic Algorithms are applied for sensor bias detection and estimation. This hybrid approach takes advantage of the nonlinear estimation capability provided by neural networks while improving the robustness to measurement uncertainty through the application of Genetic Algorithms. The hybrid diagnostic technique also has the ability to rank multiple potential solutions for a given set of anomalous sensor measurements in order to reduce false alarms and missed detections. The performance of the hybrid diagnostic technique is evaluated through some case studies derived from a turbofan engine simulation. The results show this approach is promising for reliable diagnostics of aircraft engines.
Kobayashi, Takahisa↗
A Model-based Health Monitoring and Diagnostic System for the UH-60 Helicopter
Model-based reasoning techniques hold much promise in providing comprehensive monitoring and diagnostics capabilities for complex systems. We are exploring the use of one of these techniques, which utilizes multi-signal modeling and the TEAMS-RT real-time diagnostic engine, on the UH-60 Rotorcraft Aircrew Systems Concepts Airborne Laboratory (RASCAL) flight research aircraft. We focus on the engine and transmission systems, and acquire sensor data across the 1553 bus as well as by direct analog-to-digital conversion from sensors to the QHuMS (Qualtech health and usage monitoring system) computer. The QHuMS computer uses commercially available components and is rack-mounted in the RASCAL facility. A multi-signal model of the transmission and engine subsystems enables studies of system testability and analysis of the degree of fault isolation available with various instrumentation suites. The model and examples of these analyses will be described and the data architectures enumerated. Flight tests of this system will validate the data architecture and provide real-time flight profiles to be further analyzed in the laboratory.
Patterson-Hine, Ann↗
Biogeochemical Protocols and Diagnostics for the CMIP6 Ocean Model Intercomparison Project (OMIP)
The Ocean Model Intercomparison Project (OMIP) focuses on the physics and biogeochemistry of the ocean component of Earth system models participating in the sixth phase of the Coupled Model Intercomparison Project (CMIP6). OMIP aims to provide standard protocols and diagnostics for ocean models, while offering a forum to promote their common assessment and improvement. It also offers to compare solutions of the same ocean models when forced with reanalysis data (OMIP simulations) vs. when integrated within fully coupled Earth system models (CMIP6). Here we detail simulation protocols and diagnostics for OMIP's biogeochemical and inert chemical tracers. These passive-tracer simulations will be coupled to ocean circulation models, initialized with observational data or output from a model spin-up, and forced by repeating the 1948-2009 surface fluxes of heat, fresh water, and momentum. These so-called OMIP-BGC simulations include three inert chemical tracers (CFC-11, CFC-12, SF [subscript] 6) and biogeochemical tracers (e.g., dissolved inorganic carbon, carbon isotopes, alkalinity, nutrients, and oxygen). Modelers will use their preferred prognostic BGC model but should follow common guidelines for gas exchange and carbonate chemistry. Simulations include both natural and total carbon tracers. The required forced simulation (omip1) will be initialized with gridded observational climatologies. An optional forced simulation (omip1-spunup) will be initialized instead with BGC fields from a long model spin-up, preferably for 2000 years or more, and forced by repeating the same 62-year meteorological forcing. That optional run will also include abiotic tracers of total dissolved inorganic carbon and radiocarbon, CTabio and 14CTabio, to assess deep-ocean ventilation and distinguish the role of physics vs. biology. These simulations will be forced by observed atmospheric histories of the three inert gases and CO2 as well as carbon isotope ratios of CO2. OMIP-BGC simulation protocols are founded on those from previous phases of the Ocean Carbon-Cycle Model Intercomparison Project. They have been merged and updated to reflect improvements concerning gas exchange, carbonate chemistry, and new data for initial conditions and atmospheric gas histories. Code is provided to facilitate their implementation.
Carbon↗
Using Transport Diagnostics to Understand Chemistry Climate Model Ozone Simulations
We demonstrate how observations of N2O and mean age in the tropical and midlatitude lower stratosphere (LS) can be used to identify realistic transport in models. The results are applied to 15 Chemistry Climate Models (CCMs) participating in the 2010 WMO assessment. Comparison of the observed and simulated N2O/mean age relationship identifies models with fast or slow circulations and reveals details of model ascent and tropical isolation. The use of this process-oriented N2O/mean age diagnostic identifies models with compensating transport deficiencies that produce fortuitous agreement with mean age. We compare the diagnosed model transport behavior with a model's ability to produce realistic LS O3 profiles in the tropics and midlatitudes. Models with the greatest tropical transport problems show the poorest agreement with observations. Models with the most realistic LS transport agree more closely with LS observations and each other. We incorporate the results of the chemistry evaluations in the SPARC CCMVal Report (2010) to explain the range of CCM predictions for the return-to-1980 dates for global (60 S-60 N) and Antarctic column ozone. Later (earlier) Antarctic return dates are generally correlated to higher (lower) vortex Cl(sub y) levels in the LS, and vortex Cl(sub y) is generally correlated with the model's circulation although model Cl(sub y) chemistry or Cl(sub y) conservation can have a significant effect. In both regions, models that have good LS transport produce a smaller range of predictions for the return-to-1980 ozone values. This study suggests that the current range of predicted return dates is unnecessarily large due to identifiable model transport deficiencies.
Strahan, S. E.↗
A Model-Based Expert System for Space Power Distribution Diagnostics
When engineers diagnose system failures, they often use models to confirm system operation. This concept has produced a class of advanced expert systems that perform model-based diagnosis. A model-based diagnostic expert system for the Space Station Freedom electrical power distribution test bed is currently being developed at the NASA Lewis Research Center. The objective of this expert system is to autonomously detect and isolate electrical fault conditions. Marple, a software package developed at TRW, provides a model-based environment utilizing constraint suspension. Originally, constraint suspension techniques were developed for digital systems. However, Marple provides the mechanisms for applying this approach to analog systems such as the test bed, as well. The expert system was developed using Marple and Lucid Common Lisp running on a Sun Sparc-2 workstation. The Marple modeling environment has proved to be a useful tool for investigating the various aspects of model-based diagnostics. This report describes work completed to date and lessons learned while employing model-based diagnostics using constraint suspension within an analog system.
Quinn, Todd M.↗
The kinetic analog of the pressure–strain interaction
Energy transport in weakly collisional plasma systems is often studied with fluid models and diagnostics. However, the applicability of fluid models is limited when collisions are weak or absent, and using a fluid approach can obscure kinetic processes that provide key insights into the physics of energy transport. Kinetic diagnostics retain all of the information in 3D-3V phase space and thereby reach beyond the insights of fluid models to elucidate the mechanisms responsible for collisionless energy transport. In this work, we derive the Kinetic Pressure–Strain (KPS): a kinetic analog of the pressure–strain interaction, which is the channel between flow energy density and internal energy density in fluid models. Through two case studies of electron Landau damping, we demonstrate that the KPS diagnostic can elucidate kinetic mechanisms that are responsible for energy transport in this channel, just as the related field–particle correlation is known to identify kinetic mechanisms of transport between electromagnetic field energy density and kinetic energy density in particle flows. In addition, we show that resonant electrons play a major role in transferring energy between fluid flows and internal energy during the process of Landau damping.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Age and Pathway Diagnostics for a Stratospheric General Circulation Model
Using a variety of age diagnostic experiments we examine the stratospheric age spectrum of the Goddard Finite Volume Generd Circulation Model. Pulse tracer release age-of-air computations are compared to forward and backward trajectory computations. These comparisons show good agreement, and the age-of-air also compares well with observed long lived tracers. Pathway diagnostics show how air arrives in the lowermost stratosphere and the age structure of that region. Using tracers with different lifetimes we can estimate the age spectrum - this technique should be useful in diagnosing transport from various trace gas observations.
Schoeberl, Mark R.↗
Fuels and Combustion Technology for Advanced Aircraft Engines [Les Propergols et les Systèmes de Combustion pour les Moteurs d'Aéronefs]
The Conference Proceedings contains the 38 papers presented at the Propulsion and Energetics Panel 81st Symposium on "Fuels and Combustion Technology for Advanced Aircraft Engines" which was held from 10th-14th May 1993, in Fiuggi, Italy. The Technical Evaluation Report and the Keynote Address are included at the beginning, and discussions follow most papers. The Symposium was arranged in the following Sessions: Technology Overview Papers (2); Modelling: Pollutant Formation (4); Modelling: Combustor Design (5); High Temperature Fuels and Fuel Systems (6); Combustion Research: Performance (6); Combustion Research: Emissions (5); Fuel Atomization: Diagnostics and Modelling (5); and Combustion Research: Flowfleld and Mixing (4). The last paper is a contribution from Russia not allocated to a session. New technologies for low NOx combustors and advanced high-pressure/high temperature cycle engines result in unique problems in design and performance. There have been significant advances in modelling and diagnostics to aid the development of these technologies. The purpose of the Symposium was to bring together experts from industry, research establishments and universities to discuss fundamental and applied research in these areas as relevant to the development of advanced gas turbine engines, to exchange practical experience and to discuss the state of the art.
Fuels for aircraft↗
JANNAF Combustion Subcommittee Meeting
This volume, the first of four volumes, is a collection of 33 unclassified/unlimited papers which were presented at the 33rd Joint Army-Navy-NASA-Air Force (JANNAF) Combustion Subcommittee Meeting in conjunction with the Propulsion Systems Hazards at the Naval Postgraduate School, Monterey, CA. The JANNAF papers contained in this volume review airbreathing combustion measurement, performance and control; electrothermal-chemical gun experiment and modeling; liquid propellant gun experiment and modeling; solid propellant gun interior ballistics; formulation modeling and diagnostics, ignition, and gun barrel wear modeling, blast and flash; and ram, fastcore and gas generator gun propulsion concepts.
Fry, Ronald S.↗
Plasma CVD of Carbon Nanotubes
Carbon nanotubes(CNT) exhibit remarkable mechanical and unique electronic properties and thus have created excitement in the research community about their potential in electronics, computing, sensor and structural applications. Realization of these applications critically depends on the ability to control the properties(such as diameter, chirality) as well purity. We have investigated CNT growth using an inductively coupled plasma(ICP) process using hydrocarbon feedstock. The catalyst required for nanotube growth consists of thin sputtered layers of aluminum and iron(10 nm each) and aligned carbon nanotubes have been obtained. Optical emission diagnostics as well as a plasma modeling effort have been undertaken to understand growth mechanisms. This presentation will discuss growth characteristics under various pressure, power and feedgas compositions and our understanding from modeling and diagnostics.
Delzeit, Lance↗
eagles-project/asediag
Aerosol process analysis in model-native Spectral Element (SE) grid. Aerosol Diagnostics on Model Native Grid is a Python-based tool designed for diagnosing aerosol processes in E3SM. It is particularly designed to analyze simulation data on the model-native spectral element (SE) grid, soit is also known as Aerosol SE Diagnostics or “asediag”
Hassan, Taufiq↗