A novel machine learning based lumping approach for the reduction of large kinetic mechanisms for plasma-assisted combustion applications
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Rekkas-Ventiris, Georgios (ORCID:0000000226586586)↗
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Results for “generator model”
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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Smooth Mathematical Representation of the DER_A Aggregated Model
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97 MATHEMATICS AND COMPUTING↗
Geomagnetic field modeling by optimal recursive filtering
Five individual 5 year mini-batch geomagnetic models were generated and two computer programs were developed to process the models. The first program computes statistics (mean sigma, weighted sigma) on the changes in the first derivatives (linear terms) of the spherical harmonic coefficients between mini-batches. The program ran successfully. The statistics are intended for use in computing the state noise matrix required in the information filter. The second program is the information filter. Most subroutines used in the filter were tested, but the coefficient statistics must be analyzed before the filter is run.
Source record↗
Control of a Flexible Space Antenna: A Finite Dimensional Perspective Based on Distributed Parameter Theory
The methods presented are based on results from infinite dimensional control theory, but they can be described and used in a finite dimensional context. This blend leads to an approach which employs powerful ideas on convergence, and is also quite practical for systems of realistic complexity. Appropriate reduced order models are generated simultaneously with the development of the compensator. The required models change as a function of changes in the performance demanded, sensor and actuator location, inherent damping, disturbances, etc. Thus they are driven by the control and estimation problems at hand. The compensators which emerge are very close to the ideal compensators which would be obtained with a very large order model. However, some simplification is frequently possible. The method of balanced realizations was found to be effective for this purpose.
Mingori, D. L.↗
A nonlinear model of the phasic dynamics of muscle activation
A phasic excitation-activation (PEXA) model is presented of the process of motoneuron excitation and the resultant activation and force development of a motor unit. The model input is an amount of depolarizing current (as when injected with an intracellular electrode), and the model output is muscle force. The model includes dynamics and nonlinearities similar to phenomena discovered experimentally by others: the firing rate response of motoneurons to steps of depolarizing current and the catch-like enhancement of force produced by overlapping motor neuron action potentials. The parameter values used in this model are derived from experimentally measured data and are expressed in physical units. Model predictions extend to published data beyond those used in generating the model parameter values.
Hannaford, Blake↗
Thermal analysis of combinatorial solid geometry models using SINDA
Algorithms have been developed using Monte Carlo techniques to determine the thermal network parameters necessary to perform a finite difference analysis on Combinatorial Solid Geometry (CSG) models. Orbital and laser fluxes as well as internal heat generation are modeled to facilitate satellite modeling. The results of the thermal calculations are used to model the infrared (IR) images of targets and assess target vulnerability. Sample analyses and validation are presented which demonstrate code products.
Gerencser, Diane↗
Prognostic model and failure mechanisms of steam generators in Sodium-Cooled fast reactors
This paper presents a prognostic model for sodium-cooled fast reactor (SFR) steam generators (SGs). Here, the purpose of the model is to estimate the remaining useful life of SFR SGs and thus to support the decision-making of autonomous control. SFR SGs are of great interest for plant integrity due to their harsh operation environment. They operate at higher temperatures and higher coolant-to-steam pressure differences than those of current light water reactors (LWR). The severity of the SFR SG failure consequences, which include water-sodium contact, is another reason. Understanding its failure mechanisms is important for the development of its prognostic model. Based on our literature review and physics-based analysis, we concluded that creep would be a dominant degradation mode of SFR SGs due to SFR’s high-temperature and high-pressure environment. Thus, creep is the focus of the prognostic model. Various other failure modes were also investigated in this study. The mechanical fatigue due to flow-induced vibration is usually observed in early developmental phases and would not be an important issue during normal operation. The thermal fatigue due to thermal stripping is occasionally observed in other components in SFRs but does not affect SG integrity. Pure water stress corrosive crack, fretting, and so on are commonly observed in LWR SGs but are significantly less important in SFR SGs because of the high temperatures, high pressure differences, and chemical properties of liquid sodium. Based on these investigations, a prognostic model focusing on creep failures was developed. It estimates the failure probability profile by sampling the Larson-Miller parameter (LMP) and temperature and associated uncertainties through Monte Carlo methods. Two case studies were presented. The first one demonstrated the model’s capability to calculate the failure probability for a new specimen within a given time. If the tube is working under temperatures of 500C ± 3 and pressures of 15.2 MPa, which leads to LMP of 20,100 ± 50, the failure probabilities within 50, 70, and 90 years are approximately 0.1 %, 3.2 %, and 17.5 %. The second demonstrated how adjusting the workload can help to protect the integrity of the component. For an old tube reaching 99 % of its lifespan, continuing to run at temperatures of 500C ± 3 and LMP of 20,100 ± 50 leads to a failure probability of about 29.0 % within a year. If the temperature is reduced by 5C, the failure probability can be reduced to 2.5 %, and, if the pressure is also reduced such that the LMP is increased by 100, the failure probability can further be reduced to 0.12 %.
21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
Explainable AI for Multivariate Time Series Pattern Exploration: Latent Space Visual Analytics With Temporal Fusion Transformer and Variational Autoencoders in Power Grid Event Diagnosis
Detecting and analyzing complex patterns in multivariate time-series data is crucial for decision-making in urban and environmental system operations. However, challenges arise from the high dimensionality, intricate complexity, and interconnected nature of complex patterns, which hinder the understanding of their underlying physical processes. Existing AI methods often face limitations in interpretability, computational efficiency, and scalability, reducing their applicability in real-world scenarios. This paper proposes a novel visual analytics framework that integrates two generative AI models, Temporal Fusion Transformer (TFT) and Variational Autoencoders (VAEs), to reduce complex patterns into lower-dimensional latent spaces and visualize them in 2D using dimensionality reduction techniques such as PCA, t-SNE, and UMAP with DBSCAN. These visualizations, presented through coordinated and interactive views and tailored glyphs, enable intuitive exploration of complex multivariate temporal patterns, identifying patterns’ similarities and uncover their potential correlations for a better interpretability of the AI outputs. The framework is demonstrated through a case study on power grid signal data, where it identifies multi-label grid event signatures, including faults and anomalies with diverse root causes. Additionally, novel metrics and visualizations are introduced to validate the models and assess the performance, efficiency, and consistency of latent maps generated by VAE, which have been utilized in prior studies for latent space cartography and used as a benchmark in this study, and the emerging TFT architecture under various configurations. These analyses provide actionable insights for model parameter tuning and reliability improvements. Comparative results highlight that TFT achieves shorter run times and superior scalability to diverse time-series data shapes compared to VAE. This work advances fault diagnosis in multivariate time series, fostering explainable AI to support critical system operations.
Explainable AI↗
Combustion Stability Assessments of the Black Brant Solid Rocket Motor
The Black Brant variation of the Standard Brant developed in the 1960's has been a workhorse motor of the NASA Sounding Rocket Project Office (SRPO) since the 1970's. In March 2012, the Black Brant Mk1 used on mission 36.277 experienced combustion instability during a flight at White Sands Missile Range, the third event in the last four years, the first occurring in November, 2009, the second in April 2010. After the 2010 event the program has been increasing the motor's throat diameter post-delivery with the goal of lowering the chamber pressure and increasing the margin against combustion instability. During the most recent combustion instability event, the vibrations exceeded the qualification levels for the Flight Termination System. The present study utilizes data generated from T-burner testing of multiple Black Brant propellants at the Naval Air Warfare Center at China Lake, to improve the combustion stability predictions for the Black Brant Mk1 and to generate new predictions for the Mk2. Three unique one dimensional (1-D) stability models were generated, representing distinct Black Brant flights, two of which experienced instabilities. The individual models allowed for comparison of stability characteristics between various nozzle configurations. A long standing "rule of thumb" states that increased stability margin is gained by increasing the throat diameter. In contradiction to this experience based rule, the analysis shows that little or no margin is gained from a larger throat diameter. The present analysis demonstrates competing effects resulting from an increased throat diameter accompanying a large response function. As is expected, more acoustic energy was expelled through the nozzle, but conversely more acoustic energy was generated due to larger gas velocities near the propellant surfaces.
Fischbach, Sean↗
Incorporation of Failure Into an Orthotropic Three-Dimensional Model with Tabulated Input Suitable for Use in Composite Impact Problems
The need for accurate material models to simulate the deformation, damage and failure of polymer matrix composites under impact conditions is becoming critical as these materials are gaining increased use in the aerospace and automotive communities. The aerospace community has identified several key capabilities which are currently lacking in the available material models in commercial transient dynamic finite element codes. To attempt to improve the predictive capability of composite impact simulations, a next generation material model is being developed for incorporation within the commercial transient dynamic finite element code LS-DYNA. The material model, which incorporates plasticity, damage and failure, utilizes experimentally based tabulated input to define the evolution of plasticity and damage and the initiation of failure as opposed to specifying discrete input parameters such as modulus and strength. The plasticity portion of the orthotropic, three-dimensional, macroscopic composite constitutive model is based on an extension of the Tsai-Wu composite failure model into a generalized yield function with a non-associative flow rule. For the damage model, a strain equivalent formulation is used to allow for the uncoupling of the deformation and damage analyses. In the damage model, a semi-coupled approach is employed where the overall damage in a particular coordinate direction is assumed to be a multiplicative combination of the damage in that direction resulting from the applied loads in various coordinate directions. For the failure model, a tabulated approach is utilized in which a stress or strain based invariant is defined as a function of the location of the current stress state in stress space to define the initiation of failure. Failure surfaces can be defined with any arbitrary shape, unlike traditional failure models where the mathematical functions used to define the failure surface impose a specific shape on the failure surface. In the current paper, the complete development of the failure model is described and the generation of a tabulated failure surface for a representative composite material is discussed.
Impact↗
Implementation of a Tabulated Failure Model Into a Generalized Composite Material Model Suitable for Use in Impact Problems
The need for accurate material models to simulate the deformation, damage and failure of polymer matrix composites under impact conditions is becoming critical as these materials are gaining increased use in the aerospace and automotive communities. The aerospace community has identified several key capabilities which are currently lacking in the available material models in commercial transient dynamic finite element codes. To attempt to improve the predictive capability of composite impact simulations, a next generation material model is being developed for incorporation within the commercial transient dynamic finite element code LS-DYNA. The material model, which incorporates plasticity, damage and failure, utilizes experimentally based tabulated input to define the evolution of plasticity and damage and the initiation of failure as opposed to specifying discrete input parameters such as modulus and strength. The plasticity portion of the orthotropic, three-dimensional, macroscopic composite constitutive model is based on an extension of the Tsai-Wu composite failure model into a generalized yield function with a non-associative flow rule. For the damage model, a strain equivalent formulation is used to allow for the uncoupling of the deformation and damage analyses. For the failure model, a tabulated approach is utilized in which a stress or strain based invariant is defined as a function of the location of the current stress state in stress space to define the initiation of failure. Failure surfaces can be defined with any arbitrary shape, unlike traditional failure models where the mathematical functions used to define the failure surface impose a specific shape on the failure surface. In the current paper, the complete development of the failure model is described and the generation of a tabulated failure surface for a representative composite material is discussed.
polymer matrix composites↗
SCIMON: Scientific Inspiration Machines Optimized for Novelty
We explore and enhance the ability of neu- ral language models to generate novel scien- tific directions grounded in literature. Work on literature-based hypothesis generation has traditionally focused on binary link prediction— severely limiting the expressivity of hypothe- ses. This line of work also does not focus on optimizing novelty. We take a dramatic depar- ture with a novel setting in which models use as input background contexts (e.g., problems, experimental settings, goals), and output natu- ral language ideas grounded in literature. We present SCIMON, a modeling framework that uses retrieval of “inspirations” from past scien- tific papers, and explicitly optimizes for novelty by iteratively comparing to prior papers and up- dating idea suggestions until sufficient novelty is achieved. Comprehensive evaluations reveal that GPT-4 tends to generate ideas with over- all low technical depth and novelty, while our methods partially mitigate this issue. Our work represents a first step toward evaluating and developing language models that generate new ideas derived from the scientific literature.
Ji, Heng↗
ADVANCED THERMAL-HYDRAULIC MODEL OF HEAT RECOVERY STEAM GENERATORS
Steam-side oxidation at elevated temperatures in heat recovery steam generators (HRSGs) can lead to overheating of local tubes, potential oxide scale exfoliation, and damage to critical equipment. Predicting the oxide growth distribution requires detailed knowledge of the distribution of tube metal temperatures. To address these challenges, a computational fluid dynamics (CFD) model of a high-pressure superheater (HPSH) was developed within the Siemens’ STAR-CCM+ CFD commercial software. The HPSH section of the steam generator was selected for modeling because of its high oxidation rates.The model development included several steps. In the first step, an oxidation model based on a parabolic oxidation relationship was implemented. The oxidation growth predicted by the model was then verified for a full-load boiler operation case. In the second step, a three-dimensional CFD model was developed to account for the thermal and flow physics involved in HRSGs. The CFD model was then verified and validated on a simplified geometry that contained six row-tubes which mimicked the tube arrangements of an HPSH section. Numerical results compared well with published experimental results. In the third step, the oxidation model was coupled to the HRSG’s CFD model, and a comparison study was performed for two cases: (a) regular finless tubes and (b) finned tubes. Preliminary results showed that the oxide thickness predicted by the case with tube fins was higher compared to that of the finless tube case, thus demonstrating the need to model the effects of the tube fins on oxide thickness.
Panicker, Nithin↗
Cubit for MCNP Unstructured Mesh Analysis of Oktavian Benchmarks
The Monte Carlo N-Particle (MCNP) transport code developed by Los Alamos National Laboratory (LANL) can be used to transport various particles across user defined three dimensional (3D) geometries. Traditionally, these geometries are created as constructive solid geometry (CSG), involving the use of Boolean operators on defined surfaces to create 3D regions known as cells. A newer method of geometry definition in the MCNP code is unstructured mesh (UM) embedded within a CSG cell using the universe and fill repeated-structure features. An MCNP UM calculation requires an MCNP input file and mesh geometry file. The MCNP code cannot be used to generate UM geometry models. A computer-aided design (CAD) software is typically used to construct a solid geometry model, and a CAD file is then imported into a mesh generation software to prepare and generate a mesh model. Some mesh generation software packages have the ability to create a solid geometry and thus a separate CAD software for creating a CAD model is not needed. In this work, Cubit, a geometry creation and meshing software developed by Sandia National Laboratories, is used to construct UM models for MCNP simulations.
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
Understanding Generative AI Content with Embedding Models
The construction of high-quality numerical features is critical to any quantitative data analysis. Feature engineering has been historically addressed by carefully hand-crafting data representations based on domain expertise. This work views the internal representations of modern deep neural networks (DNNs), called embeddings, as an implicit form of traditional feature engineering. For trained DNNs, we show that these embeddings can reveal interpretable, high-level concepts in unstructured sample data. We use these embeddings in natural language and computer vision tasks to uncover both inherent heterogeneity in the underlying data and human-understandable explanations for it. In particular, we find empirical evidence that there is inherent separability between real data and those generated from AI models.
Vargas, Max↗
Generation of lower-hybrid noise by superthermal cross-field ion currents
A kinetic model for generating lower-hybrid waves by a low-density, superthermal ion beam directed across a magnetic field is investigated. Growth rate calculations demonstrate the salient features of the process, in particular, the small threshold drift of several background ion thermal speeds required for instability. The mechanism is suitable for collisionless dissipation in systems which evince the characteristics of anomalous resistivity in the presence of relatively small electrical currents.
Barbosa, D. D.↗
Dynamic and Structural Gas Turbine Engine Modeling
Model the interactions between the structural dynamics and the performance dynamics of a gas turbine engine. Generally these two aspects are considered separate, unrelated phenomena and are studied independently. For diagnostic purposes, it is desirable to bring together as much information as possible, and that involves understanding how performance is affected by structural dynamics (if it is) and vice versa. This can involve the relationship between thrust response and the excitation of structural modes, for instance. The job will involve investigating and characterizing these dynamical relationships, generating a model that incorporates them, and suggesting and/or developing diagnostic and prognostic techniques that can be incorporated in a data fusion system. If no coupling is found, at the least a vibration model should be generated that can be used for diagnostics and prognostics related to blade loss, for instance.
Turso, James A.↗
Studies of uncontrolled air traffic patterns, phase 1
The general aviation air traffic flow patterns at uncontrolled airports are investigated and analyzed and traffic pattern concepts are developed to minimize the midair collision hazard in uncontrolled airspace. An analytical approach to evaluate midair collision hazard probability as a function of traffic densities is established which is basically independent of path structure. Two methods of generating space-time interrelationships between terminal area aircraft are presented; one is a deterministic model to generate pseudorandom aircraft tracks, the other is a statistical model in preliminary form. Some hazard measures are presented for selected traffic densities. It is concluded that the probability of encountering a hazard should be minimized independently of any other considerations and that the number of encounters involving visible-avoidable aircraft should be maximized at the expense of encounters in other categories.
Baxa, E. G., Jr.↗