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Results for “conditional generative models”

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 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

A Model Based Approach to Extract Health Information from Textual Data

In current nuclear power plants (NPPs) a large amount of condition-based data is being generated and stored to assess and monitor component health and performance. The format of this data can be either numeric (e.g., pump vibration data) or textual (e.g., condition report which assess component health). While assessing component health from numeric data can be performed with a large variety of methods, the extraction of information from textual data still remains a challenge. Natural language processing (NLP) methods are starting to be deployed in current NPPs mainly to filter out incident reports (IRs) that are not safety related by employing supervised machine learning methods. However, these methods do not really provide the quantitative information that might be contained in IRs. This paper presents an approach to extract information from textual data (e.g., from IRs, maintenance reports) that is based on NLP data analytics methods coupled with model-based system engineer (MBSE) models. NLP methods are employed to perform syntactic and semantic analyses. Syntactic analysis analyzes the grammatical structure of a sentence; such analysis includes: part of speech (POS) tagging (i.e., identification of grammatic elements of each string - e.g., nouns, verbs), named entity recognition (i.e., identification of text entities - e.g., names, dates, events), and relation extraction (e.g., coreference resolution). On the other hand, semantic analysis is designed to analyze the logic structure of a sentence. Through a specific set of rules, our methods can identify whether a sentence contains health information of a component (e.g., degraded performance, anomaly behavior) or the causal relationship between two events (i.e., a cause-effect pair). An innovative element of our approach is that semantic analysis relies on MBSE models to identify links between textual elements. MBSE are diagrams designed to represent system and component dependencies (from both a form and functional point of view). In our approach, MBSE models emulate system engineer knowledge about component/system architecture. This paper presents in detail how the integration of NLP methods and MBSE models is performed. Few analysis examples focusing on centrifugal pumps are presented.

97 - MATHEMATICS AND COMPUTING↗
NASA NTRS2007

Flaperon Modification Effect on Jet-Flap Interaction Noise Reduction for Chevron Nozzles

Jet-flap interaction (JFI) noise can become an important component of far field noise when a flap is immersed in the engine propulsive stream or is in its entrained region, as in approach conditions for under-the-wing engine configurations. We experimentally study the effect of modifying the flaperon, which is a high speed aileron between the inboard and outboard flaps, at both approach and take-off conditions using scaled models in a free jet. The flaperon modifications were of two types: sawtooth trailing edge and mini vortex generators (vg s). Parametric variations of these two concepts were tested with a round coaxial nozzle and an advanced chevron nozzle, with azimuthally varying fan chevrons, using both far field microphone arrays and phased microphone arrays for source diagnostics purposes. In general, the phased array results corroborated the far field results in the upstream quadrant pointing to JFI near the flaperon trailing edge as the origin of the far field noise changes. Specific sawtooth trailing edges in conjunction with the round nozzle gave marginal reduction in JFI noise at approach, and parallel co-rotating mini-vg s were somewhat more beneficial over a wider range of angles, but both concepts were noisier at take-off conditions. These two concepts had generally an adverse JFI effect when used in conjunction with the advanced chevron nozzle at both approach and take-off conditions.

Thomas, Russell H.↗
NASA NTRSDate not supplied

NASA Space Launch System Artemis I & II Post Flight Ascent Aerothermal Environments Overview

Since 2011 the Aerosciences Branch/EV33 at NASA Marshall Space Flight Center has been involved with the development of ascent external aerothermal environments for the NASA Space Launch System (SLS) Block 1 launch vehicle for the purposes of supporting thermal analysis and the design of thermal protection systems. The SLS Block 1 Artemis I and II launch vehicles successfully launched from Pad39B at NASA Kennedy Space Center on November 16th, 2022 and April 1st, 2026, respectively. Over 70 aerothermal islands, consisting of over 265 operational instruments captured aerodynamic heating and plume induced environments throughout the launch vehicles. Gauges consisted of calorimeters, radiometers, gas temperature probes, pressure transducers, bi-directional pressure probes and thermocouples. Prior to launch, aerothermal design environment models were generated to predict ascent aerodynamic heating and plume induced environments over a design space that covered a range of vehicle trajectories that varied atmospheric, vehicle performance, and off-nominal, engine-out conditions. Post flight reconstruction models were developed for each flight island using the Day-of-Launch (DOL) Best Equivalent Trajectory (BET) that provided freestream conditions and propulsion system boundary conditions. This paper discusses a summary of the ascent aerothermal environments observed during the flights and the respective modelling approaches and the performance of them through comparisons of flight data and predictions.

aerothermodynamics↗
DOE OSTI2025

Computationally efficient models for aqueous organic redox flow batteries

The rising usage of intermittent energy has garnered the need for large scale energy storage systems. Redox flow batteries (RFB) based energy storage system shows promising potential. Numerical simulations and machine learning approaches have been widely used to study RFB performance. The development of autonomous material discovery framework and digital twin of energy storage system usually needs to query cell performance through fast response models. In this study, two computationally efficient models are introduced: a physics-based analytical flow battery model (EZBattery), and a machine learning operator model (Deep Operator Network, denoted by DeepONet). Both models can provide cell performance near instantly, and prediction accuracy was systematically examined on an application of evaluating the performances of a 780 cm 2 aqueous organic redox flow battery (AORFB), using potential anolyte candidates in dihydroxyphenazine (DHP)-based family of organic materials. A validated computationally expansive 3-dimensional multi-physics finite element model by COMSOL was used as the ground truth and provided the training data set for the DeepONet. 1280 samples were generated with 10 properties to mimic the different possible anolyte candidates, and the cell performances were evaluated under 10 different combined operating conditions. The accuracy comparisons for the two computationally efficient models show that both models can provide comparable accuracy in predicting cell charging/discharging voltage curves. DeepONet can provide slightly higher overall accuracy than EZBattery with faster calculation speed, but highly relies on the training dataset. EZBattery does not need a training dataset and can provide interpretable physics-based explanations of the results, while being more flexible to adjust to adapt any different cell designs, flow battery architectures, and electrolyte materials.

Analytical model↗
NASA NTRS1991

Application of modern control design methodology to oblique wing research aircraft

A Linear Quadratic Regulator synthesis technique was used to design an explicit model following control system for the Oblique Wing Research Aircraft (OWRA). The forward path model (Maneuver Command Generator) was designed to incorporate the desired flying qualities and response decoupling. The LQR synthesis was based on the use of generalized controls, and it was structured to provide a proportional/integral error regulator with feedforward compensation. An unexpected consequence of this design approach was the ability to decouple the control synthesis into separate longitudinal and lateral directional designs. Longitudinal and lateral directional control laws were generated for each of the nine design flight conditions, and gain scheduling requirements were addressed. A fully coupled 6 degree of freedom open loop model of the OWRA along with the longitudinal and lateral directional control laws was used to assess the closed loop performance of the design. Evaluations were performed for each of the nine design flight conditions.

Vincent, James H.↗
NASA NTRS1998

A Method for Generating Reduced-Order Linear Models of Multidimensional Supersonic Inlets

Simulation of high speed propulsion systems may be divided into two categories, nonlinear and linear. The nonlinear simulations are usually based on multidimensional computational fluid dynamics (CFD) methodologies and tend to provide high resolution results that show the fine detail of the flow. Consequently, these simulations are large, numerically intensive, and run much slower than real-time. ne linear simulations are usually based on large lumping techniques that are linearized about a steady-state operating condition. These simplistic models often run at or near real-time but do not always capture the detailed dynamics of the plant. Under a grant sponsored by the NASA Lewis Research Center, Cleveland, Ohio, a new method has been developed that can be used to generate improved linear models for control design from multidimensional steady-state CFD results. This CFD-based linear modeling technique provides a small perturbation model that can be used for control applications and real-time simulations. It is important to note the utility of the modeling procedure; all that is needed to obtain a linear model of the propulsion system is the geometry and steady-state operating conditions from a multidimensional CFD simulation or experiment. This research represents a beginning step in establishing a bridge between the controls discipline and the CFD discipline so that the control engineer is able to effectively use multidimensional CFD results in control system design and analysis.

Chicatelli, Amy↗
NASA NTRS2003

Towards an Automated Full-Turbofan Engine Numerical Simulation

The objective of this study was to demonstrate the high-fidelity numerical simulation of a modern high-bypass turbofan engine. The simulation utilizes the Numerical Propulsion System Simulation (NPSS) thermodynamic cycle modeling system coupled to a high-fidelity full-engine model represented by a set of coupled three-dimensional computational fluid dynamic (CFD) component models. Boundary conditions from the balanced, steady-state cycle model are used to define component boundary conditions in the full-engine model. Operating characteristics of the three-dimensional component models are integrated into the cycle model via partial performance maps generated automatically from the CFD flow solutions using one-dimensional meanline turbomachinery programs. This paper reports on the progress made towards the full-engine simulation of the GE90-94B engine, highlighting the generation of the high-pressure compressor partial performance map. The ongoing work will provide a system to evaluate the steady and unsteady aerodynamic and mechanical interactions between engine components at design and off-design operating conditions.

Reed, John A.↗
NASA NTRS2000

Investigation of Instabilities and Heat Transfer Phenomena in Supercritical Fuels at High Heat Flux and Temperatures

A series of heated tube experiments was performed to investigate fluid instabilities that occur during heating of supercritical fluids. In these tests, JP-7 flowed vertically through small diameter tubes at supercritical pressures. Test section heated length, diameter, mass flow rate, inlet temperature, and heat flux were varied in an effort to determine the range of conditions that trigger the instabilities. Heat flux was varied up to 4 BTU/sq in./s, and test section wall temperatures reached as high as 1950 F. A statistical model was generated to explain the trends and effects of the control variables. The model included no direct linear effect of heat flux on the occurrence of the instabilities. All terms involving inlet temperature were negative, and all terms involving mass flow rate were positive. Multiple tests at conditions that produced instabilities provided inconsistent results. These inconsistencies limit the use of the model as a predictive tool. Physical variables that had been previously postulated to control the onset of the instabilities, such as film temperature, velocity, buoyancy, and wall-to-bulk temperature ratio, were evaluated here. Film temperatures at or near critical occurred during both stable and unstable tests. All tests at the highest velocity were stable, but there was no functional relationship found between the instabilities and velocity, or a combination of velocity and temperature ratio. Finally, all of the unstable tests had significant buoyancy at the inlet of the test section, but many stable tests also had significant buoyancy forces.

Linne, Diane L.↗
NASA NTRS2003

Aerodynamic Design Study of an Advanced Active Twist Rotor

An Advanced Active Twist Rotor (AATR) is currently being developed by the U.S. Army Vehicle Technology Directorate at NASA Langley Research Center. As a part of this effort, an analytical study was conducted to determine the impact of blade geometry on active-twist performance and, based on those findings, propose a candidate aerodynamic design for the AATR. The process began by creating a baseline design which combined the dynamic design of the original Active Twist Rotor and the aerodynamic design of a high lift rotor concept. The baseline model was used to conduct a series of parametric studies to examine the effect of linear blade twist and blade tip sweep, droop, and taper on active-twist performance. Rotor power requirements and hub vibration were also examined at flight conditions ranging from hover to advance ratio = 0.40. A total of 108 candidate designs were analyzed using the second-generation version of the Comprehensive Analytical Model of Rotorcraft Aerodynamics and Dynamics (CAMRAD II) code. The study concluded that the vibration reduction capabilities of a rotor utilizing controlled, strain-induced twisting are enhanced through the incorporation of blade tip sweep, droop, and taper into the blade design, while they are degraded by increasing the nose-down linear blade twist. Based on the analysis of rotor power, hub vibration, and active-twist response, a candidate aerodynamic design for the AATR consisting of a blade with approximately 10 degrees of linear blade twist and a blade tip design with 30 degree sweep, 10 degree droop, and 2.5:1 taper ratio over the outer five percent of the blade is proposed.

Sekula, Martin K.↗
DOE OSTI2024

Learning-Based Building Flexibility Estimation and Control to Improve Microgrid Economics and Resilience: Preprint

This paper proposes a learning-based building flexibility estimation and control framework to improve system economics and resilience. A data-driven building load flexibility model consisting of weather forecasting and estimating load consumption is proposed to quantify building heating, ventilation, and air conditioning (HVAC) load flexibility. A reinforcement learning-based microgrid controller is proposed to dispatch distributed generators, distributed energy resources, and build HVAC loads while taking flexibility information as one of the inputs. Simulation analysis is conducted on the model of a real microgrid in California. The effectiveness of the proposed learning-based building flexibility estimation and control in reducing microgrid energy costs and improving the sustainability of critical loads is demonstrated.

building load flexibility↗
NASA NTRS1988

Cryogenic, high speed, turbopump bearing cooling requirements

Although the Space Shuttle Main Engine (SSME) has repeatedly demonstrated the capability to perform during launch, the High Pressure Oxidizer Turbopump (HPOTP) main shaft bearings have not met their 7.5 hour life requirement. A tester is being employed to provide the capability of subjecting full scale bearings and seals to speeds, loads, propellants, temperatures, and pressures which simulate engine operating conditions. The tester design permits much more elaborate instrumentation and diagnostics than could be accommodated in an SSME turbopump. Tests were made to demonstrate the facilities; and the devices' capabilities, to verify the instruments in its operating environment and to establish a performance baseline for the flight type SSME HPOTP Turbine Bearing design. Bearing performance data from tests are being utilized to generate: (1) a high speed, cryogenic turbopump bearing computer mechanical model, and (2) a much improved, very detailed thermal model to better understand bearing internal operating conditions. Parametric tests were also made to determine the effects of speed, axial loads, coolant flow rate, and surface finish degradation on bearing performance.

Dolan, Fred J.↗
NASA NTRS1985

Creep fatigue life prediction for engine hot section materials (isotropic)

The first two years of a two-phase program aimed at improving the high temperature crack initiation life prediction technology for gas turbine hot section components are discussed. In Phase 1 (baseline) effort, low cycle fatigue (LCF) models, using a data base generated for a cast nickel base gas turbine hot section alloy (B1900+Hf), were evaluated for their ability to predict the crack initiation life for relevant creep-fatigue loading conditions and to define data required for determination of model constants. The variables included strain range and rate, mean strain, strain hold times and temperature. None of the models predicted all of the life trends within reasonable data requirements. A Cycle Damage Accumulation (CDA) was therefore developed which follows an exhaustion of material ductility approach. Material ductility is estimated based on observed similarities of deformation structure between fatigue, tensile and creep tests. The cycle damage function is based on total strain range, maximum stress and stress amplitude and includes both time independent and time dependent components. The CDA model accurately predicts all of the trends in creep-fatigue life with loading conditions. In addition, all of the CDA model constants are determinable from rapid cycle, fully reversed fatigue tests and monotonic tensile and/or creep data.

Moreno, Vito↗
NASA NTRS2012

Acoustic Investigation of Jet Mixing Noise in Dual Stream Nozzles

In an earlier study, a prediction model for jet noise in dual stream jets was proposed that is founded on velocity scaling laws in single stream jets and similarity features of the mean velocity and turbulent kinetic energy in dual stream flows. The model forms a composite spectrum from four component single-stream jets each believed to represent noise-generation from a distinct region in the actual flow. While the methodology worked effectively at conditions considered earlier, recent examination of acoustic data at some unconventional conditions indicate that further improvements are necessary in order to expand the range of applicability of the model. The present work demonstrates how these predictions compare with experimental data gathered by NASA and industry for the purpose of examining the aerodynamic and acoustic performance of such nozzles for a wide range of core and fan stream conditions. Of particular interest are jets with inverted velocity and temperature profiles and the appearance of a second spectral peak at small aft angles to the jet under such conditions. It is shown that a four-component spectrum succeeds in modeling the second peak when the aft angle refraction effects are properly incorporated into the model. A tradeoff of noise emission takes place between two turbulent regions identified as transition and fully mixed regions as the fan stream velocity exceeds that of the core stream. The effect of nozzle discharge coefficients will also be discussed.

Khavaran, Abbas↗
DOE OSTI2025

Holistic Microstructure Control Strategies in Photopolymerization‐Induced Phase Separation of Acrylate Systems

Open porous materials, known for their large surface area and interconnected structures, are essential in various applications, including batteries, ion exchange, catalysis, filtration, and electronic waste recycling. A critical aspect of the functionality of porous membranes is the precise control of pore size and morphology. Photopolymerization-induced phase separation (photo-PIPS) offers a convenient and versatile methods for creating porous structures. However, controlling the porous morphology remains challenging due to the complex interplay between thermodynamics, polymerization kinetics, and monomer structures, which makes it difficult to establish the relationship between processing conditions and resulting morphology in photo-PIPS. Herein, a physics-based phase-field model capable of generating and characterizing the microstructures of porous materials based on both average and localized features is developed. Using the phase-field simulations as test bed, the effects of polarity, light intensity, and curing temperature, as well as the previously unexplored roles of chain transfer agents and substrates, on the morphology of the resulting porous microstructure are investigated. Experiments are performed to verify the results predicted by the simulations. This work lays out a comprehensive guide for designing PIPS-derived porous microstructures and offers practical engineering strategies for tailoring microstructure-level topology and size of pores for application-specific needs.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Field-level reconstruction from foreground-contaminated 21-cm maps

Current and upcoming 21-cm experiments will soon be able to map 21-cm spatial fluctuations in three dimensions for a wide range of redshifts. However, bright foreground contamination and the nature of radio interferometry create significant challenges, making it difficult to access rich cosmological information from the Fourier modes that lie within the “foreground wedge”. Here, in this work, we introduce two approaches aiming to reconstruct the full 21-cm density field, including the missing modes in the wedge: (a) a field-level inference under an effective field theory (EFT) framework; (b) a diffusion-based deep generative model trained on simulations. Under the EFT framework, we implement a fully differentiable forward model that maps the initial conditions of matter fluctuations to the observed, foreground-filtered 21-cm maps. This enables a gradient-based sampler to simultaneously sample the initial conditions and bias parameters, allowing a physically motivated mode reconstruction. Alternatively, we apply a variational diffusion model to perform 21-cm density reconstruction at the map level. Our model is trained on semi-numerical simulations over a wide range of astrophysical parameters. Our results from both approaches should provide improved cosmological constraints from the field level and also enable cross-correlation between experiments that have little or no overlapping modes.

cosmological perturbation theory↗
DOE OSTI2024

Investigating Oscillations in Bulb Turbine Plant During Islanded black start Operation

This paper investigates the frequency oscillatory behavior displayed by the bulb turbine-based run-of-river (ROR) hydropower system under islanded operation. These oscillations prevent higher loading of these generators (under islanded conditions) and hence reduce the black start capability of these generators. To investigate the problem, first, a transfer function model of the bulb-turbine system, sensitive to the effects of head variation, blade angle, and other non-linearities pertaining to turbine characteristics is derived. Next, by analyzing this transfer function model and through simulations, it is determined that system inertia along with other parameters could be responsible for these oscillations. Also, through simulations it is shown that the same ROR system’s behavior is different under islanded mode compared to grid-connected mode.

13 HYDRO ENERGY↗
DOE OSTI2026

CTGAN-TVAE

SAND2026-18914O CTGAN-TVAE (Conditional Tabular Generative Adversarial Networks-Tabular Variational Autoencoders) generates extensive sets of variable generation data through a hybrid framework. It enhances latent space representation by combining TVAE's robust feature-embedding with CTGAN's ability to condition categorical variables such as time. CTGAN-TVAE employs a fully connected neural network within a conditional generative adversarial network framework to manage continuous and categorical data effectively, capturing complex feature interactions without needing sequential modeling. This was developed as part of NNSA-MSIPP: Minority Serving Institution Partnership Program, Grant Number DE-NA0004016. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.

Newlun, Cody [Sandia National Lab. (SNL-CA), Liver↗
DOE OSTI2024

Dynamic Temporal Graph Sequence Data for Resilience-Oriented Distribution Network Reconfiguration

This dataset comprises temporal dynamic graph sequences generated from power grid simulations focused on grid reconfiguration to enhance resilience. The simulations model failure propagation under varying conditions, with nodes assigned distinct failure probabilities. For each time step, the dataset captures the evolution of node states (functional or failed) and features critical to grid operations, such as pv_output, load_profile, load_dispatch, dg_output, loss, and voltage. Node types include sources, normal loads, and nodes with specific equipment like PVs, micro turbines, or shunt capacitors. The dataset is structured to support the training of dynamic graph neural networks, facilitating research on node feature prediction and edge dynamics under failure scenarios. Three distinct configurations are included, providing a robust foundation for modeling power grid resilience.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗