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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 613 records · Page 34
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Error analysis of a hybrid control drum worth model

This paper presents a perturbation-based model for control drum worth prediction which employs both physics-based and statistics-based components. Control drums, or control shims, are cylindrical in shape and span the axial length of the core. A portion of the cylinder is coated in neutron absorbing material and the drum can rotate to introduce the absorbing material to the body of the core to reduce reactivity. The model can be expensive to create due to the requirement for full-core Monte Carlo eigenvalue calculations. Therefore, it is important to analyze how the errors in Monte Carlo calculated k{sub eff} used for model training affect model performance. It was found that the error in predicted criticalities could average to 70 pcm in the most complex form of the model and 215 pcm in the simplest form of the model. Furthermore, it was found that the Monte Carlo uncertainty in quantities calculated with Serpent used to train the models had minimal impact on the error observed from the model. Lastly, one of the forms of the hybrid model could be trained in considerably less computational time if the Monte Carlo calculations were run to higher uncertainty in k{sub eff} with a small penalty to model performance.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
NASA NTRS2015

Predicting Time Series Outputs and Time-to-Failure for an Aircraft Controller Using Bayesian Modeling

Safety of unmanned aerial systems (UAS) is paramount, but the large number of dynamically changing controller parameters makes it hard to determine if the system is currently stable, and the time before loss of control if not. We propose a hierarchical statistical model using Treed Gaussian Processes to predict (i) whether a flight will be stable (success) or become unstable (failure), (ii) the time-to-failure if unstable, and (iii) time series outputs for flight variables. We first classify the current flight input into success or failure types, and then use separate models for each class to predict the time-to-failure and time series outputs. As different inputs may cause failures at different times, we have to model variable length output curves. We use a basis representation for curves and learn the mappings from input to basis coefficients. We demonstrate the effectiveness of our prediction methods on a NASA neuro-adaptive flight control system.

Statistics↗
NASA NTRS1990

System identification requirements for high-bandwidth rotorcraft flight control system design

The application of system identification methods to high-bandwidth rotorcraft flight control system design is examined. Flight test and modeling requirements are illustrated using flight test data from a BO-105 hingeless rotor helicopter. The proposed approach involves the identification of nonparametric frequency-response models followed by parametric (transfer funtion and state space) model identification. Results for the BO-105 show the need for including coupled body/rotor flapping and lead-lag dynamics in the identification model structure to allow the accurate prediction of control system bandwidth limitations. Lower-order models are useful for estimating nominal control system performance only when the flight data used for the identification are band-limited to be consistent with the frequency range of applicability of the model. The flight test results presented in this paper are consistent with theoretical studies by previous researchers.

Tischler, Mark B.↗
NASA NTRS2017

Two-Pendulum Model of Propellant Slosh in Europa Clipper PMD Tank

The objective of this fluids analysis is to model propellant slosh for the Europa Clipper mission using a two-pendulum model, such that controls engineers can predict slosh behavior during the mission. Propellant slosh causes shifts in center of mass and exerts forces and torques on the spacecraft which, if not adequately controlled, can lead to mission failure. The two-pendulum model provides a computationally simple model that can be used to predict slosh for the Europa Clipper tank geometry. The Europa Clipper tank is cylindrical with a domed top and bottom and includes a propellant management device (PMD). Due to the lack of experimental data in low gravity environments, computational fluid dynamics (CFD) simulation results were used as 'real' slosh behavior for two propellants at three fill fractions. Key pendulum parameters were derived that allow the pendulum model's center of mass, forces, and moments to closely match the CFD data. The parameter trends were examined as a function of tank fill fraction and compared with solutions to analytic equations that describe the frequency of slosh in tanks with simple geometries. The trends were monotonic as expected, and parameters resembled analytical predictions; any differences could be explained by the specific differences in the geometry of the tank. This paper summarizes the new method developed at Goddard Space Flight Center (GSFC) for deriving pendulum parameters for two-pendulum equivalent sloshing models. It presents the results of this method and discusses the validity of the results. This analysis is at a completed stage and will be applied in the immediate future to the evolving tank geometry as Europa Clipper moves past its preliminary design review (PDR) phase.

Propellant Slosh↗
DOE OSTI2023

Effects of Substance Use and Antisocial Personality on Neuroimaging-Based Machine Learning Prediction of Schizophrenia

Abstract Background and hypothesis Neuroimaging-based machine learning (ML) algorithms have the potential to aid the clinical diagnosis of schizophrenia. However, literature on the effect of prevalent comorbidities such as substance use disorder (SUD) and antisocial personality (ASPD) on these models’ performance has remained unexplored. We investigated whether the presence of SUD or ASPD affects the performance of neuroimaging-based ML models trained to discern patients with schizophrenia (SCH) from controls. Study design We trained an ML model on structural MRI data from public datasets to distinguish between SCH and controls (SCH = 347, controls = 341). We then investigated the model’s performance in two independent samples of individuals undergoing forensic psychiatric examination: sample 1 was used for sensitivity analysis to discern ASPD (N = 52) from SCH (N = 66), and sample 2 was used for specificity analysis to discern ASPD (N = 26) from controls (N = 25). Both samples included individuals with SUD. Study results In sample 1, 94.4% of SCH with comorbid ASPD and SUD were classified as SCH, followed by patients with SCH + SUD (78.8% classified as SCH) and patients with SCH (60.0% classified as SCH). The model failed to discern SCH without comorbidities from ASPD + SUD (AUC = 0.562, 95%CI = 0.400–0.723). In sample 2, the model’s specificity to predict controls was 84.0%. In both samples, about half of the ASPD + SUD were misclassified as SCH. Data-driven functional characterization revealed associations between the classification as SCH and cognition-related brain regions. Conclusion Altogether, ASPD and SUD appear to have effects on ML prediction performance, which potentially results from converging cognition-related brain abnormalities between SCH, ASPD, and SUD.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2024

Preliminary Results on Process Modeling Tools for Determining Variability in Additively Manufactured Stainless Steel 316 Parts

The Advanced Materials and Manufacturing Technologies program aims to accelerate the development, qualification, demonstration, and deployment of advanced materials and manufacturing technologies to enable reliable and economical nuclear energy. However, the distinct characteristics of additive manufacturing (AM) materials, stemming from their unique processing history, microstructure, and properties, pose significant challenges for the qualification and certification of nuclear components. These challenges primarily arise from component-scale variations in microstructure and properties influenced by local process conditions and geometry, which affect thermal history, melt pool dynamics, and microstructure evolution. Computational modeling tools can play a crucial role in predicting and controlling this variability. This report presents preliminary results on process modeling tools designed to predict microstructure variability in additively manufactured stainless steel 316 parts. It details the software packages and physical modeling approaches employed to simulate an AM component within an automated process modeling workflow. Initial results are demonstrated through comparisons between predicted microstructures and experimental measurements across various representative processing conditions. The report concludes by discussing the challenges inherent in process modeling of AM components and outlines a plan for future development needs.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Assessment of Microstructure Prediction Capabilities for Powder Bed Fusion Stainless Steel 316

The Advanced Materials and Manufacturing Technologies program aims to accelerate the development, qualification, demonstration, and deployment of advanced materials and manufacturing technologies to enable reliable and economical nuclear energy. However, the characteristic process-structure-property relationships of additive manufacturing (AM) materials pose challenges for the qualification and certification of AM nuclear components. In particular, component-scale variations in microstructure and properties can be driven by localized changes in melt pool dynamics due to how process parameters interact with different part geometries. Computational modeling tools can play a crucial role in predicting and controlling this variability. This report presents final results on process modeling tools designed to predict microstructure variability in additively manufactured stainless steel 316 parts. It details the software packages and physical modeling approaches employed to simulate an AM component within an automated process modeling workflow. Results are demonstrated through comparisons between predicted microstructures and experimental measurements across various representative processing conditions. The report concludes by discussing identified challenges and future opportunities for connecting the developed simulation workflow with mechanics simulations for prediction of part performance.

36 MATERIALS SCIENCE↗
NASA NTRS1989

The modeling of gas phase permeation through iron and nickel membranes

The gas phase permeation of hydrogen through metal membranes encompasses many kinetic processes. This paper reviews a permeation model which incorporates second order gas-surface reaction kinetics with simple bulk diffusion. The model is used to investigate the effect of this particular surface reaction of steady-state permeation. The dependence of the steady-state permeation flux on temperature, pressure, and thickness of the membrane has been calculated. The model predicts that the bulk controlled steady-state flux will change to a surface limited steady-state flux as either the temperature or thickness of the membrane is reduced. Finally, using independently derived parameters, the model is compared with permeation measurements on iron and nickel membranes.

Kuhn, David K.↗
DOE OSTI2022

Improved geophysical monitoring of carbon sequestration through parameter linkage to reservoir modeling

Predictive reservoir modeling, even if present in the form of only basic hydrogeological model assumptions, is expected to accompany the majority of carbon capture and sequestration monitoring activities. It thus represents a source of prior information about the migration of injected fluids that can benefit geophysical survey planning and ensuing monitoring. Constraining the imaging of geophysical monitoring data with reservoir modeling is preferable over standalone geophysical imaging because of additional complementary hydrogeological information. However, fully coupled hydrogeophysical data inversion for flow-modeling parameters that control saturation predictions is an involved process. Within the context of three-dimensional electromagnetic (EM) inversion of data from borehole-to-surface layouts, we employ a "poor people's" alternative. The approach constrains geophysical inversion parameters through saturation predictions. The coupling is realized through spatially variable lower and upper parameter bounds that scale with gas saturation magnitudes, the latter provided by reservoir modeling. In this work, enhancement of three-dimensional time-lapse plume EM imaging is demonstrated for simulated sequestration into a depleted gas reservoir.

58 GEOSCIENCES↗
NASA NTRS1995

Trend analysis of in-situ spectral reflectance data from the Thermal Control Surfaces Experiment (TCSE)

The Thermal Control Surfaces Experiment (TCSE) on the LDEF was a comprehensive experiment that combined in-space measurements with extensive pre- and post-flight analyses of thermal control surfaces to determine the effects of exposure to the low earth orbit (LEO) space environment. The TCSE is the first space experiment to directly measure in-situ total hemispherical reflectance of thermal control surfaces in the same way they are routinely measured in the laboratory. In-space optical measurements performed by the TCSE provide the unique opportunity for trend analysis of the performance of materials in the space environment. Such trend analysis of flight data offers the potential to develop an empirical life time prediction model for several thermal control surfaces. For material research, trend analysis of the TCSE flight data, particularly the spectral data, can provide insight into the damage mechanisms of space exposure. Trend analysis for the TCSE samples has been limited to those materials that were not significantly eroded by the atomic oxygen (AO) environment. The performance of several materials on the LDEF mission was dominated by AO effects. Trend analysis was performed on both the detailed spectral reflectance measurements (in-space, pre-flight, and post-flight) and on the integrated solar absorptance. Results of this analysis for the five selected TCSE materials are presented along with the spectral flight data. Possible degradation and effects mechanisms will be discussed to better understand and predict the behavior of these materials in the LEO space environment.

Wilkes, Donald R.↗
NASA NTRS2010

Correlation of Wissler Human Thermal Model Blood Flow and Shiver Algorithms

The Wissler Human Thermal Model (WHTM) is a thermal math model of the human body that has been widely used to predict the human thermoregulatory response to a variety of cold and hot environments. The model has been shown to predict core temperature and skin temperatures higher and lower, respectively, than in tests of subjects in crew escape suit working in a controlled hot environments. Conversely the model predicts core temperature and skin temperatures lower and higher, respectively, than in tests of lightly clad subjects immersed in cold water conditions. The blood flow algorithms of the model has been investigated to allow for more and less flow, respectively, for the cold and hot case. These changes in the model have yielded better correlation of skin and core temperatures in the cold and hot cases. The algorithm for onset of shiver did not need to be modified to achieve good agreement in cold immersion simulations

Bue, Grant↗
NASA NTRSDate not supplied

Generalized Predictive Control for Active Stability Augmentation and Vibration Reduction on an Aeroelastic Tiltrotor Model

Tiltrotor aircraft are defining the state-of-the-art in vertical lift technology as they have the potential to greatly expand rotary-wing operational boundaries. However, they are often limited in forward flight speed due to complex coupled rotor and wing dynamic instabilities. The U.S. Army and NASA have been developing a new wind tunnel model, the TiltRotor Aeroelastic Stability Testbed(TRAST), to test proprotors in the NASA Langley Research Center Transonic Dynamics Tunnel (TDT) to investigate aeroelastic stability in cruise. The test is intended to provide high-quality research data for analytical tool development and validation. In addition, the TRAST model will support, develop, and mature new technologies for the design of advanced proprotor aircraft. Stability augmentation and vibration reduction during testing is planned with the use of an active control methodology known as Generalized Predictive Control(GPC). GPC is an autoregressive control law that experimentally acquires a system identification to derive the input-output relation of controls and corresponding sensors. This type of control law is especially useful for complex dynamic interactions that are difficult to explicitly model such as proprotor pylon instability, often referred to as whirl flutter. GPC has been successfully employed on other tiltrotor vehicles to suppress whirl flutter instabilities and vibrations. To aid in the characterization of the wind-tunnel model and in tool development, an analytical representation of the wind-tunnel model was developed using the rotorcraft comprehensive analysis system (RCAS) that simulates structural dynamics and aerodynamics. RCAS was used to derive state-space estimates of the physical plant at various flight conditions to test control law effectiveness. This paper will present an overview of the test article development, a description of RCAS, an explanation of the GPC methodology, and results of GPC being applied to state-space plant estimates of the TRAST model. In these simulations, GPC was effective at stabilizing the aircraft beyond the whirl-flutter boundary while simultaneously reducing vibrations across the flight regime. Additionally, a modern advancement to GPC, termed advanced GPC (AGPC), is introduced that enables a self-adapting system identification. Preliminary results show that AGPC is successful at self-correction as the plant changes from what was used for system identification.

tiltrotor↗
NASA NTRS1995

Looking around: 35 years of oculomotor modeling

Eye movements have attracted an unusually large number of researchers from many disparate fields, especially over the past 35 years. The lure of this system stemmed from its apparent simplicity of description, measurement, and analysis, as well as the promise of providing a "window in the mind." Investigators in areas ranging from biological control systems and neurological diagnosis to applications in advertising and flight simulation expected eye movements to provide clear indicators of what the sensory-motor system was accomplishing and what the brain found to be of interest. The parallels between compensatory eye movements and perception of spatial orientation have been a subject for active study in visual-vestibular interaction, where substantial knowledge has accumulated through experiments largely guided by the challenge of proving or disproving model predictions. Even though oculomotor control has arguably benefited more from systems theory than any other branch of motor control, many of the original goals remain largely unfulfilled. This paper considers some of the promising potential benefits of eye movement research and compares accomplishments with anticipated results. Four topics are considered in greater detail: (i) the definition of oculomotor system input and output, (ii) optimization of the eye movement system, (iii) the relationship between compensatory eye movements and spatial orientation through the "internal model," and (iv) the significance of eye movements as measured in (outer) space.

Flight Experiment↗
DOE OSTI2024

Forward and inverse predictive transient models of TREAT using surrogate reactivity models

In this work, we present two novel approaches for predicting the power evolution and control rod height of the Transient Reactor Test Facility (TREAT) to support experiment modeling; specifically, transient analysis of the NASA-sponsored Sirius series of experiments. These approaches utilize steady-state Monte Carlo model, point kinetics model, and surrogate models to predict power evolution and control rod axial position during transient experiments. Both approaches were tested and validated against several Sirius experiments that were performed in the TREAT facility at different power levels. The validation test results show very good agreement with the experimental data, and the models were able to accurately predict the power evolution and the axial control rod position with an average error within 3.0%. Finally, this indicates that these approaches will help the reactor engineering team of the TREAT facility in preparing and predicting the power and temperature of the experiment.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2026

Building Operation Model (Morpheus) for Dallas Fort Worth Airport (CRADA CRD-19-16301 Final Report)

The primary objective of this project was to leverage digital twin technology to enhance the design and operation of DFW Airport terminals and their associated energy systems. To achieve this, Morpheus, a building digital twin, was developed to guide improvements in airport operations, specifically targeting reductions in peak power demand and overall energy consumption.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS2013

Effect of Residual Noncondensables on Pressurization and Pressure Control of a Zero-Boil-Off Tank in Microgravity

The Zero-Boil-Off Tank (ZBOT) Experiment is a small-scale experiment that uses a transparent ventless Dewar and a transparent simulant phase-change fluid to study sealed tank pressurization and pressure control with applications to on-surface and in-orbit storage of propellant cryogens. The experiment will be carried out under microgravity conditions aboard the International Space Station in the 2014 timeframe. This paper presents preliminary results from ZBOT's ground-based research that focuses on the effects of residual noncondensable gases in the ullage on both pressurization and pressure reduction trends in the sealed Dewar. Tank pressurization is accomplished through heating of the test cell wall in the wetted and un-wetted regions simultaneously or separately. Pressure control is established through mixing and destratification of the bulk liquid using a temperature controlled forced jet flow with different degrees of liquid jet subcooling. A Two-Dimensional axisymmetric two-phase CFD model for tank pressurization and pressure control is also presented. Numerical prediction of the model are compared to experimental 1g results to both validate the model and also indicate the effect of the noncondensable gas on evolution of pressure and temperature distributions in the ullage during pressurization and pressure control. Microgravity simulations case studies are also performed using the validated model to underscore and delineate the profound effect of the noncondensables on condensation rates and interfacial temperature distributions with serious implications for tank pressure control in reduced gravity.

Marangoni and Natural Convection↗
NASA NTRS1976

Correlation study of theoretical and experimental results for spin tests of a 1/10 scale radio control model

A correlation study was conducted to determine the ability of current analytical spin prediction techniques to predict the flight motions of a current fighter airplane configuration during the spin entry, the developed spin, and the spin recovery motions. The airplane math model used aerodynamics measured on an exact replica of the flight test model using conventional static and forced-oscillation wind-tunnel test techniques and a recently developed rotation-balance test apparatus capable of measuring aerodynamics under steady spinning conditions. An attempt was made to predict the flight motions measured during stall/spin flight testing of an unpowered, radio-controlled model designed to be a 1/10 scale, dynamically-scaled model of a current fighter configuration. Comparison of the predicted and measured flight motions show that while the post-stall and spin entry motions were not well-predicted, the developed spinning motion (a steady flat spin) and the initial phases of the spin recovery motion are reasonably well predicted.

Bihrle, W., Jr.↗