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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 469 records · Page 26

GGOT total pressure loss control concept evaluation

Total pressure loss is one of the most important parameters in the design of a turbine. This parameter effects not only the turbine performance, but consequently the engine power balance and engine performance. Computational Fluid Dynamics (CFD) can be an effective tool in predicting turbine total pressure loss, and also for performing sensitivity studies to achieve an optimal design with respect to pressure loss. In the present study, the AEROVISC code was used to predict the total pressure loss in the Turbine Technology Team Gas Generator Oxidizer Turbine (GGOT). The objectives in this study are two-fold. It is first necessary to determine an optimal methodology in predicting total pressure loss. The type of grid, grid density and distribution are parameters which may affect the loss prediction. Also, the effect of using a standard K-epsilon turbulence model with wall functions versus a two-layer turbulence model needs to be investigated. The use of grid embedding to resolve areas with high flow gradients needs to be explored. The second objective of the study is to apply the optimal methodology toward evaluating different tip leakage control concepts.

Blumenthal, R. F.↗

A guide to the use of the pressure disk rotor model as implemented in INS3D-UP

This is a guide for the use of the pressure disk rotor model that has been placed in the incompressible Navier-Stokes code INS3D-UP. The pressure disk rotor model approximates a helicopter rotor or propeller in a time averaged manner and is intended to simulate the effect of a rotor in forward flight on the fuselage or the effect of a propeller on other aerodynamic components. The model uses a modified actuator disk that allows the pressure jump across the disk to vary with radius and azimuth. The cyclic and collective blade pitch angles needed to achieve a specified thrust coefficient and zero moment about the hub are predicted. The method has been validated with experimentally measured mean induced inflow velocities as well as surface pressures on a generic fuselage. Overset grids, sometimes referred to as Chimera grids, are used to simplify the grid generation process. The pressure disk model is applied to a cylindrical grid which is embedded in the grid or grids used for the rest of the configuration. This document will outline the development of the method, and present input and results for a sample case.

Chaffin, Mark S.↗

Adaptive Finite Element Methods for Continuum Damage Modeling

The paper presents an application of adaptive finite element methods to the modeling of low-cycle continuum damage and life prediction of high-temperature components. The major objective is to provide automated and accurate modeling of damaged zones through adaptive mesh refinement and adaptive time-stepping methods. The damage modeling methodology is implemented in an usual way by embedding damage evolution in the transient nonlinear solution of elasto-viscoplastic deformation problems. This nonlinear boundary-value problem is discretized by adaptive finite element methods. The automated h-adaptive mesh refinements are driven by error indicators, based on selected principal variables in the problem (stresses, non-elastic strains, damage, etc.). In the time domain, adaptive time-stepping is used, combined with a predictor-corrector time marching algorithm. The time selection is controlled by required time accuracy. In order to take into account strong temperature dependency of material parameters, the nonlinear structural solution a coupled with thermal analyses (one-way coupling). Several test examples illustrate the importance and benefits of adaptive mesh refinements in accurate prediction of damage levels and failure time.

Min, J. B.↗

Examination of Scanning Electron Microscope and Computed Tomography Images of PICA

Micrographs of PICA (Phenolic Impregnated Carbon Ablator) taken using a Scanning Electron Microscope (SEM) and 3D images taken with a Computed Tomography (CT) system are examined. PICA is a carbon fiber based composite (Fiberform ) with a phenolic polymer matrix. The micrographs are taken at different surface depths and at different magnifications in a sample after arc jet testing and show different levels of oxidative removal of the charred matrix (Figs 1 though 13). CT scans, courtesy of Xradia, Inc. of Concord CA, were captured for samples of virgin PICA, charred PICA and raw Fiberform (Fig. 14). We use these images to calculate the thermal conductivity (TC) of these materials using correlation function (CF) methods. CF methods give a mathematical description of how one material is embedded in another and is thus ideally suited for modeling composites like PICA. We will evaluate how the TC of the materials changes as a function of surface depth. This work is in collaboration with ETH-Zurich, which has expertise in high temperature materials and TC modeling (including CF methods).

Lawson, John W.↗

Leveraging High-Level Synthesis to Migrate Motor Control Algorithms From Microcontroller to FPGA

As motor control algorithms become increasingly complex, traditional microcontroller-based implementations are reaching computational limits that prevent the controller from operating at the required speed. This paper presents a novel workflow leveraging High-Level Synthesis (HLS) to migrate motor control algorithms from a microcontroller implementation to a Field-Programmable Gate Array (FPGA) implementation. The proposed approach utilizes the free Vitis HLS software to automatically convert Embedded Coder-generated C code from a Simulink model into Hardware Description Language (HDL) code suitable for FPGA deployment.

FPGA↗

Leveraging High-Level Synthesis to Migrate Motor Control Algorithms From Microcontroller to FPGA

As motor control algorithms become increasingly complex, traditional microcontroller-based implementations are reaching computational limits that prevent the controller from operating at the required speed. This paper presents a novel workflow leveraging High-Level Synthesis (HLS) to migrate motor control algorithms from a microcontroller implementation to a Field-Programmable Gate Array (FPGA) implementation. The proposed approach utilizes the free Vitis HLS software to automatically convert Embedded Coder-generated C code from a Simulink model into Hardware Description Language (HDL) code suitable for FPGA deployment.

FPGA↗

Theoretical Modeling of Formic Acid (HCOOH), Formate (HCOO(-)), and Ammonia (NH(4)) Vibrational Spectra in Astrophysical Ices

Ions embedded in icy grain mantles are thought to account for various observed infrared spectroscopic features, particularly in certain young stellar objects. The dissociation of formic acid (HCOOH) in astrophysical ices to form the formate ion (HCOO(-)) was modeled with density functional theory cluster calculations. Like isocyanic acid (HOCN), HCOOH was found to spontaneously deprotonate when sufficient water is present to stabilize charge transfer complexes. Both ammonia and water can serve as proton acceptors, yielding ammonium (NH4(+)) and hydronium (H3O(+)) counterions. Computed frequencies of weak infrared features produced by stretching and bending modes in both HCOO(-) and HCOOH were compared with experimental and astronomical data. Our results confirm laboratory assignments that a band at 1381 cm(exp -1) can be attributed to the CH bend in either HCOO(-) or HCOOH, but a band at 1349 cm(exp -1) corresponds to CO stretching in HCOO(-). Another feature at 1710 cm(exp -1) (5.85 m) can possibly be assigned to a CO stretching mode in HCOOH, as suggested by experiment, but the agreement is less satisfactory. In addition, we examine and analyze spectroscopic features associated with NH+4, both as a counterion to HCOO(-) or OCN(-) and in isolation, in order to compare with experimental and astronomical data in the 7 m region.

Park, Jin-Young↗

Finite-Element Vibration Analysis and Modal Testing of Graphite Epoxy Tubes and Correlation Between the Data

Structural materials in the form of graphite epoxy composites with embedded rubber layers are being used to reduce vibrations in rocket motor tubes. Four filament-wound, graphite epoxy tubes were studied to evaluate the effects of the rubber layer on the modal parameters (natural vibration frequencies, damping, and mode shapes). Tube 1 contained six alternating layers of 30-degree helical wraps and 90-degree hoop wraps. Tube 2 was identical to tube 1 with the addition of an embedded 0.030-inch-thick rubber layer. Tubes 3 and 4 were identical to tubes 1 and 2, respectively, with the addition of a Textron Kelpoxy elastomer. This report compares experimental modal parameters obtained by impact testing with analytical modal parameters obtained by NASTRAN finite-element analysis. Four test modes of tube 1 and five test modes of tube 3 correlate highly with corresponding analytical predictions. Unsatisfactory correlation of test and analysis results occurred for tubes 2 and 4 and these comparisons are not shown. Work is underway to improve the analytical models of these tubes. Test results clearly show that the embedded rubber layers significantly increase structural modal damping as well as decrease natural vibration frequencies.

Taleghani, Barmac K.↗

Validation of a Thermo-Ablative Model of Elastomeric Internal Insulation Materials

In thermo-ablative material modeling, as in many fields of analysis, the quality of the existing models significantly exceeds that of the experimental data required for their validation. In an effort to narrow this gap, a laboratory-scale internal insulation test bed was developed that exposes insulation samples to realistic solid rocket motor (SRM) internal environments while being instrumented to record real-time rates of both model inputs (i.e., chamber pressure, total surface heat flux, and radiative heat flux) as well as model outputs (i.e., material decomposition depths (MDDs) and in-depth material temperatures). In this work, the measured SRM internal environment parameters were used in conjunction with equilibrium thermochemistry codes as inputs to one-dimensional thermo-ablative models of the PBINBR and CFEPDM insulation samples used in the lab-scale test firings. The computed MDD histories were then compared with those deduced from real-time X-ray radiography of the insulation samples, and the calculated in-depth temperatures were compared with those measured by embedded thermocouples. The results of this exercise emphasize the challenges of modeling and testing elastomeric materials in SRM environments while illuminating the path forward to improved fidelity.

Martin, Heath T.↗

Embedded mesh solution of the 2-D Euler equations - Evaluation of interface formulations

Solution of the steady 2-D Euler equations using mesh embedding, or local grid refinement, with a cell-centered finite volume scheme is investigated. Embedded regions which are topologically similar to the global grid are considered. An isoenergetic model for the governing equations is used in Jameson's finite volume multistage scheme with modifications to the boundary conditions and smoothing. A detailed study of the embedding interface flux and smoothing formulations is conducted. Taylor expansion analysis reveals that local second order spatial accuracy is not possible if a conservative interface flux formulation is used. The analysis also gives constraints for local first order accuracy. An energy stability analysis indicates that downwind weighting of interface fluxes causes local instabilities. Analysis shows that conservative interface smoothing formulations must have a locally convective component, but that correct interface formulations allow globally dissipative smoothing. Embedded mesh solutions obtained with this scheme are presented for a transonic airfoil. They show that if embedding interfaces are close to the shocks, then small modifications in the interface location can have large effects on converge and solution accuracy.

Allmaras, S. R.↗

Modeling and Inverse Controller Design for an Unmanned Aerial Vehicle Based on the Self-Organizing Map

The next generation of aircraft will have dynamics that vary considerably over the operating regime. A single controller will have difficulty to meet the design specifications. In this paper, a SOM-based local linear modeling scheme of an unmanned aerial vehicle (UAV) is developed to design a set of inverse controllers. The SOM selects the operating regime depending only on the embedded output space information and avoids normalization of the input data. Each local linear model is associated with a linear controller, which is easy to design. Switching of the controllers is done synchronously with the active local linear model that tracks the different operating conditions. The proposed multiple modeling and control strategy has been successfully tested in a simulator that models the LoFLYTE UAV.

Cho, Jeongho↗

Semantic Stealth: Crafting Covert Adversarial Patches for Sentiment Classifiers Using Large Language Models

Deep learning models have been shown to be vulnerable to adversarial attacks, in which perturbations to their inputs cause the model to produce incorrect predictions. As opposed to adversarial attacks in computer vision, where small changes introduced to pixel values can drastically alter a model's output while remaining imperceptible to humans, text-based attacks are difficult to conceal due to the discrete nature of tokens. Consequently, unconstrained gradient-based attacks often produce adversarial examples that lack semantic meaning, rendering them detectable through visual inspection or perplexity filters. In contrast to methods that rely on gradient-based optimization in the embedding space, we propose an approach that leverages a Large Language Model's ability to generate grammatically correct and semantically meaningful text to craft adversarial patches that seamlessly blend in with the original input text. These patches can be used to alter the behavior of a target model, such as a text classifier. Since our approach does not rely on gradient backpropagation, it only requires access to the target model's confidence scores, making it a grey-box attack. We demonstrate the feasibility of our approach using open-source LLMs, including Intel's Neural Chat, Llama2, and Mistral-Instruct, to generate adversarial patches capable of altering the predictions of a distilBERT model fine-tuned on the IMDB reviews dataset for sentiment classification.

Roa Carvajal, Maria↗

Hybrid Quantum–Classical Graph Transformers for Efficient Sentiment Analysis

Quantum Machine Learning (QML) offers a promising paradigm that leverages quantum computing principles to develop efficient and expressive models for learning from complex and structured data. Recent advances in natural language processing (NLP) and artificial intelligence (AI) have demonstrated capabilities in understanding, generating, and reasoning over linguistic and multimodal information. In this work, we present the Quantum Graph Transformer (QGT), a hybrid quantum–classical architecture that extends graph transformer capabilities through quantum self-attention. The QGT models variable-length sentences as token graphs, where both the embedding encoding and the self-attention mechanisms are implemented using parameterized quantum circuits (PQCs), enabling efficient contextual learning with significantly fewer trainable parameters. We train QGT using both fully connected and 𝑘 -nearest-neighbor graph structures and evaluate it on five benchmark sentiment-classification datasets. Experimental results show that QGT consistently achieves higher or comparable accuracy to existing quantum NLP models and outperforms a Classical Graph Transformer (CGT) baseline with identical architecture, achieving 29.4 × fewer parameters while requiring 3–5 × fewer samples to reach comparable performance. These findings highlight the potential of graph-based quantum models as scalable and data-efficient architectures for natural language understanding.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Transfer function models for using empirical and physics-based simulation signal response data

In many situations, real or induced flaws such as tight cracks with known morphology cannot be manufactured in part geometry specimens or in real parts. Typically, surface fatigue cracks are manufactured in simple geometry specimens such as flat plates, dog-bone shaped flat or cylindrical specimens. If a nondestructive evaluation (NDE)technique is required to provide a reliably detectable flaw size, denoted asa90/95, for induced flaws in a part, then a direct method for qualifying the NDE procedure is to use appropriate induced flaw specimens and perform NDE procedure demonstration on the specimens. Probability of detection (POD)analysis of the empirical data may provide estimation of a90/95. This approach is described as direct POD demonstration testing, which may follow guidelines of MIL-HDBK-1823. This paper considers a case, where embedded tight cracklike induced flaws are to be detected reliably using a signal response based NDE procedure. Here, it is assumed that it is not practical to make surface or embedded induced flaw specimens in part geometry or configuration. Therefore, a direct POD demonstration testing cannot be undertaken. It is also assumed that simulation of signal response is possible for both surface and embedded induced flaws in part geometry specimens using a physics-based model. The proposed approach for NDE procedure qualification uses artificial flaws in simple geometry and part geometry specimens, and induced flaws in the same type of simple geometry specimens. Signal response data is taken on all sets of artificial and induced flaws in simple geometry and part geometry specimens. Moreover, simulated signal response data is generated for surface and embedded flaws. Thus, a case of five signal response versus flaw size datasets is considered. Three of the datasets are empirical and two datasets are physics model-based simulation datasets. A method of devising and using transfer function calculation dataset blocks to estimate the either the reliably detectable flaw size or the demonstration flaw size is provided.

Nondestructive evaluation↗

A siphon-flow model of the photospheric Evershed flow in a sunspot

The Evershed flow at photospheric heights in a sunspot penumbra is modeled theoretically as a siphon flow along individual, arched magnetic flux tubes embedded in an atmosphere permeated by a uniform magnetic field. This approach is suggested by the recent evidence that the penumbra is a deep structure with a significant amount of emerging flux, rather than a shallow structure overlying field-free gas. The model resolves two problems associated with siphon-flow models based on a shallow penumbra: it produces arched flux tubes of sufficient horizontal extent, and it explains how the optically thin flux tubes carrying the Evershed flow can appear dark.

Thomas, John H.↗

Validating Requirements for Fault Tolerant Systems Using Model Checking

Model checking is shown to be an effective tool in validating the behavior of a fault tolerant embedded spacecraft controller. The case study presented here shows that by judiciously abstracting away extraneous complexity, the state space of the model could be exhaustively searched allowing critical functional requirements to be validated down to the design level. Abstracting away detail not germane to the problem of interest leaves by definition a partial specification behind. The success of this procedure shows that it is feasible to effectively validate a partial specification with this technique. Three anomalies were found in the system one of which is an error in the detailed requirements, and the other two are missing/ambiguous requirements. Because the method allows validation of partial specifications, it also is an effective methodology towards maintaining fidelity between a co-evolving specification and an implementation.

Schneider, Francis↗

Validating Requirements for Fault Tolerant Systems Using Model Checking

Model checking is shown to be an effective tool in validating the behavior of a fault tolerant embedded spacecraft controller. The case study presented here shows that by judiciously abstracting away extraneous complexity, the state space of the model could be exhaustively searched allowing critical functional requirements to be validated down to the design level.

Fault↗

A variable-gain output feedback control design approach

A multi-model design technique to find a variable-gain control law defined over the whole operating range is proposed. The design is formulated as an optimal control problem which minimizes a cost function weighing the performance at many operating points. The solution is obtained by embedding into the Multi-Configuration Control (MCC) problem, a multi-model robust control design technique. In contrast to conventional gain scheduling which uses a curve fit of single model designs, the optimal variable-gain control law stabilizes the plant at every operating point included in the design. An iterative algorithm to compute the optimal control gains is presented. The methodology has been successfully applied to reconfigurable aircraft flight control and to nonlinear flight control systems.

Haylo, Nesim↗