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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 991 records · Page 55

All sources NASA NTRS DOE OSTI

NASA NTRS2005

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↗

DOE OSTI2021

Conserved role of ATP synthase in mammalian cilia

Highlights: • ATP synthase localizes to cilia in mammalian cells. • ATP synthase is involved in ciliogenesis. • ATP synthase probably participates in polycystin signalling pathway. We previously found that ATP synthases localize to male-specific sensory cilia and control the ciliary response by regulating polycystin signalling in Caenorhabditis elegans. Herein, we discovered that the ciliary localization of ATP synthase is evolutionarily conserved in mammals. We showed that the ATP synthase subunit F1β is colocalized with the cilia marker acetylated α-tubulin in both mammalian renal epithelial cells (MDCK) and normal mouse cholangiocytes (NMCs). Treatment with ATP synthase inhibitor oligomycin impaired ciliogenesis in MDCK cells, and F1β was co-immunoprecipitated with PKD2 in mammalian cells. Our study provides evidence for the evolutionarily conserved localization of ATP synthase in cilia from worm to mammals. Defects in ATP synthase can lead to ciliary dysfunction, which may be a potential mechanism of polycystic kidney disease.

60 APPLIED LIFE SCIENCES↗

NASA NTRS1989

Energy-absorption capability of composite tubes and beams

In this study the objective was to develop a method of predicting the energy-absorption capability of composite subfloor beam structures. Before it is possible to develop such an analysis capability, an in-depth understanding of the crushing process of composite materials must be achieved. Many variables affect the crushing process of composite structures, such as the constituent materials' mechanical properties, specimen geometry, and crushing speed. A comprehensive experimental evaluation of tube specimens was conducted to develop insight into how composite structural elements crush and what are the controlling mechanisms. In this study the four characteristic crushing modes, transverse shearing, brittle fracturing, lamina bending, and local buckling were identified and the mechanisms that control the crushing process defined. An in-depth understanding was developed of how material properties affect energy-absorption capability. For example, an increase in fiber and matrix stiffness and failure strain can, depending upon the configuration of the tube, increase energy-absorption capability. An analysis to predict the energy-absorption capability of composite tube specimens was developed and verified. Good agreement between experiment and prediction was obtained.

Farley, Gary L.↗

NASA NTRS2005

Autonomous Congestion Control in Delay-Tolerant Networks

Congestion control is an important feature that directly affects network performance. Network congestion may cause loss of data or long delays. Although this problem has been studied extensively in the Internet, the solutions for Internet congestion control do not apply readily to challenged network environments such as Delay Tolerant Networks (DTN) where end-to-end connectivity may not exist continuously and latency can be high. In DTN, end-to-end rate control is not feasible. This calls for congestion control mechanisms where the decisions can be made autonomously with local information only. We use an economic pricing model and propose a rule-based congestion control mechanism where each router can autonomously decide on whether to accept a bundle (data) based on local information such as available storage and the value and risk of accepting the bundle (derived from historical statistics).

delay tolerant networking↗

DOE OSTI2022

A neural network‐enhanced reproducing kernel particle method for modeling strain localization

Abstract Modeling the localized intensive deformation in a damaged solid requires highly refined discretization for accurate prediction, which significantly increases the computational cost. Although adaptive model refinement can be employed for enhanced effectiveness, it is cumbersome for the traditional mesh‐based methods to perform while modeling the evolving localizations. In this work, neural network‐enhanced reproducing kernel particle method (NN‐RKPM) is proposed, where the location, orientation, and shape of the solution transition near a localization is automatically captured by the NN approximation via a block‐level neural network (NN) optimization. The weights and biases in the blocked parameterization network control the location and orientation of the localization. The designed basic four‐kernel NN block is capable of capturing a triple junction or a quadruple junction topological pattern, while more complicated localization topological patters are captured by the superposition of multiple four‐kernel NN blocks. The standard RK approximation is then utilized to approximate the smooth part of the solution, which permits a much coarser discretization than the high‐resolution discretization needed to capture sharp solution transitions with the conventional methods. A regularization of the NN approximation is additionally introduced for discretization‐independent material responses. The effectiveness of the proposed NN‐RKPM is verified by a series of numerical verifications.

Baek, Jonghyuk↗

NASA NTRS1993

Fuzzy logic controllers: A knowledge-based system perspective

Over the last few years we have seen an increasing number of applications of Fuzzy Logic Controllers. These applications range from the development of auto-focus cameras, to the control of subway trains, cranes, automobile subsystems (automatic transmissions), domestic appliances, and various consumer electronic products. In summary, we consider a Fuzzy Logic Controller to be a high level language with its local semantics, interpreter, and compiler, which enables us to quickly synthesize non-linear controllers for dynamic systems.

Bonissone, Piero P.↗

NASA NTRS2000

Shape-dependent control of cell growth, differentiation, and apoptosis: switching between attractors in cell regulatory networks

Development of characteristic tissue patterns requires that individual cells be switched locally between different phenotypes or "fates;" while one cell may proliferate, its neighbors may differentiate or die. Recent studies have revealed that local switching between these different gene programs is controlled through interplay between soluble growth factors, insoluble extracellular matrix molecules, and mechanical forces which produce cell shape distortion. Although the precise molecular basis remains unknown, shape-dependent control of cell growth and function appears to be mediated by tension-dependent changes in the actin cytoskeleton. However, the question remains: how can a generalized physical stimulus, such as cell distortion, activate the same set of genes and signaling proteins that are triggered by molecules which bind to specific cell surface receptors. In this article, we use computer simulations based on dynamic Boolean networks to show that the different cell fates that a particular cell can exhibit may represent a preprogrammed set of common end programs or "attractors" which self-organize within the cell's regulatory networks. In this type of dynamic network model of information processing, generalized stimuli (e.g., mechanical forces) and specific molecular cues elicit signals which follow different trajectories, but eventually converge onto one of a small set of common end programs (growth, quiescence, differentiation, apoptosis, etc.). In other words, if cells use this type of information processing system, then control of cell function would involve selection of preexisting (latent) behavioral modes of the cell, rather than instruction by specific binding molecules. Importantly, the results of the computer simulation closely mimic experimental data obtained with living endothelial cells. The major implication of this finding is that current methods used for analysis of cell function that rely on characterization of linear signaling pathways or clusters of genes with common activity profiles may overlook the most critical features of cellular information processing which normally determine how signal specificity is established and maintained in living cells. Copyright 2000 Academic Press.

Review↗

DOE OSTI2025

Lightweight Metal Stamping Optimization Enabled by Artificial Intelligence

Successfully manufacturing an automotive body structure made via the sheet metal stamping process depends upon simultaneous consideration of component design, tooling design, stamping process control, and material properties. In many cases, introducing lightweight sheet materials (e.g., aluminum alloys, magnesium alloys, advanced high strength steels) holds the potential to significantly reduce vehicle weight, but challenges the stamping process by introducing materials with inherently less ductility. Successful and repeatable applications require co-developing the stamping process controls with the varying material properties, including formability. During the stamping process, as soon as the forming limit of the sheet is exceeded, the material shows localized necking which quickly leads to splits. Controlling process variability to avoid these material splits will enable deployment of less formable, lighter, and stronger materials for stamped automotive components. A typical optimization procedure for manufacturing requires an iterative process involving parameter setting, execution of computational simulations, and modifying the parameters. The entire process demands substantial computational time, making it impractical for real-time feedback towards rapid corrective actions required for in-line control for running production processes. To overcome this challenge, artificial intelligence (AI) can be leveraged to determine optimal manufacturing parameters within a single manufacturing cycle time. This research proposes an in-line optimization framework incorporating a trained AI model to predict kidney-shaped die forming. Preliminary results indicate that the AI framework can accurately predict draw-in values based on a given parameter set, a process referred to as forward prediction. Furthermore, the AI framework can also predict the optimal parameter set that leads to the desired draw-in values, referred to as inverse optimization (or backward prediction). This research has been performed in collaborations with USCAR (US Council for Automotive Research) and AutoForm. The members of USCAR are Ford, GM, and Stellantis.

36 MATERIALS SCIENCE↗

NASA NTRS2023

Marin County Wildfires Ii: Improving Fire Suppression Modeling to Inform Fire Prevention and Suppression Decisions in Marin County, Ca

A future of increased wildfires requires greater integration of spatial analysis and local knowledge of emergency responders. We examine the application of a Potential Operational Delineations (PODs) framework for strategic pre-fire planning in Marin County. PODs are spatial units for wildfire management that combine predictive modeling and local firefighter expertise to identify potential control locations as unit boundaries and assess the difficulty of suppression within units. Additionally, this project explores the integration of road networks and social vulnerability to assess environmental justice in evacuation safety. This project constitutes a novel application of the PODs framework as it integrates expertise from Marin County senior firefighters with a Fireline Location Model (FLM) to achieve POD definition and uses a Suppression Difficulty Score (SDS) to rank each POD. The FLM uses network analysis and hydrologic modeling to identify key roads and ridgelines as boundaries and combines them with expert knowledge, in the form of workshops, to construct PODs. Once identified, PODs are classified using SDS, which includes processed inputs such as LiDAR-derived aboveground biomass, ECOSTRESS Evaporative Stress Index, land use cover type from Sentinel-2 Imagery, and a digital elevation model. Environmental justice for evacuation safety incorporated three key road metrics such as connectivity, travel area, and exit capacity, the Social Vulnerability Index from the Center for Disease Control, and cell coverage to determine a final Evacuation Difficulty Score. Results indicate a strong link between road networks as primary POD boundaries, with ridgelines and waterways as secondary and tertiary locations. Specifically, we find 78.5% of expertise-identified POD boundaries align with FLM-determined boundaries. More validation is needed to support this process; however, initial results signal a feasible framework to integrate expertise and spatial analysis in local level strategic fire planning

Wildfire modeling↗

NASA NTRS1985

Active control of compressible flows on a curved surface

The effect of localized, time periodic surface heating and cooling over a curved surface is studied. This is a mechanism for the active control of unstable disturbances by phase cancellation and reinforcement. It is shown that the pressure gradient induced by the curvature significantly enhances the effectiveness of this form of active control. In particular, by appropriate choice of phase, active surface heating can completely stabilize and unstable wave.

Maestrello, L.↗

NASA NTRS1985

Active control of compressible flows on a curved surface

Maestrello, L.↗

DOE OSTI2022

Manipulating the insulator–metal transition through tip-induced hydrogenation

Manipulating the insulator–metal transition in strongly correlated materials has attracted a broad range of research activity due to its promising applications in, for example, memories, electrochromic windows and optical modulators. Electric-field-controlled hydrogenation using ionic liquids and solid electrolytes is a useful strategy to obtain the insulator–metal transition with corresponding electron filling, but faces technical challenges for miniaturization due to the complicated device architecture. Here, in this work, we demonstrate reversible electric-field control of nanoscale hydrogenation into VO 2 with a tunable insulator–metal transition using a scanning probe. The Pt-coated probe serves as an efficient catalyst to split hydrogen molecules, while the positive-biased voltage accelerates hydrogen ions between the tip and sample surface to facilitate their incorporation, leading to non-volatile transformation from insulating VO 2 into conducting H x VO 2 . Remarkably, a negative-biased voltage triggers dehydrogenation to restore the insulating VO 2 . This work demonstrates a local and reversible electric-field-controlled insulator–metal transition through hydrogen evolution and presents a versatile pathway to exploit multiple functional devices at the nanoscale.

36 MATERIALS SCIENCE↗

NASA NTRS1991

Dynamics of local grid manipulations for internal flow problems

The control point method of algebraic grid generation is briefly reviewed. The review proceeds from the general statement of the method in 2-D unencumbered by detailed mathematical formulation. The method is supported by an introspective discussion which provides the basis for confidence in the approach. The more complex 3-D formulation is then presented as a natural generalization. Application of the method is carried out through 2-D examples which demonstrate the technique.

Eiseman, Peter R.↗

DOE OSTI2023

Quasi-deterministic localization of Er emitters in thin film TiO 2 through submicron-scale crystalline phase control

With their shielded 4f orbitals, rare-earth ions (REIs) offer optical and electron spin transitions with good coherence properties even when embedded in a host crystal matrix, highlighting their utility as promising quantum emitters and memories for quantum information processing. Among REIs, trivalent erbium (Er 3+ ) uniquely has an optical transition in the telecom C-band, ideal for transmission over optical fibers, making it well suited for applications in quantum communication. The deployment of Er 3+ emitters into a thin film TiO 2 platform has been a promising step toward scalable integration; however, like many solid-state systems, the deterministic spatial placement of quantum emitters remains an open challenge. Here, we investigate laser annealing as a means to locally tune the optical resonance of Er 3+ emitters in TiO 2 thin films on Si. Using both nanoscale x-ray diffraction measurements and cryogenic photoluminescence spectroscopy, we show that tightly focused below-gap laser annealing can induce anatase to rutile phase transitions in a nearly diffraction-limited area of the films and improve local crystallinity through grain growth. As a percentage of Er:TiO 2 is converted to rutile, the Er 3+ optical transition blueshifts by 13 nm. We explore the effects of changing laser annealing time and show that the amount of optically active Er:rutile increases linearly with laser power. We additionally demonstrate local phase conversion on microfabricated Si structures, which holds significance for quantum photonics.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Use of intrinsic hysteresis for the active control of internal transport barriers in magnetically confined fusion plasmas

In magnetically confined fusion devices, control of internal transport barriers (ITBs) is important both to enhance and suppress the turbulent transport to improve confinement control. Barrier control should allow for the improvement of confinement to aid in achieving the needed fusion criteria while also permitting the degradation of confinement to control profiles and clean the device by moving out the impurities accumulated near the core. In this work, we present a novel control scenario that takes advantage of the hysteresis intrinsic to transport barriers to easily cycle through enhanced and degraded confinement regimes. The control scenario is illustrated using a five-field simplified transport model for an ITB using typical parameters of a neutral beam injection-heated DIII-D tokamak discharge. Pellets and ion cyclotron resonance frequency power are used as control knobs for this active control scenario. These knobs adequately modify at will the local gradients and, therefore, the growth rates and shearing rates, allowing for easy and efficient control of the barrier by taking advantage of the barrier hysteresis. The result is a control cycle that could be operated with a relatively small amount of power in high performance regimes which, nowadays, typically require large power to control. It may also have advantages to avoid, or at least ameliorate, the appearance of magnetohydrodynamic instabilities in the barrier region.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

NASA NTRS1988

An application of active surface heating for augmenting lift and reducing drag of an airfoil

Application of active control to separated flow on the RC(6)-08 airfoil at high angle of attack by localized surface heating is numerically simulated by integrating the compressible 2-D nonlinear Navier-Stokes equation solver. Active control is simulated by local modification of the temperature boundary condition over a narrow strip of the upper surface of the airfoil. Both mean and perturbed profiles are favorably altered when excited with the same natural frequency of the shear layer by moderate surface heating for both laminar and turbulent separation. The shear layer is found to be very sensitive to localized surface heating in the vicinity of the separation point. The excitation field at the surface sufficiently altered both the local as well as the global circulation to cause a significant increase in lift and reduction in drag.

Maestrello, Lucio↗

DOE OSTI2022

Quasi-linear toroidal simulations of resonant magnetic perturbations in eight ITER H-mode scenarios

Abstract Both linear and quasi-linear aspects of the plasma response to the resonant magnetic perturbation (RMP) field are numerically investigated for various H-mode scenarios in ITER, covering the pre-fusion power operation and the fusion power operation phases. Linear response computations for eight ITER scenarios, with varying plasma current and toroidal magnetic field, reveal that the best coil current phasing for controlling the type-I edge localized modes (ELMs) scales roughly linearly with the edge safety factor. The coil phasing is defined as the relative toroidal phase of the coil currents between different rows, for a given toroidal harmonic. Quasi-linear initial value simulation, which is the focus of the present study, shows that application of the n = 3 ( n is the toroidal mode number) RMP field has a minimum side effect on the plasma core momentum confinement but potentially a large effect on the global particle transport. Generally, the RMP field with the best (worst) coil phasing for ELM control produces the strongest (weakest) effect on the plasma edge flow and the overall density. This robustly holds for all eight ITER scenarios. Consequently, in order to minimize the RMP induced side effects while achieving ELM control (suppression) in ITER, a compromise is necessary in choosing the coil current configuration.

Physics↗

DOE OSTI2025

Stabilizing Non-Abelian Topological Order Against Heralded Noise via Local Lindbladian Dynamics

An important open question for the current generation of highly controllable quantum devices is understanding which phases can be realized as stable steady states under local quantum dynamics. In this work, we show how robust steady-state phases with both Abelian and non-Abelian mixed-state topological order can be stabilized, in two spatial dimensions, against generic “heralded” noise using active dynamics that incorporate measurement and feedback, modeled as a fully local Lindblad master equation. These topologically ordered steady states are two-way connected to pure topologically ordered ground states using local quantum channels, and preserve quantum information for a time that is exponentially large in the system size. Specifically, we present explicit constructions of families of local Lindbladians for both Abelian (ℤ 2 ) and non-Abelian (𝐷 4 ) topological order whose steady states host mixed-state topological order when the noise is below a threshold strength. As the noise strength is increased, these models exhibit first-order transitions to intermediate mixed-state phases where they encode robust classical memories, followed by (first-order) transitions to a trivial steady state at high noise rates. When the noise is imperfectly heralded, steady-state order disappears but our active dynamics significantly enhances the lifetime of the encoded logical information. To carry out the numerical simulations for the non-Abelian 𝐷 4 case, we introduce a generalized stabilizer tableau formalism that permits efficient simulation of the non-Abelian Lindbladian dynamics.

Monte Carlo methods↗