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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 721 records · Page 40
All sourcesNASA NTRSDOE OSTI
NASA NTRS1993

A new approach for designing self-organizing systems and application to adaptive control

There is tremendous interest in the design of intelligent machines capable of autonomous learning and skillful performance under complex environments. A major task in designing such systems is to make the system plastic and adaptive when presented with new and useful information and stable in response to irrelevant events. A great body of knowledge, based on neuro-physiological concepts, has evolved as a possible solution to this problem. Adaptive resonance theory (ART) is a classical example under this category. The system dynamics of an ART network is described by a set of differential equations with nonlinear functions. An approach for designing self-organizing networks characterized by nonlinear differential equations is proposed.

Ramamoorthy, P. A.↗
NASA NTRS1992

The prediction of nonlinear dynamic loads on helicopters from flight variables using artificial neural networks

A method of indirectly monitoring component loads through common flight variables is proposed which requires an accurate model of the underlying nonlinear relationships. An artificial neural network (ANN) model learns relationships through exposure to a database of flight variable records and corresponding load histories from an instrumented military helicopter undergoing standard maneuvers. The ANN model, utilizing eight standard flight variables as inputs, is trained to predict normalized time-varying mean and oscillatory loads on two critical components over a range of seven maneuvers. Both interpolative and extrapolative capabilities are demonstrated with agreement between predicted and measured loads on the order of 90 percent to 95 percent. This work justifies pursuing the ANN method of predicting loads from flight variables.

Cook, A. B.↗
NASA NTRS1994

The Second Annual International Space University Alumni Conference

The papers presented at the conference reflect the multidisciplinary nature of the International Space University (ISU) and its alumni. The first papers presented hold special relevance to the design projects, and cover such topics as lunar-based astronomical instrumentation, solar lunar power generation, habitation on the moon, and the legal issues governing multinational astronauts conducting research in space. The next set of papers cover various technical issues such as project success assessment, satellite networks and space station dynamics, thus reflecting the diverse backgrounds of the ISU alumni.

Johnson, Les↗
NASA NTRS1994

Adaptive Neuron Model: An architecture for the rapid learning of nonlinear topological transformations

A method for the rapid learning of nonlinear mappings and topological transformations using a dynamically reconfigurable artificial neural network is presented. This fully-recurrent Adaptive Neuron Model (ANM) network was applied to the highly degenerate inverse kinematics problem in robotics, and its performance evaluation is bench-marked. Once trained, the resulting neuromorphic architecture was implemented in custom analog neural network hardware and the parameters capturing the functional transformation downloaded onto the system. This neuroprocessor, capable of 10(exp 9) ops/sec, was interfaced directly to a three degree of freedom Heathkit robotic manipulator. Calculation of the hardware feed-forward pass for this mapping was benchmarked at approximately 10 microsec.

Tawel, Raoul↗
NASA NTRS1994

Correction to the luni-solar precession from very long baseline interferometry

The redetermination of the luni-solar precession is performed by using Very Long Baseline Interferometry (VLBI) catalogues of extragalactic radio sources containing positions at observation epochs which cover 9 years. The positions of the sources have been determined by the VLBI network of the Crustal Dynamics Project of NASA from measurements covering consecutive half year and one year intervals between 1981 and 1989. In the course of their reduction the International Astronomical Union (IAU) recommended precession terms were applied. On the assumption of an imperfection of the luni-solar precession it is expected that the positions of each source obtained at different epochs but uniformly reduced to the reference system J2000.0 exhibit an apparent proper motion. We attributed this motion tentatively to precession and solved for a correction of the luni-solar precession by making a least squares fit to the position differences between homonymous sources in the set of catalogues. The 18.6 yr terms of nutation entered the process as parameters the values of which were set by choice from the reservoir of recent determinations. Twenty-five sources contributed to the analysis with the effect that the annual and semi-annual catalogues contain 16 sources on the average. The analysis confirmed the slightly overestimated IAU value of the luni-solar precession yielding a mean correction of -3.59 +/- 1.14 mas/yr from the annual and -3.84 +/- 1.16 mas/yr from the semi-annual catalogues. We discuss these secular terms and their dependence on the adopted nutation terms.

Walter, H. G.↗
NASA NTRS1995

Two Unipolar Terminal-Attractor-Based Associative Memories

Two unipolar mathematical models of electronic neural network functioning as terminal-attractor-based associative memory (TABAM) developed. Models comprise sets of equations describing interactions between time-varying inputs and outputs of neural-network memory, regarded as dynamical system. Simplifies design and operation of optoelectronic processor to implement TABAM performing associative recall of images. TABAM concept described in "Optoelectronic Terminal-Attractor-Based Associative Memory" (NPO-18790). Experimental optoelectronic apparatus that performed associative recall of binary images described in "Optoelectronic Inner-Product Neural Associative Memory" (NPO-18491).

Liu, Hua-Kuang↗
NASA NTRS2006

The NASA F-15 Intelligent Flight Control Systems: Generation II

The Second Generation (Gen II) control system for the F-15 Intelligent Flight Control System (IFCS) program implements direct adaptive neural networks to demonstrate robust tolerance to faults and failures. The direct adaptive tracking controller integrates learning neural networks (NNs) with a dynamic inversion control law. The term direct adaptive is used because the error between the reference model and the aircraft response is being compensated or directly adapted to minimize error without regard to knowing the cause of the error. No parameter estimation is needed for this direct adaptive control system. In the Gen II design, the feedback errors are regulated with a proportional-plus-integral (PI) compensator. This basic compensator is augmented with an online NN that changes the system gains via an error-based adaptation law to improve aircraft performance at all times, including normal flight, system failures, mispredicted behavior, or changes in behavior resulting from damage.

Buschbacher, Mark↗
NASA NTRS2011

Combined Weekly Coordinate Solutions from SLR and DORIS

In International Terrestrial Reference Frame (ITRF) 2005 and ITRF2008, the approach for the construction of solutions by the IERS has been for individual analysis centers of each technique to process geodetic tracking data, and for each technique to develop a solution (or contribution) that is integrated into the final ITRF solution by careful combination of the technique solutions. The connections between the geodetic networks are realized by the application of local ties. In an alternate approach, we may assure processing homogeneity by creating normal equations for different techniques with the same orbit determination software, using identically derived algorithms. Another derivative of this approach is to realize the ties between the techniques using satellites tracked with multiple techniques; in effect tieing the networks together using satellite dynamics. In this solution, we develop a time series and a set of cumulative solutions from Satellite Laser Ranging (SLR) & Doppler Orbitography and Radio-positioning Integrated by Satellite (DORIS) based on homogeneous processing with the NASA GEODYN precise orbit determination suite of programs, where we jointly combine weekly the SLR data to Lageos1, Lageos2, Starlette, and Stella with the DORIS data from SPOT2-SPOT5, as well as satellites that utilize both techniques (TOPEX/Poseidon, Envisat, Jason-2). We discuss the modeling that is applied including upgrades implemented since the submission of the GSC ITRF2008 contributions for IDS. Firstly, we compare the SLR-only solutions comprising four geodetic satellites with the standard approach of utilizing only Lageos1 & Lageos2. Secondly, we evaluate the impact on the DORIS coordinates of the joint analysis with the SLR data.

Lemoine, F.↗
NASA NTRS2011

Modularized TGFbeta-Smad Signaling Pathway

The Transforming Growth Factor beta (TGFbeta) signaling pathway is a prominent regulatory signaling pathway controlling various important cellular processes. It can be induced by several factors, including ionizing radiation. It is regulated by Smads in a negative feedback loop through promoting increases in the regulatory Smads in the cell nucleus, and subsequent expression of inhibitory Smad, Smad7 to form a ubiquitin ligase with Smurf targeting active TGF receptors for degradation. In this work, we proposed a mathematical model to study the radiation-induced Smad-regulated TGF signaling pathway. By modularization, we are able to analyze each module (subsystem) and recover the nonlinear dynamics of the entire network system. Meanwhile the excitability, a common feature observed in the biological systems, along the TGF signaling pathway is discussed by mathematical analysis and numerical simulation.

Li, Yongfeng↗
NASA NTRS2012

Multiscale Dynamics of Solar Magnetic Structures

Multiscale topological complexity of the solar magnetic field is among the primary factors controlling energy release in the corona, including associated processes in the photospheric and chromospheric boundaries.We present a new approach for analyzing multiscale behavior of the photospheric magnetic flux underlying these dynamics as depicted by a sequence of high-resolution solar magnetograms. The approach involves two basic processing steps: (1) identification of timing and location of magnetic flux origin and demise events (as defined by DeForest et al.) by tracking spatiotemporal evolution of unipolar and bipolar photospheric regions, and (2) analysis of collective behavior of the detected magnetic events using a generalized version of the Grassberger-Procaccia correlation integral algorithm. The scale-free nature of the developed algorithms makes it possible to characterize the dynamics of the photospheric network across a wide range of distances and relaxation times. Three types of photospheric conditions are considered to test the method: a quiet photosphere, a solar active region (NOAA 10365) in a quiescent non-flaring state, and the same active region during a period of M-class flares. The results obtained show (1) the presence of a topologically complex asymmetrically fragmented magnetic network in the quiet photosphere driven by meso- and supergranulation, (2) the formation of non-potential magnetic structures with complex polarity separation lines inside the active region, and (3) statistical signatures of canceling bipolar magnetic structures coinciding with flaring activity in the active region. Each of these effects can represent an unstable magnetic configuration acting as an energy source for coronal dissipation and heating.

Magnetic fields↗
NASA NTRS2017

Distributed Timing and Localization (DiGiTaL)

The Distributed Timing and Localization (DiGiTaL) system provides nano satellite formations with unprecedented,centimeter-level navigation accuracy in real time and nanosecond-level time synchronization. This is achieved through the integration of a multi-constellation Global Navigation Satellite System (GNSS) receiver, a Chip-Scale Atomic Clock (CSAC), and a dedicated Inter-Satellite Link (ISL). In comparison, traditional single spacecraft GNSS navigation solutions are accurate only to the meter-level due to the sole usage of coarse pseudo-range measurements. To meet the strict requirements of future miniaturized distributed space systems, DiGiTaL uses powerful error-cancelling combinations of raw carrier-phase measurements which are exchanged between the swarming nano satellites through a decentralized network. A reduced-dynamics estimation architecture on board each individual nano satellite processes the resulting millimeter-level noise measurements to reconstruct the fullformation state with high accuracy.

Small Spacecraft↗
NASA NTRS2019

Supply Chain Ecosystem for Urban Air Mobility

Future urban mobility promises to deliver transformative impact across the value chain. Consequently, suppliers will face disruption in the form of new technologies, stakeholders and market dynamics. How can supply networks be optimized to meet capabilities that are yet unknown? This session will explore what business models and supply chain strategies can best deliver value for urban air transport and will address how to scale these networks at the pace of this rapidly evolving ecosystem.

Urban Air Mobility↗
NASA NTRSDate not supplied

Strategic Planning with Unscented Optimal Guidance for Urban Air Mobility

This study proposes a strategic trajectory planning framework to support development of Urban Air Mobility (UAM) traffic networks and optimization of UAM aircraft trajectories that are robust to uncertain wind fields. The development of UAM traffic networks considers static aviation constraints and dynamic weather constraints in urban airspace and the connections to ground transportation networks for preliminary selection of feasible time-optimal routes. The trajectory optimization of UAM aircraft utilizes an unscented optimal guidance approach to generate cost-optimal trajectories constrained on the selected sigma values of probability distribution of uncertain wind fields while ensuring that the end-point constraints are met for reducing wind-induced trajectory uncertainty. Unscented guidance commands are assessed based on trajectory perturbations at subsequent end-points in various wind fields by conducting Monte Carlo simulations.An example of wind-optimal UAM corridor and the associated trajectory-based operation volume is created utilizing the perturbations of the unscented trajectories for preliminary assessment of required aircraft separation minima without knowledge of aircraft navigation performance.

Strategic Planning↗
DOE OSTI2020

Model-Agnostic Algorithm for Real-Time Attack Identification in Power Grid using Koopman Modes

Malicious activities on measurements from sensors like Phasor Measurement Units (PMUs) can mislead the control center operator into taking wrong control actions resulting in disruption of operation, financial losses, and equipment damage. In particular, false data attacks initiated during power systems transients caused due to abrupt changes in load and generation can fool the conventional model-based detection methods relying on thresholds comparison to trigger an anomaly. In this paper, we propose a Koopman mode decomposition (KMD) based algorithm to detect and identify false data attacks in real-time. The Koopman modes (KMs) are capable of capturing the nonlinear modes of oscillation in the transient dynamics of the power networks and reveal the spatial embedding of both natural and anomalous modes of oscillations in the sensor measurements. The Koopman-based spatio-temporal nonlinear modal analysis is used to filter out the false data injected by an attacker. The performance of the algorithm is illustrated on the IEEE 68-bus test system using synthetic attack scenarios generated on GridSTAGE, a recently developed multivariate spatio-temporal data generation framework for simulation of adversarial scenarios in cyber-physical power systems.

Nandanoori, Sai Pushpak↗
DOE OSTI2022

Systems and methods for powder bed additive manufacturing anomaly detection

Detection and classification of anomalies for powder bed metal additive manufacturing. Anomalies, such as recoater blade impacts, binder deposition issues, spatter generation, and some porosities, are surface-visible at each layer of the building process. A multi-scaled parallel dynamic segmentation convolutional neural network architecture provides additive manufacturing machine and imaging system agnostic pixel-wise semantic segmentation of layer-wise powder bed image data. Learned knowledge is easily transferrable between different additive manufacturing machines. The anomaly detection can be conducted in real-time and provides accurate and generalizable results.

Scime, Luke R.↗
DOE OSTI2026

Covalent Adaptable Networks: Reprocessable Cross-Linked Polymers

Thermoset polymers have desirable properties, such as excellent thermal and mechanical stability, but their covalent cross-links typically prevent repair or recycling. By enabling and controlling dynamic exchange reactions within polymer networks, their covalent bonds rearrange and allow the polymer to be reshaped. These viscoelastic polymer networks, now known as covalent adaptable networks (CANs), are an important frontier for improving plastic circularity, as well as for designing valuable stimuli-responsive materials. This Review describes the history of CANs, dating back to the early days of polymer science, and the evolution of their classification and nomenclature. A comprehensive survey of dynamic reactions and linkage chemistries is provided, as well as methods to characterize and reprocess CANs. Beyond straightforward reprocessing, many advanced applications of CANs and their composites are now emerging. Lastly, we provide perspective on how the development of new chemistries, strategies to control stimuli-responsive bond exchange and mechanical properties, and a deep understanding of exchange reactions will advance this field toward scalable, sustainable, and high-value materials.

Sun, Molly [Northwestern University, Evanston, IL ↗
NASA NTRS1991

Experimental validation of docking and capture using space robotics testbeds

This presentation describes the application of robotic and computer vision systems to validate docking and capture operations for space cargo transfer vehicles. Three applications are discussed: (1) air bearing systems in two dimensions that yield high quality free-flying, flexible, and contact dynamics; (2) validation of docking mechanisms with misalignment and target dynamics; and (3) computer vision technology for target location and real-time tracking. All the testbeds are supported by a network of engineering workstations for dynamic and controls analyses. Dynamic simulation of multibody rigid and elastic systems are performed with the TREETOPS code. MATRIXx/System-Build and PRO-MATLAB/Simulab are the tools for control design and analysis using classical and modern techniques such as H-infinity and LQG/LTR. SANDY is a general design tool to optimize numerically a multivariable robust compensator with a user-defined structure. Mathematica and Macsyma are used to derive symbolically dynamic and kinematic equations.

Spofford, John↗