Search NASA⌕ Search

SEARCH · Search NASA

Results for “Classical Control”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 631 records · Page 35

Multi-Maneuver Clohessy-Wiltshire Targeting

Orbital rendezvous involves execution of a sequence of maneuvers by a chaser vehicle to bring the chaser to a desired state relative to a target vehicle while meeting intermediate and final relative constraints. Intermediate and final relative constraints are necessary to meet a multitude of requirements such as to control approach direction, ensure relative position is adequate for operation of space-to-space communication systems and relative sensors, provide fail-safe trajectory features, and provide contingency hold points. The effect of maneuvers on constraints is often coupled, so the maneuvers must be solved for as a set. For example, maneuvers that affect orbital energy change both the chaser's height and downrange position relative to the target vehicle. Rendezvous designers use experience and rules-of-thumb to design a sequence of maneuvers and constraints. A non-iterative method is presented for targeting a rendezvous scenario that includes a sequence of maneuvers and relative constraints. This method is referred to as Multi-Maneuver Clohessy-Wiltshire Targeting (MM_CW_TGT). When a single maneuver is targeted to a single relative position, the classic CW targeting solution is obtained. The MM_CW_TGT method involves manipulation of the CW state transition matrix to form a linear system. As a starting point for forming the algorithm, the effects of a series of impulsive maneuvers on the state are derived. Simple and moderately complex examples are used to demonstrate the pattern of the resulting linear system. The general form of the pattern results in an algorithm for formation of the linear system. The resulting linear system relates the effect of maneuver components and initial conditions on relative constraints specified by the rendezvous designer. Solution of the linear system includes the straight-forward inverse of a square matrix. Inversion of the square matrix is assured if the designer poses a controllable scenario - a scenario where the the constraints can be met by the sequence of maneuvers. Matrices in the linear system are dependent on selection of maneuvers and constraints by the designer, but the matrices are independent of the chaser's initial conditions. For scenarios where the sequence of maneuvers and constraints are fixed, the linear system can be formed and the square matrix inverted prior to real-time operations. Example solutions are presented for several rendezvous scenarios to illustrate the utility of the method. The MM_CW_TGT method has been used during the preliminary design of rendezvous scenarios and is expected to be useful for iterative methods in the generation of an initial guess and corrections.

Dannemiller, David P.↗

Quantum Anomalies in Condensed Matter

Quantum materials provide a fertile ground in which to test and realize unusual phenomena such as quantum anomalies predicted by quantum field theory. There are three important symmetries that are broken when classical field theory is moved into the quantum regime, the scale anomaly, the axial (chiral) anomaly, and the parity anomaly. Several potential device applications may be realized by the discovery of quantum anomalies in condensed matter, enabled by the new physics they embody, including ultra‐sensitive dark matter detectors, far infrared optical modulators, micro‐bolometric detectors, low‐dissipation ballistic transporters, terahertz‐based qubits, terahertz polarization state controls, passive magnetic field sensors, stable topological superconductors that host Majorana fermions, and qubits topologically protected against decoherence. In this perspective article, the definition of these quantum anomalies is laid out, how little is known in the context of condensed matter, and how quantum anomalies are predicted to manifest as anomalous electronic, thermal, and magnetic behavior in experiments on topological quantum materials, including Weyl and Dirac semimetals. Furthermore, the importance that mechanical strain and defects will play in modifying signatures of quantum anomalies is discussed.

36 MATERIALS SCIENCE↗

Spatiotemporal control of structure and dynamics in a polar active fluid

We apply optimal control theory to drive a polar active fluid into new behaviors: relocating asters, reorienting waves, and on-demand switching between states. This study reveals general principles to program active matter for useful functions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Modeling of Compressible Flow with Friction and Heat Transfer Using the Generalized Fluid System Simulation Program (GFSSP)

The present paper describes the verification and validation of a quasi one-dimensional pressure based finite volume algorithm, implemented in Generalized Fluid System Simulation Program (GFSSP), for predicting compressible flow with friction, heat transfer and area change. The numerical predictions were compared with two classical solutions of compressible flow, i.e. Fanno and Rayleigh flow. Fanno flow provides an analytical solution of compressible flow in a long slender pipe where incoming subsonic flow can be choked due to friction. On the other hand, Raleigh flow provides analytical solution of frictionless compressible flow with heat transfer where incoming subsonic flow can be choked at the outlet boundary with heat addition to the control volume. Nonuniform grid distribution improves the accuracy of numerical prediction. A benchmark numerical solution of compressible flow in a converging-diverging nozzle with friction and heat transfer has been developed to verify GFSSP's numerical predictions. The numerical predictions compare favorably in all cases.

Bandyopadhyay, Alak↗

Physical Models of Cognition

This paper presents and discusses physical models for simulating some aspects of neural intelligence, and, in particular, the process of cognition. The main departure from the classical approach here is in utilization of a terminal version of classical dynamics introduced by the author earlier. Based upon violations of the Lipschitz condition at equilibrium points, terminal dynamics attains two new fundamental properties: it is spontaneous and nondeterministic. Special attention is focused on terminal neurodynamics as a particular architecture of terminal dynamics which is suitable for modeling of information flows. Terminal neurodynamics possesses a well-organized probabilistic structure which can be analytically predicted, prescribed, and controlled, and therefore which presents a powerful tool for modeling real-life uncertainties. Two basic phenomena associated with random behavior of neurodynamic solutions are exploited. The first one is a stochastic attractor ; a stable stationary stochastic process to which random solutions of a closed system converge. As a model of the cognition process, a stochastic attractor can be viewed as a universal tool for generalization and formation of classes of patterns. The concept of stochastic attractor is applied to model a collective brain paradigm explaining coordination between simple units of intelligence which perform a collective task without direct exchange of information. The second fundamental phenomenon discussed is terminal chaos which occurs in open systems. Applications of terminal chaos to information fusion as well as to explanation and modeling of coordination among neurons in biological systems are discussed. It should be emphasized that all the models of terminal neurodynamics are implementable in analog devices, which means that all the cognition processes discussed in the paper are reducible to the laws of Newtonian mechanics.

Zak, Michail↗

Design Choices in Anomaly Detection for Industrial Control Systems: Insights from Gas Pipeline Data

Industrial control systems (ICS) remain vulnerable to increasingly sophisticated cyberattacks, yet evaluating anomaly detection models in these environments is challenging due to temporal dependencies, missing-not-at-random patterns, and extremely imbalanced datasets. These factors make common practices—especially random data splits and naïve imputation—prone to severe temporal leakage, which can inflate reported performance and obscure real-world limitations. In this work, we systematically examine classical machine learning models, temporal deep learning architecture, and tensor-decomposition–based methods on a gas-pipeline dataset using a fully temporally separated evaluation pipeline designed to mimic realistic deployment conditions. Our findings show that proper temporal handling and MNAR-aware preprocessing significantly alter the relative performance of popular anomaly-detection methods, providing practical guidance for designing reliable, leakage-resistant ICS intrusion-detection systems.

97 MATHEMATICS AND COMPUTING↗

The Impact of Time-Aware Design Choices in ICS Anomaly Detection

Industrial control systems (ICS) remain vulnerable to increasingly sophisticated cyberattacks, yet evaluating anomaly detection models in these environments is challenging due to temporal dependencies, missing-not-at-random patterns, and extremely imbalanced datasets. These factors make common practices—especially random data splits and na¨ıve imputation— prone to severe temporal leakage, which can inflate reported performance and obscure real-world limitations. In this work, we systematically examine classical machine learning models, temporal deep learning architecture, and tensordecomposition– based methods on a gas-pipeline dataset using a fully temporally separated evaluation pipeline designed to mimic realistic deployment conditions. Our findings show that proper temporal handling and MNAR-aware preprocessing significantly alter the relative performance of popular anomaly-detection methods, providing practical guidance for designing reliable, leakage-resistant ICS intrusion-detection systems.

97 MATHEMATICS AND COMPUTING↗

Two AFC Loops For Low CNR And High Dynamics

Two alternative digital automatic-frequency-control (AFC) loops proposed to acquire (or reacquire) and track frequency of received carrier radio signal. Intended for use where carrier-to-noise ratios (CNR's) low and carrier frequency characterized by high Doppler shift and Doppler rate because of high relative speed and acceleration, respectively, between transmitter and receiver. Either AFC loops used in place of phase-locked loop. New loop concepts integrate ideas from classical spectrum-estimation, digital-phase-locked-loop, and Kalman-Filter theories.

Hinedi, Sami M.↗

Hybrid equations of motion for flexible multibody systems using quasi-coordinates

A variety of engineering systems, such as automobiles, aircraft, rotorcraft, robots, spacecraft, etc., can be modeled as flexible multibody systems. The individual flexible bodies are in general characterized by distributed parameters. In most earlier investigations they were approximated by some spatial discretization procedure, such as the classical Rayleigh-Ritz method or the finite element method. This paper presents a mathematical formulation for distributed-parameter multibody systems consisting of a set of hybrid (ordinary and partial) differential equations of motion in terms of quasi-coordinates. Moreover, the equations for the elastic motions include rotatory inertia and shear deformation effects. The hybrid set is cast in state form, thus making it suitable for control design.

Meirovitch, L.↗

The Prediction of Ducted Fan Engine Noise Via a Boundary Integral Equation Method

A computationally efficient Boundary Integral Equation Method (BIEM) for the prediction of ducted fan engine noise is presented. The key features of the BIEM are its versatility and the ability to compute rapidly any portion of the sound field without the need to compute the entire field. Governing equations for the BIEM are based on the assumptions that all acoustic processes are linear, generate spinning modes, and occur in a uniform flow field. An exterior boundary value problem (BVP) is defined that describes the scattering of incident sound by an engine duct with arbitrary profile. Boundary conditions on the duct walls are derived that allow for passive noise control treatment. The BVP is recast as a system of hypersingular boundary integral equations for the unknown duct surface quantities. BIEM solution methodology is demonstrated for the scattering of incident sound by a thin cylindrical duct with hard walls. Numerical studies are conducted for various engine parameters and continuous portions of the total pressure field are computed. Radiation and duct propagation results obtained are in agreement with the classical results of spinning mode theory for infinite ducts.

Boundary integral equation↗

Recovery of 29 Second Oscillations in Hubble Space Telescope Eclipse Observations of the Cataclysmic Variable UX Ursae Majoris

Low-amplitude (approximately 0.5%) 29 s oscillations have been detected in Hubble Space Telescope Faint Object Spectrograph eclipse observations of the nova-like cataclysmic variable UX UMa. These are the same dwarf nova-type oscillations that were originally discovered in this system in 1972. The 29 s oscillations are seen in one pair of eclipse sequences obtained with the FOS/PRISM in 1994 November but not in a similar pair obtained with the FOS/GI60L grating in August of the same year. The oscillations in the PRISM data are sinusoidal to within the small observational errors and undergo an approximately - 360' phase shift during eclipses (i.e., one cycle is lost). The amplitudes are highest at pre-eclipse orbital phases and exhibit a rather gradual eclipse whose shape is roughly similar to, although perhaps slightly narrower than, LTX UMa's overall light curve in the PRISM bandpass (2000-8000 A). Spectra of the oscillations have been constructed from pre-, mid, and post-eclipse data segments of the November observations. The spectra obtained from the out-of-eclipse segments are extremely blue, and only lower limits can be placed on the temperature of the source that dominates the modulated flux at these orbital phases. Lower limits derived from blackbody (stellar atmosphere) model fits to these data are >or equal to 95,000 K (> or equal to 85,000 K); the corresponding upper limits on the projected area of this source are all less than 2% of the white dwarf (WD) surface area. By contrast, oscillation spectra derived from mid- eclipse data segments are much redder. Fits to these spectra yield temperature estimates in the range 20,000 K approximately greater T and T approximately less than 30,000 K for both blackbody and stellar atmosphere models and corresponding projected areas of a few percent of the WD surface area. These estimates are subject to revision if the modulated emission is optically thin. We suggest that the ultimate source of the oscillations is a hot, compact region near disk center, but that a significant fraction of the observed, modulated flux is due to reprocessing of the light emitted by this source in the accretion disk atmosphere. The compact source is occulted at orbital phases near mid-eclipse, leaving only part of the more extended reprocessing region(s) to produce the weak oscillations that persist even at conjunction. The highly sinusoidal oscillation pulse shape does not permit the identification of the compact comonent in this model with emission produced by a rotating disturbance in the inner disk or in a classical, equatorial boundary layer. Instead, this component could arise in a bright spot on the surface of the WD, possibly associated with a magnetic pole. However, a standard intermediate polar model can also be ruled out since UX UMa's oscillation period has been seen to change on timescales much shorter than the minimum timescale required to spin up the WD by accretion torques. A model invoking magnetically controlled accretion onto differentially rotating WD surface layers may be viable, but needs more theoretical work.

Knigge, Christian↗

Post-instability behavior of solids

The necessity of model reformulation in elasticity results from the failure of hyperbolicity of the governing equations of motion for classical models. The reformulation is based upon the introduction of additional kinematical microstructures in the form of multivalued displacement and velocity field (or fractal functions) which are generated by the mechanism of the instability. The small scale motions describing this microstructure interact with the original large scale motion and restore the hyperbolicity of new governing equations of motion. The applications of the reformulated models to the problem of vibrational control and impact energy absorption are discussed.

Zak, M.↗

An Executable Choreography Framework for Dynamic Service-Oriented Architectures

Interoperability and loose coupling requirements are pushing the next generation of distributed applications towards more decentralized and more dynamic interaction schemes, which the classic requestJresponse communication paradigm can hardly accommodate. Hence, sound foundations and mechanisms for the establishment of unmticiptitteb peer-to-peer interactions across organizational boundaries are of significant importance to upcoming middleware platforms. The Executable Choreography Framework (ECF) is a middleware-level framework that targets dynamic and decentralized service compositions. The ECF combines transparent context propagation with aspect-oriented software composition techniques to dynamically refine the default control and data flow of service invocations. The framework provides a ground for experimentation with dynamic and distributed workflows, and a base to assess their safety and applicability when depioyed across organizational boundaries.

Akkawi, Faisal↗

Thermodynamic and Kinetic Modulation of Methylammonium Lead Bromide Crystallization Revealed by In Situ Monitoring

Hybrid organic–inorganic perovskite (HOIP) crystals are promising optoelectronic materials, but little is known about either the thermodynamic and kinetic controls on crystal growth or the underlying growth mechanism(s). Herein, we use fluid cell atomic force microscopy (AFM) and solution nuclear magnetic resonance (NMR) spectroscopy to investigate growth of the model HOIP crystal CH 3 NH 3 PbBr 3 (MAPbBr 3 ) and to determine how formic acid (HCOOH) modulates the thermodynamics and kinetics of growth. The results show that growth of MAPbBr 3 in dimethylformamide (DMF) proceeds through the classical pathway by the spreading of atomic crystal steps generated at screw dislocations on the {100} surface. Temperature dependent step velocity measurements demonstrate that with increasing concentration, HCOOH decreases both the solubility of MAPbBr 3 and the kinetic coefficient (b) of step movement. 1 H-NMR measurements indicate that HCOOH increases the lifetime of the methylammonium (MA + ) ions and promotes the association of MAPbBr 3 , thus tuning the solubility of the perovskite. HCOOH also alters the molecular tumbling motion and bulk diffusion of the MA + ions, possibly via H-bonding. Further, our findings establish a direct correlation between the mesoscale crystal growth kinetics and the molecular-scale interactions between organic additives and constituent ions, providing unprecedented insights for developing predictive syntheses of HOIP crystals with defined size, crystal habit and shape, and defect distribution.

36 MATERIALS SCIENCE↗

Applications of Nickelate perovskites for neuromorphic computing from electronic structure and Machine Learning

While the limit of Moore's law is presently being reached with current microelectronic technologies, we need to develop new paradigms that overcome this limitation. In that respect, neuromorphic computing is a concept that emulates the neural behavior and response of the human brain, and it has been recognized as a promising alternative approach. In this research project, we will perform multi-fidelity scale bridging to explore the potential use of materials with metal to insulator transition for neuromorphic applications. In particular, rare earth nickelates are promising for such purposes, as the transition in these materials is quite sensitive to a broad set of different external stimuli. Our multi-fidelity approach will bridge the high-fidelity electronic structure calculations with classical potentials. We will bridge dynamical mean field theory with a classical atomistic representation via a deep learning force field. The neural network is trained with energies, charges, and forces obtained by accurate electronic structure theories based on Dynamical Mean Field Theory. The configurational space is generated from known crystal phases, ab initio molecular dynamics with exchange-correlation functionals corrected with the Hubbard model, disordered phases with different concentrations of oxygen vacancies, and nonsymmetrical positions and induced strain by grain interfaces or contact with a substrate. Strategies to train the model with a reduced number of training examples are obtained from active learning methods, and new structures for improving the learning process are generated by using machine learning autoencoders. This classical potential will be validated through a diversity of electronic structure methods and represents an important step to combine the flexibility and accuracy of first-principles with the speed of classical potentials. The generated multi-fidelity surrogate model will be used to understand the role of strain, oxygen vacancies, proton doping, the variation of the crystal phase, substrate effects, vibrational effects as the octahedral rotation, grain boundaries and defect effects on the response of a Metal to Insulator Transition (MIT) in correlated materials. Long time and large-scale simulations will help understand the role of different stimuli to control the hysteresis of the MIT, as it has been experimentally suggested. Selected configurations will be analyzed with higher-level theories to provide an accurate electronic description and to study how the orbitals and charges are rearranged under different conditions.

36 MATERIALS SCIENCE↗

Modified Interior Distance Functions (Theory and Methods)

In this paper we introduced and developed the theory of Modified Interior Distance Functions (MIDF's). The MIDF is a Classical Lagrangian (CL) for a constrained optimization problem which is equivalent to the initial one and can be obtained from the latter by monotone transformation both the objective function and constraints. In contrast to the Interior Distance Functions (IDF's), which played a fundamental role in Interior Point Methods (IPM's), the MIDF's are defined on an extended feasible set and along with center, have two extra tools, which control the computational process: the barrier parameter and the vector of Lagrange multipliers. The extra tools allow to attach to the MEDF's very important properties of Augmented Lagrangeans. One can consider the MIDFs as Interior Augmented Lagrangeans. It makes MIDF's similar in spirit to Modified Barrier Functions (MBF's), although there is a fundamental difference between them both in theory and methods. Based on MIDF's theory, Modified Center Methods (MCM's) have been developed and analyzed. The MCM's find an unconstrained minimizer in primal space and update the Lagrange multipliers, while both the center and the barrier parameter can be fixed or updated at each step. The MCM's convergence was investigated, and their rate of convergence was estimated. The extension of the feasible set and the special role of the Lagrange multipliers allow to develop MCM's, which produce, in case of nondegenerate constrained optimization, a primal and dual sequences that converge to the primal-dual solutions with linear rate, even when both the center and the barrier parameter are fixed. Moreover, every Lagrange multipliers update shrinks the distance to the primal dual solution by a factor 0 less than gamma less than 1 which can be made as small as one wants by choosing a fixed interior point as a 'center' and a fixed but large enough barrier parameter. The numericai realization of MCM leads to the Newton MCM (NMCM). The approximation for the primal minimizer one finds by Newton Method followed by the Lagrange multipliers update. Due to the MCM convergence, when both the center and the barrier parameter are fixed, the condition of the MDF Hessism and the neighborhood of the primal ninimizer where Newton method is 'well' defined remains stable. It contributes to both the complexity and the numerical stability of the NMCM.

Polyak, Roman A.↗

Ultrastrong magnon-magnon coupling and chiral spin-texture control in a dipolar 3D multilayered artificial spin-vortex ice

Strongly-interacting nanomagnetic arrays are ideal systems for exploring reconfigurable magnonics. They provide huge microstate spaces and integrated solutions for storage and neuromorphic computing alongside GHz functionality. These systems may be broadly assessed by their range of reliably accessible states and the strength of magnon coupling phenomena and nonlinearities. Increasingly, nanomagnetic systems are expanding into three-dimensional architectures. This has enhanced the range of available magnetic microstates and functional behaviours, but engineering control over 3D states and dynamics remains challenging. Here, we introduce a 3D magnonic metamaterial composed from multilayered artificial spin ice nanoarrays. Comprising two magnetic layers separated by a non-magnetic spacer, each nanoisland may assume four macrospin or vortex states per magnetic layer. This creates a system with a rich 16 N microstate space and intense static and dynamic dipolar magnetic coupling. The system exhibits a broad range of emergent phenomena driven by the strong inter-layer dipolar interaction, including ultrastrong magnon-magnon coupling with normalised coupling rates of $\frac{Δf}{v}$ = 0.57, GHz mode shifts in zero applied field and chirality-control of magnetic vortex microstates with corresponding magnonic spectra.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗