Next-generation power and sensor technologies: a new perspective on dual space-terrestrial applications
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Hendricks, Terry J.↗
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Next-generation power and sensor technologies: a new perspective on dual space-terrestrial applications
UNKNOWN
Hendricks, Terry J.↗
Next-generation power and sensor technologies: dual space-terrestrial applications
UNKNOWN
Hendricks, Terry J.↗
Convective precipitation retrievals from space-borne dual frequency (Ka- and W-band) radar observations
The 2017 Decadal Survey highlighted Earth System Science themes, science and application questions that led to the inclusion aerosols (A), clouds, convection, and precipitation (CCP) in the list of designated observables (DOs) to be pursued within the decade following the survey. Multiple observing system architectures were considered during the NASA A-CCP study, and dual frequency Ka-W band radars have been identified as components of the most likely architectures due to their ability to significantly contribute to the achievement of the science objectives and their synergy with other essential instruments. We present an algorithm to estimate convective precipitation from dual frequency, Ka- and W-band, observations applicable to the observing system architectures considered in the A-CCP study. The algorithm is based on the radar profiling algorithm used within the operational NASA GPM combined algorithm but features an additional module that makes the retrieval problem well-posed in cases of severe attenuation and potential loss of signal below the freezing level. The additional module is developed from GPM combined retrievals and consists of a procedure that generates an ensemble of potential retrievals consistent with the portions of the Ka-band and W-band observation profiles above the noise level. The ensemble solution is refined based on estimates of Path Integrated Attenuation (PIA) from the Surface Reference Technique (SRT) and radiometric observations.
Mircea Grecu↗
Control strategy for a dual-arm maneuverable space robot
A simple strategy for the attitude control and arm coordination of a maneuverable space robot with dual arms is proposed. The basic task for the robot consists of the placement of marked rigid solid objects with specified pairs of gripping points and a specified direction of approach for gripping. The strategy consists of three phases each of which involves only elementary rotational and translational collision-free maneuvers of the robot body. Control laws for these elementary maneuvers are derived by using a body-referenced dynamic model of the dual-arm robot.
Wang, P. K. C.↗
Quantum algorithm for the linear Vlasov equation with collisions
The Vlasov equation is a nonlinear partial differential equation that provides a first-principles description of the dynamics of plasmas. Its linear limit is routinely used in plasma physics to investigate plasma oscillations and stability. In this paper, we present a quantum algorithm that simulates the linearized Vlasov equation with and without collisions, in the one-dimensional electrostatic limit. Rather than solving this equation in its native spatial and velocity phase space, we adopt an efficient representation in the dual space yielded by a Fourier-Hermite expansion. For a given simulation time, the Fourier-Hermite representation is exponentially more compact, thus yielding a classical algorithm that can match the performance of a previously proposed quantum algorithm for this problem. Further, this representation results in a system of linear ordinary differential equations (ODEs) which can be solved with well-developed quantum algorithms: a Hamiltonian simulation in the collisionless case, and quantum ODE solvers in the collisional case. In particular, we demonstrate that a quadratic speedup in system size is attainable.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
The Quantum Condition Space
Abstract The fundamental properties of quantum physics are exploited to evaluate event probabilities with projection measurements. Next, to study what events can be specified by quantum methods, the concept of the condition space is introduced, which is found to be the dual space of the classical outcome space of bit strings. Like the classical outcome space generates the quantum state space, the condition space generates the quantum condition space being the central idea of this work. The quantum condition space permits the existence of entangled conditions having no classical equivalent. In addition, the quantum condition space is related to the quantum state space by a Fourier transform guaranteed by the Pontryagin duality, and therefore an entropic uncertainty principle can be defined. The quantum condition space offers a novel perspective of understanding quantum states with the duality picture. Furthermore, the quantum conditions have physical meanings and realizations of their own and thus may be studied for purposes beyond the original motivation of characterizing events for probability evaluation. Finally, the relation between the condition space and quantum circuits provides insights into how quantum states are collectively modified by quantum gates, which may lead to deeper understanding of the complexity of quantum circuits.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
Reuniting crystallography with real space: Ab initio structure elucidation with 4D-STEM
Structure elucidation via single-crystal methods has historically lacked experimental access to real-space information, instead relying exclusively on diffraction-space measurements of Bragg reflections. Here we exploit the dual-space imaging power of 4D scanning transmission electron microscopy to meaningfully integrate real-space information into the crystallographic workflow. We show that virtual apertures assembled by segmentation of high-angle annular dark-field images enable i) pixel-by-pixel separation of coherent Bragg signal from clusters of closely spaced nanocrystals and ii) selective extraction of integrated intensities from thinner subregions of individual specimens, facilitating retroactive tuning of multiple scattering artifacts. This strategy empowers us to simply pick and choose whichever nanoscale regions of interest generate the highest-quality diffraction patterns, allowing us to solve several independent structures of the metal-organic framework UiO-66 from specimens whose agglomerated morphology proved intractable for conventional microcrystal electron diffraction. Our method is compatible with both rotational and serial approaches to data processing, ultimately divulging the first scanning nanobeam electron diffraction structures determined by direct methods at subangstrom resolution.
Saha, Ambarneil↗
Optimal filter design subject to output delobe constraints
The design of filters for detection and estimation in radar and communications systems is considered, with inequality constraints on the maximum output sidelobe levels. A constrained optimization problem in Hilbert space is formulated, incorporating the sidelobe constraints via a partial ordering of continuous functions. Generalized versions (in Hilbert space) of the Kuhn-Tucker and Duality Theorems allow the reduction of this problem to an unconstrained one in the dual space of regular Borel measures. A convergent algorithm is presented for computational solution of the dual problem.
Fortmann, T. E.↗
Comments on dual-mode nuclear space power and propulsion system concepts
Some form of Dual-Mode Nuclear Space Power & Propulsion System (D-MNSP&PS) will be essential to spacefaring throughout teh solar system and that such systems must evolve as mankind moves into outer space. The initial D-MNPSP&PS Reference System should be based on (1) present (1990), and (2) advanced (1995) technology for use on comparable mission in the 2000 and 2005 time period respectively. D-MNSP&PS can be broken down into a number of subsystems: Nuclear subsystems including the energy source and controls for the release of thermal power at elevated temperatures; power conversion subsystems; waste heat rejection subsystems; and control and safety subsystems. These systems are briefly detailed.
Layton, J. Preston↗
Optimal filter design subject to output sidelobe constraints - Theoretical considerations
The design of filters for detection and estimation in radar and communications systems is considered, with inequality constraints on the maximum output sidelobe levels. A constrained optimization problem in Hilbert space is formulated, incorporating the sidelobe constraints via a partial ordering of continuous functions. Generalized versions (in Hilbert space) of the Kuhn-Tucker and duality theorems allow the reduction of this problem to an unconstrained one in the dual space of regular Borel measures.
Fortmann, T. E.↗
A superlinear interior points algorithm for engineering design optimization
We present a quasi-Newton interior points algorithm for nonlinear constrained optimization. It is based on a general approach consisting of the iterative solution in the primal and dual spaces of the equalities in Karush-Kuhn-Tucker optimality conditions. This is done in such a way to have primal and dual feasibility at each iteration, which ensures satisfaction of those optimality conditions at the limit points. This approach is very strong and efficient, since at each iteration it only requires the solution of two linear systems with the same matrix, instead of quadratic programming subproblems. It is also particularly appropriate for engineering design optimization inasmuch at each iteration a feasible design is obtained. The present algorithm uses a quasi-Newton approximation of the second derivative of the Lagrangian function in order to have superlinear asymptotic convergence. We discuss theoretical aspects of the algorithm and its computer implementation.
Herskovits, J.↗
Isolated and interacting round parallel heated jets
An experimental study of the flowfield of heated and unheated single and dual jet configurations was performed. This study of two parallel jets is unique since most previous aerodynamic structure experiments were limited to single round and two-dimensional jets. The present closely spaced dual jet geometry was motivated by the potential jet noise reduction available from this configuration. This geometry has shown promise as a method for redirecting jet noise away from ground based observers in side by side or over/under turbofan engine mountings on aircraft (Simonich et al., 1984). Since the effectiveness of this noise reduction technique is based on the existence of two independent jets, an understanding of the aerodynamics of the merging process is essential to establishing the acoustic benefits. The experimental program was structured so that Mach number, jet exit temperature, and spacing to diameter ratios could be independently varied to isolate each effect.
Simonich, J. C.↗
Stacking the odds in favor of a space propulsion jackpot
When faced with a variety of technical options to solve a problem, program planners often try to identify one potential winner, then channel their resources into this option. The more scarce their resources are perceived to be, the more likely they are to fall into this trap of illogic. The real ideal solution could well be an optimum combination of options, not just one. Many propulsion opportunities are tantalizing solutions to the potentially high cost of travelling to other planets. Among these opportunities, nuclear thermal rockets (NTR), nuclear electric propulsion (NEP), and asteroid derived propellants stand out as high-payoff modest-challenge options, as near term as they are resolved to be made. But which to choose? Or should higher risk higher payoff technology be opted for, such as fusion? The approach advocated here, technoflex, is one that addresses NTR, NEP, and asteroid propellants in harmony rather than in isolation. Technoflex is technology rich, and option flexible. Technoflex should cost roughly the same as a classic phased technology elimination approach. The synergistic benefits amongst these three options, how they can be efficiently pursued together, and how they can fit with longer range technologies are stressed. Even if no single option reaches its highest expectations, the combinations of any two partial winners would still give big dividends. These combinations are cheap propellants in space, dual mode high thrust/low thrust, or versatile propellant NTR. The triple payoff is excellent, even if all three options would pan out below expectations. If only one option reaches its potential, it could make the other two still worth their investment. If all three options meet full expectations, the triple payoff is a space propulsion jackpot which makes concern about the initial investment ludicrous as well as open up the solar system to expedient exploration.
Willoughby, Alan J.↗
Optical neural engine for solving scientific partial differential equations
Abstract Solving partial differential equations (PDEs) is the cornerstone of scientific research and development. Data-driven machine learning (ML) approaches are emerging to accelerate time-consuming and computation-intensive numerical simulations of PDEs. Although optical systems offer high-throughput and energy-efficient ML hardware, their demonstration for solving PDEs is limited. Here, we present an optical neural engine (ONE) architecture combining diffractive optical neural networks for Fourier space processing and optical crossbar structures for real space processing to solve time-dependent and time-independent PDEs in diverse disciplines, including Darcy flow equation, the magnetostatic Poisson’s equation in demagnetization, the Navier-Stokes equation in incompressible fluid, Maxwell’s equations in nanophotonic metasurfaces, and coupled PDEs in a multiphysics system. We numerically and experimentally demonstrate the capability of the ONE architecture, which not only leverages the advantages of high-performance dual-space processing for outperforming traditional PDE solvers and being comparable with state-of-the-art ML models but also can be implemented using optical computing hardware with unique features of low-energy and highly parallel constant-time processing irrespective of model scales and real-time reconfigurability for tackling multiple tasks with the same architecture. The demonstrated architecture offers a versatile and powerful platform for large-scale scientific and engineering computations.
Tang, Yingheng (ORCID:0009000153622546)↗
The Newton Modified Barrier Method for QP Problems
The Modified Barrier Functions (MBF) have elements of both Classical Lagrangians (CL) and Classical Barrier Functions (CBF). The MBF methods find an unconstrained minimizer of some smooth barrier function in primal space and then update the Lagrange multipliers, while the barrier parameter either remains fixed or can be updated at each step. The numerical realization of the MBF method leads to the Newton MBF method, where the primal minimizer is found by using Newton's method. This minimizer is then used to update the Lagrange multipliers. In this paper, we examine the Newton MBF method for the Quadratic Programming (QP) problem. It will be shown that under standard second-order optimality conditions, there is a ball around the primal solution and a cut cone in the dual space such that for a set of Lagrange multipliers in this cut cone, the method converges quadratically to the primal minimizer from any point in the aforementioned ball, and continues to do so after each Lagrange multiplier update. The Lagrange multipliers remain within the cut cone and converge linearly to their optimal values. Any point in this ball will be called a "hot start". Starting at such a "hot start", at most Omicron(1n 1n epsilon(exp -1)) Newton steps are sufficient to perform the primal minimization which is necessary for the Lagrange multiplier update. Here, epsilon > 0 is the desired accuracy. Because of the linear convergence of the Lagrange multipliers, this means that only Omicron(1n epsilon(exp -1))omicron(ln 1n epsilon(exp-1)) Newton steps are required to reach an epsilon-approximation to the solution from any "hot start". In order to reach the "hot start", one has to perform Omicron(square root(m) 1n C) Newton steps, where m characterizes the size of the problem and C > 0 is the condition number of the QP problem. This condition number will be characterized explicitly in terms of key parameters of the QP problem, which in turn depend on the input data and the size of the problem.
Melman, A.↗
The development of a solid-state hydrogen sensor for rocket engine leakage detection
Hydrogen propellant leakage poses significant operational problems in the rocket propulsion industry as well as for space exploratory applications. Vigorous efforts have been devoted to minimizing hydrogen leakage in assembly, test, and launch operations related to hydrogen propellant. The objective has been to reduce the operational cost of assembling and maintaining hydrogen delivery systems. Specifically, efforts have been made to develop a hydrogen leak detection system for point-contact measurement. Under the auspices of Lewis Research Center, the Electronics Design Center at Case Western Reserve University, Cleveland, Ohio, has undertaken the development of a point-contact hydrogen gas sensor with potential applications to the hydrogen propellant industry. We envision a sensor array consisting of numbers of discrete hydrogen sensors that can be located in potential leak sites. Silicon-based microfabrication and micromachining techniques are used in the fabrication of these sensor prototypes. Evaluations of the sensor are carried out in-house at Case Western Reserve University as well as at Lewis Research Center and GenCorp Aerojet, Sacramento, California. The hydrogen gas sensor is not only applicable in a hydrogen propulsion system, but also usable in many other civilian and industrial settings. This includes vehicles or facility use, or in the production of hydrogen gas. Dual space and commercial uses of these point-contacted hydrogen sensors are feasible and will directly meet the needs and objectives of NASA as well as various industrial segments.
Liu, Chung-Chiun↗