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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
NASA NTRS2017

QSPIN: A High Level Java API for Quantum Computing Experimentation

QSPIN is a high level Java language API for experimentation in QC models used in the calculation of Ising spin glass ground states and related quadratic unconstrained binary optimization (QUBO) problems. The Java API is intended to facilitate research in advanced QC algorithms such as hybrid quantum-classical solvers, automatic selection of constraint and optimization parameters, and techniques for the correction and mitigation of model and solution errors. QSPIN includes high level solver objects tailored to the D-Wave quantum annealing architecture that implement hybrid quantum-classical algorithms [Booth et al.] for solving large problems on small quantum devices, elimination of variables via roof duality, and classical computing optimization methods such as GPU accelerated simulated annealing and tabu search for comparison. A test suite of documented NP-complete applications ranging from graph coloring, covering, and partitioning to integer programming and scheduling are provided to demonstrate current capabilities.

Quantu↗
NASA NTRSDate not supplied

Tradeoffs When Considering Deep Reinforcement Learning for Contingency Management in Advanced Air Mobility

Air transportation is undergoing a rapid evolution globally with the introduction of Advanced Air Mobility (AAM) and with it comes novel challenges and opportunities for transforming aviation. As AAM operations introduce increasing heterogeneity in vehicle capabilities and density, increased levels of automation are likely necessary to achieve operational safety and efficiency goals. This paper focuses on one example where increased automation has been suggested. Autonomous operations will need contingency management systems that can monitor evolving risk across a span of interrelated (or interdependent) hazards and, if necessary, execute appropriate control interventions via supervised or automated decision making. Accommodating this complex environment may require automated functions (autonomy) that apply artificial intelligence (AI) techniques that can adapt and respond to a quickly changing environment. This paper explores the use of Deep Reinforcement Learning (DRL) which has shown promising performance in complex and high-dimensional environments where the objective can be constructed as a sequential decision-making problem. An extension of a prior formulation of the contingency management problem as a Markov Decision Process (MDP) is presented and uses a DRL framework to train agents that mitigate hazards present in the simulation environment. A comparison of these learning-based agents and classical techniques is presented in terms of their performance, verification difficulties, and development process.

machine learning↗
NASA NTRS2012

Kuang's Semi-Classical Formalism for Electron Capture Cross-Sections in Ion-Ion Collisions at Approximately to MeV/amu: Application to ENA Modeling

Recent discovery by STEREO A/B of energetic neutral hydrogen is spurring an interest and need for reliable estimates of electron capture cross sections at few MeVs per nucleon as well as for multi-electron ions. Required accuracy in such estimates necessitates detailed and involved quantum-mechanical calculations or expensive numerical simulations. For ENA modeling and similar purposes, a semi-classical approach offers a middle-ground approach. Kuang's semiclassical formalism to calculate electron-capture cross sections for single and multi-electron ions is an elegant and efficient method, but has so far been applied to limited and specific laboratory measurements and at somewhat lower energies. Our goals are to test and extend Kuang s method to all ion-atom and ion-ion collisions relevant to ENA modeling, including multi-electron ions and for K-shell to K-shell transitions.

Barghouty, A. F.↗
NASA NTRSDate not supplied

Exploring Quantum State Preparation Using Tensor Networks and Sparse Wavefunction Simulations

The variational quantum eigenvalue solver is a powerful hybrid quantum-classical approach that has been suggested as a candidate method to run on near-term quantum hardware for computing ground state electronic energies of molecular systems. However, even for small molecules, the number of variational parameters and qubits required to minimize the electronic energy is beyond the reach of current quantum computers except for small basis sets. We explore a new paradigm for state preparation where we test how much of the optimization can be approximately prepared with classical computers to reduce the number of optimization steps performed using a quantum device. By adapting a recent algorithm for the factorized form of the UCC ansatz, we can study molecular electronic structure problems with up to 64 qubits. In addition, we also test a related approach of using tensor networks to optimize quantum circuits in order to benchmark various lattice models. We present results using these approaches and discuss strategies for incorporating these ideas into variational algorithms involving near-term quantum computers. Our results help demonstrate the strength of the UCC ansatz and address pressing questions about optimal initial parameterizations and circuit construction.

quantum computing↗
NASA NTRS1976

Monte Carlo calculations of diatomic molecule gas flows including rotational mode excitation

The direct simulation Monte Carlo method was used to solve the Boltzmann equation for flows of an internally excited nonequilibrium gas, namely, of rotationally excited homonuclear diatomic nitrogen. The semi-classical transition probability model of Itikawa was investigated for its ability to simulate flow fields far from equilibrium. The behavior of diatomic nitrogen was examined for several different nonequilibrium initial states that are subjected to uniform mean flow without boundary interactions. A sample of 1000 model molecules was observed as the gas relaxed to a steady state starting from three specified initial states. The initial states considered are: (1) complete equilibrium, (2) nonequilibrium, equipartition (all rotational energy states are assigned the mean energy level obtained at equilibrium with a Boltzmann distribution at the translational temperature), and (3) nonequipartition (the mean rotational energy is different from the equilibrium mean value with respect to the translational energy states). In all cases investigated the present model satisfactorily simulated the principal features of the relaxation effects in nonequilibrium flow of diatomic molecules.

Yoshikawa, K. K.↗
NASA NTRS2010

Hidden Statistics Approach to Quantum Simulations

Recent advances in quantum information theory have inspired an explosion of interest in new quantum algorithms for solving hard computational (quantum and non-quantum) problems. The basic principle of quantum computation is that the quantum properties can be used to represent structure data, and that quantum mechanisms can be devised and built to perform operations with this data. Three basic non-classical properties of quantum mechanics superposition, entanglement, and direct-product decomposability were main reasons for optimism about capabilities of quantum computers that promised simultaneous processing of large massifs of highly correlated data. Unfortunately, these advantages of quantum mechanics came with a high price. One major problem is keeping the components of the computer in a coherent state, as the slightest interaction with the external world would cause the system to decohere. That is why the hardware implementation of a quantum computer is still unsolved. The basic idea of this work is to create a new kind of dynamical system that would preserve the main three properties of quantum physics superposition, entanglement, and direct-product decomposability while allowing one to measure its state variables using classical methods. In other words, such a system would reinforce the advantages and minimize limitations of both quantum and classical aspects. Based upon a concept of hidden statistics, a new kind of dynamical system for simulation of Schroedinger equation is proposed. The system represents a modified Madelung version of Schroedinger equation. It preserves superposition, entanglement, and direct-product decomposability while allowing one to measure its state variables using classical methods. Such an optimal combination of characteristics is a perfect match for simulating quantum systems. The model includes a transitional component of quantum potential (that has been overlooked in previous treatment of the Madelung equation). The role of the transitional potential is to provide a jump from a deterministic state to a random state with prescribed probability density. This jump is triggered by blowup instability due to violation of Lipschitz condition generated by the quantum potential. As a result, the dynamics attains quantum properties on a classical scale. The model can be implemented physically as an analog VLSI-based (very-large-scale integration-based) computer, or numerically on a digital computer. This work opens a way of developing fundamentally new algorithms for quantum simulations of exponentially complex problems that expand NASA capabilities in conducting space activities. It has been illustrated that the complexity of simulations of particle interaction can be reduced from an exponential one to a polynomial one.

Zak, Michail↗
NASA NTRSDate not supplied

Tradeoffs When Considering Deep Reinforcement Learning for Contingency Management in Advanced Air Mobility

Air transportation is undergoing a rapid evolution globally with the introduction of Advanced Air Mobility (AAM) and with it comes novel challenges and opportunities for transforming aviation. As AAM operations introduce increasing heterogeneity in vehicle capabilities and density, increased levels of automation are likely necessary to achieve operational safety and efficiency goals. This paper focuses on one example where increased automation has been suggested. Autonomous operations will need contingency management systems that can monitor evolving risk across a span of interrelated (or interdependent) hazards and, if necessary, execute appropriate control interventions via supervised or automated decision making. Accommodating this complex environment may require automated functions (autonomy) that apply artificial intelligence (AI) techniques that can adapt and respond to a quickly changing environment. This paper explores the use of Deep Reinforcement Learning (DRL) which has shown promising performance in complex and high-dimensional environments where the objective can be constructed as a sequential decision-making problem. An extension of a prior formulation of the contingency management problem as a Markov Decision Process (MDP) is presented and uses a DRL framework to train agents that mitigate hazards present in the simulation environment. A comparison of these learning-based agents and classical techniques is presented in terms of their performance, verification difficulties, and development process.

machine learningautonomous systems; flight simulat↗
NASA NTRS1980

Study of boundary-layer transition using transonic-cone preston tube data

The laminar boundary layer on a 10 degree cone in a transonic wind tunnel was studied. The inviscid flow and boundary layer development were simulated by computer programs. The effects of pitch and yaw angles on the boundary layer were examined. Preston-tube data, taken on the boundary-layer-transition cone in the NASA Ames 11 ft transonic wind tunnel, were used to develope a correlation which relates the measurements to theoretical values of laminar skin friction. The recommended correlation is based on a compressible form of the classical law-of-the-wall. The computer codes successfully simulates the laminar boundary layer for near-zero pitch and yaw angles. However, in cases of significant pitch and/or yaw angles, the flow is three dimensional and the boundary layer computer code used here cannot provide a satisfactory model. The skin-friction correlation is thought to be valid for body geometries other than cones.

Reed, T. D.↗
NASA NTRS1993

Simulation of sloshing dynamics induced forces and torques actuated on dewar container driven by gravity gradient and jitter accelerations in microgravity

Some experimental spacecraft use superconducting sensors for gyro read-out and so must be maintained at a very low temperature. The boil-off from the cryogenic liquid used to cool the sensors can also be used, as the Gravity Probe B (GP-B) spacecraft does, as propellant to maintain attitude control and drag-free operation of the spacecraft. The cryogenic liquid for such spacecraft is, however, susceptible to both slosh-like motion and non-axisymmetric configurations under the influence of various kinds of gravity jitter and gravity gradient accelerations. Hence, it is important to quantify the magnitude of the liquid-induced perturbations on the spacecraft. We use the example of the GP-B to investigate such perturbations by numerical simulations. For this spacecraft disturbances can be imposed on the liquid by atmospheric drag, spacecraft attitude control maneuvers, and the earth's gravity gradient. More generally, onboard machinery vibrations and crew motion can also create disturbances. Recent studies suggest that high frequency disturbances are relatively unimportant in causing liquid motions in comparison to low frequency ones. The results presented here confirm this conclusion. After an initial calibration period, the GP-B spacecraft rotates in orbit at 0.1 rpm about the tank symmetry axis. For this rotation rate, the equilibrium liquid free surface shape is a 'doughnut' configuration for all residual gravity levels of 10(exp -6) g(sub 0) or less, as shown by experiments and by numerical simulations; furthermore, the superfluid behavior of the 1.8 K liquid helium used in GP-B eliminates temperature gradients and therefore such effects as Marangoni convection do not have to be considered. Classical fluid dynamics theory is used as the basis of the numerical simulations here, since Mason's experiments show that the theory is applicable for cryogenic liquid helium in large containers. To study liquid responses to various disturbances, we investigate and simulate three levels of gravity jitter (10(exp -6), 10(exp -7), and 10(exp -8) g(sub 0)) each at three predominant frequencies (0.1, 1.0, and 10 Hz), combined with a gravity gradient appropriate for the GP-B orbit. Dynamical evolution of sloshing dynamics excited fluid forces and torque fluctuations exerted on the dewar container driven by the combined gravity gradient and jitter accelerations are also investigated and simulated.

Hung, R. J.↗
NASA NTRS1997

Numerical Simulation of Unsteady Aerodynamic Models

This report documents the results of the numerical simulations of unsteady aerodynamic models. The results focus on numerical accuracy and efficiency, and the robustness of the numerical methods. The aerodynamic models includes the classical Wagner and Kussner functions and the Leishman-Beddoes dynamic stall model. The simulations includes the numerical approximations of the Duhamel's integrals using both indicial (step) and impulse responses, the numerical integrations of the state-space models, and the exact solutions. The report also presents the conversion among different model representations.

Nguyen, Khanh Q.↗
NASA NTRS1978

Analytical study of STOL Aircraft in ground effect. Part 1: Nonplanar, nonlinear wing/jet lifting surface method

A nonlinear, nonplanar three dimensional jet flap analysis, applicable to the ground effect problem, is presented. Lifting surface methodology is developed for a wing with arbitrary planform operating in an inviscid and incompressible fluid. The classical, infintely thin jet flap model is employed to simulate power induced effects. An iterative solution procedure is applied within the analysis to successively approximate the jet shape until a converged solution is obtained which closely satisfies jet and wing boundary conditions. Solution characteristics of the method are discussed and example results are presented for unpowered, basic powered and complex powered configurations. Comparisons between predictions of the present method and experimental measurements indicate that the improvement of the jet with the ground plane is important in the analyses of powered lift systems operating in ground proximity. Further development of the method is suggested in the areas of improved solution convergence, more realistic modeling of jet impingement and calculation efficiency enhancements.

Shollenberger, C. A.↗
NASA NTRS1989

A pointing system design concept for Space Station attached payloads

A study has been conducted to recommend a pointing system design and architecture that can accommodate the articulated pointing requirements levied on the Space Station Freedom Attached Payload Pointing System. A conceptual design of a control system is developed using classical rate and position control techniques. A high fidelity simulation testbed has been developed as the principal tool for the pointing performance evaluation. Techniques of model reduction are applied to reduce the model order to a manageable size for incorporation into the testbed. The disturbance rich space station environment has been modeled, and nonlinearities such as bearing friction, motor and sensor noise are also considered. Simulations were performed with representatie payloads at nominal pointing orientations. The results show that the tight instrument pointing requirements and the severe Space Station disturbance environment render a marginal performance for a conventional (direct drive and hardmount) gimbal pointing system, particularly for lightweight payloads. A gimbal system that incorporates a passive base isolator and reactionless actuation appears to provide a significant imporvement in pointing performance over the conventional pointing systems.

Wong, Edward↗
NASA NTRS1991

RNG in turbulence and modeling of bypass transition

Two projects are considered: the Renormalization Group (RNG) analysis of turbulence modeling, and the calculation of bypass transition through turbulence modeling. RNG is a process which eliminates small scales on the uneliminated large scales as the change in the transport properties. It is because of this property of RNG that it was previously suggested that RNG could be used as a model builder in turbulence modeling. The possibility is studied of constructing RNG based turbulence models, and to try to proceed to do the modeling through RNG in parallel with the classical approach. The numerical predictions made by RNG models and by classical models is compared against data from Direct Numerical Simulation. While in an environment with freestream turbulence, the transition initiated by the instability of the laminar boundary layer to Tollmien-Schlichting waves is found to be a bypass one in which turbulent spots are formed without T-S wave amplification. The formation is a random process, and flow within a turbulent spot is almost fully turbulent. This suggests the possibility of using turbulence modeling to describe and predict the bypass transition.

Yang, Zhigang↗
NASA NTRS1992

Training effectiveness assessment: Methodological problems and issues

The U.S. military uses a large number of simulators to train and sustain the flying skills of helicopter pilots. Despite the enormous resources required to purchase, maintain, and use those simulators, little effort has been expended in assessing their training effectiveness. One reason for this is the lack of an evaluation methodology that yields comprehensive and valid data at a practical cost. Some of these methodological problems and issues that arise in assessing simulator training effectiveness, as well as problems with the classical transfer-of-learning paradigm were discussed.

Cross, Kenneth D.↗
NASA NTRS1994

The effect of wave-particle interactions on the polar wind: Preliminary results

A Monte Carlo simulation was developed in order to study the effects of wave-particle interactions (WPI) on the plasma outflow in the polar wind. The simulation also considered the other mechanisms included in the `classical' polar wind studies such as gravity, the polarization electrostatic field, and the divergence of geomagnetic field lines. Although the plasma consisted of electrons, H(+) and O(+) ions, we emphasized the behavior of H(+) in this preliminary study. The ion distribution function, as well as the profiles of its moments (density, drift velocity, temperatures, etc.) were found for different levels of WPI, that is, for different values of normalized diffusion rates in the velocity space (normalized D(sub perpendicular) H(+)). We found that as the WPI strength increases: (1) the ion drift velocity increases and its density decreases; (2) the perpendicular temperature T(sub perpendicular) (H(+)) increases; (3) the parallel temperature T(sub parallel) (H(+)) first decreases and then increases due to the balance between the parallel adiabatic cooling and the transfer of the energy from the perpendicular to the parallel direction; and (4) the temperature anisotropy ((T(sub parallel) (H(+))/T(sub perpendicular) (H(+)) is reduced and even reversed in some cases. For strong WPI (normalized D(sub perpendicular) (H(+) much greater than 1), the ion distribution function shows weak conic features at high altitudes.

Barakat, A. R.↗
NASA NTRS1997

Radio Occultation Investigation of the Rings of Saturn and Uranus

The proposed work addresses two main objectives: (1) to pursue the development of the random diffraction screen model for analytical/computational characterization of the extinction and near-forward scattering by ring models that include particle crowding, uniform clustering, and clustering along preferred orientations (anisotropy). The characterization is crucial for proper interpretation of past (Voyager) and future (Cassini) ring, occultation observations in terms of physical ring properties, and is needed to address outstanding puzzles in the interpretation of the Voyager radio occultation data sets; (2) to continue the development of spectral analysis techniques to identify and characterize the power scattered by all features of Saturn's rings that can be resolved in the Voyager radio occultation observations, and to use the results to constrain the maximum particle size and its abundance. Characterization of the variability of surface mass density among the main ring, features and within individual features is important for constraining the ring mass and is relevant to investigations of ring dynamics and origin. We completed the developed of the stochastic geometry (random screen) model for the interaction of electromagnetic waves with of planetary ring models; used the model to relate the oblique optical depth and the angular spectrum of the near forward scattered signal to statistical averages of the stochastic geometry of the randomly blocked area. WE developed analytical results based on the assumption of Poisson statistics for particle positions, and investigated the dependence of the oblique optical depth and angular spectrum on the fractional area blocked, vertical ring profile, and incidence angle when the volume fraction is small. Demonstrated agreement with the classical radiative transfer predictions for oblique incidence. Also developed simulation procedures to generate statistical realizations of random screens corresponding to uniformly packed ring models, and used the results to characterize dependence of the extinction and near-forward scattering on ring thickness, packing fraction, and the ring opening angle.

Marouf, Essam A.↗
NASA NTRS1998

Spread-Spectrum Carrier Estimation With Unknown Doppler Shift

We present a method for the frequency estimation of a BPSK modulated, spread-spectrum carrier with unknown Doppler shift. The approach relies on a classic periodogram in conjunction with a spectral matched filter. Simulation results indicate accurate carrier estimation with processing gains near 40. A DSP-based prototype has been implemented for real-time carrier estimation for use in New Mexico State University's proposal for NASA's Demand Assignment Multiple Access service.

DeLeon, Phillip L.↗
NASA NTRS2003

On the Critical Behaviour, Crossover Point and Complexity of the Exact Cover Problem

Research into quantum algorithms for NP-complete problems has rekindled interest in the detailed study a broad class of combinatorial problems. A recent paper applied the quantum adiabatic evolution algorithm to the Exact Cover problem for 3-sets (EC3), and provided an empirical evidence that the algorithm was polynomial. In this paper we provide a detailed study of the characteristics of the exact cover problem. We present the annealing approximation applied to EC3, which gives an over-estimate of the phase transition point. We also identify empirically the phase transition point. We also study the complexity of two classical algorithms on this problem: Davis-Putnam and Simulated Annealing. For these algorithms, EC3 is significantly easier than 3-SAT.

Morris, Robin D.↗