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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 37 records · Page 2

Improving Free-Piston Stirling Engine Specific Power

This work uses analytical methods to demonstrate the potential benefits of optimizing piston and/or displacer motion in a Stirling Engine. Isothermal analysis was used to show the potential benefits of ideal motion in ideal Stirling engines. Nodal analysis is used to show that ideal piston and displacer waveforms are not optimal in real Stirling engines. Constrained optimization was used to identify piston and displacer waveforms that increase Stirling engine specific power.

Stirling Engine↗

Improving Free-Piston Stirling Engine Specific Power

This work uses analytical methods to demonstrate the potential benefits of optimizing piston and/or displacer motion in a Stirling engine. Isothermal analysis was used to show the potential benefits of ideal motion in ideal Stirling engines. Nodal analysis is used to show that ideal piston and displacer waveforms are not optimal in real Stirling engines. Constrained optimization was used to identify piston and displacer waveforms that increase Stirling engine specific power.

Briggs, Maxwell H.↗

Electron density profile and associated fluctuation measurements using a microwave reflectometry diagnostic on Helically Symmetric eXperiment (HSX)

Abstract A dual-band frequency-modulated reflectometry is employed on the Helically Symmetric eXperiment (HSX) stellarator. This system equips a fast PIN switch to alternate the frequency source between two voltage-controlled oscillators, providing an operational frequency range from 14.5 GHz to 25.5 GHz. A monostatic antenna geometry and an ellipsoidal mirror are implemented in the vessel of HSX, where the polarization of the transmitted microwave can be switched between O- and X-mode to accommodate the magnetic field and plasma density. Although the original system was designed for density fluctuation measurement, significant efforts have been undertaken to improve the system performance and to realize the density profile inversion. Recent improvements of the system reported here include calibration of the dispersion in the transmission line, optimization of the waveform, and implementation of the Choi-Williams time–frequency distribution for spectral analysis. In this paper, we present the optimization of the reflectometry system along with first experimental measurements of the density profile and observations of fluctuations during gas puffing experiments.

Han, X. (ORCID:0000000184986433)↗

Inverse Biot–Savart Optimization for Superconducting Accelerator Magnets

Superconducting (SC) magnets for accelerator concepts are often synthesized by numerically optimizing magnetic field waveforms, a process that requires a subsequent solution of a constrained inverse problem to identify suitable SC magnet windings. When the desired field distribution is intuitive, the inverse process is facilitated by seeding preconceived coil distributions into design optimization methods for refinement. With more complex magnetic field distributions, an initial design may be unknown, and topology optimization tools are required to synthesize current distributions without a priori guidance from a subject matter expert. In this work, we develop a constrained inverse Biot-Savart topology optimization methodology that synthesizes optimal distributions of current density in racetrack-like SC coils. The problem structure is exploited through a computationally efficient quadratic programming formulation, and the method is applied to recently published magnetic field waveforms for a recirculating proton phase shifter, a proton therapy gantry, and dipole magnets with sharp field transitions. The method and results herein identify novel winding configurations that can help magnet designers bring accelerator concepts to fruition.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Improving Free-Piston Stirling Engine Power Density

Analyses and experiments demonstrate the potential benefits of optimizing piston and displacer motion in a free piston Stirling Engine. Isothermal analysis shows the theoretical limits of power density improvement due to ideal motion in ideal Stirling engines. More realistic models based on nodal analysis show that ideal piston and displacer waveforms are not optimal, often producing less power than engines that use sinusoidal piston and displacer motion. Constrained optimization using nodal analysis predicts that Stirling engine power density can be increased by as much as 58% using optimized higher harmonic piston and displacer motion. An experiment is conducted in which an engine designed for sinusoidal motion is forced to operate with both second and third harmonics, resulting in a maximum piston power increase of 14%. Analytical predictions are compared to experimental data showing close agreement with indirect thermodynamic power calculations, but poor agreement with direct electrical power measurements.

Stirling engines↗

Improving Power Density of Free-Piston Stirling Engines

Analyses and experiments demonstrate the potential benefits of optimizing piston and displacer motion in a free piston Stirling Engine. Isothermal analysis shows the theoretical limits of power density improvement due to ideal motion in ideal Stirling engines. More realistic models based on nodal analysis show that ideal piston and displacer waveforms are not optimal, often producing less power than engines that use sinusoidal piston and displacer motion. Constrained optimization using nodal analysis predicts that Stirling engine power density can be increased by as much as 58 using optimized higher harmonic piston and displacer motion. An experiment is conducted in which an engine designed for sinusoidal motion is forced to operate with both second and third harmonics, resulting in a maximum piston power increase of 14. Analytical predictions are compared to experimental data showing close agreement with indirect thermodynamic power calculations, but poor agreement with direct electrical power measurements.

space technology↗

Improving Power Density of Free-Piston Stirling Engines

Analyses and experiments demonstrate the potential benefits of optimizing piston and displacer motion in a free-piston Stirling Engine. Isothermal analysis shows the theoretical limits of power density improvement due to ideal motion in ideal Stirling engines. More realistic models based on nodal analysis show that ideal piston and displacer waveforms are not optimal, often producing less power than engines that use sinusoidal piston and displacer motion. Constrained optimization using nodal analysis predicts that Stirling engine power density can be increased by as much as 58 percent using optimized higher harmonic piston and displacer motion. An experiment is conducted in which an engine designed for sinusoidal motion is forced to operate with both second and third harmonics, resulting in a piston power increase of as much as 14 percent. Analytical predictions are compared to experimental data and show close agreement with indirect thermodynamic power calculations, but poor agreement with direct electrical power measurements.

aerospace engineering↗

Dynamic Catalysis Fundamentals: I. Fast calculation of limit cycles in dynamic catalysis

Dynamic catalysis—the forced oscillation of catalytic reaction coordinate potential energy surfaces (PES)—has recently emerged as a promising method for the acceleration of heterogeneously-catalyzed reactions. Theoretical study of enhancement of rates and supra-equilibrium product yield via dynamic catalysis has, to-date, been severely limited by onerous computational demands of forward integration of stiff, coupled ordinary differential equations (ODEs) that are necessary to quantitatively describe periodic cycling between PESs. Here, we establish a new approach that reduces, by ≳108×, the computational cost of finding the time-averaged rate at dynamic steady state (i.e. the limit cycle for linear and nonlinear systems of kinetic equations). Our developments are motivated by and conceived from physical and mathematical insight drawn from examination of a simple, didactic case study for which closed-form solutions of rate enhancement are derived in explicit terms of periods of oscillation and elementary step rate constants. Generalization of such closed-form solutions to more complex catalytic systems is achieved by introducing a periodic boundary condition requiring the dynamic steady state solution to have the same periodicity as the kinetic oscillations and solving the corresponding differential equations by linear algebra or Newton-Raphson-based approaches. The methodology is well-suited to extension to non-linear systems for which we detail the potential for multiple solutions or solutions with different periodicities. For linear and non-linear systems alike, the acute decrement in computational expense enables rapid optimization of oscillation waveforms and, consequently, accelerates understanding of the key catalyst properties that enable maximization of reaction rates, conversions, and selectivities during dynamic catalysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Viscous Aerodynamic Shape Optimization with Installed Propulsion Effects

Aerodynamic shape optimization is demonstrated to tailor the under-track pressure signature of a conceptual low-boom supersonic aircraft. Primarily, the optimization reduces nearfield pressure waveforms induced by propulsion integration effects. For computational efficiency, gradient-based optimization is used and coupled to the discrete adjoint formulation of the Reynolds-averaged Navier Stokes equations. The engine outer nacelle, nozzle, and vertical tail fairing are axi-symmetrically parameterized, while the horizontal tail is shaped using a wing-based parameterization. Overall, 48 design variables are coupled to the geometry and used to deform the outer mold line. During the design process, an inequality drag constraint is enforced to avoid major compromise in aerodynamic performance. Linear elastic mesh morphing is used to deform volume grids between design iterations. The optimization is performed at Mach 1.6 cruise, assuming standard day altitude conditions at 51,707-ft. To reduce uncertainty, a coupled thermodynamic engine cycle model is employed that captures installed inlet performance effects on engine operation.

computational fluid dynamics↗

Integrating deep neural networks with full-waveform inversion: Reparameterization, regularization, and uncertainty quantification

Full-waveform inversion (FWI) is an accurate imaging approach for modeling the velocity structure by minimizing the misfit between recorded and predicted seismic waveforms. However, the strong nonlinearity of FWI resulting from fitting oscillatory waveforms can trap the optimization in local minima. We have adopted a neural-network-based full-waveform inversion (NNFWI) method that integrates deep neural networks with FWI by representing the velocity model with a generative neural network. Neural networks can naturally introduce spatial correlations as regularization to the generated velocity model, which suppresses noise in the gradients and mitigates local minima. Furthermore, the velocity model generated by neural networks is input to the same partial differential equation (PDE) solvers used in conventional FWI. The gradients of the neural networks and PDEs are calculated using automatic differentiation, which back propagates gradients through the acoustic PDEs and neural network layers to update the weights of the generative neural network. Experiments on 1D velocity models, the Marmousi model, and the 2004 BP model determine that NNFWI can mitigate local minima, especially for imaging high-contrast features such as salt bodies, and it significantly improves the inversion in the presence of noise. Adding dropout layers to the neural network model also allows analyzing the uncertainty of the inversion results through Monte Carlo dropout. NNFWI opens a new pathway to combine deep learning and FWI for exploiting the characteristics of deep neural networks and the high accuracy of PDE solvers. Because NNFWI does not require extra training data and optimization loops, it provides an attractive and straightforward alternative to conventional FWI.

58 GEOSCIENCES↗

Optimization of microwave emission from laser filamentation with a machine learning algorithm

We demonstrate that is it possible to optimize the yield of microwave radiation from plasmas generated by laser filamentation in atmosphere through manipulation of the laser wavefront. A genetic algorithm controls a deformable mirror that reconfigures the wavefront using the microwave waveform amplitude as feedback. Optimization runs performed as a function of air pressure show that the genetic algorithm can double the microwave field strength relative to when the mirror surface is flat. Here, an increase in the volume and brightness of the plasma fluorescence accompanies the increase in microwave radiation, implying an improvement in the laser beam intensity profile through the filamentation region due to the optimized wavefront.

Englesbe, Alexander↗

Randomized Sketching Algorithms for Low-Memory Dynamic Optimization

This paper develops a novel limited-memory method to solve dynamic optimization problems. The memory requirements for such problems often present a major obstacle, particularly for problems with PDE constraints such as optimal flow control, full waveform inversion, and optical tomography. In these problems, PDE constraints uniquely determine the state of a physical system for a given control; the goal is to find the value of the control that minimizes an objective. While the control is often low dimensional, the state is typically more expensive to store. This paper suggests using randomized matrix approximation to compress the state as it is generated and shows how to use the compressed state to reliably solve the original dynamic optimization problem. Concretely, the compressed state is used to compute approximate gradients and to apply the Hessian to vectors. The approximation error in these quantities is controlled by the target rank of the sketch. This approximate first- and second-order information can readily be used in any optimization algorithm. As an example, we develop a sketched trust-region method that adaptively chooses the target rank using a posteriori error information and provably converges to a stationary point of the original problem. Numerical experiments with the sketched trust-region method show promising performance on challenging problems such as the optimal control of an advection-reaction-diffusion equation and the optimal control of fluid flow past a cylinder.

97 MATHEMATICS AND COMPUTING↗

Closed-loop optimization of fast trapped-ion shuttling with sub-quanta excitation

Shuttling ions at high speed and with low motional excitation is essential for realizing fast and high-fidelity algorithms in many trapped-ion-based quantum computing architectures. Achieving such performance is challenging due to the sensitivity of an ion to electric fields and the unknown and imperfect environmental and control variables that create them. Here we implement a closed-loop optimization of the voltage waveforms that control the trajectory and axial frequency of an ion during transport in order to minimize the final motional excitation. The resulting waveforms realize fast round-trip transport of a trapped ion across multiple electrodes at speeds of 0.5 electrodes per microsecond (35 m∙s -1 for a one-way transport of 210 μm in 6 s) with a maximum of 0.36 ± 0.08 mean quanta gain. This sub-quanta gain is independent of the phase of the secular motion at the distal location, obviating the need for an electric field impulse or time delay to eliminate the coherent motion.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Demonstration of low-density, high-performance operation of sustained spheromaks and favorable scalability toward compact, low-cost fusion power plants (Final Scientific/Technical Report)

This project worked to advance the technical viability of a novel method for efficiently sustaining stable, high-performance spheromak plasma configurations to serve as the basis of compact, low-cost fusion power plants. In particular, our group worked to improve the method of Steady Inductive Helicity Injection (SIHI) with Imposed-Dynamo Current Drive (IDCD) for spheromak plasma sustainment. Prior to this project demonstrations of this plasma sustainment technology have achieved plasma performance consistent with entry milestone 3 of the BETHE FOA. Research and development (R&D) activities for this project were focused on increasing plasma performance toward a level consistent with exit milestone 4. To do this the PI and his group worked to increase the performance of sustained spheromaks produced in an existing experimental prototype (HIT-SIU) while improving confidence in projections to and design of future, higher performance devices through three primary R&D activities: 1) Improved control over the density of plasma in the device throughout a discharge to provide a pathway for demonstration of spheromaks Ohmically heating to the Mercier beta limit via: a. Fueling the device directly with plasma through the installation of pre-ionized source on the injectors b. Optimization of electrical current waveforms in the driver circuits to enable low-density plasma formation with a lower fueling rate 2) Computational demonstration of a validated, realistic injector circuit coupled to a dynamic plasma model capable of use as a design tool for SIHI drivers and associated circuits for new experimental design points on the pathway to commercial reactors. The improvements in plasma performance achieved during research activity 1), and the computational projections performed in research activity 2) increased the technological readiness level (TRL) of this fusion energy concept toward a level sufficient to attract early-stage private investment and/or other forms of follow-on investment to pursue required R&D activities required for the eventual fusion power plants based on this novel technical approach.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Pulsed Inductive Plasma Acceleration: Performance Optimization Criteria

Optimization criteria for pulsed inductive plasma acceleration are developed using an acceleration model consisting of a set of coupled circuit equations describing the time-varying current in the thruster and a one-dimensional momentum equation. The model is nondimensionalized, resulting in the identification of several scaling parameters that are varied to optimize the performance of the thruster. The analysis reveals the benefits of underdamped current waveforms and leads to a performance optimization criterion that requires the matching of the natural period of the discharge and the acceleration timescale imposed by the inertia of the working gas. In addition, the performance increases when a greater fraction of the propellant is initially located nearer to the inductive acceleration coil. While the dimensionless model uses a constant temperature formulation in calculating performance, the scaling parameters that yield the optimum performance are shown to be relatively invariant if a self-consistent description of energy in the plasma is instead used.

Polzin, Kurt A.↗

Automated system for analyzing the activity of individual neurons

This paper presents a signal processing system that: (1) provides an efficient and reliable instrument for investigating the activity of neuronal assemblies in the brain; and (2) demonstrates the feasibility of generating the command signals of prostheses using the activity of relevant neurons in disabled subjects. The system operates online, in a fully automated manner and can recognize the transient waveforms of several neurons in extracellular neurophysiological recordings. Optimal algorithms for detection, classification, and resolution of overlapping waveforms are developed and evaluated. Full automation is made possible by an algorithm that can set appropriate decision thresholds and an algorithm that can generate templates on-line. The system is implemented with a fast IBM PC compatible processor board that allows on-line operation.

Bankman, Isaac N.↗

Generation of Intense Low-Divergence Isolated Soft-X-Ray Attosecond Pulses in a Gas-Filled Waveguide Using Three-Color Synthesized Laser Pulses

Isolated attosecond pulses (IAPs) in the soft-x-ray (SXR) region have been successfully produced via high-order harmonic generation in a gas medium at several laboratories, but pulse energies are much lower compared to the IAPs in the extreme ultraviolet. Here, we show that in a gas-filled hollow waveguide, an efficient gating method using a few-cycle three-color synthesizer is able to generate stronger SXR IAPs. We show that an 104-as IAP in the SXR region (central energy of 210 eV) with a higher pulse energy (0.9 nJ) and a lower divergence (within 1.5 mrad) can be generated with a three-color laser beam for input pulse energy at 0.62 mJ, under the condition of optimal gas pressure and waveguide length. The enhancement of the IAP is attributed to favorable phase matching of SXR high harmonics caused by the evolution of the three-color waveform during its propagation in the waveguide, which can be understood by analyzing the time shift of the waveform due to the interplay of the waveguide mode, atomic dispersion, and plasma dispersion. We check that the gating method is quite robust with respect to the phase jitter in the waveform. The advantage of this method is further demonstrated by comparing the generation of SXR high harmonics and attosecond pulses with two other schemes: the three-color waveform in a gas cell and a previously optimized two-color waveform in a gas-filled waveguide.

74 ATOMIC AND MOLECULAR PHYSICS↗

A Faster-Than-Real-Time Framework for Reliability-Oriented Simulation of PV Inverters

Physics-of-Failure (PoF) based reliability assessment for photovoltaic (PV) inverters requires long-duration electrical and electrothermal stress histories, yet generating such stress histories with high-fidelity switching models over year long mission profiles is computationally prohibitive. Conventional methods either sacrifice modeling fidelity for speed or require runtimes that are impractical for design iteration and uncertainty studies. To address this bottleneck, this paper presents a High-Performance Computing (HPC) based simulation frame work for faster-than-real-time reliability-oriented simulation. The proposed framework integrates the Average-to-Switching (A2S) method with parallel computing techniques to accelerate switching-level waveform reconstruction. We further introduce optimization strategies, including cluster merging and sensitivity based mission profile screening, to reduce the computational burden. Evaluated using real-world mission profile inputs and a MATLAB/Simulink switching-model reference, the framework reduces the simulation time for a one-year mission from an intractable multi-year duration to approximately 7.3 minutes while maintaining low waveform error. This acceleration provides a practical reliability-oriented simulation engine that can be coupled with component-specific aging models for subsequent PV inverter PoF assessment.

High-performance Computing↗