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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 1,657 records · Page 92
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Optimal Power Sharing Speed Compensation in On-road Wireless EV Charging Systems

Dynamic wireless charging of electric vehicles (EV) is an emerging technology with the potential to address range anxiety and reduce the size of batteries or provide charge-sustaining operation. Charging demand for dynamic wireless charging systems (DWCS) varies greatly in response to location-specific traffic behaviors including the number and speed of vehicles. This paper highlights the potential reduction of load variation with speed compensation and simulates opportunities to maximize the number of cars charged concurrently through “power sharing” or altering power output to slower cars while maintaining a maximum delivered energy. An improved sub-minute model for synthetic traffic is proposed to effectively model DWCS load on high speed roadways and a power electronics model is created based on an existing prototype developed by ORNL to investigate the potential for power sharing. Reductions in the average speed of traffic can greatly increase instantaneous DWCS load by as much as 26%, complicating capacity sizing. Parametric studies with a LCC-S power electronics model shows feasible power reduction of more than 20%, while maintaining a maximum achievable efficiency greater than 90%. Speed compensation on a roadway with large speed variation can reduce average power expected by 21% and increase the maximum number of cars charged simultaneously by 30%. The application of power sharing may significantly reduce load variability due to speed, allow for increased car hosting capability, and guarantee a maximum energy delivered.

Lewis, Donovin D.↗
NASA NTRS2004

Design of Ultra-High-Power-Density Machine Optimized for Future Aircraft

The NASA Glenn Research Center's Structural Mechanics and Dynamics Branch is developing a compact, nonpolluting, bearingless electric machine with electric power supplied by fuel cells for future "more-electric" aircraft with specific power in the projected range of 50 hp/lb, whereas conventional electric machines generate usually 0.2 hp/lb. The use of such electric drives for propulsive fans or propellers depends on the successful development of ultra-high-power-density machines. One possible candidate for such ultra-high-power-density machines, a round-rotor synchronous machine with an engineering current density as high as 20,000 A/sq cm, was selected to investigate how much torque and power can be produced.

Choi, Benjamin B.↗
NASA NTRS1998

Image compression system and method having optimized quantization tables

A digital image compression preprocessor for use in a discrete cosine transform-based digital image compression device is provided. The preprocessor includes a gathering mechanism for determining discrete cosine transform statistics from input digital image data. A computing mechanism is operatively coupled to the gathering mechanism to calculate a image distortion array and a rate of image compression array based upon the discrete cosine transform statistics for each possible quantization value. A dynamic programming mechanism is operatively coupled to the computing mechanism to optimize the rate of image compression array against the image distortion array such that a rate-distortion-optimal quantization table is derived. In addition, a discrete cosine transform-based digital image compression device and a discrete cosine transform-based digital image compression and decompression system are provided. Also, a method for generating a rate-distortion-optimal quantization table, using discrete cosine transform-based digital image compression, and operating a discrete cosine transform-based digital image compression and decompression system are provided.

Ratnakar, Viresh↗
DOE OSTI2021

Juqbox.jl

The Juqbox.jl package implements functionality for solving the quantum optimal control problem for realizing logical gates in closed quantum systems. The dynamics of the quantum system is modeled by Schroedinger's equation, which takes to form of a linear system of ordinary differential equations (ODE). Juqbox.jl solves this ODE by numerical time stepping and applies a gradient-based optimization technique to determine control pulses for driving an initial state to a final state, according to the desired logical gate transformation. To evaluate the gradient, Juqbox.jl applies the ``first discretize, then optimize'' approach based on a discrete adjoint time stepping technique. The actual optimization is performed by the open source Ipopt libaray. Juqbox.jl is written in the Julia programming language which, among many other features, provides a convenient interface to the Ipopt library.

PETERSSON, NILSA.↗
DOE OSTI2025

Autonomous Synthesis of Metastable Materials Using a Modular Mixed-Flow Reactor

Understanding and controlling atomic-level processes at solid-liquid interfaces is key to advancing technologies in energy storage, carbon capture, critical element recovery, and materials synthesis. Many of these processes are dominated by the formation of short-lived intermediate precipitates that determine the final properties of synthesized materials. However, studying these intermediates is challenging due to their sensitivity and the reliance on trial-and-error methods. To address this, we developed an automated variable-volume mixed-flow reactor (MFR) to optimize metastable material synthesis and investigate rapid kinetic processes. This state-of-the-art MFR system, paired with an automated modeling framework, enables efficient synthesis and real-time analysis of transient phases. Benchmarking with advanced capabilities, such as wide-/small-angle X-ray scattering, allows us to resolve fast nucleation and growth dynamics that were previously inaccessible. By combining automation, ML-guided optimization, and tailored kinetic modeling, this approach provides a robust platform for improving material design and achieving precise control over solid-liquid reactions.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Role of Intradomain Heterogeneity on Ion and Polymer Dynamics in Block Polymer Electrolytes: Investigating Interfacial Mobility and Ion-Specific Dynamics and Transport

Block polymers show promise as solid-state battery electrolytes due to the optimization of conductive and mechanical properties enabled via tuning of block chemistry and length. We investigate a polystyrene-block-poly(oligo-oxyethylene methacrylate) (PS-b-POEM) electrolyte doped with various lithium salts to investigate the role of molecular structure on ion transport properties and on local ion dynamics and associations. Anion charge becomes more delocalized with increasing size, reducing the coupling between salt ions while increasing coupling between ion and polymer chain motions and creating a more mobile overall environment. We observe support for this ion-polymer coupling via 1 H, 7 Li and 19 F NMR spectroscopy, from which we obtain ion-specific mobility transition temperatures that differ from the polymer glass transition temperature. We also note faster transport and weaker local energetic interactions with anion size using temperature-dependent NMR diffusometry. 1 H NMR spectroscopy further elucidates polymer chain dynamics and enables quantification of the temperature-dependent fraction of the conducting block that is immobile near the PS-POEM domain interface. As a result, NMR thus represents a species-specific and timescale-specific platform to quantify phase and interface behavior, and to correlate ion-specific transport with polymer chain dynamics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Extended Lagrangian Born–Oppenheimer molecular dynamics using a Krylov subspace approximation

It is shown how the electronic equations of motion in extended Lagrangian Born–Oppenheimer molecular dynamics simulations can be integrated using low-rank approximations of the inverse Jacobian kernel. This kernel determines the metric tensor in the harmonic oscillator extension of the Lagrangian that drives the evolution of the electronic degrees of freedom. The proposed kernel approximation is derived from a pseudoinverse of a low-rank estimate of the Jacobian, which is expressed in terms of a generalized set of directional derivatives with directions that are given from a Krylov subspace approximation. The approach allows a tunable and adaptive approximation that can take advantage of efficient preconditioning techniques. The proposed kernel approximation for the integration of the electronic equations of motion makes it possible to apply extended Lagrangian first-principles molecular dynamics simulations to a broader range of problems, including reactive chemical systems with numerically sensitive and unsteady charge solutions. This can be achieved without requiring exact full calculations of the inverse Jacobian kernel in each time step or relying on iterative non-linear self-consistent field optimization of the electronic ground state prior to the force evaluations as in regular direct Born–Oppenheimer molecular dynamics. We note the low-rank approximation of the Jacobian is directly related to Broyden’s class of quasi-Newton algorithms and Jacobian-free Newton–Krylov methods and provides a complementary formulation for the solution of nonlinear systems of equations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS2004

Orbit Design for Phase I and II of the Magnetospheric Multiscale Mission

The Magnetospheric Multiscale Mission (MMS) is a NASA mission intended to make fundamental advancements in our understanding of the Earth s magnetosphere. There are three processes that MMS is intended to study including magnetic reconnection, charged particle acceleration, and turbulence. There are four phases of the MMS mission and each phase is designed to study a particular region of the Earth's magnetosphere. The mission is composed of a formation of four spacecraft that are nominally in a regular tetrahedron formation. In this work, we present optimal orbit designs for Phase I and II. This entails designing reference orbits such that the spacecraft dwell-time in the region of interest is a maximum. This is non-trivial because the Earth's magnetosphere is dynamic and its shape and position are not constant in inertial space. Optimal orbit design for MMS also entails designing the formation so that the relative motion of the four spacecraft yields the greatest science return. We develop performance metrics that are directly related to the science return, and use Sequential Quadratic Programming (SQP) to determine optimal relative motion solutions. While designing for optimal science return, we also consider practical constraints such as maximum eclipse time and minimum inter-spacecraft separation distances. Data are presented that illustrates how long we can ensure that the formation remains in the relevant region of the Earth's magnetosphere. We also draw general conclusions about where in the orbit acceptable tetrahedron configurations can be provided and for how long.

Hughes, Steve P.↗
DOE OSTI2024

ARPA-E Grid Optimization (GO) Competition Challenge 3

Synthetic Input Data and Team Results for the GO Competition Challenge 3 for Events 1 - 4 and the Sandbox, along with problem and format descriptions and code to validate data and solutions, are available here. Data for industry scenarios will not be made public. The Grid Optimization (GO) Competition Challenge 3 focused on the security-constrained optimal power flow (SCOPF) problem. It is part of a continuing effort begun with Challenges 1 and 2, to successfully discover, develop, and test innovative and disruptive software solutions for critical energy challenges and to overcome existing barriers. The broader goal of the of the GO Competition is to accelerate the development of transformational and disruptive methods for solving problems related to the electric power grid and to provide a transparent, fair, and comprehensive evaluation of new solution methods. Challenge 3 used multiperiod dynamic markets, including advisory models for extreme weather events, day-ahead markets, and the real-time markets with an extended look-ahead. In Event 4, whose submission window was August 31-September 4, 2023, 14 teams solved for the objective values of 669 scenarios (39 scenarios required solutions both with and without line switching being allowed). The 591 synthetic scenarios from 9 network models (3.6 GB) are available here. Ten teams were funded to participate and 7 won prizes totaling $2,400,000. The largest prize ($550,000) went to Mississippi State University. An additional $600,000 was awarded in Event 3 (6/15-16/2023). No prizes were awarded in Events 1 (1/25-27/2023) or 2 (4/13-14/2023). For more information on the competition and challenge see the "GO Competition Challenge 3 Information" resource below.

ACOPF↗
DOE OSTI2024

Multi-amplifier Sensing Charge-coupled Devices for Next Generation Spectroscopy

We present characterization results and performance of a prototype Multiple-Amplifier Sensing (MAS) silicon charge-coupled device (CCD) sensor with 16 channels potentially suitable for faint object astronomical spectroscopy and low-signal, photon-limited imaging. The MAS CCD is designed to reach sub-electron readout noise by repeatedly measuring charge through a line of amplifiers during the serial transfer shifts. Using synchronized readout electronics based on the Dark Energy Spectroscopic Instrument CCD controller, we report a read noise of 1.03 e$^{−}$ rms pix$^{−1}$ at a speed of 26 μs pix$^{−1}$ with a single-sample readout scheme where charge in a pixel is measured only once for each output stage. At these operating parameters, we find the amplifier-to-amplifier charge transfer efficiency (ACTE) to be >0.9995 at low counts for all amplifiers but one for which the ACTE is 0.997. This charge transfer efficiency falls above 50,000 electrons for the read-noise optimized voltage configuration we chose for the serial clocks and gates. The amplifier linearity across a broad dynamic range from ∼300 to 35,000 e$^{−}$ was also measured to be ±2.5%. We describe key operating parameters to optimize on these characteristics and describe the specific applications for which the MAS CCD may be a suitable detector candidate.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Addition of Chloroform in a Solvent-in-Salt Electrolyte: Outcomes in the Microscopic Dynamics in Bulk and Confinement

Solvent-in-salt electrolytes (SISEs) are a promising alternative to the electrolytes currently used in commercial devices. Despite the SISEs’ advantages, their utilization is not yet realized due to the poor mobility of their chemical species. Here, we explore this problem by adding chloroform to a SISE formed by acetonitrile and a Li-salt. First, we performed illustrative cycling experiments to highlight the potential of this approach. Then, we focused on the description of the microscopic dynamics of the electrolytes and exposed the relevant aspects to be considered for their optimal performance. While the conductivity at low temperatures may be enhanced by the addition of chloroform, only subtle changes occur at room temperature. As revealed by molecular dynamics simulations and quasielastic neutron scattering (QENS) experiments, this effect is related to the preservation of the structure expected for a highly concentrated solution and promotion of the formation of ionic aggregates. These outcomes occur despite the increase in the overall mobility of the chemical species. The dynamics of the electrolytes in porous carbon was also investigated using QENS. In these circumstances, low concentrations of chloroform lead to diffusivities of the molecular species higher than those observed for the bulk electrolytes. As chloroform’s concentration increases, no further changes in the diffusivities are observed. Nonetheless, chloroform is mostly immobilized on the carbon surfaces and this behavior may be intensified at compositions closer to the eutectic mixture.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1992

Discrete-time entropy formulation of optimal and adaptive control problems

The discrete-time version of the entropy formulation of optimal control of problems developed by G. N. Saridis (1988) is discussed. Given a dynamical system, the uncertainty in the selection of the control is characterized by the probability distribution (density) function which maximizes the total entropy. The equivalence between the optimal control problem and the optimal entropy problem is established, and the total entropy is decomposed into a term associated with the certainty equivalent control law, the entropy of estimation, and the so-called equivocation of the active transmission of information from the controller to the estimator. This provides a useful framework for studying the certainty equivalent and adaptive control laws.

Tsai, Yweting A.↗
NASA NTRS1990

A Unified Statistical Rain-Attenuation Model for Communication Link Fade Predictions and Optimal Stochastic Fade Control Design Using a Location-Dependent Rain-Statistic Database

A static and dynamic rain-attenuation model is presented which describes the statistics of attenuation on an arbitrarily specified satellite link for any location for which there are long-term rainfall statistics. The model may be used in the design of the optimal stochastic control algorithms to mitigate the effects of attenuation and maintain link reliability. A rain-statistics data base is compiled, which makes it possible to apply the model to any location in the continental U.S. with a resolution of 0-5 degrees in latitude and longitude. The model predictions are compared with experimental observations, showing good agreement.

Manning, Robert M.↗
NASA NTRS1973

A suboptimal stochastic controller for an N-body spacecraft

Considerable attention, in the open literature, is being focused on the problem of developing a suitable set of deterministic dynamical equations for a complex spacecraft. This paper considers the problem of determining a stochastic optimal controller for an n-body spacecraft. The approach used in obtaining the stochastic controller involves the application, interpretation, and combination of advanced dynamical principles and the theoretical aspects of modern control theory. The stochastic controller obtained herein for a complicated model of a spacecraft uses sensor angular measurements associated with the base body to obtain smoothed estimates of the entire state vector. It can be easily implemented, and it enables system performance to be significantly improved.

Larson, V.↗
NASA NTRS1975

Radiometric performance of the Viking Mars lander cameras

The Viking lander cameras feature an array of 12 silicon photodiodes for electronic focus selection and multispectral imaging. Comparisons of absolute radiometric calibrations of the four cameras selected for the mission to Mars with performance predictions based on their design data revealed minor discrepancies. These discrepancies were caused primarily by the method used to calibrate the photosensor array and apparently also from light reflections internal to the array. The sensitivity and dynamic range of all camera channels are found to be sufficient for high quality pictures, providing that the commandable gains and offsets can be optimized for the scene radiance; otherwise, the quantization noise may be too high or the dynamic range too low for an adequate characterization of the scene.

Huck, F. O.↗
NASA NTRSDate not supplied

Quantum Mechanical Simulations of Dynamics of Electronic Excitations in Low-Dimensional Photovoltaics Materials

Dynamics of electronically excited states including exciton generation and relaxation, exciton-exciton interaction, and charge/energy transfer and transport, are critical to understanding and optimizing photovoltaic materials. Although considerable progress has been made, accurate experimental characterization of such crucial dynamics remains extremely challenging, especially in low-dimensional materials. In this talk, I will discuss how the advancement of quantum mechanical simulations of the dynamics of electronic excitations can reveal the physical mechanisms hindering or improving solar energy harvest. Specifically, we find that surface dangling-bond defects on silicon quantum dots cause rapid charge recombination and low carrier mobility in the inorganic-organic PV cells. Although small quantum dots are essentially free of defects, their optical gaps are too large. To solve this issue, a full-spectrum-light-absorption scheme is computationally designed, taking advantage of complexity and flexibility of low-dimensional materials consisting of different characteristics and dimensions. In this scheme the multifunctional ligands are used to (1) passivate against oxidation, (2) facilitate interfacial charge transfer, and (3) improve both charge transport and optical absorption. A joint theoretical and experimental study has demonstrated the feasibility of this approach. Finally, I will briefly talk about how this scheme and the well-tested quantum mechanical simulations can be employed to help improve energy-conversion efficiency in perovskite photovoltaics including perovskite-based tandem cells.

Zhigang Wu↗
DOE OSTI2023

Operation Optimization Using Reinforcement Learning with Integrated Artificial Reasoning Framework

In large and complex systems, operational decision-making requires a systematic analysis with a vast amount of data from both process parameters and component status monitoring. In this paper, we present an integrated artificial reasoning approach for system state transition models that can help operational decision-making with explainable and traceable reasoning. The integrated artificial reasoning framework is a physics-based approach of defining the system structure in a Bayesian network, so we leveraged it in a Markov decision process (MDP) for finding optimal operational solutions. In our proposed framework, the MDP is implemented on a dynamic Bayesian network (DBN), which represents causalities in a system. The multilevel flow modeling was utilized in order to extract these causalities in a more efficient and objective manner. Since multilevel flow modeling is based on the fundamental energy and mass conservation laws, the target system is decomposed into several mass, energy, and information structures, which serve as the basis for a DBN. The MDP consists of the processes of finding a solution for the Bellman equation, which can be derived from the conditional probability equations of the constructed DBN. System operators can capture stochastic system dynamics as multiple subsystem state transitions based on their physical relations and uncertainties coming from the component degradation process or random failures. We analyzed a simplified example system to illustrate finding an optimal operational policy with this approach.

Kim, Junyung↗
DOE OSTI2022

Physics-based modeling and information-theoretic sensor and settings selection for tool wear detection in precision machining

Precision machining of metals is an energy intensive process with applications and impacts across the manufacturing industry. The energy efficiency, product yield, and maintenance of the precision machine require a digital twin that can assist with prognostics and health management. In this report a physics-based model is developed and validated against face milling data, and then used for the timely and precise inference of machining faults that cannot be measured directly. Computer numerical control (CNC) measurements of power and force are used through this physics-based machining model to predict deviations of the outputs of power consumption and cutting forces during normal operation. A model-based fault detection and isolation methodology is applied to determine the optimal (traditional and available) sensor suite and the test settings (admissible input values) that improve the inference of tool wear in face milling. The optimal sensor suite and input test settings are obtained by solving a mixed integer non-linear program that optimizes information-theoretic metrics relevant to the detection and isolation of tool wear from steady-state or transient machining measurements. Dynamic time warping and k—NN classification are then used to validate the robustness of the optimal design for fault detection test design, including the optimal sensor suite.

42 ENGINEERING↗