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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 811 records · Page 45
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

An Intelligent Metasurface-Based Wireless Power Transfer System

Wireless Power Transfer (WPT) systems are getting more popular in recent years in a wide range of application areas. However, the performance of wireless power transfer systems is adversely affected by coil misalignment and increased power transfer distance. To overcome the limitations, the proposed method in this paper will place an intelligent controllable metasurface between the transmitter and receiver coils. The goal is to establish the feasibility of a metasurface-assisted, intelligent WPT charging system by variable coil design and angle of arrival estimation using machine learning for multiple misalignment cases. We will feed these angles of arrival data to reconfigure the metasurface. The inclusion of a controllable metasurface will improve efficiency and increase the power transfer distance.

Aydin, Emrullah↗
DOE OSTI2019

Deep Transfer Learning With Field-Based Measurements for Large Area Classification

Classification of Electro-Optical (EO) datasets using Deep Neural Networks (DNNs) has lead to high-performance supervised learning algorithms. However, DNNs require a large amount of labeled data for training which often have limited availability in ecological studies. Up-to-date classification of vegetation in sensitive Arctic ecosystems continue to be a challenge. In an ecosystem undergoing rapid change, capturing the dynamics of vegetation requires the existing maps of vegetation (such as Alaska Existing Vegetation Type (AKEVT), circa 2000) to be updated based on frequent field based observation of vegetation. A method is needed to transfer the knowledge gained from field-collected observations to a larger area using DNNs. Transfer learning is a machine learning technique where a model trained on one task is re-purposed on another similar task. This paper seeks to train DNNs using field-collected observations and apply transfer learning to apply the knowledge gained to update existing vegetation map at larger scale. We test two DNN methods, (1) a deep multilayer perceptron (MLP) model and (2) siamese MLP network that uses a structure to rank similarity between inputs and can be used for training datasets with few samples and show good performance with limited datasets (e.g. few-shot learning). The results show ∼90% accuracy (using the field observations for evaluation) when transfer learning is applied to a siamese network, compared to ∼45% accurate when a MLP is trained on the AKEVT and evaluated on the field observations. The approach show promise for improving and update the existing vegetation maps over large areas using limited field-based observations.

Langford, Zach↗
DOE OSTI2021

The Sensitivity Analysis of Coil Misalignment for a 200-kW Dynamic Wireless Power Transfer System with an LCC-S and LCC-P Compensation

The dynamic wireless power transfer systems may reduce the battery size of electric vehicles while maintaining the travel range. Similar to the stationary wireless power transfer systems, the compensation networks are desired in dynamic wireless charging systems at the primary and secondary sides to reduce the reactive power requirement from the source and improve the efficiency. Consequently, it is essential to understand the behavior of the compensation networks, especially the sensitivity to misalignments. This paper presents a sensitivity analysis of LCC-S and LCC-P compensation networks for a 200-kW power transfer with variations in the coupling coefficient due to the electric vehicle travel and misalignments between the pads. The sensitivity study combines the electromagnetic finite element analysis and circuit analysis to determine the impact of misalignments on the wireless power transfer system characteristics. The theoretical analysis is verified by conducting circuit simulations at discrete points to verify the accuracy of the mathematical model.

Kavimandan, Utkarsh↗
DOE OSTI2019

Horizontal transfer of a pathway for coumarate catabolism unexpectedly inhibits purine nucleotide biosynthesis

A microbe’s ecological niche and biotechnological utility are confirmed by its specific set of co-evolved metabolic pathways. The acquisition of new pathways, through horizontal gene transfer or genetic engineering, can have unpredictable consequences. In this work, we show that two different pathways for coumarate catabolism failed to function when initially transferred into Escherichia coli . Using laboratory evolution, we elucidated the factors limiting activity of the newly acquired pathways and the modifications required to overcome these limitations. Both pathways required host mutations to enable effective growth with coumarate, but the necessary mutations differed. In one case, a pathway intermediate inhibited purine nucleotide biosynthesis, and this inhibition was relieved by single amino acid replacements in IMP dehydrogenase. A strain that natively contains this coumarate catabolism pathway, Acinetobacter baumannii , is resistant to inhibition by the relevant intermediate, indicating that natural pathway transfers have faced and overcome similar challenges. Molecular dynamics simulation of the wild type and a representative single-residue mutant provide insight into the structural and dynamic changes that relieve inhibition. These results reflect how deleterious interactions can limit pathway transfer, that these interactions can be traced to specific molecular interactions between host and pathway, and how evolution or engineering can alleviate these limitations.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Measurement of the Natural Convection Heat Transfer in a Magnesium Oxide Electrolytic Cell Concept

The rate of heat transfer by natural convection between the wall and electrolyte of an electrolytic cell that produces magnesium (Mg) from magnesium oxide (MgO) at temperatures near 1000 °C in a molten fluoride salt electrolyte is presented. An experimental model of the cell was developed that enabled measurements of the heat transfer in the absence of electrolysis and at temperatures less than 100 °C over ranges of Rayleigh numbers from 1 × 10 -7 to 7 × 10 -8 and Prandtl numbers from 2 to 6200, ranges that include those anticipated in the operation of the MgO electrolytic cell. The model avoids the substantial experimental challenges associated with the high-temperature, corrosive molten salt to enable a conservative estimate of the heat transfer at a lower cost and greater accuracy than would otherwise be possible. The results are correlated by the expression Nu = 0.412Ra 0.23 Pr 0.15 with Nusselt numbers spanning 30–80. The application of the correlation shows that the heat transfer between the cell wall and the molten fluoride electrolyte at ≈1000 °C is characterized by convection coefficients between 100 and 600 W/m 2 -K and is fast enough to enable heat fluxes up to 10 W/cm 2 without compromising the structural integrity of the steel cell wall.

Engineering↗
DOE OSTI2020

Wettability Effects on Falling Film Flow and Heat Transfer Over Horizontal Tubes in Jet Flow Mode

The performance of a falling-film heat exchanger is strongly linked to the surface characteristics and the heat transfer processes that take place over the tubes. The primary aim of this numerical study is to characterize the influence of surface wettability on the film flow behavior and its associated surface heat transfer in the jet-flow mode. Volume of fluid (VOF) based simulations are carried out for horizontal tubes with different surface wettabilities. The wettability of the tube surfaces is represented using the Kistler's dynamic contact angle model. Surface wettability effects ranging from superhydrophilic to superhydrophobic are studied by varying the equilibrium contact angle from 2 deg to 175 deg. Two different liquid mass flow rates of 0.06 and 0.18 kg/m-s corresponding to the inline and staggered jet flow modes are studied. Results are presented in terms of the liquid film thickness, the contact areas between the different phases (solid–liquid and liquid–air), and the heat transfer coefficient or Nusselt number. The resistance imposed by the increasing contact angles inhibits the extent of the liquid spreading over the tube surface, and this, in turn, influences the liquid film thickness, and the wetted area of the tube surface. A significant decrement in the heat transfer rate from the tube surfaces was observed as the equilibrium contact angle increased from 2 deg to 175 deg. The local distributions of the Nusselt number over the tube surface are strongly influenced by the flow recirculation in the liquid bulk.

Engineering↗
DOE OSTI2021

Atomic-Level, Energy-Conversion Heat Transfer

Abstract Heat is stored in quanta of kinetic and potential energies in matter. The temperature represents the equilibrium and excited occupation (boson) of these energy conditions. Temporal and spatial temperature variations and heat transfer are associated with the kinetics of these equilibrium excitations. During energy-conversion (between electron and phonon systems), the occupancies deviate from equilibria, while holding atomic-scale, inelastic spectral energy transfer kinetics. Heat transfer physics reaches nonequilibrium energy excitations and kinetics among the principal carriers, phonon, electron (and holes and ions), fluid particle, and photon. This allows atomic-level tailoring of energetic materials and energy-conversion processes and their efficiencies. For example, modern thermal-electric harvesters have transformed broad-spectrum, high-entropy heat into a narrow spectrum of low-entropy emissions to efficiently generate thermal electricity. Phonoelectricity, in contrast, intervenes before a low-entropy population of nonequilibrium optical phonons becomes a high-entropy heat. In particular, the suggested phonovoltaic cell generates phonoelectricity by employing the nonequilibrium, low-entropy, and elevated temperature optical-phonon produced population—for example, by relaxing electrons, excited by an electric field. A phonovoltaic material has an ultranarrow electronic bandgap, such that the hot optical-phonon population can relax by producing electron-hole pairs (and power) instead of multiple acoustic phonons (and entropy). Examples of these quanta and spectral heat transfer are reviewed, contemplating a prospect for education and research in this field.

Engineering↗
DOE OSTI2023

Experimental and Computational Heat Transfer Study of sCO 2 Single-Jet Impingement

This study experimentally and computationally investigates the heat transfer capability of supercritical carbon dioxide (sCO 2 ) single jet impingement. The evaluated jet Reynolds number range is between 80,000 and 600,000, with a nondimensional jet-to-target surface spacing of 2.8. CO 2 -impinging jet stagnation conditions were maintained at approximately 200 bar and a temperature of ∼400 °C for most experiments. The goal is to understand how changes in the aforementioned parameters influence heat transfer between the working fluid and the heated surface. Additionally, due to the elevated Reynolds numbers and difference in thermodynamic properties between air and CO 2 , air-derived impingement correlations may not be appropriate for CO 2 impingement; these correlations will be evaluated against experimental sCO 2 impingement data. At the time of this study, no sCO 2 impingement data was available relevant to sCO 2 power cycles. The target surface is a 1.5-in. diameter copper block centered on the 3 mm jet orifice. A mica heating element bolted to the bottom of the copper block provides a uniform heat flux. Thermocouples embedded in the copper block are used to determine the surface temperature. Nusselt numbers obtained from experimental sCO 2 test data are compared to area-averaged Nusselt numbers from air-derived correlations. The comparisons showed that air correlations drastically underpredict the heat transfer when sCO 2 is used as the working fluid. A modified sCO 2 correlation using experimental data at discussed conditions is derived based on an existing air correlation. A CFD study is also performed to further investigate sCO 2 heat transfer characteristics, and assess the numerical model applicability to this problem type.

42 ENGINEERING↗
DOE OSTI2023

Optical information transfer through random unknown diffusers using electronic encoding and diffractive decoding

Free-space optical information transfer through diffusive media is critical in many applications, such as biomedical devices and optical communication, but remains challenging due to random, unknown perturbations in the optical path. We demonstrate an optical diffractive decoder with electronic encoding to accurately transfer the optical information of interest, corresponding to, e.g., any arbitrary input object or message, through unknown random phase diffusers along the optical path. This hybrid electronic-optical model, trained using supervised learning, comprises a convolutional neural network-based electronic encoder and successive passive diffractive layers that are jointly optimized. After their joint training using deep learning, our hybrid model can transfer optical information through unknown phase diffusers, demonstrating generalization to new random diffusers never seen before. The resulting electronic-encoder and optical-decoder model was experimentally validated using a 3D-printed diffractive network that axially spans <70λ, where λ = 0.75 mm is the illumination wavelength in the terahertz spectrum, carrying the desired optical information through random unknown diffusers. The presented framework can be physically scaled to operate at different parts of the electromagnetic spectrum, without retraining its components, and would offer low-power and compact solutions for optical information transfer in free space through unknown random diffusive media.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Direct light–induced spin transfer between different elements in a spintronic Heusler material via femtosecond laser excitation

Heusler compounds are exciting materials for future spintronics applications because they display a wide range of tunable electronic and magnetic interactions. Here, we use a femtosecond laser to directly transfer spin polarization from one element to another in a half-metallic Heusler material, Co 2 MnGe. This spin transfer initiates as soon as light is incident on the material, demonstrating spatial transfer of angular momentum between neighboring atomic sites on time scales < 10 fs. Using ultrafast high harmonic pulses to simultaneously and independently probe the magnetic state of two elements during laser excitation, we find that the magnetization of Co is enhanced, while that of Mn rapidly quenches. Density functional theory calculations show that the optical excitation directly transfers spin from one magnetic sublattice to another through preferred spin-polarized excitation pathways. This direct manipulation of spins via light provides a path toward spintronic devices that can operate on few-femtosecond or faster time scales.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Trapped-ion quantum simulation of electron transfer models with tunable dissipation

Electron transfer is at the heart of many fundamental physical, chemical, and biochemical processes essential for life. The exact simulation of these reactions is often hindered by the large number of degrees of freedom and by the essential role of quantum effects. Here, we experimentally simulate a paradigmatic model of molecular electron transfer using a multispecies trapped-ion crystal, where the donor-acceptor gap, the electronic and vibronic couplings, and the bath relaxation dynamics can all be controlled independently. By manipulating both the ground-state and optical qubits, we observe the real-time dynamics of the spin excitation, measuring the transfer rate in several regimes of adiabaticity and relaxation dynamics. Our results provide a testing ground for increasingly rich models of molecular excitation transfer processes that are relevant for molecular electronics and light-harvesting systems.

Science & Technology - Other Topics↗
DOE OSTI2026

Optimal Transfer Operators in Algebraic Two-Level Methods for Nonsymmetric and Indefinite Problems

Consider an algebraic two-level method applied to the 𝑛-dimensional linear system 𝐴⁢𝒙 = 𝒃 using fine-space preconditioner (i.e., “relaxation” or “smoother”) 𝑀, with 𝑀 ≈ 𝐴, restriction and interpolation 𝑅 and 𝑃, and algebraic coarse-space operator 𝐴 𝑐 : = 𝑅 ∗ ⁢𝐴⁢𝑃. Then, what are the best possible transfer operators 𝑅 and 𝑃 of a given dimension 𝑛 𝑐 < 𝑛? Brannick et al. [12] showed that when 𝐴 and 𝑀 are Hermitian positive definite (HPD), the optimal interpolation is such that its range contains the 𝑛 𝑐 smallest generalized eigenvectors of the matrix pencil (𝐴, 𝑀). Recently, in Ali et al. [5] we generalized this framework to the non-HPD setting, by considering both right (interpolation) and left (restriction) generalized eigenvectors of (𝐴, 𝑀) and defining corresponding nonsymmetric transfer operators {𝑅#, 𝑃#}. Tight convergence bounds for {𝑅#, 𝑃#} are derived in spectral radius, as well as a proof of pseudo-optimality. Note, {𝑅#, 𝑃#} are typically complex valued, which is not practical for real-valued problems. Here, in this work, we build on [5], first characterizing all inner products in which the coarse-space correction defined by {𝑅#, 𝑃#} is orthogonal. We then develop tight two-level convergence bounds in these norms, and prove that the underlying transfer operators {𝑅#, 𝑃#} are genuinely optimal. As a special case, our theory both recovers and extends the HPD results from [12]. Finally, we show how to construct optimal, real-valued transfer operators in the case of that 𝐴 and 𝑀 are real valued, but are not HPD. Numerical examples arising from a discretized advection-reaction equation, wave-equation, and Stokes equations are used to verify and illustrate the theory.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Shell-model calculations for two-neutron transfer near the $N=20$ island of inversion

We describe connections between shell-model calculation results and predictions for two-nucleon transfer reactions. Measurements of the 30 Mg(t,p) 32 Mg reaction were used to identify a low-lying shape-coexisting 0 + state in 32 Mg. Interpretations of those early, limited data were based on simple empirical models. The cross sections for two-nucleon transfer are, however, extremely sensitive to the details of the nuclear-structure. Motivated by the possibility of new high-resolution two-nucleon transfer measurements around the N = 20 Island of Inversion, we have performed shell-model calculations wave functions for states in the nuclei 30,32 Mg using the SDPF-M and SDPF-MU interactions, and from those calculations obtain the two-nucleon transfer amplitudes that we use to predict cross sections for the 28,30 Mg(t,p) 30,32 Mg reactions. The combined results show how the nuclear structure properties influence experimental observables for the (t,p) reaction. We compare our results with the existing data.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2019

The eRHIC spin rotator and the beam optics of the 400 MeV transfer line to RCS

The 400 MeV LINAC 1 of the proposed eRHIC collider 1 is the first acceleration stage of the 18 GeV electron accelerator. The second acceleration stage of the electron accelerator is the Rapid Cycling Synchrotron (RCS), which can increase the energy of the electron bunches to 18 GeV and subsequently extract transfer and inject the 18 GeV electron bunches into the 18 GeV electron Storage Ring (SR) to collide with the hadron bunches of the existing (Relativistic Heavy Ion Collider (RHIC)) accelerator. This paper describes the beam optics of the transfer line between the 400 MeV LINAC and the RCS accelerator (LtRCS). The function of the LtRCS line is twofold, first to transfer the electron beam from the exit of the 400 MeV LINAC to the injection point of the RCS 1 and second to rotate the stable spin direction of the polarized electrons from the longitudinal direction to the vertical. A detailed description of the constraints to be satisfied by the LtRCS transfer line will be given. Finally, a section will also be devoted to discuss the spin rotator 2 .

43 PARTICLE ACCELERATORS↗
DOE OSTI2023

Electrochemical Characterization of Biomolecular Electron Transfer at Conductive Polymer Interfaces

Bio-electrochemical systems (BESs) are promising for renewable energy generation but remain hindered by inefficient electron transfer at electrode surfaces. As the toolbox of bio-anode materials increases, rigorous electrochemical characterization of emerging materials is needed. Here, we holistically characterize the electrochemical interaction of flavin mononucleotide (FMN), an electron shuttle in biological systems and a cofactor for oxidoreductase enzymes, with the bio-inspired mixed conducting polymer poly{3-[6'-(N-methylimidazolium)hexyl]thiophene} (P3HT-Im + ). The behavior of this polymer is compared to the equivalent polymer without the histidine-like imidazolium. We find improved conductivity and charge storage in imidazolium-containing polymers beyond what is explained by differences in the electroactive area. The P3HT-Im + further shows internal charge storage but with negligible faradaic contribution, indicating that charge storage capacity may translate to improved biocatalysis non-intuitive ways. Finally, one-electron transfer is observed between FMN and glassy carbon, while a bio-similar two-electron transfer is observed for the P3HT-Im + . To our knowledge, this is the first example of a concerted two-electron transfer between FMN and an electrode interface, which we attribute to the bio-inspired, histidine-like imidazolium functional groups in the polymer. These studies demonstrate the importance of bio-relevant materials characterization when such materials are deployed in BESs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Understanding the Role of Complexation in the Charge-Transfer Kinetics of the Cu 2+ + e ↔ Cu 1+ Redox Reaction in Ethaline Deep Eutectic Solvent

Deep eutectic solvent (DES) based electrolytes are gaining attention for electrochemical applications. As such, knowledge of the charge transfer kinetics in DES and its dependence on electrolyte composition and temperature is important. Using Cu 2+ + e ↔ Cu 1+ as a model system, we demonstrate that metal redox reactions in chloride-containing DES media suffer from sluggish charge transfer kinetics. The exchange current density, i 0 , displayed a peculiar inverse relationship with the bulk chloride concentration, [Cl – ] b . The i 0 decreased from 7.9 to 3.0 mA/cm 2 when [Cl – ] b increased from 2.8 to 4.6 M at 30°C. Such dependence is shown to originate from Cl – complexation with reactant and product species. Furthermore, i 0 increased with an increase in Cu n + bulk concentration in the 50–200 mM range. Also, increase in temperature elevated i 0 . The charge transfer coefficient α c , however, remained constant (~0.5) and was unaffected by Cu n + or Cl – concentrations or by temperature. To explain how charge transfer kinetics depend on the various system parameters, a model incorporating complexation phenomena was developed and its predictions were compared to experiments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

A Right Transfer Access Control Model of Internet of Things Based on Smart Contract

Sensor nodes play a crucial role in the promotion of development of Internet of Things (IoT). Through this transaction, RO defines access control policies in script form based on ABAC's access control model to grant access right. The identity of all users in the model is identified by address. This paper builds a more flexible right transfer access control model by means of combining the Attribute-Based Access Control model (ABAC) and blockchain technology. Owing to the characteristics of ABAC’s attributes and right association, the massive problems of some sensor nodes can be solved. At the same time, for the sake of addressing the dynamic problems such as node access and right transfer, right transfer contract (TS) and access control contract (CS) are employed on the chain to ensure efficient and safe transmission of rights. To solve on-chain storage problems and ensure transparency of the operation, the idea of Rollup in Ethereum expansion is used to upload the final state of protocol policy and right exchange to the chain. Any user can know the policy and current right transfer status at any time. Finally, comparative and security analysis show that the model presented here can solve IoT devices’ massive and dynamic problems more effectively and it is more secure than the traditional models.

Wang, Jiuru↗
DOE OSTI2021

Progressive transfer learning for low-frequency data prediction in full waveform inversion

To effectively overcome the cycle-skipping issue in full waveform inversion (FWI), we developed a deep neural network (DNN) approach to predict the absent low-frequency components by exploiting the hidden physical relation connecting the low- and the high-frequency data. To efficiently solve this challenging nonlinear regression problem, two novel strategies were proposed to design the DNN architecture and to optimize the learning process: (1) dual data feed structure; (2) progressive transfer learning. With the dual data feed structure, not only the high-frequency data, but also the corresponding beat tone data are fed into the DNN to relieve the burden of feature extraction. The second strategy, progressive transfer learning, enables us to train the DNN using a single evolving training dataset. Within the framework of the progressive transfer learning, the training dataset continuously evolves in an iterative manner by gradually retrieving the subsurface information through the physics-based inversion module, progressively enhancing the prediction accuracy of the DNN and propelling the inversion process out of the local minima. Here, the synthetic numerical experiments suggest that, without any a priori geological information, the low-frequency data predicted by the progressive transfer learning are sufficiently accurate for an FWI engine to produce reliable subsurface velocity models free of cycle-skipping artifacts.

02 PETROLEUM↗