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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 1,693 records · Page 94
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

All‐Printed Ultrahigh‐Responsivity MoS 2 Nanosheet Photodetectors Enabled by Megasonic Exfoliation

Abstract Printed 2D materials, derived from solution‐processed inks, offer scalable and cost‐effective routes to mechanically flexible optoelectronics. With micrometer‐scale control and broad processing latitude, aerosol‐jet printing (AJP) is of particular interest for all‐printed circuits and systems. Here, AJP is utilized to achieve ultrahigh‐responsivity photodetectors consisting of well‐aligned, percolating networks of semiconducting MoS 2 nanosheets and graphene electrodes on flexible polyimide substrates. Ultrathin (≈1.2 nm thick) and high‐aspect‐ratio (≈1 μm lateral size) MoS 2 nanosheets are obtained by electrochemical intercalation followed by megasonic atomization during AJP, which not only aerosolizes the inks but also further exfoliates the nanosheets. The incorporation of the high‐boiling‐point solvent terpineol into the MoS 2 ink is critical for achieving a highly aligned and flat thin‐film morphology following AJP as confirmed by grazing‐incidence wide‐angle X‐ray scattering and atomic force microscopy. Following AJP, curing is achieved with photonic annealing, which yields quasi‐ohmic contacts and photoactive channels with responsivities exceeding 10 3 A W −1 that outperform previously reported all‐printed visible‐light photodetectors by over three orders of magnitude. Megasonic exfoliation coupled with properly designed AJP ink formulations enables the superlative optoelectronic properties of ultrathin MoS 2 nanosheets to be preserved and exploited for the scalable additive manufacturing of mechanically flexible optoelectronics.

2D materials↗
DOE OSTI2025

A Variational Autoencoder Model Toward Molecular Structure Representation Learning of Fuels

Here, in this work, a Variational Autoencoder (VAE)-based data-driven modeling framework is developed with the overarching goal of enabling fuel design. The VAE model is trained on a large dataset with several chemical species to learn a compressed latent space molecular representation. Chemical structure in the form of Simplified Molecular Input Line Entry System (SMILES) string is fed as input, encoded into the VAE latent space, and decoded back to the SMILES string using Long Short-Term Memory (LSTM) networks. Complexities of the VAE training loss function are thoroughly examined by varying the weightage (beta (𝜷) parameter) of the latent space regularization term, thereby assessing the balance between reconstruction accuracy and validity, and focusing on both accurate molecular structure reconstruction and latent space consistency. Two different strategies for 𝜷 variation are evaluated: linear annealing and cyclic annealing. In addition, the impact of total correlation adjustment and hierarchical priors is also studied with regard to the balance between reconstruction fidelity and latent space regularization, and potential issues such as posterior collapse, over-regularization, and poor disentanglement of latent variables. Overall, the best performance of the model is achieved with hierarchical priors and incrementally increasing 𝜷 from 0 to a threshold value of 0.25 over 75 epochs. The generative VAE model can be readily coupled with Quantitative Structure–Property Relationship (QSPR) analysis to develop an integrated end-to-end framework for fuel-property prediction and molecular design of novel promising fuels.

fuel design↗
DOE OSTI2019

Discovery of novel bacterial queuine salvage enzymes and pathways in human pathogens

Queuosine (Q) is a complex tRNA modification widespread in eukaryotes and bacteria that contributes to the efficiency and accuracy of protein synthesis. Eukaryotes are not capable of Q synthesis and rely on salvage of the queuine base (q) as a Q precursor. While many bacteria are capable of Q de novo synthesis, salvage of the prokaryotic Q precursors preQ 0 and preQ 1 also occurs. With the exception of Escherichia coli YhhQ, shown to transport preQ 0 and preQ 1 , the enzymes and transporters involved in Q salvage and recycling have not been well described. In this work, we discovered and characterized 2 Q salvage pathways present in many pathogenic and commensal bacteria. The first, found in the intracellular pathogen Chlamydia trachomatis , uses YhhQ and tRNA guanine transglycosylase (TGT) homologs that have changed substrate specificities to directly salvage q, mimicking the eukaryotic pathway. The second, found in bacteria from the gut flora such as Clostridioides difficile , salvages preQ 1 from q through an unprecedented reaction catalyzed by a newly defined subgroup of the radical-SAM enzyme family. The source of q can be external through transport by members of the energy-coupling factor (ECF) family or internal through hydrolysis of Q by a dedicated nucleosidase. This work reinforces the concept that hosts and members of their associated microbiota compete for the salvage of Q precursors micronutrients.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Preferential quenching of 5 d antiferromagnetic order in Sr 3 (Ir 1– x Mn x ) 2 O 7

The breakdown of J eff = 1/2 antiferromagnetism in the limit of strong disorder is studied in Sr 3 (Ir 1– x Mn x ) 2 O 7 . Upon Mn-substitution, antiferromagnetic ordering of the Ir cations becomes increasingly two-dimensional, resulting in the complete suppression of longrange Ir magnetic order above x ≈ 0.25. Long-range antiferromagnetism however persists on the Mn sites to higher Mn concentrations ( x > 0.25) and is necessarily mediated via a random network of majority Ir sites. Our data suggest a shift in the Mn valence from Mn 4+ to Mn 3+ at intermediate doping levels, which in turn generates nonmagnetic Ir 5+ sites and suppresses long-range order within the Ir network. Here, the collapse of long-range J eff = 1/2 antiferromagnetism and the survival of percolating antiferromagnetic order on Mn-sites demonstrates a complex 3 d –5 d exchange process that surprisingly enables minority Mn spins to order far below the conventional percolation threshold for a bilayer square lattice.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Application of the variational autoencoder to detect the critical points of the anisotropic Ising model

We generalize the previous study on the application of variational autoencoders to the two-dimensional Ising model to a system with anisotropy. Due to the self-duality property of the system, the critical points can be located exactly for the entire range of anisotropic coupling. This presents an excellent test bed for the validity of using a variational autoencoder to characterize an anisotropic classical model. Furthermore, we reproduce the phase diagram for a wide range of anisotropic couplings and temperatures via a variational autoencoder without the explicit construction of an order parameter. Considering that the partition function of ($d$ + 1)-dimensional anisotropic models can be mapped to that of the $d$-dimensional quantum spin models, the present study provides numerical evidence that a variational autoencoder can be applied to analyze quantum systems via the quantum Monte Carlo method.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2026

Discovery of Probabilistic Dirichlet-to-Neumann Maps on Graphs

Dirichlet-to-Neumann maps enable the coupling of multiphysics simulations across computational subdomains by ensuring continuity of state variables and fluxes at artificial interfaces. We present a novel method for learning Dirichlet-to-Neumann maps on graphs using Gaussian processes, specifically for problems where the data obey a conservation law arising from an underlying partial differential equation. Our approach combines discrete exterior calculus and nonlinear optimal recovery to infer relationships between vertex and edge values. This framework yields data-driven predictions with uncertainty quantification across the entire graph, even when observations are limited to a subset of vertices and edges. By minimizing the reproducing kernel Hilbert space norm while penalizing kernel complexity through maximum likelihood estimation, our method ensures that the resulting surrogate strictly enforces conservation laws without overfitting. We demonstrate our method on two representative applications: subsurface flow in fracture networks and arterial blood flow. Finally, the results demonstrate that the method maintains high accuracy and well-calibrated uncertainty estimates even under severe data scarcity, highlighting its potential for scientific applications where limited data and reliable uncertainty quantification are critical.

Dirichlet-to-Neumann map↗
NASA NTRS2010

NASA Tech Briefs, October 2010

Topics covered include: Hybrid Architecture Active Wavefront Sensing and Control; Carbon-Nanotube-Based Chemical Gas Sensor; Aerogel-Positronium Technology for the Detection of Small Quantities of Organic and/or Toxic Materials; Graphene-Based Reversible Nano-Switch/Sensor Schottky Diode; Inductive Non-Contact Position Sensor; High-Temperature Surface-Acoustic-Wave Transducer; Grid-Sphere Electrodes for Contact with Ionospheric Plasma; Enabling IP Header Compression in COTS Routers via Frame Relay on a Simplex Link; Ka-Band SiGe Receiver Front-End MMIC for Transponder Applications; Robust Optimization Design Algorithm for High-Frequency TWTs; Optimal and Local Connectivity Between Neuron and Synapse Array in the Quantum Dot/Silicon Brain; Method and Circuit for In-Situ Health Monitoring of Solar Cells in Space; BGen: A UML Behavior Network Generator Tool; Platform for Post-Processing Waveform-Based NDE; Electrochemical Hydrogen Peroxide Generator; Fabrication of Single, Vertically Aligned Carbon Nanotubes in 3D Nanoscale Architectures; Process to Create High-Fidelity Lunar Dust Simulants; Lithium-Ion Electrolytes Containing Phosphorous-Based, Flame-Retardant Additives; InGaP Heterojunction Barrier Solar Cells; Straight-Pore Microfilter with Efficient Regeneration; Determining Shear Stress Distribution in a Laminate; Self-Adjusting Liquid Injectors for Combustors; Handling Qualities Prediction of an F-16XL-Based Reduced Sonic Boom Aircraft; Tele-Robotic ATHLETE Controller for Kinematics - TRACK; Three-Wheel Brush-Wheel Sampler; Heterodyne Interferometer Angle Metrology; Aligning Astronomical Telescopes via Identification of Stars; Generation of Optical Combs in a WGM Resonator from a Bichromatic Pump; Large-Format AlGaN PIN Photodiode Arrays for UV Images; Fiber-Coupled Planar Light-Wave Circuit for Seed Laser Control in High Spectral Resolution Lidar Systems; On Calculating the Zero-Gravity Surface Figure of a Mirror; Optical Modification of Casimir Forces for Improved Function of Micro- and Nano-Scale Devices; Analysis, Simulation, and Verification of Knowledge-Based, Rule-Based, and Expert Systems; Core and Off-Core Processes in Systems Engineering; Digital Reconstruction Supporting Investigation of Mishaps; and Template Matching Approach to Signal Prediction.

Source record↗
NASA NTRS2007

Circuit and Method for Communication Over DC Power Line

A circuit and method for transmitting and receiving on-off-keyed (OOK) signals with fractional signal-to-noise ratios uses available high-temperature silicon- on-insulator (SOI) components to move computational, sensing, and actuation abilities closer to high-temperature or high-ionizing radiation environments such as vehicle engine compartments, deep-hole drilling environments, industrial control and monitoring of processes like smelting, and operations near nuclear reactors and in space. This device allows for the networking of multiple, like nodes to each other and to a central processor. It can do this with nothing more than the already in-situ power wiring of the system. The device s microprocessor allows it to make intelligent decisions within the vehicle operational loop and to effect control outputs to its associated actuators. The figure illustrates how each node converts digital serial data to OOK 18-kHz in transmit mode and vice-versa in receive mode; though operations at lower frequencies or up to a megahertz are within reason using this method and these parts. This innovation s technique modulates a DC power bus with millivolt-level signals through a MOSFET (metal oxide semiconductor field effect transistor) and resistor by OOK. It receives and demodulates this signal from the DC power bus through capacitive coupling at high temperature and in high ionizing radiation environments. The demodulation of the OOK signal is accomplished by using an asynchronous quadrature detection technique realized by a quasi-discrete Fourier transform through use of the quadrature components (0 and 90 phases) of the carrier frequency as generated by the microcontroller and as a function of the selected crystal frequency driving its oscillator. The detected signal is rectified using an absolute-value circuit containing no diodes (diodes being non-operational at high temperatures), and only operational amplifiers. The absolute values of the two phases of the received signal are then summed and hard limited (digitized) by comparing them to a reference level and are then input into a microprocessor as a serial bit stream. The quasi-discrete Fourier transform is performed in high-temperature components (operational amplifiers, analog switches, resistors, and capacitors). The demodulated signal is a serial data stream that is input to the UART (universal asynchronous receiver transmitter) receiver pin of the microprocessor. The OOK of the carrier frequency uses the output of the UART pin as an enabling signal that drives the gate of the MOSFET. Logic low bits enable the carrier frequency (realized by using the 0 phase signal from the microcontroller, though either phase may be used) to be DC-coupled to the power supply bus through a current-limiting resistor mounted between the MOSFET drain and the supply rail. The presence of logic lows on the power supply rail is realized by carrier bursts while logic highs are realized by the absence of bursts.

Krasowski, Michael J.↗
NASA NTRS2022

Identifying Chemical Aerosol Signatures Using Optical Suborbital Observations: How Much Can Optical Properties Tell us about Aerosol Composition?

Improvements in air quality and Earth’s climate predictions require improvements of the aerosol speciation in chemical transport models, using observational constraints. Aerosol speciation (e.g., organic aerosols, black carbon, sulfate, nitrate, ammonium, dust or sea salt) is typically determined using in situ instrumentation. Continuous, routine surface network aerosol composition measurements are not uniformly widespread over the globe. Satellites, on the other hand, can provide a maximum coverage of the horizontal and vertical atmosphere but observe aerosol optical properties (and not aerosol speciation) based on remote sensing instrumentation. Combinations of satellite-derived aerosol optical properties can inform on air mass aerosol types (AMTs e.g., clean marine, dust, polluted continental). However, these AMTs are subjectively defined, might often be misclassified and are hard to relate to the critical parameters that need to be refined in models. In this paper, we derive AMTs that are more directly related to sources and hence to speciation. They are defined, characterized, and derived using simultaneous in situ gas-phase, chemical and optical instruments on the same aircraft during the Study of Emissions and Atmospheric Composition, Clouds, and Climate Coupling by Regional Surveys (SEAC4RS, US, summer of 2013). First, we prescribe well-informed AMTs that display distinct aerosol chemical and optical signatures to act as a training AMT dataset. These in situ observations reduce the errors and ambiguities in the selection of the AMT training dataset. We also investigate the relative skill of various combinations of aerosol optical properties to define AMTs and how much these optical properties can capture dominant aerosol speciation. We find distinct optical signatures for biomass burning (from agricultural or wildfires), biogenic and dust-influence AMTs. Useful aerosol optical properties to characterize these signatures are the extinction angstrom exponent (EAE), the single scattering albedo, the difference of single scattering albedo in two wavelengths, the absorption coefficient, the absorption angstrom exponent (AAE), and the real part of the refractive index (RRI). We find that all four AMTs studied when prescribed using mostly airborne in situ gas measurements, can be successfully extracted from at least three combinations of airborne in situ aerosol optical properties (e.g., EAE, AAE and RRI) over the US during SEAC4RS. However, we find that the optically based classifications for BB from agricultural fires and polluted dust include a large percentage of misclassifications that limit the usefulness of results relating to those classes. The technique and results presented in this study are suitable to develop a representative, robust and diverse source-based AMT database. This database could then be used for widespread retrievals of AMTs using existing and future remote sensing suborbital instruments/networks. Ultimately, it has the potential to provide a much broader observational aerosol data set to evaluate chemical transport and air quality models than is currently available by direct in situ measurements. This study illustrates how essential it is to explore existing airborne datasets to bridge chemical and optical signatures of different AMTs, before the implementation of future spaceborne missions (e.g., the next generation of Earth Observing System (EOS) satellites addressing Aerosol, Cloud, Convection and Precipitation (ACCP) designated observables).

Meloe S F Kacenelenbogen↗
DOE OSTI2022

Surrogate models for plasma displacement and current in 3D perturbed magnetohydrodynamic equilibria in tokamaks

Abstract A numerical database of over one thousand perturbed three-dimensional (3D) equilibria has been generated, constructed based on the MARS-F (Liu et al 2000 Phys. Plasmas 7 3681) computed plasma response to the externally applied 3D field sources in multiple tokamak devices. Perturbed 3D equilibria with the n = 1–4 ( n is the toroidal mode number) toroidal periodicity are computed. Surrogate models are created for the computed perturbed 3D equilibrium utilizing model order reduction (MOR) techniques. In particular, retaining the first few eigenstates from the singular value decomposition (SVD) of the data is found to produce reasonably accurate MOR-representations for the key perturbed quantities, such as the perturbed parallel plasma current density and the plasma radial displacement. SVD also helps to reveal the core versus edge plasma response to the applied 3D field. For the database covering the conventional aspect ratio devices, about 95% of data can be represented by the truncated SVD-series with inclusion of only the first five eigenstates, achieving a relative error (RE) below 20%. The MOR-data is further utilized to train neural networks (NNs) to enable fast reconstruction of perturbed 3D equilibria, based on the two-dimensional equilibrium input and the 3D source field. The best NN-training is achieved for the MOR-data obtained with a global SVD approach, where the full set of samples used for NN training and testing are stretched and form a large matrix which is then subject to SVD. The fully connected multi-layer perceptron, with one or two hidden layers, can be trained to predict the MOR-data with less than 10% RE. As a key insight, a better strategy is to train separate NNs for the plasma response fields with different toroidal mode numbers. It is also better to apply MOR and to subsequently train NNs separately for conventional and low aspect ratio devices, due to enhanced toroidal coupling of Fourier spectra in the plasma response in the latter case.

3D equilibrium↗
DOE OSTI2022

Feature Extraction for Pipeline Defects Inspection Based Upon Distributed Acoustic Fiber Optic Sensing Data

Fiber-optic distributed acoustic sensing (DAS) is becoming an increasingly important tool for real-time monitoring of energy and civil infrastructure structural health such as pipelines. We present a systematic theoretical study of the potential for DAS to be directly coupled with guided ultrasonic waves typically used in conventional acoustic non-destructive evaluation (NDE) methods for real-time pipeline health monitoring. We are referring to this innovative new NDE technique as ultrasonic guided wave and optical fiber sensor fusion. In the practical application of DAS coupled with guided ultrasonic waves, the structural design of (1) the specific guided waves excited, (2) the physical installation of the acoustic transducers and the fiber optic sensors, and (3) the functional performance specifications (gauge length, sensitivity, Etc.) of fiber optic DAS have an important influence on overall capabilities of the monitoring system. Meanwhile, physics-based analysis of acoustic waves is still a challenge due to the complex nature of the Lamb wave when it propagates, scatters, and disperses in the presence of structural defects. In this work, we simulate carbon steel pipes relevant for oil and gas pipeline applications with diameters of approximately 6-12” and wall thickness of 0.5” as the objects to be monitored. By establishing and implementing these capabilities, we seek to pursue an in-depth study on structural parameter optimization of DAS network, measurement range, and signal processing with an ultimate goal of increasing the sensitivity and efficacy of DAS to defect identification for various modes of corrosion expected in practice. To study the characteristics of scattered acoustic waves and performance of DAS for defect identification, we simulated the response of DAS for multiple pipe structures, defect types, and DAS sensor network configuration using finite element software Ansys, then the properties of signal response are extracted to construct defect-sensitive features. The raw data simulated, and the associated features extracted can ultimately be utilized as annotated training data to benchmark various designs for DAS applications, guided acoustic excitation sources, and learning model parameters to enhance early detection of potentially problematic defects.

Pipeline Defects Inspection, Fiber-optic sensors, ↗
DOE OSTI2020

Multimode Storage of Quantum Microwave Fields in Electron Spins over 100 ms

In this work, we report long coherence times (up to 300 ms) for near-surface bismuth donor electron spins in silicon coupled to a superconducting microresonator, biased at a clock transition. This enables us to demonstrate the partial absorption of a train of weak microwave fields in the spin ensemble, their storage for 100 ms, and their retrieval, using a Hahn-echo-like protocol. Phase coherence and quantum statistics are preserved in the storage.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Tutorial: Machine Learning and Artificial Intelligence in Batteries

Machine learning (ML) promises to compress the time needed to characterize battery performance, lifetime and safety. By coupling ML with physical models and metrics, that learning can bridge across materials, chemistries and cell designs. This tutorial will discuss the most popular ML techniques and resources and review recent work in the electrochemical literature. Applications include materials discovery, image recognition for quantitative microscopy analysis, fast charge algorithm development and life prediction.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Convergence of micro-geochemistry and micro-geomechanics towards understanding proppant shale rock interaction: A Caney shale case study in southern Oklahoma, USA

As a direct outcome of economic development coupled with an increase in population, global energy demand will continue to rise in the coming decades. Although renewable energy sources are increasingly investigated for optimal production, the immediate needs require focus on energy sources that are currently available and reliable, with a minimal environmental impact; the efficient exploration and production of unconventional hydrocarbon resources is bridging the energy needs and energy aspirations, during the current energy transition period. The main challenges are related to the accurate quantification of the critical rock properties that influence production, their heterogeneity and the multiscale driven physico-chemical nature of rock–fluid interactions. A key feature of shale reservoirs is their low permeability due to dominating nanoporosity of the clay-rich matrix. As a means of producing these reservoirs in a cost-effective manner, a prerequisite is creation of hydraulic fracture networks capable of the highest level of continued conductivity. Fracturing fluid chemical design, formation brine geochemical composition, and rock mineralogy all contribute to swelling-induced conductivity damage. The Caney Shale is an organic-rich, often calcareous mudrock. Many studies have examined the impact that clay has on different kinds of shale productivity but there is currently no data reported on the Caney Shale in relation to horizontal drilling; all reported data on the Caney Shale is on vertical wells which are shallow, compared to an emerging play that is at double the depth. Here, in this work we develop geochemical–geomechanical integration of rock properties at micro-and nanoscales that can provide insights into the potential proppant embedment and its mitigation. The novel methodology amalgamates the following: computed X-ray tomography, scanning electron microscopy, energy dispersive spectroscopy, micro-indentation, and Raman spectroscopy techniques. Here, our results show that due to the multiscale heterogeneity in the Caney Shale, these geochemical and structural properties translate into a variation in mechanical properties that will impact interaction between the proppant and the host shale rock.

03 NATURAL GAS↗
NASA NTRS1987

Design of a reconfigurable modular manipulator system

Using manipulators with a fixed configuration for specific tasks is appropriate when the task requirements are known beforehand. However, in less predictable situations, such as an outdoor construction site or aboard a space station, a manipulator system requires a wide range of capabilities, probably beyond the limitations of a single, fixed-configuration manipulator. To fulfill this need, researchers have been working on a Reconfigurable Modular Manipulator System (RMMS). Researchers have designed and are constructing a prototype RMMS. The prototype currently consists of two joint modules and four link modules. The joints utilize a conventional harmonic drive and torque motor actuator, with a small servo amplifier included in the assembly. A brushless resolver is used to sense the joint position and velocity. For coupling the modules together, a standard electrical connector and V-band clamps for mechanical connection are used, although more sophisticated designs are under way for future versions. The joint design yields an output torque to 50 ft-lbf at joint speeds up to 1 radian/second. The resolver and associated electronics have resolutions of 0.0001 radians, and absolute accuracies of plus or minus 0.001 radians. Manipulators configured from these prototype modules will have maximum reaches in the 0.5 to 2 meter range. The real-time RMMS controller consists of a Motorola 68020 single-board computer which will perform real time servo control and path planning of the manipulator. This single board computer communicates via shared memory with a SUN3 workstation, which serves as a software development system and robot programming environment. Researchers have designed a bus communication network to provide multiplexed communication between the joint modules and the computer controller. The bus supports identification of modules, sensing of joint states, and commands to the joint actuator. This network has sufficient bandwidth to allow servo sampling rates in excess of 500 Hz.

Schmitz, D.↗
DOE OSTI2025

Design Principles for Resonant Wave Energy Converters: Benchmarking Power Capture and Flow

Control co-design (CCD) in Wave Energy Converters (WECs) integrates the controller, power take-off (PTO), and buoy models during system design to optimize power output. Using the bi-conjugate impedance matching principle, this study models the PTO as a two-port network, revealing impedance matching conditions at the input and output ports as a function of the buoy, PTO, and controller. Here, this study examines the pairing of a flywheel-type pitch resonator PTO within a given buoy constrained by limited space and ballast capacity. The results show that physical constraints imposed by the buoy affect PTO performance. While controller tuning achieves optimal output impedance matching and flywheel inertia is maximized within the buoy's limitations, the PTO's input impedance remains smaller than the complex conjugate of the buoy's intrinsic impedance. This mismatch limits the PTO's ability to generate sufficient reaction torque, particularly outside the resonance frequency, resulting in narrow-band power transfer. The findings emphasize the need for PTO design modifications to improve input power transfer. Pendulum-based PTO mechanisms are proposed as alternatives to couple with multiple buoy motion modes and improve wave-to-wire efficiency while respecting system constraints.

Control Co-Design↗
DOE OSTI2025

Addendum to SAND2023-09604 Xyce lumped-element transmission line model verification to support Empire-Cable cable SGEMP analyses

This report supplements the Verification of Empire-Cable SAND report by expanding on the use of Xyce to simulate the coupling to a transmission line cable model. While Empire-Cable solves its governing equations on a high-order, finite-element mesh with an an implicit-in-time formulation, Xyce must use a first order graph for the circuit and explicit-in-time approach to be compatible with non-linear electrical device models. Thus, given the different solution methodologies in Xyce as compared to Empire-Cable, the convergence rates are expected to be different but the overall quality of the solution should be the same. The original four canonical problems studied in the Empire-Cable verification report are replicated here running in Xyce using transmission line modeling parameters from the verification report. Overall, agreement between the codes is excellent with Xyce’s convergence rates being limited mostly to first order due to the circuit network approximation of a transmission line being a first order approximation.

42 ENGINEERING↗
NASA NTRS1989

Low frequency electric and magnetic fields

Following preliminary investigations of the low frequency electric and magnetic fields that may exists in the Earth-ionospheric cavity, measurements were taken with state-of-the art spectrum analyzers. As a follow up to this activity, an investigation was initiated to determine sources and values for possible low frequency signal that would appear in the cavity. The lowest cavity resonance is estimated at about 8 Hz, but lower frequencies may be an important component of our electromagnetic environment. The potential field frequencies produced by the electron were investigated by a classical model that included possible cross coupling of the electric and gravitation fields. During this work, an interesting relationship was found that related the high frequency charge field with the extremely low frequency of the gravitation field. The results of numerical calculations were surprisingly accurate and this area of investigation is continuing. The work toward continued development of a standardized monitoring facility is continuing with the potential of installing the prototype at West Virginia State College early in 1990. This installation would be capable of real time monitoring of ELF signals in the Earth-ionoshpere cavity and would provide some directional information. A high gain, low noise, 1/f frequency corrected preamplifier was designed and tested for the ferrite core magnetic sensor. The potential application of a super conducting sensor for the ELF magnetic field detection is under investigation. It is hoped that a fully operational monitoring network could pinpoint the location of ELF signal sources and provide new information on where these signals originate and what causes them, assuming that they are natural in origin.

Spaniol, Craig↗