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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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The magnetizing inductance of the isolated Cuk converter introduces an undesirable pair of closely spaced complex xeros and poles, or a glitch, in the control-to-output transfer function.
Kinetic inductance detectors (KIDs) are a promising technology for low-noise, highly-multiplexible mm- and submm-wave detection. KIDs have a number of advantages over other detector technologies, which make them an appealing option in the cosmic microwave background B-mode anisotropy search, including passive frequency domain multiplexing and relatively simple fabrication, but have suffered from challenges associated with noise control. Here we describe design and fabrication of a 20-pixel prototype array of lumped element molybdenum KIDs. We show Q, frequency and temperature measurements from the array under dark conditions. We also present evidence for a double superconducting gap in molybdenum.
One of the key technologies associated with fission power systems (FPS) is the annular linear induction pump (ALIP). ALIPs are used to circulate liquid-metal fluid for transporting thermal energy from the nuclear reactor to the power conversion device. ALIPs designed and built to date for FPS project applications have not performed up to expectations. A unique, two-step approach was taken toward the multi-physics examination of an ALIP using ANSYS Maxwell 3D and Fluent. This multi-physics approach was developed so that engineers could investigate design variations that might improve pump performance. Of interest was to determine if simple geometric modifications could be made to the ALIP components with the goal of increasing the Lorentz forces acting on the liquid-metal fluid, which in turn would increase pumping capacity. The multi-physics model first calculates the Lorentz forces acting on the liquid metal fluid in the ALIP annulus. These forces are then used in a computational fluid dynamics simulation as (a) internal boundary conditions and (b) source functions in the momentum equations within the Navier-Stokes equations. The end result of the two-step analysis is a predicted pump pressure rise that can be compared with experimental data.
One of the key technologies associated with fission power systems (FPS) is the annular linear induction pump (ALIP). ALIPs are used to circulate liquid-metal fluid for transporting thermal energy from the nuclear reactor to the power conversion device. ALIPs designed and built to date for FPS project applications have not performed up to expectations. A unique, two-step approach was taken toward the multi-physics examination of an ALIP using ANSYS Maxwell 3D and Fluent. This multi-physics approach was developed so that engineers could investigate design variations that might improve pump performance. Of interest was to determine if simple geometric modifications could be made to the ALIP components with the goal of increasing the Lorentz forces acting on the liquid-metal fluid, which in turn would increase pumping capacity. The multi-physics model first calculates the Lorentz forces acting on the liquid metal fluid in the ALIP annulus. These forces are then used in a computational fluid dynamics simulation as (a) internal boundary conditions and (b) source functions in the momentum equations within the Navier-Stokes equations. The end result of the two-step analysis is a predicted pump pressure rise that can be compared with experimental data.
Wireless sensors placed in high temperature environments, such as aircraft engines, are desirable to reduce the mass and complexity of routing wires. While communication with the sensors is straight forward, providing power wirelessly is still a challenge. This paper introduces an inductive wireless power transfer circuit incorporating SiC Schottky diodes and its operation from room temperature (25 C) to 500 C.
We propose a “magneto-inductive” technology, employing a sensitive receiver based on a Superconducting Quantum Interference Device (SQUID), to enable communications through conductive media, so as to pave the way for exploration of ocean worlds, especially a Europa scenario. Concepts for ice penetration systems to access the presumed liquid ocean on Europa are under development but it was previously considered impractical if not impossible to communicate through the briny ice with conventional propagating electromagnetic signals.
We are investigating a novel superconducting detector and readout method that could lead to photon counting, energy resolving focal plane arrays. This concept is intrinsically different from STJ and TES detectors, and in principle could deliver large pixel counts, high sensitivity, and Fano-limited spectral resolution in the ptical/UV/X-ray bands. The readout uses the monotonic relation between the kinetic surface inductance L***subs***, of a superconductor and the density of quasiparticles n, which holds even at temperatures far below T***subc***. This allows a sensitive readout of the number of excess quasiparticles in the detector by monitoring the transmission phase of a resonant circuit. The most intriguing aspect of this concept is that passive frequency multiplexing could be used to read out ~ l0***super4*** detectors with a single HEMT amplifier. Single x-ray events have been observed in prototype detectors.
Thermoplastic composites have experienced renewed enthusiasm within the U.S. aerospace industry, due in part to opportunities for rapidly manufacturing large structures. Unlike the lengthy cure cycles required by thermosets, the thermoplastic matrix prepreg requires only heat and pressure to consolidate consecutive layers of material; with sufficient inter-ply contact time to develop a strong interface. The manufacturing requirements for thermoplastics provide manufacturing flexibility and of particular interest are in-situ consolidation processes; i.e consolidation during layup on a tool. In-situ consolidation removes the time-consuming and costly secondary processing step of autoclave or press consolidation. Process variables which contribute to laminate quality include temperature, heat transfer, inter-ply contact time, and consolidation pressure. Most of the work to date related to in-situ consolidation has been in conjunction with automated fiber placement (AFP), where prepreg tows are consolidated when placed on the tool. Considering this process for a braided structure adds complexity relative to AFP due to the rapid lay-down rate of the braider and simultaneous placement of a multiple prepreg tows. Processes considered for consolidation during AFP could not be applied to a braided part. Alternatively, a fully braided preform could be consolidated on the tool using well established thermoplastic welding techniques. The goal of this effort was to evaluate the effectiveness of induction welding to consolidate braided carbon fiber/thermoplastic composite tubes up to eight plies in thickness. The manufacturing process, thermal characterization, and initial mechanical property data of the consolidated tubes are reported.
Next generation gas turbine engine health monitoring for high performance jet engine-powered aircraft will incorporate integrated microelectronic sensors specifically designed to enhance aircraft functionality, engine efficiency, and safety. Temperature, air flow and pressure associated with the gas path as well as emissions from the engine correlate to the state of the combustor and other engine health conditions. Monitoring these parameters accurately requires positioning electronic sensors in the hot zone of the gas turbine engine, which exposes them to temperatures in excess of 400ºC. At these temperatures, signal amplification is needed at the transducer level to distinguish the desired measured signal from the significant electronic noise generated by the harsh environment. In this presentation, we report on the simulation, development, fabrication, and testing on a high temperature Class-A amplifier which utilizes a 4H-SiC Static Induction Transistor (SIT) as the active device and input/output matching and DC bias networks comprised of thin-film spiral inductors, metal-insulator-metal capacitors, and thick film chip resistors. A small signal model that emulates the operation of the 4H-SiC SIT from 25 to 400ºC, with an emphasis on operation at 400οC, was utilized. Measurements were performed from 25 to 400ºC to generate current-voltage curves, capacitive transistor characteristics and high frequency scattering parameters (S-parameters). The measured data was used to extrapolate the transconductance, gm, as a function of temperature for model development. Circuit simulation tools were used to generate S-parameters, which were compared to the measured values. At 400οC, a maximum difference between measured and simulated S-parameters for frequencies from 20 to 100 MHz were 3.84%, 0.68%, 10.61%, and 3.26% for S21, S12, S11, and S22, respectively. The average transit frequency, ft, was calculated from measured values to be 197.8 MHz, while the simulated value from the model was found to be 200 MHz. The Amplifier’s S-parameters were recorded at 20-100 MHz over a temperature range of 25-400ºC and show a gain of approximately 15.8 and 5.80 dBm at 25 and 400ºC, respectively. The input and output reflection coefficients at 50 MHz and 400ºC were -18.5 and -15.2 dB, respectively. The noise figure and phase noise were measured over the temperature range of 25-400ºC and recorded. The noise figure increased 21% at 50 MHz over the temperature range, while the 1 kHz offset of the phase noise remained below -110 dB. The stability factor, K, calculated with measured and simulated data demonstrates unconditional stability over the frequency range at 400ºC. Lastly, the 1-dB compression point was measured at 50 MHz and 400ºC with an approximated output of 9.5 dBm.
This paper presents an adaptive damping controller for wind power plants in which the turbines are equipped with doubly-fed induction generators. The controller is designed to respond to an input control signal that is triggered according to the system operating conditions. A processing unit continuously estimates the electromechanical modes of oscillation based on real-time streaming data acquired from a phasor measurement unit that is strategically positioned on the grid. The decision to trigger (or not trigger) the control signal is automatic, based on the relative damping of the dominant mode. The modes are estimated using the dynamic mode decomposition algorithm with time-delay embedding. Numerical simulations performed on the two-area system demonstrate that the proposed controller enhances the rotor angle stability for both small-signal and large disturbances, and is adaptive to changing grid conditions.
Abstract The straightforward synthesis of several Fluorinated Polycyclic Aromatic Hydrocarbons by the efficient, transition‐metal‐free, arene fluorine nucleophilic substitution reaction is described, and the full investigation of their liquid crystalline and optical properties reported. The key precursors for this study, i. e. 2,2’‐dilithio‐4,4′,5,5′‐tetraalkoxy‐1,1’‐biphenyl derivatives, were obtained in two steps from the highly selective Scholl oxidative homo‐coupling of 3,4‐dialkoxy‐1‐bromobenzene, followed by quantitative double‐lithiation. In situ room temperature nucleophilic annulation with either perfluorobenzene or perfluoronaphthalene leads to 1,2,3,4‐tetrafluoro‐6,7,10,11‐tetraalkxoytriphenylenes and 9,10,11,12,13,14‐hexafluoro‐2,3,6,7‐tetraalkoxybenzo[f]tetraphenes, respectively, in good yields. Exploiting the same strategy, subsequent double annulations resulted in the formation of 9,18‐difluoro‐2,3,6,7,11,12,15,16‐octa(alkoxy)tribenzo[f,k,m]tetraphenes and 9,10,19,20‐tetrafluoro‐2,3,6,7,12,13,16,17‐octakis(hexyloxy)tetrabenzo[a,c,j,l]tetracenes, respectively. Despite the presence of only four alkoxy chains, the polar “Janus” mesogens display a columnar hexagonal mesophase over broad temperature ranges, with higher mesophase stability than the archetypical 2,3,6,7,10,11‐hexa(alkoxy)triphenylenes and their hydrogenated counterparts. The improvement or induction of mesomorphism is attributed to efficient antiparallel face‐to‐face π‐stacking driven by the establishment of non‐covalent perfluoroarene‐arene intermolecular interactions. The larger lipophilic discotic π‐extended compounds also exhibit columnar mesomorphism, over similar temperature ranges and stability than their hydrogenated homologs. Finally, these fluorinated molecules form stringy gels in various solvents, and show interesting solvatochromic emission properties in solution as well as strong emission in thin films and gels.
A major barrier to integrating pyrolysis-derived oil into conventional refinery technology is the presence of impurities, particularly halogens and metals, that can deactivate catalysts. This study presents a novel, cost-effective approach for the simultaneous analysis of a subset of halogens, metals, nonmetals, and metalloids in complex, industrially relevant distilled pyrolysis oil samples, this was previously achievable only through multiple techniques. Excellent results were obtained using a widely accessible inductively coupled plasma mass spectrometry (ICP-MS) method with helium gas mode and standard laboratory consumables, enabling high-throughput analysis and efficient evaluation of adsorbent performance. Sample preparation is straightforward, requiring only dilution in a compatible matrix, and provides accurate and precise quantification, with 75%–137% spike recovery for Be, Ti, V, Cr, Fe, Ni, Co, Cu, As, Se, Mo, Cd, Sb, Tl, and Pb, and 62%–65% spike recovery for Cl and 109%–133% spike recovery for Br. Additionally, an enhanced version of the method using ICP-MS/MS and hydrogen gas is described, which has higher accuracy with 69%–112% spike recovery for Be, B, Ti, V, Fe, Co, Ni, Cu, As, Se, Mo, Cd, Sb, Tl, and Pb, with 85%–102% spike recovery for Cl and 63%–93% spike recovery for Br. Helium mode detection limits for industrially relevant elements (V, Fe, Ni, Cu, As, and Pb) are less than 1.7 µg/kg, and less than 0.2 mg/kg for Br and Cl. Furthermore, this methodology facilitates rapid systematic evaluation of adsorption capacities of materials under time-on-stream conditions and supports robust comparisons across diverse operating environments.
Rationale Signal detection for uranium–lead (U–Pb) dating of zircon is typically performed via ion counters. Here, we develop a preliminary understanding of the strengths and limitations of faraday‐cup‐based detection. Methods A suite of zircon reference materials and the NIST‐610 glass were sampled using laser ablation followed by U–Pb isotope ratio measurement on a Neoma multicollector‐inductively coupled plasma‐mass spectrometer. Results We were able to produce geologically accurate 207 Pb/ 206 Pb, 206 Pb/ 238 U, and 207 Pb/ 235 U ratios for the NIST‐610 glass and the zircon standards, with ages ranging from ~2.5 Ga to ~337 Ma (TanBrown A, Oracle, 91550, Mud Tank, Temora, and Plešovice). Two of the younger zircon standards examined (94‐35, ~55.6 Ma, and Fish Canyon, 28.6 Ma) yielded accurate 206 Pb/ 238 U but not 207 Pb/ 235 U or 207 Pb/ 206 Pb ratios, whereas the youngest zircon standard (Penglai, ~4.4 Ma) failed for all three ratios of interest. The accuracy and precision of the all‐faraday method are directly tied to signal intensity, with reliable data capable of being produced even when both isotopes in a ratio have signals below ~0.001 V (equivalent to ~62 500 cps on an ion counter). Conclusion The all‐faraday cup multicollection method provides sufficient sensitivity to obtain geologically meaningful U–Pb data, with possible advantages being that laser pit depth‐dependent changes in the observed interelemental fractionation behavior may be easier to correct using a static collector configuration compared to when the ion beam is swept across a single detector while also removing the need for an interdetector‐type calibration. Further work is needed to refine the all‐faraday cup method (e.g., application of background subtraction and common Pb corrections, outlier removal, and interelement as well as down‐hole fractionation corrections), but our initial results demonstrate that the faraday detector method has sufficient sensitivity to warrant further study.
Public transit agencies are focused on making their fixed-line bus systems more energy efficient by introducing electric (EV) and hybrid (HV) vehicles to their fleets. However, because of the high upfront cost of these vehicles, most agencies are tasked with managing a mixed-fleet of internal combustion vehicles (ICEVs), EVs, and HVs. In managing mixed-fleets, agencies require accurate predictions of energy use for optimizing the assignment of vehicles to transit routes, scheduling charging, and ensuring that emission standards are met. The current state-of-the-art is to develop separate neural network models to predict energy consumption for each vehicle class. Although different vehicle classes’ energy consumption depends on a varied set of covariates, we hypothesize that there are broader generalizable patterns that govern energy consumption and emissions. In this paper, we seek to extract these patterns to aid learning to address two problems faced by transit agencies. First, in the case of a transit agency which operates many ICEVs, HVs, and EVs, we use multi-task learning (MTL) to improve accuracy of forecasting energy consumption. Second, in the case where there is a significant variation in vehicles in each category, we use inductive transfer learning (ITL) to improve predictive accuracy for vehicle class models with insufficient data. As this work is to be deployed by our partner agency, we also provide an online pipeline for joining the various sensor streams for fixed-line transit energy prediction. Here, we find that our approach outperforms vehicle-specific baselines in both the MTL and ITL settings.
The trace impurities of a uranium ore concentrate (UOC) can be examined to determine mine source, methods of production, and quality. This study presents a method to determine the concentration of halides and main group elements, specifically P, S, Br and I, utilizing triple quadrupole inductively coupled plasma–mass spectrometry. These analytes were measured in a uranium matrix to simulate a UOC sample. The concentrations determined with this method showed agreement with known values. Solutions with and without uranium were compared. A UOC certified reference material, CUP-2, was analyzed to further demonstrate the effectiveness of the method.
The thermal decomposition approach was used for the synthesis of MFe2O4 magnetic nanoparticles (MNPs) by substituting M as Co, Mn, and Zn. The obtained MNPs were characterized for magneto-structural properties using X-Ray diffraction patterns, FTIR, Raman and Mossbauer spectroscopy techniques which confirm the formation of phase pure cubic spinel ferrite with space group Fd3m and five Raman active modes. The size, morphology, and compositional analysis was performed using HRTEM and EDX where the size of MNPs was found to be less than 10 nm that attains superparamagnetism. The magnetic hyperthermia performance of obtained MNPs was evaluated by induction heating experiments at magnetic field range 13.3 to 26.7 kAm-1. The specific absorption rate (SAR) and intrinsic loss power (ILP) values were determined at different magnetic fields within the human tolerable range and correlated with magneto-structural properties to evaluate its potential for possible magnetic particle hyperthermia therapy.
Here, calcium fluoride formed by the reaction between ammonium bifluoride and calcium chloride was investigated as a dominating matrix for quantitative analysis by laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS). Transformation from a solid sample to the calcium fluoride-based matrix permitted quantitative analysis based on calibration standards made from elemental standards. A low abundance stable calcium isotope, i.e. 44 Ca + , was monitored as the internal standard for quantitative analysis by LA-ICP-MS. Correlation coefficient factors for multiple elements were obtained with values over 0.999. The results for multiple elements in a certified reference material of soil (NIST SRM 2710a) agreed with the certified values in the range of expanded uncertainty, indicating the present method was valid for quantitation of elements in solid samples.
We present machine learning methods to predict hydrologic features such as streamflow and soil moisture from spatially and temporally varying hydrological and meteorological data. Here, we used a temporal reduction technique to reduce computation and memory requirements and trained a Long Short-Term Memory (LSTM) network to predict soil moisture and streamflow over multiple watersheds. We show LSTM networks can be trained in a fraction of the time required by complex process-based and attention-based models such as Soil and Water Assessment Tool (SWAT) and GeoMAN without sacrificing accuracy. We also demonstrate that outside data - sourced from a watershed other than the target - can be used to train LSTM to comparable or even superior prediction accuracy. The success of LSTM in such spatially-inductive settings shows hydrologic features can be predicted with minimal prior knowledge of the watershed in question. Finally, we make all methodologies of this work publicly available as an end-to-end software pipeline that facilitates rapid prototyping of hydrologic learners.