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A wave energy conversion (WEC) system includes a float body, a heave plate, a tether, and a controller. The tether couples the heave plate to the float body. The controller controls the tether between survivability modes. Each survivability mode adjusts a tension and/or length of the tether.
It is becoming apparent that insufficient mixing occurs in the pelagic ocean to maintain the large scale thermohaline circulation. Observed mixing rates fall a factor of ten short of classical indices such as Munk's "Abyssal Recipe." The growing suspicion is that most of the mixing in the sea occurs near topography. Exciting recent observations by Polzin et al., among others, fuel this speculation. If topographic mixing is indeed important, it must be acknowledged that its geographic distribution, both laterally and vertically, is presently unknown. The vertical distribution of mixing plays a critical role in the Stommel Arons model of the ocean interior circulation. In recent numerical studies, Samelson demonstrates the extreme sensitivity of flow in the abyssal ocean to the spatial distribution of mixing. We propose to study the topographic mixing problem through an integrated program of modeling and observation. We focus on tidally forced mixing as the global energetics of this process have received (and are receiving) considerable study. Also, the well defined frequency of the forcing and the unique geometry of tidal scattering serve to focus the experiment design. The Hawaiian Ridge is selected as a study site. Strong interaction between the barotropic tide and the Ridge is known to take place. The goals of the Hawaiian Ocean Mixing Experiment (HOME) are to quantify the rate of tidal energy loss to mixing at the Ridge and to identify the mechanisms by which energy is lost and mixing generated. We are challenged to develop a sufficiently comprehensive picture that results can be generalized from Hawaii to the global ocean. To achieve these goals, investigators from five institutions have designed HOME, a program of historic data analysis, modeling and field observation. The Analysis and Modeling efforts support the design of the field experiments. As the program progresses, a global model of the barotropic (depth independent) tide, and two models of the baroclinic (depth varying) tide, all validated with near-Ridge data, will be applied, to reveal the mechanisms of tidal energy conversion along the Ridge, and allow spatial and temporal integration of the rate of conversion. Field experiments include a survey to identify "hot spots" of enhanced mixing and barotropic to baroclinic conversion, a Nearfield study identifying the dominant mechanisms responsible for topographic mixing, and a Farfield program which quantifies the barotropic energy flux convergence at the Ridge and the flux divergence associated with low mode baroclinic waves radiation. The difference is a measure of the tidal power available for mixing at the Ridge. Field work is planned from years 2000 through 2002, with analysis and modeling efforts extending through early 2006. If successful, HOME will yield an understanding of the dominant topographic mixing processes applicable throughout the global ocean. It will advance understanding of two central problems in ocean science, the maintenance of the abyssal stratification, and the dissipation of the tides. HOME data will be used to improve the parameterization of dissipation in models which presently assimilate TOPEX-POSEIDON observations. The improved understanding of the dynamics and spatial distribution of mixing processes will benefit future long-term programs such as CLIVAR.
In this study, two commercially similar polycrystalline Ni-based disk superalloys (LSHR and ME3) were creep tested at 760C and 552MPa to approximately 0.3% plastic strain. LSHR consistently displayed superior creep properties at this stress/temperature regime even though the microstructural characteristics between the two alloys were comparable. High resolution structural and chemical analysis, however, revealed significant differences between the two alloys among active gamma prime shearing modes involving superlattice intrinsic and extrinsic stacking faults. In ME3, Co and Cr segregation and Ni and Al depletion were observed along the intrinsic faults - revealing a gamma prime -to- gamma phase transformation. Conversely in LSHR, an alloy with a higher W content, Co and W segregation was observed along the intrinsic faults. This observation combined with scanning transmission electron microscopy (STEM) simulations confirm a gamma prime-to-D019 phase transformation along the intrinsic faults in LSHR. Using experimental observations and density functional theory calculations, a novel local phase transformation strengthening mechanism is proposed that could be further utilized to improve the high temperature creep capabilities of Ni-base disk alloys.
Protonic ceramic electrochemical cells (PCECs) are promising solid-state energy conversion devices which enable the conversion of energy between electricity and hydrogen at intermediate temperatures. Rapid conversion between chemical and electrical energy via PCEC technology will assist in overcoming grand challenges in energy storage. To achieve highly efficient reversible operation between hydrogen production and electricity generation, boosting water-oxidation and oxygen reduction activities of the oxygen electrode while maintaining the durable operation is one of the early-stage technical opportunities. In this study, an A-site deficient layered perovskite (PrBa 0.8 Ca 0.2 ) 0.95 Co 2 O 6–δ has been developed as an oxygen electrode for a PCEC which presents superior electrochemical performances. The electrolysis current density reached as high as –0.72 A cm –2 at 1.3 V, and a peak power density of 0.540 W cm –2 was obtained at 600 °C in electrolysis and fuel cell mode, respectively. The PCEC with the new electrode shows good durability under practical operating conditions for 160 hours in both operating modes with no observable degradation. Here, the reversibility between the electrolysis and fuel cell mode is also successfully demonstrated.
Phonons are important carriers of energy and information in many cryogenic devices used for quantum information science and in fundamental physics experiments such as dark matter detectors. In these systems phonon behavior can be dominated by interfaces, hence there is increasing demand for a more detailed understanding of interfacial phonon transport in relevant material systems. Previous studies have focused on understanding thermal transport over the entire phonon spectrum at and above room temperature. At ultra-low temperatures, however, knowledge is missing regarding athermal phonon behavior due to the challenge in modeling the extreme conditions in micro-scale, heterogeneous cryogenic systems, as well as extracting single-phonon information from a large ensemble. In this work, we delineate interfacial phonon transport using a combination of classical molecular dynamics (MD) and phonon wave packet simulations, to illustrate the consistency and differences between the ensemble- and single-phonon dynamics. We consider three single-crystal Si surface reconstructions --- (1×1), (v3×v3) and (7×7) --- and model both experimentally observed Si(1×1)/Al interfaces and hypothesized Si(v3×v3)/Al and Si(7×7)/Al interfaces. The overall interfacial thermal conductance calculated from non-equilibrium MD shows that for the Si(1×1)/Al system, the presence of Al twin grain boundaries can hinder phonon transport and reduce thermal conductance by 2--12% relative to single-crystal Al; whereas the Si (v3×v3) and (7×7) reconstructions can enhance it by 6--19%. Normal mode decomposition reveals that both the increase and decrease in conductance are related to inelastic phonon scattering. Single-phonon wave packet simulations show results consistent with NEMD, while further suggesting that phonon polarization conversion is significant even when elastic transmission dominates, and that the interfacial structures have anisotropic impacts on atomic vibrations along different lattice directions. Our findings suggest alternative perspectives in achieving selective phonon transport through controlling interfacial structures of materials with atomically-precise fabrication techniques, and that the phonon wave packet formalism is a potentially powerful method for developing a detailed understanding of non-equilibrium phenomena in the low-temperature limit.
New nuclear power plants may be one of the technologies for future zero carbon electricity production. These future systems will however also need significant flexibility to cope with fluctuating demand and large share of intermittent renewable supply, rather than running in conventional baseload generation. The present work explores the use of thermal energy storage (TES) as a buffer between the reactor heat and its conversion to electricity, enabling flexible operation of nuclear plants. The focus is on maximizing flexibility, ideally as full decoupling of the nuclear and power cycle islands, as well as on system efficiency in various modes. A system design presented for a high temperature gas cooled reactor (HTGR) presents a slightly complex solution, as separate high- and low-temperature TES systems are required in order to cover the extended temperature range. Although this configuration imposes certain limitations on the discharge system configuration, it also presents the opportunity to design a more efficient system. For this case in particular, a steam reheat cycle is advantageous. Dynamic models were developed for the decoupled system in order to generate insights into aspects of off design operation and system control. A technoeconomic analysis, furthermore, provides sizing and costing of the component, followed by size and dispatch economic optimization considering energy arbitrage. This optimization shows that in all explored markets, the addition of TES system with the proposed configuration results in positive impact on project net present value. Further sensitivity analyses show impact of multiple inputs and possible technical limitations.
This work investigates the influence of sodium promotion on Ag/m-ZrO 2 catalysts for methanol steam reforming (MSR), focusing on activity, selectivity, surface chemistry, and mechanistic pathways. Temperature programmed reduction (TPR), XANES/EXAFS, CO 2 TPD, DRIFTS, and temperature programmed surface reaction methods were combined with fixed bed MSR testing to develop an integrated structure–function understanding of Na-modified Ag-ZrO 2 interfaces. Na addition systematically increases surface basicity, stabilizes strongly basic O 2− sites, and weakens the ν(CH) vibrational mode of surface formate, thereby facilitating C–H bond scission and accelerating decarboxylation to CO 2 . At moderate promoter levels (0.5–1.0 wt.% Na), the catalysts show significantly enhanced CO 2 selectivity and increased conversion relative to unpromoted Ag/m-ZrO 2 , while CH 4 formation remains negligible. Excessive Na (≥1.8 wt.%) leads to slower formate decomposition, greater carbonate stabilization, and suppressed conversion, revealing a narrow optimum around 1 wt.% Na. Short-term stability testing demonstrates steady conversion and product selectivity for both unpromoted and Na-promoted catalysts, with the latter maintaining markedly higher CO 2 selectivity. Although Pt/YSZ retains far superior intrinsic activity at ~10× higher space velocity, Ag offers a cost-advantaged alternative where lower cost metals are desirable. Collectively, these findings show that Na promotion enables tunable MSR selectivity on Ag/m-ZrO 2 by directing formate decomposition toward the CO 2 -forming pathway.
Rechargeable lithium battery (RLB) technology is transforming portable devices, vehicle electrification, and grid modernization. To make RLB durable, reliable and safe, conducting failure mode and effect analysis (FMEA) to identify failure mechanism under the operating conditions is very desirable. However, this ability is often overlooked or even lacking. The failure analysis (FA) is often conducted by laboratory testing and postmortem analysis, and the knowledge typically empirical. Here we present a quantitative approach for FMEA that can reveal how failure modes and effects reduce the capacity of a RLB. This approach is based on the state of the battery for FMEA, contrary to the conventional approach based on operating or testing conditions. The key aspect of this FMEA method is to convert the experimental results to a state-of-charge (SOC)-based analytic methodology. Such a conversion can separate the thermodynamic and kinetic attributes of capacity fade based on compositional correspondence in the electrode, so the loss and the decreased utilization of the active materials can be determined respectively.
Electron tomography is a powerful tool for characterization of three-dimensional (3D) nanoscale materials and devices. Bright-field (BF) and high-angle annular dark-field (HAADF) scanning transmission electron microscopy (STEM) are two widely used imaging modes in electron tomography. These imaging modalities have proven to be useful for characterizing the structure of carbon-supported platinum (Pt/C) electrocatalysts used in fuel cells, which are an important class of clean energy conversion systems. BF and HAADF-STEM images are typically simultaneously acquired due to the complementary information they contain, as BF-STEM is more suitable for characterizing carbon due to its ability to detect lighter elements, while HAADF-STEM is more suitable for characterizing platinum due to its sensitivity to atomic number. However, the quality of BF- and HAADF-STEM images is often compromised by various artifacts, such as local blurring due to abrupt contrast changes as well as missing wedge artifacts which can severely impact the accuracy of the reconstructed 3D images. The traditional methods of reconstruction, such as Filtered Back-projection (FBP), Simultaneous Iterative Reconstruction Technique (SIRT), and Model-Based Iterative Reconstruction (MBIR), are often not suitable for removing these artifacts effectively. Here, to address this challenge, we present a novel approach called MBIR with Artifact Reduction and Adaptive Regularization (MBIR-ARAR).
Near-field radiative heat transfer (NFRHT) between irregularly shaped dielectric particles made of SiO 2 and morphology characterized by Gaussian random spheres is studied. Particles are modeled using the discrete system Green's function (DSGF) approach, which is a volume integral numerical method based on fluctuational electrodynamics. This method is applicable to finite, three-dimensional objects, and all system interactions are defined independent of thermal excitation by a generalized system Green's function. The DSGF method is deemed suitable to model NFRHT between irregularly shaped particles after verification against the analytical solution for chains of two and three SiO 2 spheres. The NFRHT results reveal that geometric irregularity in particles leads to a reduction of the total conductance from that of comparable perfect spheres at vacuum separation distances smaller than the particle size, a regime in which NFRHT is a surface phenomenon. At vacuum separation distances larger than the particle size, NFRHT becomes a volumetric process, and the total conductance between irregularly shaped particles converges to that of comparable perfect spheres. Spectral analysis reveals, however, that particle irregularity leads to damping and broadening of resonances at all separation distances, thereby highlighting the importance of the DSGF method for spectral engineering in the near field. The reduced spectral coherence when particle size is larger than the vacuum separation distance is attributed to coupling of surface phonon-polaritons within the randomly generated, distorted particle features. For particle size smaller than the vacuum separation distance, resonance broadening and damping are linked with the multiple localized surface phonon modes supported by the composite spherical harmonic morphologies of the Gaussian random spheres. In conclusion, this paper has direct implications for thermal management of packed particle systems, with applications in radiative property control, electronics, energy conversion, and nanomanufacturing.
The data acquisition system monitors five types of transducers: (1) platinum and germanium resistance thermometers; (2) superconducting liquid level indicators for both cryogen tanks; (3) pressure transducers for both tanks; (4) strain gauges at critical structural locations; and (5) flowmeters for monitoring cryogen tank boiloff which are linear voltage output transducers. All the transducers produce a voltage proportional to the parameter they measure; this is routed to a single six and one-half digit voltmeter by way of an 80-channel multiplexer. The data acquisition program has six main functions: (1) definition and modification of the channels to be stimulated; (2) sensor stimulation and measurement; (3) raw data storage; (4) raw data conversion; (5) real-time formatting and output of raw or converted data; and (6) editing. The heart of the program is a driver section that represents approximately 20 percent of the code. The driver mode sequences and controls the six main functions.
Future space missions may use laser power beaming systems with a free electron laser (FEL) to transmit light to a photovoltaic array receiver. To investigate the efficiency of solar cells with pulsed laser light, several types of GaAs, Si, CuInSe2, and GaSb cells were tested with the simulated pulse format of the induction and radio frequency (RF) FEL. The induction pulse format was simulated with an 800-watt average power copper vapor laser and the RF format with a frequency-doubled mode-locked Nd:YAG laser. Averaged current vs bias voltage measurements for each cell were taken at various optical power levels and the efficiency measured at the maximum power point. Experimental results show that the conversion efficiency for the cells tested is highly dependent on cell minority carrier lifetime, the width and frequency of the pulses, load impedance, and the average incident power. Three main effects were found to decrease the efficiency of solar cells exposed to simulated FEL illumination: cell series resistance, LC 'ringing', and output inductance. Improvements in efficiency were achieved by modifying the frequency response of the cell to match the spectral energy content of the laser pulse with external passive components.
Since the beginnings of space travel, various microwave power amplifier designs have been employed. These included Class-A, -B, and -C bias arrangements. However, shared limitation of these topologies is the inherent high total consumption of input power associated with the generation of radio frequency (RF)/microwave power. The power amplifier has always been the largest drain for the limited available power on the spacecraft. Typically, the conversion efficiency of a microwave power amplifier is 10 to 20%. For a typical microwave power amplifier of 20 watts, input DC power of at least 100 watts is required. Such a large demand for input power suggests that a better method of RF/microwave power generation is required. The price paid for using a linear amplifier where high linearity is unnecessary includes higher initial and operating costs, lower DC-to-RF conversion efficiency, high power consumption, higher power dissipation and the accompanying need for higher capacity heat removal means, and an amplifier that is more prone to parasitic oscillation. The first use of a higher efficiency mode of power generation was described by Baxandall in 1959. This higher efficiency mode, Class-D, is achieved through distinct switching techniques to reduce the power losses associated with switching, conduction, and gate drive losses of a given transistor.
This device is a biasable, submillimeter-wave, balanced mixer fabricated using JPL s monolithic membrane process a simplified version of planar membrane technology. The primary target application is instrumentation used for analysis of atmospheric constituents, pressure, temperature, winds, and other physical and chemical properties of the atmospheres of planets and comets. Other applications include high-sensitivity gas detection and analysis. This innovation uses a balanced configuration of two diodes allowing the radio frequency (RF) signal and local oscillator (LO) inputs to be separated. This removes the need for external diplexers that are inherently narrowband, bulky, and require mechanical tuning to change frequency. Additionally, this mixer uses DC bias-ability to improve its performance and versatility. In order to solve problems relating to circuit size, the GaAs membrane process was created. As much of the circuitry as possible is fabricated on-chip, making the circuit monolithic. The remainder of the circuitry is precision-machined into a waveguide block that holds the GaAs circuit. The most critical alignments are performed using micron-scale semiconductor technology, enabling wide bandwidth and high operating frequencies. The balanced mixer gets superior performance with less than 2 mW of LO power. This can be provided by a simple two-stage multiplier chain following an amplifier at around 90 GHz. Further, the diodes are arranged so that they can be biased. Biasing pushes the diodes closer to their switching voltage, so that less LO power is required to switch the diodes on and off. In the photo, the diodes are at the right end of the circuit. The LO comes from the waveguide at the right into a reduced-height section containing the diodes. Because the diodes are in series to the LO signal, they are both turned on and off simultaneously once per LO cycle. Conversely, the RF signal is picked up from the RF waveguide by the probe at the left, and flows rightward to the diodes. Because the RF is in a quasi- TEM (suspended, microstrip-like) mode, it impinges on the diodes in an anti-parallel mode that does not couple to the waveguide mode. This isolates the LO and RF signals. This operation is similar to a cross-bar mixer used at low frequencies, except the RF signal enters through the back-short end of the waveguide rather than through the side. The RF probe also conveys the down-converted intermediate frequency (IF) signal out to an off-chip circuit board through a simple LC low-pass filter to the left as indicated. The bias is brought to the diodes through a bypass capacitor at the top.
The phenomenon of neutrino flavor conversion whereby the flavor of a neutrino particle can change between its time of production and later detection was the first definitive evidence of physics beyond the Standard Model. Some of the oscillation parameters used to describe this conversion are not yet well measured, leaving important questions still open regarding flavor conversion both in vacuum and as neutrinos travel through matter. NOvA is a long-baseline neutrino oscillation experiment that uses Fermilab's predominantly $\nu_\mu$ NuMI beam. A 14 kton oil-based liquid scintillator far detector 810 km away is used to measure neutrino oscillation through the $\nu_\mu$ disappearance and $\nu_e$ appearance channels. Super-K is a 50 kton water Cherenkov detector, which measures the disappearance of $\nu_e$ produced during solar fusion. The high density environment of the sun decreases the $\nu_e$ survival probability at higher energies observable in Super-K compared to the vacuum-dominated oscillations at lower energies. However, the transition region is overshadowed by radioactive background in the detector. In both of these experiments, the separation of neutrino detection events from background and classification of neutrino flavor are crucial tasks that benefit from the introduction of machine learning. Chapter 1 gives an overview of neutrinos and the context under which flavor conversion is measured in this dissertation. Chapters 2-7 present the results of a Bayesian sampling approach for the latest NOvA 3-flavor oscillation analysis with $26.6 \times 10^{20}$ protons on target in neutrino mode and $12.5 \times 10^{20}$ in antineutrino mode collected over 10 years. Chapters 8-13 present the results of extending the Super-K solar analysis to lower energies during its fourth phase with 2970 days of livetime.
The phenomenon of neutrino flavor conversion whereby the flavor of a neutrino particle can change between its time of production and later detection was the first definitive evidence of physics beyond the Standard Model. Some of the oscillation parameters used to describe this conversion are not yet well measured, leaving important questions still open regarding flavor conversion both in vacuum and as neutrinos travel through matter. NOvA is a long-baseline neutrino oscillation experiment that uses Fermilab's predominantly $\nu_\mu$ NuMI beam. A 14 kton oil-based liquid scintillator far detector 810 km away is used to measure neutrino oscillation through the $\nu_\mu$ disappearance and $\nu_e$ appearance channels. Super-K is a 50 kton water Cherenkov detector, which measures the disappearance of $\nu_e$ produced during solar fusion. The high density environment of the sun decreases the $\nu_e$ survival probability at higher energies observable in Super-K compared to the vacuum-dominated oscillations at lower energies. However, the transition region is overshadowed by radioactive background in the detector. In both of these experiments, the separation of neutrino detection events from background and classification of neutrino flavor are crucial tasks that benefit from the introduction of machine learning. Chapter 1 gives an overview of neutrinos and the context under which flavor conversion is measured in this dissertation. Chapters 2-7 present the results of a Bayesian sampling approach for the latest NOvA 3-flavor oscillation analysis with $26.6 \times 10^{20}$ protons on target in neutrino mode and $12.5 \times 10^{20}$ in antineutrino mode collected over 10 years. Chapters 8-13 present the results of extending the Super-K solar analysis to lower energies during its fourth phase with 2970 days of livetime.
The phenomenon of neutrino flavor conversion whereby the flavor of a neutrino particle can change between its time of production and later detection was the first definitive evidence of physics beyond the Standard Model. Some of the oscillation parameters used to describe this conversion are not yet well measured, leaving important questions still open regarding flavor conversion both in vacuum and as neutrinos travel through matter. NOvA is a long-baseline neutrino oscillation experiment that uses Fermilab's predominantly $\nu_\mu$ NuMI beam. A 14 kton oil-based liquid scintillator far detector 810 km away is used to measure neutrino oscillation through the $\nu_\mu$ disappearance and $\nu_e$ appearance channels. Super-K is a 50 kton water Cherenkov detector, which measures the disappearance of $\nu_e$ produced during solar fusion. The high density environment of the sun decreases the $\nu_e$ survival probability at higher energies observable in Super-K compared to the vacuum-dominated oscillations at lower energies. However, the transition region is overshadowed by radioactive background in the detector. In both of these experiments, the separation of neutrino detection events from background and classification of neutrino flavor are crucial tasks that benefit from the introduction of machine learning. Chapter 1 gives an overview of neutrinos and the context under which flavor conversion is measured in this dissertation. Chapters 2-7 present the results of a Bayesian sampling approach for the latest NOvA 3-flavor oscillation analysis with $26.6 \times 10^{20}$ protons on target in neutrino mode and $12.5 \times 10^{20}$ in antineutrino mode collected over 10 years. Chapters 8-13 present the results of extending the Super-K solar analysis to lower energies during its fourth phase with 2970 days of livetime.
Pyrolysis offers a relatively green and economical method to convert waste plastics into valuable chemicals and fuels without the need for harmful solvents, toxic chemicals, or costly high-pressure reactors. Despite its popularity among chemical upcycling technologies, industrial adoption suffers from feedstock heterogeneity, low-quality products, and catalyst deactivation. Most plastics in our daily lives are formulated with functional additives, fillers, and colorants. These additives remaining in end-of-life waste streams increase feedstock heterogeneity, creating a challenging issue in recycling plastics. Still, the potential impacts of additives on the chemical upcycling of plastics have been poorly understood. In this study, polyethylene compounded with a range of widely used additives (antioxidants, stabilizers, pigments, fillers, slip agents, and flame retardants) was subjected to both thermal pyrolysis and catalytic pyrolysis in different catalyst-to-feedstock contact modes. It showed that many inorganic additives, such as talc, kaolin, CaCO 3 , TiO 2 , carbon black, and zinc stearate, facilitated polymer decomposition during pyrolysis, increasing light hydrocarbons while also promoting aromatic and carbon residue formation. Conversely, antioxidants and stabilizers inhibited depolymerization, favoring heavier hydrocarbons. During catalytic pyrolysis with HZSM-5 zeolite, additives strongly enhanced aromatic and catalytic coke formation, especially when there was direct contact between plastics and catalysts. Although certain additives seem beneficial in the short term by promoting polymer cracking and improving the selectivity of aromatics, the transport of the additives and their degradation products and increased carbon coking can contaminate products, deactivate or modify catalysts, and foul reactors. These findings address a critical knowledge gap in effectively converting waste plastics via a greener route.