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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 271 records · Page 15

All sources NASA NTRS DOE OSTI

DOE OSTI2020

A Priority-Based Control Strategy and Performance Bound for Aggregated HVAC-Based Load Shaping

Air conditioning systems have been recognized as a potential, cost-effective resource for shaping electrical load in a power system. This work presents a new priority-based control strategy that explicitly addresses three requirements for using a collection of air conditioning units in this capacity. These are 1) tracking a regulation signal, 2) maintaining the building temperature near its set point, and 3) satisfying a cycling constraint of the air conditioners. After introducing the control strategy, we derive a bound for the regulation signal within which tracking is guaranteed while also satisfying the temperature requirement. These results are illustrated with simulations.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2020

OsWRKY21 and OsWRKY108 function redundantly to promote phosphate accumulation through maintaining the constitutive expression of OsPHT1;1 under phosphate‐replete conditions

Summary Plant Phosphate Transporter 1 (PHT1) proteins, probably the only influx transporters for phosphate (Pi) uptake, are partially degraded on sufficient Pi levels to prevent excessive Pi accumulation. Therefore, the basal/constitutive expression level of PHT1 genes is vital for maintaining Pi uptake under Pi‐replete conditions. Rice ( Oryza sativa ) OsPHT1;1 is a unique gene as it is highly expressed and not responsive to Pi, however the mechanism for maintaining its basal/constitutive expression remains unknown. Using biochemical and genetic approaches, we identified and functionally characterised the transcription factors maintaining the basal/constitutive expression of OsPHT1;1 . OsWRKY21 and OsWRKY108 interact within the nucleus and both bind to the W‐box in the OsPHT1;1 promoter. Overexpression of OsWRKY21 or OsWRKY108 led to increased Pi accumulation, resulting from elevated expression of OsPHT1;1 . By contrast, oswrky21 oswrky108 double mutants showed decreased Pi accumulation and OsPHT1;1 expression in a Pi‐dependent manner. Moreover, similar to ospht1;1 mutants, plants expressing the OsWRKY21–SRDX fusion protein (a chimeric dominant suppressor) were impaired in Pi accumulation in Pi‐replete roots, accompanied by downregulation of OsPHT1;1 expression. Our findings demonstrated that rice WRKY transcription factors function redundantly to promote Pi uptake by activating OsPHT1;1 expression under Pi‐replete conditions, and represent a novel pathway independent of the central Pi signalling system.

Zhang, Jun↗

DOE OSTI2020

Controlled removal of hydrogen atoms from H-terminated silicon surfaces

The controlled formation of dangling bond structures on a H-terminated silicon surface is the first step in an atomically precise method of fabrication of silicon quantum electronic devices. An ultrahigh vacuum scanning tunneling microscope (STM) tip is used to selectively desorb hydrogen atoms from a Si(100)-2x1:H surface by injecting electrons with the sample held at a positive bias voltage. The authors propose a lithography method that allows the STM to operate under negative bias imaging conditions and simultaneously desorb H atoms as required. A high frequency signal is added to the negative bias voltage to deliver the required energy for hydrogen removal. The resulting current at this frequency and its harmonics are filtered to minimize their effect on the operation of the STM’s feedback control loop. The authors show that the chance of tip-sample crash during the lithography process is reduced by employing this method. They also demonstrate that this approach offers a significant potential for controlled and precise removal of H atoms from a H-terminated silicon surface and thus may be used for the fabrication of practical silicon-based atomic-scale devices.

42 ENGINEERING↗

DOE OSTI2021

Machine Learning of Bacterial Transcriptomes Reveals Responses Underlying Differential Antibiotic Susceptibility

In vitro antibiotic susceptibility testing often fails to accurately predict in vivo drug efficacies, in part due to differences in the molecular composition between standardized bacteriologic media and physiological environments within the body. Here, we investigate the interrelationship between antibiotic susceptibility and medium composition in Escherichia coli K-12 MG1655 as contextualized through machine learning of transcriptomics data. Application of independent component analysis, a signal separation algorithm, shows that complex phenotypic changes induced by environmental conditions or antibiotic treatment are directly traced to the action of a few key transcriptional regulators, including RpoS, Fur, and Fnr. Integrating machine learning results with biochemical knowledge of transcription factor activation reveals medium-dependent shifts in respiration and iron availability that drive differential antibiotic susceptibility. By extension, the data generation and data analytics workflow used here can interrogate the regulatory state of a pathogen under any measured condition and can be applied to any strain or organism for which sufficient transcriptomics data are available.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

Mitogen-activated protein kinase 6 negatively regulates secondary wall biosynthesis by modulating MYB46 protein stability in Arabidopsis thaliana

The R2R3-MYB transcription factor MYB46 functions as a master switch for secondary cell wall biosynthesis, ensuring the exquisite expression of the secondary wall biosynthetic genes in the tissues where secondary walls are critical for growth and development. At the same time, suppression of its function is needed when/where formation of secondary walls is not desirable. Little is known about how this opposing control of secondary cell wall formation is achieved. We used both transient and transgenic expression of MYB46 and mitogen-activated protein kinase 6 (MPK6) to investigate the molecular mechanism of the post-translational regulation of MYB46. We show that MYB46 is phosphorylated by MPK6, leading to site specific phosphorylation-dependent degradation of MYB46 by the ubiquitin-mediated proteasome pathway. In addition, the MPK6-mediated MYB46 phosphorylation was found to regulate in planta secondary wall forming function of MYB46. Furthermore, we provide experimental evidences that MYB83, a paralog of MYB46, is not regulated by MPK6. The coupling of MPK signaling to MYB46 function provides insights into the tissue- and/or condition-specific activity of MYB46 for secondary wall biosynthesis.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

Clean Grid Vision: A U.S. Perspective - Chapter 5. Global Power Market Trends

The evolution of the electricity sector toward competitive modern markets is occurring over a long period and responding to rapid changes in technologies, business models, and other market factors. No reformed power market anywhere in the world looks the same today as it did a decade ago. Technology has enabled some of the evolution, but perhaps it is more important that people and institutions learn from experience how to make markets better over time. Governments still have an important role—not as the authority controlling prices, but as the authority safeguarding the integrity of the economic processes that create prices in response to supply and demand and ensure reliability and other objectives are met. More VRE resources will change market conditions, but they will not change market fundamentals. Prices provide important signals for new investments and how the grid operates—including new technologies and processes discussed elsewhere in this report. If poor market design or the exercise of market power by a large entity distort these signals, outcomes will cease to be efficient and the public will bear the additional cost. Fundamentally, prices reflect supply, demand, and the cost of technological options.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2024

CLimate Impact: Determining Etiology thRough pAthways (CLDERA)

Climate impacts have broad economic, health, political, and national security ramifications. Societally relevant impacts are typically farther downstream, are the product of multiple interacting processes, and can arise over small regions and timeframes because their sources are short-term and localized. Short-term forcings (as can be seen in volcanic eruptions, climatic tipping points (e.g., the collapse of rainforests or the disappearance of sea ice), or in increasingly plausible climate interventions) fundamentally possess low signal-to-noise and could benefit from accounting for the multiple conditional processes through which a downstream impact arises. Under the Grand Challenge LDRD CLDERA (CLimate impacts: Discovering Etiology thRough pAthways), we have developed tools to enable downstream impact attribution from geographically and temporally localized source forcings in the climate. CLDERA developed methods that can distinguish how a localized source drives the climate system to respond with particular impacts. The how is embodied in pathways – the spatio-temporally evolving chain of physical processes that connects a source to a series of increasingly distant impacts. Novel analytic methods in pursuit of downstream impact attribution were developed and demonstrated on simulations and observations of the 1991 eruption of Mt. Pinatubo in the Philippines. As described within this report we have • developed stratospheric expertise and aerosol modeling capabilities in E3SM, • created original methods to detect and model pathways from source-to-impact, and • advanced climate attribution through novel methods, cases, and approaches. Further, CLDERA developed a tiered verification process consisting of controlled datasets to prototype, verify, and refine the original method development. CLDERA increased Sandia’s footprint in the climate analytics community and developed new climate collaborations whilst also creating a cadre of climate analysts at Sandia. The products from CLDERA have been extensive with a total of 9 journal articles published, 12 articles submitted and under review, and an additional 8 articles in preparation. We have produced 1750 simulated years and developed 9 code-bases. This report details these accomplishments and serves as a summary of the work completed during the CLDERA Grand Challenge.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Methods and devices configured to operated scanning tunneling microscopes using out-of-bandwidth frequency components added to bias voltage and related software

In the system and method disclosed, an ultrahigh vacuum (UHV) scanning tunneling microscope (STM) tip is used to selectively desorb hydrogen atoms from the Si(100)-2X1:H surface by injecting electrons at a negative sample bias voltage. A new lithography method is disclosed that allows the STM to operate under imaging conditions and simultaneously desorb H atoms as required. A high frequency signal is added to the negative sample bias voltage to deliver the required energy for hydrogen removal. The resulted current at this frequency and its harmonics are filtered to minimize their effect on the operation of the STM's feedback loop. This approach offers a significant potential for controlled and precise removal of hydrogen atoms from a hydrogen-terminated silicon surface and thus may be used for the fabrication of practical silicon-based atomic-scale devices.

Moheimani, Seyed Omid Reza↗

DOE OSTI2023

Health monitoring device

Example aspects of a volatile organic compound detection device, a wearable health monitoring device, and a method of monitoring a user's health are disclosed. The volatile organic compound detection device can comprise a collector comprising a collector material configured to collect volatile organic compounds given off from a user's skin; a separator comprising a gas chromatography column configured to separate mixtures of the volatile organic compounds into their constituent chemicals; and an identifier comprising a detector and a processor, the detector configured to transduce the constituent chemicals into a signal, the processor configured to process the signal to identify specific volatile organic compounds indicative of a health condition.

42 ENGINEERING↗

DOE OSTI2023

Methods and devices configured to operated scanning tunneling microscopes using out-of-bandwidth frequency components added to bias voltage and related software

Moheimani, Seyed Omid Reza↗

DOE OSTI2022

Power Electronics Based Self-Monitoring and Diagnosing for Photovoltaic Systems

Faults in photovoltaic (PV) systems can seriously affect the efficiency, energy yield, cost, safety, and reliability of PV plants. Condition monitoring of PV plants is, therefore, a very important approach to estimating the health condition of PV modules and power electronics in the system. However, additional hardware for PV system monitoring adds cost to the system's operation; delayed maintenance service also causes additional energy production loss. The Center for Power Electronics Systems (CPES) at the Virginia Polytechnic Institute and State University and Siemens Cooperate Research developed the online impedance measurement for a PV panel self-monitoring and diagnosing technology using the DC-DC converter connected to the panel. Small-signal impedances of a monocrystalline silicon PV panel were modeled and simulated to reflect fault conditions such as the short-circuit, hot-spot, and junction box faults. Modeling and simulation results were validated firstly using a test setup consisting of a solar simulator, a network analyzer, small-signal injectors, and a monocrystalline PV panel rated at 300 W.

14 SOLAR ENERGY↗

DOE OSTI2020

Mechanistic aspects of plasma-enhanced catalytic methane decomposition by time-resolved operando diffuse reflectance infrared Fourier transform spectroscopy

To study mechanistic aspects of plasma-enhanced catalysis, methane is decomposed by a supported Ni catalyst assisted by an Ar/O 2 atmospheric pressure plasma jet (APPJ). Here, the time-resolved surface response of the Ni catalyst is investigated by operando diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) using various experimental settings. Catalyst temperatures of room temperature (RT) and 500 °C and nozzle-catalyst surface distances of 3, 5 and 8 mm were examined, and the amount of O 2 of the Ar/O 2 gas mixture flowing through the APPJ was either 0 or 0.5%. A synergistic effect of surface bonded C-O was observed during the exposure of the Ni catalyst to the APPJ for low oxygen operating conditions (pure Ar jet). Surface bonded C-O formed only when there was plasma present and the C-O signal was enhanced for higher catalyst temperature. When the supported Ni catalyst was subjected to the plasma-generated particle fluxes using highly oxidizing conditions, the presence of surface bonded C-O was suppressed. The plasma-catalytic CO and CO 2 production in the gas phase measured downstream mirrored the surface behavior of C-O bonds when the plasma source operating condition was changed from a low oxygen portion to a high oxygen portion at high catalyst temperature (500 °C). CH n (n =1, 2, ) species on the catalyst surface were also studied by DRIFTS, and CHn destruction was found to correlate with C-O formation. In particular, the time-resolved CH n response showed a possible conversion process of CH n to C-O when the Ni catalyst was exposed to the plasma source. This finding may indicate a plasma-mediated regeneration of the catalyst by plasma-catalyst surface interactions.

42 ENGINEERING↗

DOE OSTI2025

Enhancing Unknown Waveform Detection by Learning Intra and Inter-domain Dependencies with Advanced Attention Fusion Mechanisms

Detection of unknown waveforms in mission-critical communications is a crucial area of interest for the Department of Energy (DoE). Traditional methods and recent deep learning-based approaches often assume that the training set includes all possible classes, which is impractical for detecting new waveforms. This limitation gives rise to the problem of open-set recognition (OSR), which involves correctly identifying known classes while detecting and rejecting unknown or unseen classes. To address this limitation, we propose a novel dual-domain complex-valued neural architecture that jointly processes time-domain and frequency-domain signal representations using transformer mechanisms. A transformer model is a deep learning architecture that uses self-attention mechanisms to process and learn relationships in sequential data. Our model employs a cosine similarity loss to extract domain-specific features and incorporates a transformer architecture in the latent space to weigh the importance of different features from the time and frequency domains. The transformer layer includes stacked self-attention and cross-attention modules to learn intra-domain and inter-domain dependencies, creating a more holistic signal representation. An attention-based fusion module intelligently combines the time and frequency-domain features using multi-head attention, enabling the network to learn the optimal feature for each domain in each input signal. Quantitative results demonstrate the impact of these architectural choices on overall performance, showing significant improvement after incorporating self and cross-attention modules and using complex attention fusion over simple weighted fusion. Our ongoing work will focus on addressing the limitations of threshold-based OSR methods by developing a novel generative framework that integrates a conditional diffusion probabilistic model (DPM). DPM is a generative framework that learns to synthesize complex data by reversing a gradual noising process using a neural network trained to denoise step-by-step. Our goal is to leverage the inherent strengths of DPMs for identifying unknown signals more robustly. One primary advantage of using a DPM is its ability to provide a more reliable anomaly score based on the model's reconstruction error, rather than relying solely on classifier confidence. Additionally, the iterative denoising process of DPMs makes this approach naturally resilient to low Signal-to-Noise Ratio (SNR) conditions, where traditional methods often fail. By implementing this generative framework, we aim to enhance the model's capability to accurately detect unknown waveforms and maintain performance in challenging environments.

99 - GENERAL AND MISCELLANEOUS↗

DOE OSTI2024

Efficient excitation and control of integrated photonic circuits with virtual critical coupling

Critical coupling in integrated photonic devices enables the efficient transfer of energy from a waveguide to a resonator, a key operation for many applications. This condition is achieved when the resonator loss rate is equal to the coupling rate to the bus waveguide. Carefully matching these quantities is challenging in practice, due to variations in the resonator properties resulting from fabrication and external conditions. Here, we demonstrate that efficient energy transfer to a non-critically coupled resonator can be achieved by tailoring the excitation signal in time. We rely on excitations oscillating at complex frequencies to load an otherwise overcoupled resonator, demonstrating that a virtual critical coupling condition is achieved if the imaginary part of the complex frequency equals the mismatch between loss and coupling rate. We probe a microring resonator with tailored pulses and observe a minimum intensity transmission T = 0.11 in contrast to a continuous-wave transmission T = 0.58, corresponding to 8 times enhancement of intracavity intensity. Our technique opens opportunities for enhancing and controlling on-demand light-matter interactions for linear and nonlinear photonic platforms.

42 ENGINEERING↗

DOE OSTI2025

Filtered Multi-Tone Spread Spectrum With Overlapping Subbands

A new form of the filter bank multi-carrier spread spectrum (FBMC-SS) waveform is presented. This new waveform modifies the filtered multi-tone spread spectrum (FMT-SS) system, and is intended to whiten the power spectral density (PSD) of the transmit signal. In the conventional FMT-SS, subcarrier bands are non-overlapping, leaving a spectral null between the adjacent subcarrier bands. To make FMT-SS more appealing for a broader set of applications than those studied in the past, we propose adding additional subcarriers centered at these nulls and thoroughly explore the impact of the added subcarriers on the system performance. This modified form of FMT-SS is referred to as overlapped FMT-SS (OFMT-SS). We explore the conditions required for maximally flattening the PSD of the synthesized OFMT-SS signal and for cancelling the interference caused by overlapping subbands. We also explore the choices of spreading gains that result in a low peak-to-average power ratio (PAPR) for a number of different scenarios. Further reduction of the PAPR of the synthesized signal through clipping methods is also explored. Additionally, we propose methods of multi-coding for increasing the data rate of the OFMT-SS waveform, while minimally impacting its PAPR.

42 - ENGINEERING↗

DOE OSTI2020

Direct Phase-Angle Detection for Three-Phase Inverters in Asymmetrical Power Grids

This paper introduces a signal reformation based direct phase-angle detection (DPD-SR) technique for three-phase inverters supporting asymmetrical grids. Asymmetries in three-phase systems may happen because of unbalanced three-phase loads, which can lead to the voltage asymmetry at the terminals of grid-tied inverters. The proposed DPD-SR technique can detect the voltage phase-angle under asymmetrical conditions. The DPD-SR technique also offers precise and rapid phase-angle detection via signal reformation and trigonometric functions. In essence, the phase-angle detection is directly derived from the trigonometric properties of the line-line voltages, while signal reformation is implemented to handle asymmetrical voltages. The proposed method measures two line-line voltages and detects the phase-angle of a three-phase system under both symmetrical and asymmetrical conditions. Unlike classical phase-locked loop (PLL) techniques, DPD-SR does not need any closed-loop PI controller, which significantly reduces the complexity and the delay in detecting the phase-angle. In this paper, the efficacy of the proposed technique is examined in comparison with the state-of-the-art PLLs under asymmetrical conditions via a set of laboratory experiments. Here, the performance of the phase-angle detection is also tested as part of an inverter feeding an asymmetrical grid.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2022

Bearing Fault Detection on Wind Turbine Gearbox Vibrations Using Generalized Likelihood Ratio-Based Indicators: Preprint

Studies in condition monitoring literature often aim to detect rolling element bearing faults because they have one of the biggest shares among defects in turbo machinery. Accordingly, several prognosis and diagnosis methods have been devised to identify fault signatures from vibration signals. The underlying idea behind traditional indicators often revolves around tracking both cyclostationarity and abnormal impulses in the vibration signals without distinguishing the two. A recently proposed method to capture the rolling element bearing degradation lays out the groundwork for new indicator families utilizing generalized likelihood ratio test. This novel approach exploits the cyclostationarity and the impulsiveness of vibration signals independently in order to estimate the most suitable indicators for a given fault. However, the method has yet to be tested on complex experimental vibration signals such as those of a wind turbine gearbox. In this study, the approach is applied to the NREL Wind Turbine Gearbox Condition Monitoring Round Robin Study data set for bearing fault detection purposes. The data set is measured on an experimental test rig of a wind turbine gearbox, hence the complexity of the vibration signals is similar to a real case. Furthermore, the new indicators are also tested with signals that carry multiple fault signatures. The outcome demonstrates that the proposed method is capable of distinguishing between healthy and damaged vibration signals measured on a complex wind turbine gearbox.

condition monitoring↗

DOE OSTI2024

Solid State Power Substation DC Node Optimization and Controller Hardware-In-The-Loop Demonstration

A solid state power substation (SSPS) node is a microgrid that integrates distributed energy resources and loads and injects/absorbs power to/from the SSPS distribution network. It is an essential building block of a futuristic distribution grid network. This paper presents the development and demonstration of optimization use cases of a SSPS DC node. By adopting multi-layer hierarchical control architecture and developing automatic device identification and dynamic optimization formulation algorithms, the SSPS DC node can perform plug-and-play resource integration and seamless transition of the optimized node operation under on and off grid condition without sophisticated algorithms, control mode changes, and user interactions. Four optimization use cases including economic dispatches with price signal changes, a sudden PV power drop, and a single directional meter and its associated costs with sending power back to the grid, and resiliency under a grid inverter trip condition were demonstrated through the real-time controller hardware-in-the-loop simulation.

Kim, Namwon↗