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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 199 records · Page 11

Design and Characterization of a Lens-Coupled System for Dynamic X-Ray Diffraction

X-ray diffraction (XRD) is a necessary technique for understanding states of materials under static and dynamic loading conditions. The higher-pressure Equation of State (EOS) of many materials can only be explored via shock or ramp compression at temperatures and pressures of interest. While static XRD work has yielded EOS measurements in the 100 - 200 GPa regime, dynamic X-ray diffraction (DXRD) can explore EOS phases in the TPa regime, which closely resembles inner-core planetary conditions. DXRD hinges on the ability to measure the exact phase or phase change of a material while under dynamic loading conditions. Macroscopic diagnostic systems (e.g. velocimetry and pyrometry) can infer a phase change but not identify the specific phase entered by a material. While microscopic (atomic-level) diagnostic systems (e.g. DXRD) have been designed and implemented in Department of Energy’s (DOE) National Laboratories complex, the unique nature of Sandia National Laboratories’ Pulsed Power Facility (Z Machine) prohibits the use of such devices. The destructive nature of Z experiments presents a challenge to data capture and retrieval. Furthermore there are electromagnetic interference, X-ray background, and mechanical constraints to consider. Thus, a multi-part X-ray diagnostic for use on the Z Machine and Z-Beamlet Laser system has been designed and analyzed. Portions of this new DYnamic SCintillator Optic (DYSCO) have been built, tested and fielded. A data analysis software has been written. Finally, the radiance profile of the DYSCO’s scintillator has been characterized through experiments performed at the University of Arizona.

36 MATERIALS SCIENCE↗

Method for Coupled Electromagnetic and Circuit Simulations to Evaluate Surge Arrester Performance in Protecting Equipment Against E1 HEMP

Surge arrester behavioral modeling for realistic systems embedded in an E1 high-altitude electromagnetic pulse environment inherently encompasses three interconnected complications: (1) the need to account for signal propagation across two domains, electromagnetics and electrical; (2) the need to include both linear and nonlinear circuit components in the analysis; and (3) the need to understand that the over-current and over-voltage mitigation performance is dependent not only on the properties of the surge arrester and protected load but also on the topology of the overall electrical network. This study presents a framework to address these challenges in a systematic manner to consider the effectiveness of protective measures for a common class of equipment in power generation facilities. Full-wave simulations were carried out to derive circuit-domain (i.e., lumped element–based) equivalent models for the excitation waveform and the physical components of the system. Then, these equivalent models were imported to a circuit solver and combined with a high-frequency surge arrester model to evaluate mitigation performance. The methodology outlined is general enough such that it can be applied for other electromagnetic interference problems that involve E2/E3 HEMP or microwave emissions.

42 ENGINEERING↗

Nickel-incorporated Oxide Composites for Fiber-Optic Based Gas Sensing

Numerous high-value applications within the energy sector involve environmental conditions that are incompatible with traditional sensor technology due to degradation of electrical interconnects, packaging, or the sensors themselves. These can include chemically harsh conditions, high temperature operation, or the presence of electromagnetic interference due to high voltage. The fiber optic platform, constructed of robust, electrically insulating glass or single crystal oxides, offers a versatile and often low cost per node solution to this problem, especially with the integration of distributed sensing techniques such as optical time-domain and frequency-domain reflectometry (OTDR, OFDR). A major challenge of gas and chemical sensing on the optical fiber platform is the fabrication of robust and stable sensing materials that interact quickly and reversibly to the presence of the target analytes. In this work, we discuss the utilization of nickel-incorporated oxides on evanescent-field optical fiber sensors for gas sensing under harsh conditions relevant to multiple energy infrastructure applications. This paper will discuss a Ni/GDC (Ni / Gd-doped ceria) based sensing layer targeting conditions relevant for high-temperature (up to at least 800 oC) hydrogen sensing applications (e.g., for operation within a solid oxide fuel cell or electrolyzer). The impact of hydrogen at elevated temperatures on the optical properties of Ni/GDC will be shown and the material mechanisms for the optical response will be discussed.

gas sensors↗

A Hot‐Swappable, Fault‐Tolerant, Modular Power Converter System for Solar Photovoltaic Plants

The performance metrics of the state-of-the-art commercial solar inverters, such as system cost, operation and maintenance (O&M) cost, service life, reliability, maintainability, and power density are much lower than the target metrics needed to achieve SunShot’s 2030 levelized cost of energy (LCOE) goals. To overcome the shortcomings of the existing solar inverters, this project proposed a novel Hot-Swappable, Fault-Tolerant, Modular Power Converter (HSFT-MPC) concept for solar photovoltaic (PV) plants and proved the concept through the design, fabrication, and laboratory test validation of a single-phase HSFT-MPC prototype. The HSFT-MPC has the following distinct advantages over the state-of-the-art: 1) elimination of harmonic/ electromagnetic interference (EMI) filter in the inverter stage due to the novel topology, 2) lower system cost and higher power density due to the modular design, elimination of harmonic/EMI filter, and lower cooling requirement, 3) higher efficiency due to lower switching frequencies, 4) higher reliability and longer (50 years) service life due to simpler cooling and fault tolerance capability, 5) easier installation, lower O&M cost, and improved maintainability due to the modular design and hot-swappable power electronic building blocks (PEBBs), and 6) improved manufacturability due to the modular design. This project developed a single-phase HSFT-MPC prototype with 25kW nominal output power, 2.4kV, 60Hz nominal AC output, lower than 5% AC output voltage total harmonic distortion, over 5 kW/L inverter power density, and 99.4% inverter peak efficiency, being tolerant to failure of single and multiple PEBBs, and capable of hot swapping of the failed PEBB(s). The HSFT-MPC enables uninterruptable operation of the solar PV plant when failure of single or multiple PEBBs or PV modules occurs. Compared with the existing solar inverters in the market, the HSFT-MPC is expected to reduce the inverter failure-caused downtime and energy losses of solar PV plants by more than 60% and 50%, respectively. Project findings have been presented at major conferences in the field and published in peer-reviewed papers, which added new knowledge to the field of power electronics for solar PV systems. A minicourse on Solar PV Systems was developed for outreach activities. The minicourse will help attract young individuals to the renewable energy profession which has a significant talent shortage. The HSFT-MPC is expected to overcome all of the shortcomings of the state-of-the-art solar inverters in terms of cost, efficiency, service life, reliability, maintainability, and manufacturability targets needed to achieve SunShot’s 2030 LCOE goals. Therefore, the proposed HSFT-MPC concept has the great potential to disrupt the current solar inverter market. This project created a pathway towards industry adoption of the HSFT-MPC to help achieve 50-year service life solar PV systems. Since the solar PV plants using the HSFT-MPC will feature with higher reliability, longer service life, and easier maintenance, they are particularly useful for the rural areas with underserved populations that demand reliable and affordable clean electricity. The outcomes of the project have the strong potential to address national needs in the field of renewable energy to reduce CO 2 emissions from the electricity sector, reduce imports of energy from foreign sources, and improve energy security, efficiency, and sustainability. Since electricity is used in almost all of society’s sectors, the outcomes of the project will benefit various sectors of society and economy.

14 SOLAR ENERGY↗

A Method for Estimation and Suppression of Quasi-Periodic Noise

Electromagnetic interference, particularly from sources such as light fixtures and power supplies, negatively affects the function and performance of electronic systems. This noise, often quasi-periodic in nature, contains harmonic structure that can be used for noise estimation and suppression. This work proposes a novel method for tracking and filtering such noise signals that reduces the comb filter bandwidth required for noise estimation and suppression by tracking the instantaneous frequency of the fundamental component.

42 ENGINEERING↗

DC-Link Capacitor Design for a Neutral-Point-Less Three-Level Dual-Phase Inverter for Traction Application

Conventional multilevel inverters, such as neutral￾point-clamped and T-type inverters, have gained popularity in electric vehicle applications due to their advantages, including high voltage range, high power capability, low switching losses, low total harmonic distortion, and low electromagnetic interference. However, these traditional multilevel inverters require a neutral point connection to generate a zero-voltage vector. The neutral point current oscillates at three times the fundamental frequency, leading to voltage imbalance and overvoltage stress on the power modules. Additionally, the use of two stacked DC-link capacitors increases the volume required for the same overall capacitance and complicates packaging due to ripple current and heat dissipation from separate components. This is a significant concern for traction drive units, where space is limited. In this paper, a neutral-point-less multilevel dual three￾phase inverter topology is investigated for traction inverter applications. Simulation results demonstrate that the proposed topology effectively retains the benefits of multilevel operation while utilizing a single DC-link capacitor. The inverter model was simulated in conjunction with an industry-standard battery model to evaluate the potential for capacitor size reduction compared to a conventional three-level inverter.

33 ADVANCED PROPULSION SYSTEMS↗

Development of in-situ polymerized intrinsically conductive resin and low-cost carbon pigments offering high conductivity for sensing, EMI shielding and lighting protection

Electrically conductive composites are emerging across diverse industries such as electronic, automotive, aerospace, advanced air mobility, biomedical, infrastructure, defense and security offering static charge dissipation, electromagnetic interference shielding, lighting protection, sensing, dicing, corrosion monitoring, etc. Conductivity enhanced composites provide several advantages compared to conventional metals including weight reduction, corrosion resistance, energy efficient processability, tunable properties and multifunctionality. Polymers are typically insulating in nature and require conducting filler for electron transport. However, dispersion and polymer-filler interphases are critical and often disrupt conducting pathways. Besides, conductive fillers such as graphene, carbon nanotube, MXene, silver nanowire, etc. are expensive, limiting their wide adoption in composite industry. On the other hand, a limited number of intrinsically conductive polymers are available among which polyaniline (PANI) has been widely studied due to its high conductivity, thermal and chemical stability. However, PANI is difficult to process and exhibits weak mechanical properties. In brief, there is a significant demand for electrically conductive polymer formulation with cost-effective conducting fillers that offer processability in scale to expand the market of conductivity enhanced materials.

Kumar, Vipin [Oak Ridge National Laboratory (ORNL)↗

Design and Characterization of the Engineering Model of the Spectrometer Onboard LuSEE-Night

The Lunar Surface Electromagnetics Explorer - Night, LuSEE-Night, is a low-frequency radio astronomy experiment that will explore the cosmic Dark Ages signal on the radio quiet farside of the Moon. The LuSEE-Night carries a radio frequency spectrometer consisting of a set of antennas, analog and digital processing electronics, and will be launched by NASA's Commercial Lunar Payload Services in 2025. The spectrometer is designed to observe the spectrum of the radio sky in the 0.5−50MHz band. The engineering model (EM) of the four-channel spectrometer has been developed. The EM has been characterized for linearity, gain, noise, and their temperature dependence, confirming that the EM meets all the requirements for LuSEE-Night. Three mitigation techniques have been implemented and verified to suppress self-induced electromagnetic interference (EMI). The flight model of the spectrometer is currently being developed and is scheduled to be shipped to the integration site in early 2024

47 OTHER INSTRUMENTATION↗

Preprocessing for Unintended Conducted Emissions Classification with ResNet

Characterization of Unintended Conducted Emissions (UCE) from electronic devices is important when diagnosing electromagnetic interference, performing nonintrusive load monitoring (NILM) of power systems, and monitoring electronic device health, among other applications. Prior work has demonstrated that UCE analysis can serve as a diagnostic tool for energy efficiency investigations and detailed load analysis. While explaining the feature selection of deep networks with certainty is often not fully comprehensive, or in other applications, quite lacking, additional tools/methods for further corroboration and confirmation can help further the understanding of the researcher. This is true especially in the subject application of the study in this paper. Often the focus of such efforts is the selected features themselves, and there is not as much understanding gained about the noise in the collected data. If selected feature and noise characteristics are known, it can be used to further shape the design of the deep network or associated preprocessing. This is additionally difficult when the available data are limited, as in the case which the authors investigated in this study. Here, the authors present a novel work (which is a proposed complementary portion of the overall solution to the deep network classification explainability problem for this application) by applying a systematic progression of preprocessing and a deep neural network (ResNet architecture) to classify UCE data obtained via current transformers. By using a methodical application of preprocessing techniques prior to a deep classifier, hypotheses can be produced concerning what features the deep network deems important relative to what it perceives as noise. For instance, it is hypothesized in this particular study as a result of execution of the proposed method and periodic inspection of the classifier output that the UCE spectral features are relatively close to each other or to the interferers, as systematically reducing the beta parameter of the Kaiser window produced progressively better classification performance, but only to a point, as going below the Beta of eight produced decreased classifier performance, as well as the hypothesis that further spectral feature resolution was not as important to the classifier as rejection of the leakage from a spectrally distant interference. This can be very important in unpredictable low-FNR applications, where knowing the difference between features and noise is difficult. As a side-benefit, much was learned regarding the best preprocessing to use with the selected deep network for the UCE collected from these low power consumer devices obtained via current transformers. Baseline rectangular windowed FFT preprocessing provided a 62% classification increase versus using raw samples. After performing a more optimal preprocessing, more than 90% classification accuracy was achieved across 18 low-power consumer devices for scenarios in which the in-band features-to-noise ratio (FNR) was very poor.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Passive Islanding Detection of Inverter-Based Resources in a Noisy Environment

Islanding occurs when a load is energized solely by local generators and can result in frequency and voltage instability, changes in current, and poor power quality. Poor power quality can interrupt industrial operations, damage sensitive electrical equipment, and induce outages upon the resynchronization of the island with the grid. This study proposes an islanding detection method employing a Duffing oscillator to analyze voltage fluctuations at the point of common coupling (PCC) under a high-noise environment. Unlike existing methods, which overlook the noise effect, this paper mitigates noise impact on islanding detection. Power system noise in PCC measurements arises from switching transients, harmonics, grounding issues, voltage sags and swells, electromagnetic interference, and power quality issues that affect islanding detection. Transient events like lightning-induced traveling waves to the PCC can also introduce noise levels exceeding the voltage amplitude by more than seven times, thus disturbing conventional detection techniques. The noise interferes with measurements and increases the nondetection zone (NDZ), causing failed or delayed islanding detection. The Duffing oscillator nonlinear dynamics enable detection capabilities at a high noise level. The proposed method is designed to detect the PCC voltage fluctuations based on the IEEE standard 1547 through the Duffing oscillator. For the voltages beyond the threshold, the Duffing oscillator phase trajectory changes from periodic to chaotic mode and sends an islanded operation command to the inverter. The proposed islanding detection method distinguishes switching transients and faults from an islanded operation. Experimental validation of the method is conducted using a 3.6 kW PV setup.

Energy & Fuels↗

Vehicle Position Detection Based on Machine Learning Algorithms in Dynamic Wireless Charging

Dynamic wireless charging (DWC) has emerged as a viable approach to mitigate range anxiety by ensuring continuous and uninterrupted charging for electric vehicles in motion. DWC systems rely on the length of the transmitter, which can be categorized into long-track transmitters and segmented coil arrays. The segmented coil array, favored for its heightened efficiency and reduced electromagnetic interference, stands out as the preferred option. However, in such DWC systems, the need arises to detect the vehicle’s position, specifically to activate the transmitter coils aligned with the receiver pad and de-energize uncoupled transmitter coils. This paper introduces various machine learning algorithms for precise vehicle position determination, accommodating diverse ground clearances of electric vehicles and various speeds. Through testing eight different machine learning algorithms and comparing the results, the random forest algorithm emerged as superior, displaying the lowest error in predicting the actual position.

47 OTHER INSTRUMENTATION↗

Sealed cabinetry Patent

Sealed housing for protecting electronic equipment against electromagnetic interference

Samson, R.↗

Electromagnetic compatibility fundamentals applied to spacecraft radio communication systems

A design guide for minimizing electromagnetic interference in aerospace communication equipment for ground stations is presented. Specifically treated are the mechanisms of generating unwanted radio emissions that may affect station operations as well as other communications services, the mechanisms by which sensitive receivers become susceptible to interference, means for reducing interference, standard methods of measurement, and the problems of site selection. The sources of interference are viewed primarily as originating from communications transmitters aboard spacecraft and aircraft, ground transmitters within and outside the ground stations, and other electrical sources on the ground that are not intended to radiate.

Haber, F.↗

Probes for measuring noise current in an electronic cable

Electromagnetic interference in deep-space network receiver is often caused by stray coupling from power lines. These stray signals create potential differences between ground terminals, which leads to excessive noise in receiver circuits. Pair of probes detect and measure noise currents in conductors.

Lundy, C. C.↗