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At least 487 records · Page 27

A 100 kW 1.3 GHz Magnetron System with Amplitude and Phase Control

Calabazas Creek Research, Inc., Fermilab, and Communications & Power Industries, LLC, developed a 100 kW peak, 10 kW average, 1.3 GHz, magnetron-based, RF system for driving accelerators. Efficiency varied between 81% and 87%. Phase locking uses a novel approach that provides fast amplitude and phase control when coupled into a superconducting accelerator cavity [1]. The system was successfully tested at Fermilab and produced 100 kW in 1.5 ms pulses at a repetition rate of 2 pps. A locking bandwidth of 0.9 MHz was achieved with a drive signal of 269 W injected through a 4 port circulator. The phase locking signal was 25 dB below the magnetron output power. The spectrum of the phase locked magnetron was suitable for driving accelerator cavities. Phase modulation was demonstrated to 50 kHz (the limit of the available driver source). The average power was limited by available conditioning time. Scaling indicates 42 kW of average power should be achievable. Estimated cost is less than $1/Watt of delivered RF power, exclusive of power supplies or modulators. System design and performance measurements will be presented.

43 PARTICLE ACCELERATORS↗

Bayesian GAN-Based False Data Injection Attack Detection in Active Distribution Grids With DERs

Advancements in information and communication technologies have revolutionized monitoring and control capabilities within smart grids. However, it also brings new vulnerabilities to data acquisition systems and state estimation functions, which attackers can subtly tamper with the measurement data through compromising the communication network. Moreover, the high penetration of renewable energy sources with the inherited characteristics of uncertainty and variability further complicates the design of effective intrusion detection systems. In this paper, a Bayesian deep learning-based approach is developed to detect cyber attacks and maintain the security of smart grids. Our method specifically addresses the prevalent issue of imbalanced data in real power systems, which arises from the predominance of normal system operations over compromised or attacked states. Employing a novel Bayesian GAN-based technique, our approach successfully discriminates between secure and compromised measurement data, even in scenarios with significant data imbalance. Furthermore, the proposed method accommodates various practical application factors, ensuring accurate intrusion detection despite the presence of measurement noise. The feasibility and effectiveness of the proposed detection mechanism are validated by testing on IEEE 13-node and 123-node test systems. Simulation results and comparisons with literature methods demonstrate the superiority of proposed cybersecurity solutions.

Bayesian GAN↗

A machine learning model for predicting the minimum miscibility pressure of CO 2 and crude oil system based on a support vector machine algorithm approach

CO 2 enhanced oil recovery (EOR) is a potential way for carbon capture, utilization and storage (CCUS). Though, the effect of CO 2 injection is greatly influenced by the reservoir conditions. Typically, Minimum miscible pressure (MMP) is selected as one of the key parameters for the screening and evaluation of prospective CO 2 flooding. Conventional slim tube test is both accurate and widely accepted but it is inefficient. Existing empirical formulas for MMPs are easy to be used but have been proved inaccurate and unreliable. Machine learning-based methods have great advantages in predicting MMP. However, only predication accuracy is discussed for most models without the screening of the main control factors and further validation of the model reliability. In this paper, a new prediction model based on support vector machine (SVM) was developed for pure/impure CO 2 and crude oil system. This study was based on 147 sets of MMP data from the literature with full information on reservoir temperature, oil composition and gas composition. The main control factors were screened by several statistical methods. Unlike the conventional prediction models that verified by only prediction accuracy, learning curve and single factor control variable analysis are further validated to obtain the optimum model.

02 PETROLEUM↗

Modeling, testing, and mitigation of electromagnetic pulse on PV systems

Electromagnetic Pulse (EMP) poses a significant threat to the normal operation of power systems, especially with the increasing penetration of renewable energy. Without adequate protection, EMP can severely damage equipment or result in circuit breakdowns or short circuits. Solar photovoltaic (PV) facilities are particularly susceptible to EMP since PV systems are outdoors and exposed to EMP radiation. To assess and mitigate this threat, this paper summarizes various models and tests used to study the effects of EMP on PV systems, assesses the nature of the threat, and identifies measures to mitigate it. The paper provides a comprehensive review by categorizing analytical methods based on their pros and cons, introducing and describing EMP-related events, and providing a taxonomy of analytical methods for studying EMP. This paper compares the processes of modeling, testing, and mitigating EMP at both the component and system levels of PV systems. Furthermore, it also presents a case study that reveals the vulnerability of solar inverters to EMP using the pulse current injection method. Finally, the paper discusses some of the remaining challenges that should be considered in future solar PV system design and deployment.

14 SOLAR ENERGY↗

An atypical lipoteichoic acid from Clostridium perfringens elicits a broadly cross-reactive and protective immune response

Clostridium perfringens is a leading cause of food-poisoning and causes avian necrotic enteritis, posing a significant problem to both the poultry industry and human health. No effective vaccine against C. perfringens is currently available. Using an antiserum screen of mutants generated from a C. perfringens transposon-mutant library, here we identified an immunoreactive antigen that was lost in a putative glycosyltransferase mutant, suggesting that this antigen is likely a glycoconjugate. Following injection of formalin-fixed whole cells of C. perfringens HN13 (a laboratory strain) and JGS4143 (chicken isolate) intramuscularly into chickens, the HN13-derived antiserum was cross-reactive in immunoblots with all tested 32 field isolates, whereas only 5 of 32 isolates were recognized by JGS4143-derived antiserum. The immunoreactive antigens from both HN13 and JGS4143 were isolated, and structural analysis by MALDI-TOF-MS, GC-MS, and 2D NMR revealed that both were atypical lipoteichoic acids (LTAs) with poly-(β1→4)-ManNAc backbones substituted with phosphoethanolamine. However, although the ManNAc residues in JGS4143 LTA were phosphoethanolamine-modified, a few of these residues were instead modified with phosphoglycerol in the HN13 LTA. The JGS4143 LTA also had a terminal ribose and ManNAc instead of ManN in the core region, suggesting that these differences may contribute to the broadly cross-reactive response elicited by HN13. In a passive-protection chicken experiment, oral challenge with C. perfringens JGS4143 lead to 22% survival, whereas co-gavage with JGS4143 and α-HN13 antiserum resulted in 89% survival. This serum also induced bacterial killing in opsonophagocytosis assays, suggesting that HN13 LTA is an attractive target for future vaccine-development studies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Power Grid Reliability Estimation via Adaptive Importance Sampling

Electricity production currently generates approximately 25% of greenhouse gas emissions in the USA. Thus, increasing the amount of renewable energy is a key step to carbon neutrality. However, integrating a large amount of fluctuating renewable generation is a significant challenge for power grid operating and planning. Grid reliability, i.e., an ability to meet operational constraints under power fluctuations, is probably the most important of them. In this letter, we propose computationally efficient and accurate methods to estimate the probability of line overflow, i.e., reliability constraints violation, under a known distribution of renewable energy generation. To this end, we investigate an importance sampling approach, a flexible extension of Monte-Carlo methods, which adaptively changes the sampling distribution to generate more samples near the reliability boundary. The approach allows to estimate overload probability in real-time based only on a few dozens of random samples, compared to thousands required by the plain Monte-Carlo. Our study focuses on high voltage direct current power transmission grids with linear reliability constraints on power injections and line currents. Herein, we propose a novel theoretically justified physics-informed adaptive importance sampling algorithm and compare its performance to state-of-the-art methods on multiple IEEE power grid test cases.

power system faults↗

The Effect of Pressure on NO x Entitlement and Reaction Timescales in a Premixed Axial Jet-In-Crossflow

This paper investigates the pressure dependency of a lean premixed jet injected into a lean vitiated crossflow with an experimentally verified detailed chemistry computational fluid dynamics (CFD) model and 53 species considered. Experimental data were taken in an axially staged combustor with an optically accessible test section, allowing the use of particle image velocimetry (PIV) and CH* chemiluminescence techniques as well as point measurement of species concentration, temperature, and pressure. The experimental data cases at one, three, and five atmospheres were selected to describe the flame stabilization dependency on pressure and gain the required knowledge for an extrapolation to engine condition. Simulated exit nitrogen oxide levels were validated with experimental emission data, and a global emission trend for the NO reduction at elevated pressure and constant turbine inlet temperature level was defined. The nitrogen oxide benefit at elevated operating pressure was justified with the significantly smaller flame surface area: the analysis of the simulated spanwise and top-view profiles showed a relatively short receded core flame with nitrogen oxide production in the center at high pressure relative to a longer and larger shear layer flame at atmospheric condition that produced NO toward the inner and outer side of the flame. Furthermore, decomposition of the Damköhler number revealed the strong influence of the reaction timescales with higher reaction rates at elevated pressure, along with a moderate influence of the turbulent timescales, showing higher turbulence intensity in the lee-side recirculation zone at lower pressure.

03 NATURAL GAS↗

Pulsed Neutron Capture for monitoring CO2 Storage with Enhanced Oil Recovery in Northern Michigan

Pulsed neutron capture (PNC) logging has been used as part of the Midwest Regional Carbon Sequestration Partnership (MRCSP) monitoring of CO2 injection and storage during assessment of enhanced oil recovery (EOR) in several northern Niagaran trend reefs in Michigan. A total of four reefs were selected for these studies to monitor CO2 migration and to test the viability and effectiveness of the PNC technology on reefs in various stages (depleted, active and new reefs) of CO2-EOR activities.

Bagley↗

Simulation Studies on the Interactions of Electron Beam with Wastewater

The manufactured chemical pollutants, like 1,4 dioxane and PFAS (per- and polyfluroralkyl substances), found in the underground water and/or drinking water are challenging to be removed or biodegraded. Energetic electrons are capable of mediating and removing them. This paper utilizes FLUKA code to evaluate the beam-wastewater interaction effects with different energy, space and divergence distributions of the electron beam. With 8 MeV average energy, the electron beam exits from a 0.0127 cm thick titanium window, travels through a 4.3 cm distance air and a second 0.0127 cm thick stainless water container window with 2.43 cm radius, and finally is injected into the water area, where the volume of water is around 75 cubic cm. The distribution parameters of the electron beam are from the GPT (General Particle Tracer) simulations for UITF (Upgraded Injector Test Facility) in Jefferson lab. By varying the distributions, several measurements including the dose (or energy deposition) distribution, electron fluence, photon fluence are scored and compared. Taking the comparisons into consideration, this paper is aiming to find better electron beams for the wastewater irradiation.

Li, X.↗

DARHT Axis 1 Time-Resolved Injector Energy Measurement

The Dual-Axis Radiographic Hydrodynamic Test (DARHT) facility provides flash radiography capabilities using electron Linear Induction Accelerators (LIA’s). The strict requirements for flash radiography require a detailed understanding of the LIA’s performance, including precision measurements of the injected electron beam energy. The DARHT Axis 1 injector of produces a 3-4 MeV, 1-2 kA, 80-ns-FWHM electron beam. Injector capacitive monitors (EVACSUM) are summed to give the injector beam energy. Calibration of EVACSUM was last done in 1999 and is needed. In addition, the flatness of the injector drive voltage is controlled by a peaking capacitor in a Blumlien that is charged by the prime power tank. Time resolved measurements are used to optimize the value of this capacitor.

47 OTHER INSTRUMENTATION↗

Simulation Studies on the Interactions of Electron Beam with Wastewater

The manufactured chemical pollutants, like 1,4 dioxane and PFAS (per- and polyfluroralkyl substances), found in the underground water and/or drinking water are challenging to be removed or biodegraded. Energetic electrons are capable of mediating and removing them. This paper utilizes FLUKA code to evaluate the beam-wastewater interaction effects with different energy, space and divergence distributions of the electron beam. With 8 MeV average energy, the electron beam exits from a 0.0127 cm thick titanium window, travels through a 4.3 cm distance air and a second 0.0127 cm thick stainless water container window with 2.43 cm radius, and finally is injected into the water area, where the volume of water is around 75 cubic cm. The distribution parameters of the electron beam are from the GPT (General Particle Tracer) simulations for UITF (Upgraded Injector Test Facility) in Jefferson lab. By varying the distributions, several measurements including the dose (or energy deposition) distribution, electron fluence, photon fluence are scored and compared. Taking the comparisons into consideration, this paper is aiming to find better electron beams for the wastewater irradiation.

Li, X.↗

IC Project: The Role of Compressibility in Regulating Magnetic Energy Conversion in Reconnection Processes with Turbulence and Implications for Particle Transport and Energization

Diagnostics for the contribution of different regions in low-energy injection: a) Distribution function for the time duration of E > B particles within E > B regions. The estimated time limits for achieving injection are labeled; b) Distribution of energy gain during injection (for E > B particles) for E > B regions (blue), before E > B crossing (red), and outside E > B regions after the first crossing (black); c) Spectra for self-consistent particles (blue), test-particles that do not see electric fields in E > B regions (red) and test-particles with a resetting energy approach (green).

79 ASTRONOMY AND ASTROPHYSICS↗

Diagnosing and overcoming recombination and resistive losses in non-silicon solar cells using a silicon-inspired characterization platform

This project aimed to generate the characterization tools needed for accurate and systematic loss analysis in non-silicon photovoltaic solar cell technologies and, through the use of these tools and analysis techniques, contribute to the development of a novel class of hetero-contacts to II-VI absorbers, with the final goal of demonstrating record-breaking CdSeTe devices. CdSeTe solar cells provide a prime example of the potential impact of the techniques we proposed to develop and implement: record poly-CdSeTe cells have bandgap-voltage deficits (W oc ) of approximately 550 mV, as compared with below 400 mV for all other mature PV technologies. Similarly, these record CdSeTe devices have FFs below 80%, when other mature cells are near or above 85%. Frustratingly, a systematic identification of the origin of these sub-par performances—for example recombination or resistive losses—has been lacking, thus slowing down the development of these technologies. Similarly, it is often asserted that CdSeTe cells need a better back (hole) contact. Although most believe this is true, no one knew—at the start of this project—how high the V oc and FF could be for a given cell if it had a perfect back contact. Such characterization techniques and loss analysis methods exist and are routinely performed on c-Si solar cells (e.g. injection-dependent lifetime, Suns-V oc , transfer length method, etc). Over the years, they have been instrumental in the development of silicon devices that operate at 91% of their theoretical (Auger) limit. Lifetime testing, and the associated reconstruction of the implied-J-V curve, can moreover be performed at every cell-processing step, thus allowing a direct peek into the impact of that step on cell performance. Therefore, adapting these techniques and tools to non-Si devices would greatly improve their learning rate. In this project, we developed a Suns-ERE technique—the equipment, methodology, and know-how—to measure the implied-J-V curve, the pseudo-J-V curve, and the actual J-V curve of a thin-film solar cell, allowing an accurate assessment of the quality of the bulk material and its surface passivation, the selectivity of the contact, and its resistivity. We used this technique to show that the absorber of present CdSeTe solar cells is capable of achieving 1 V Voc,, that passivation layers exist (e.g., Al2O3) that can support such high voltages, and that the barrier is identifying contact layers that are both passivating and carrier-selective. The characterization platform created in this project and the understanding generated using it will accelerate the progress of non-silicon PV technologies. In particular, the project will contribute to CdSeTe solar cells with Voc > 1 V and cell efficiency > 24%. Such cells provide a pathway to module-level efficiencies >23%. As CdSeTe presently competes with silicon on module cost (in $\$ $/W) and yet has significantly more room for efficiency gains, the potential for LCOE reduction is particularly large. For example, CdTe modules with an efficiency of 21% would allow an LCOE below $\$ $0.04kWh -1 in average US climates.

14 SOLAR ENERGY↗

Performance Characterization of a Natural Gas–Air Rotating Detonation Engine

An experimental study of a rotating detonation engine (RDE) operating with natural gas and air at elevated chamber pressures and air preheat temperatures was conducted to quantify its performance at conditions representative of land-based power generation gas turbine engines. Here, the thrust produced by the combustor was measured to characterize its work output potential. High-frequency pressure transducers and broadband chemiluminescence measurements of the flame provided information about the wave structure and dynamics. Analysis of common performance metrics demonstrated the necessity of normalizing any RDE performance parameter by the driving system potential, typically the reactant manifold pressure. Application of a thermodynamic performance model to a generic RDE identified the area ratio between the RDE exhaust and injection throats as the primary parameter affecting delivered pressure gain. The model was further applied to draw comparison with experimental measurements of net pressure gain for identical flow conditions. Only one of the two tested injector configurations followed the predicted trends, suggesting that performance of the second was governed by physical processes other than the reactant thermodynamics. Although an absolute pressure gain was not demonstrated, it is promising that the natural gas–air RDE delivered up to 90% of the theoretical performance.

20 FOSSIL-FUELED POWER PLANTS↗

Durability Study of a High-Pressure Common Rail Fuel Injection System Using Lubricity Additive-Dosed Gasoline-Like Fuel—Improved Endurance with Upgraded Hardware

Gasoline compression ignition (GCI) is a promising combustion technology that can help the commercial transportation sector achieve operational flexibility and meet upcoming criteria pollutant regulations. However, high-pressure fuel injection systems (>1000 bar) are needed to enable GCI and fully realize its benefits compared to conventional diesel combustion. This work is a continuation of previous durability studies that identified three key technical risks after running gasoline-like fuel through a heavy-duty, common rail injection system: (i) cavitation damage to the inlet check valve of the high-pressure pump, (ii) loss of injector fueling capacity, (iii) cavitation erosion of the injector nozzle holes. Upgraded hardware solutions were tested on a consistent 400- to 800-hour NATO durability cycle with the same gasoline-like fuel as previous studies. The upgraded pump showed no signs of abnormal wear or cavitation damage to the inlet check valve. In contrast to previous studies, there were no signs of pump performance degradation observed after 400 hours of testing. Material selection and design upgrades were also made to the injector which, only showed a 6.5% loss in fueling capacity after 800 hours of durability testing compared to 49.3% previously. Finally, geometric nozzle hole features such as higher inlet radius of curvature and higher K-factor were found to correlate with reduced cavitation erosion. However, mitigation of eccentric radial needle motion (i.e., wobble) is likely needed to further suppress cavitation. In general, the results from this study indicate there are viable hardware-based solutions for improving the endurance of high-pressure systems when running with gasoline-like fuel.

33 ADVANCED PROPULSION SYSTEMS↗

Design and Experimental Demonstration of an Additive Manufactured Smart Oxy-Methane Burner for High Pressure and Supercritical Combustion

Pressurized oxy combustion-based systems can improve efficiency by recovering latent heat of the steam in the Flue Gas and achieving 90% CO2 capture. In addition, the novel Directly Heated Supercritical Carbon Dioxide (DH-SCO2) power cycles can achieve high thermal efficiencies and provide nearly full carbon capture. Additionally, due to the reduction of flue gas at higher pressure, smaller system size and capital cost reductions are also possible. Recent thermodynamic analysis of the DH-SCO2 cycle performed by the UTEP research team shows that combustion conditions in the vicinity of 300 bar pressure and 1000-1400 K temperature allow for relatively high system efficiencies while operating within the limit of available combustor materials. However, the realization of a directly heated supercritical power cycle requires combustion systems to operate in supercritical conditions and at temperature far below the blowout limit of conventional flames (above 1500 K). The thermodynamic properties along with the combustion properties and kinetics are unexplored at such conditions. Additionally, the interaction of the supercritical environment with energy components is also unknown. High-pressure combustion tests are performed using a smart burner at some intermediate pressure ranges (<20 bar) to help minimize these knowledge gaps. The knowledge obtained from the high-pressure test will assist in understanding the combustion chamber pressurization mechanism, ignition and flame behavior at the elevated pressure. The obtained data will act as a systematic first step in testing at higher pressures of 100 and 300 bar pressures.The primary purpose of this Dissertation is to demonstrate the operability of a low NOx smart burner for oxy-methane combustion at high pressure (< 20 bar) and scalable up to supercritical conditions. A shear co-axial smart burner is designed with a real-time temperature monitoring capability to understand the burner face interaction at high-pressure conditions. In addition, the burner has four independent injection ports to allow the independent injection of fuel and dilution gases in the combustor. The maximum operating capability of the burner is 575 kWth. The burner was fabricated using a Laser Powder Bed Fusion process with Nickel Alloy 718. A powder removal technology was invented comprising ultrasonic vibration, liquid nitrogen exposure and media blasting to remove powders from internal channels of the burner. The burner operability tests are performed in the high-pressure combustor and the swirl combustor. The high-pressure combustor was used to investigate the burner operability and thermal soak back at different pressurized conditions. The experimental tests in high-pressure combustor up to 275 kWth input resulted in 16.5 bar chamber pressure and 198°C thermal soaks back to the burner. The burner was capable of providing the required thermal input within a 3% deviation range. In addition, soot formation occurred at high-pressure tests. The swirl combustor was used to observe the flame stability of the burner. Flame lift-off was observed for jet velocities above 450 m/s. Additionally, lift-off decreased for low co-flow velocities. CO2 dilution experiments showed increased flame instabilities for all conditions above 50% dilution ratios. At lower thermal inputs, partial flame blow-offs occurred for dilution ratios above 50%. All conditions significantly reduced the flame temperature and increased the flame lift-off height. Finally, a 2nd generation AM smart burner was designed using the knowledge from the 1st generation burner experiments. The 2nd generation burner incorporated two sets of swirlers with 0.9 swirl no. A cooling system was also designed for long-duration tests at higher pressures. The thermal input and division of the burner's power are kept the same as the 1st generation burner. The burner is to be fabricated using nickel-alloy 718 for high-pressure handling capability. The design can sustain at high-pressure conditions up to 100 bar.

Islam, Md Nawshad Arslan↗

Detection of False Data Injection Attacks in Battery Stacks Using Input Noise-Aware Nonlinear State Estimation and Cumulative Sum Algorithms

Grid-scale battery energy storage systems (BESSs) are vulnerable to false data injection attacks (FDIAs), which could be used to disrupt state of charge (SoC) estimation. Inaccurate SoC estimation has negative impacts on system availability, reliability, safety, and the cost of operation. In this article a combination of a Cumulative Sum (CUSUM) algorithm and an improved input noise-aware extended Kalman filter (INAEKF) is proposed for the detection and identification of FDIAs in the voltage and current sensors of a battery stack. The series-connected stack is represented by equivalent circuit models, the SoC is modeled with a charge reservoir model and the states are estimated using the INAEKF. Further, the root mean squared error of the states’ estimation by the modified INAEKF was found to be superior to the traditional EKF. By employing the INAEKF, this article addresses the research gap that many state estimators make asymmetrical assumptions about the noise corrupting the system. Additionally, the INAEKF estimates the input allowing for the identification of FDIA, which many alternative methods are unable to achieve. The proposed algorithm was able to detect attacks in the voltage and current sensors in 99.16% of test cases, with no false positives. Utilizing the INAEKF compared to the standard EKF allowed for the identification of FDIA in the input of the system in 98.43% of test cases.

25 ENERGY STORAGE↗

A Large-Scale Hardware Experiment Demonstration of Operating High Inverter-Based Resource Power Systems With Grid-Forming Inverters

This paper presents experimental hardware results from a microgrid system as the penetration level of grid-forming (GFM) inverters increases. The experiment aims to showcase the advantages of GFM inverters in enhancing system stability and to investigate the operational challenges in systems relying entirely on inverter-based resources (IBRs). Five test scenarios are devised to progressively increase GFM inverter penetration levels: 0% (S1), 19% (S2), 37% (S3), 68% (S4), and 100% (S5). To ensure consistency, identical loading conditions and dynamic events are applied across all scenarios. The conducted tests include load step changes, output variation of grid-following (GFL) inverters during islanded mode, transition operations (such as synchronization to the grid and islanding), and rateof- change-of-frequency (ROCOF) and voltage jump tests during grid-connected mode. Key findings from the tests are summarized as follows: (1) Scenario S1 proved most challenging for load steps, and GFL variations because of insufficient GFM capacity, leaving the diesel generator unable to handle transient ridethrough; (2) Scenario S5 was the most difficult for transition operations, because the lack of a diesel generator to maintain stiff bus voltage resulted in unexpected reactive power flows during synchronization, causing the point of common coupling (PCC) breaker to trip; (3) Scenarios S4 and S5 were particularly challenging for ROCOF tests because of minimal system inertia, leading to large transients that triggered breaker trips; and (4) Scenario S4 exhibited the strongest voltage recovery capability because of the presence of the diesel generator and a higher number of GFM inverters, both of which possess the highest capacity for reactive power injection.

24 POWER TRANSMISSION AND DISTRIBUTION↗