Analysis of aerospace power conditioning component limitations Final report
Aerospace power conditioning in spacecraft applications improved by circuit design and components
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Aerospace power conditioning in spacecraft applications improved by circuit design and components
The Sandia National Laboratories, in California (SNL/CA) is a research and development facility, owned by the U.S. Department of Energy’s National Nuclear Security Administration agency (DOE/NNSA). The laboratory is located in the City of Livermore (the City) and is comprised of approximately 410 acres. The SNL/CA facility is operated by National Technology and Engineering Solutions of Sandia, LLC (NTESS) under a contract with the DOE/NNSA. The DOE/ NNSA’s Sandia Field Office (SFO) oversees the operations of the site. North of the SNL/CA facility is the Lawrence Livermore National Laboratory (LLNL), in which SNL/CA’s sewer system combines with before discharging to the City’s Publicly Owned Treatment Works (POTW) for final treatment and processing. The City’s POTW authorizes the wastewater discharge from SNL/CA via the assigned Wastewater Discharge Permit #1251 (the Permit), which is issued to the DOE/NNSA’s main office for Sandia National Laboratories, located in New Mexico (SNL/NM). The Monitoring and Reporting Condition 2.B of the Permit requires compliance with the semiannual reporting requirements contained in federal categorical pretreatment standards regulations (40 CFR 403.12). These regulations set numerical limits on the concentration of pollutants allowed to discharge from certain categories of industrial processes. This report is submitted to the City to satisfy this reporting requirement.
Long-term economic performance of a commercial solar-energy system was analyzed and used to predict economic performance at four additional sites. Analysis described in report was done to demonstrate viability of design over a broad range of environmental/economic conditions. Report contains graphs and tables that present evaluation procedure and results. Also contains appendixes that aid in understanding methods used.
Measurements of the rate of hydrous alteration of amorphous Mg-SiO smokes are reported as a function of temperature, as inferred by observing changes in the infrared spectra of these materials. It is shown that under the conditions reported for the nucleus of Comet Halley, based on measurements made by the Vega and Giotto missions, amorphous, anhydrous Mg-SiO smokes would become hydrated within several weeks in the dusty regolith observed on the surface. However, if such grains were released in 'jets' or from loose ice fragments, then previously amorphous grains would retain their anhydrous nature. Similarly, brief periods of aqueous activity on meteorite parent bodies would convert amorphous, fine-grained material to hydrated phyllosilicates much more rapidly than coarse mineral grains. A kinetic model might therefore be developed to explain the observed textural relationships in the matrices of carbonaceous chondrites such as Mokoia, where amorphous phyllosilicates are intimately associated with coarse anhydrous grains.
Design and environmental testing of thermal conditioning unit for liquid hydrogen propellant tank
Conventional use of Ground Penetrating Radar (GPR) is hampered by variations in background environmental conditions, such as water content in soil, resulting in poor repeatability of results over long periods of time when the radar pulse characteristics are kept the same. Target objects types might include voids, tunnels, unexploded ordinance, etc. The long-term objective of this work is to develop methods that would extend the use of GPR under various environmental and soil conditions provided an optimal set of radar parameters (such as frequency, bandwidth, and sensor configuration) are adaptively employed based on the ground conditions. Towards that objective, developing Finite Difference Time Domain (FDTD) GPR models, verified by experimental results, would allow us to develop analytical and experimental techniques to control radar parameters to obtain consistent GPR images with changing ground conditions. Reported here is an attempt at developing 20 and 3D FDTD models of buried targets verified by two different radar systems capable of operating over different soil conditions. Experimental radar data employed were from a custom designed high-frequency (200 MHz) multi-static sensor platform capable of producing 3-D images, and longer wavelength (25 MHz) COTS radar (Pulse EKKO 100) capable of producing 2-D images. Our results indicate different types of radar can produce consistent images.
This report covers the inspection findings for the Routine Inspection of the Omega Bridge conducted on September 23-25, 2022 and the Fracture Critical Member (FCM) Inspection conducted on June 26-27, 2021. Note that due to complications with the under-bridge access unit, portions of the Routine Inspection and the entire FCM Inspection could not be completed in 2022. As a result, the superstructure condition reported herein is based on the 2021 inspection whereas the deck and substructure conditions are based on the 2022 inspection. The superstructure condition will be updated when the inspection is completed in 2023. The inspections were completed according to the standards referenced in EXHIBIT “D” SCOPE OF WORK AND TECHNICAL SPECIFICATIONS including the National Bridge Inspection Standards (23 CFR Part 650, dated 12/14/2004) and other FHWA, NMDOT, and AASHTO codes and standards.
The threat for aircraft icing in clouds is a significant hazard that routinely impacts aviation operations. Accurate diagnoses and forecasts of aircraft icing conditions requires identifying the location and vertical distribution of clouds with super-cooled liquid water (SLW) droplets, as well as the characteristics of the droplet size distribution. Traditional forecasting methods rely on guidance from numerical models and conventional observations, neither of which currently resolve cloud properties adequately on the optimal scales needed for aviation. Satellite imagers provide measurements over large areas with high spatial resolution that can be interpreted to identify the locations and characteristics of clouds, including features associated with adverse weather and storms. This paper describes new techniques for interpreting cloud products derived from satellite data to infer the flight icing threat to aircraft. For unobscured low clouds, the icing threat is determined using empirical relationships developed from correlations between satellite imager retrievals of liquid water path and droplet size with icing conditions reported by pilots (PIREPS). For deep ice over water cloud systems, ice and liquid water content (IWC and LWC) profiles are derived by using the imager cloud properties to constrain climatological information on cloud vertical structure and water phase obtained apriori from radar and lidar observations, and from cloud model analyses. Retrievals of the SLW content embedded within overlapping clouds are mapped to the icing threat using guidance from an airfoil modeling study. Compared to PIREPS and ground-based icing remote sensing datasets, the satellite icing detection and intensity accuracies are approximately 90% and 70%, respectively, and found to be similar for both low level and deep ice over water cloud systems. The satellite-derived icing boundaries capture the reported altitudes over 90% of the time. Satellite analyses corresponding to the time and location of several recent aviation accidents and with icing PIREPS are also presented that reveal skill in identifying severe icing conditions. These results demonstrate the utility of satellite cloud retrievals for quantitatively diagnosing the potential for icing conditions on temporal and spatial scales that should be useful to the aviation community. Plans are being developed to deliver these new satellite products to the GOES-R Proving Ground in the near future so that they can be evaluated in operational applications.
Picochlorum celeri has among the fastest photoautotrophic growth rates (~2 h doubling time in optimal conditions) reported to date for a marine alga. This study comprehensively analyzes the levels of Picochlorum celeri photosynthetic pigments, which can reach up to ~13% of the total particulate organic carbon (POC) under light-limiting conditions. The main Picochlorum celeri pigments identified include: chlorophyll a, chlorophyll b, lutein, β-carotene, canthaxanthin, violaxanthin, neoxanthin, zeaxanthin and antheraxanthin. The ketocarotenoid canthaxanthin can accumulate up to 120 mg L -1 in Picochlorum celeri liquid culture; ~12% of it was found in an extracellular polysaccharide matrix. Using a solar-simulating automated photobioreactor, we monitor the photoacclimation of cultures maintained in unshaded conditions (<0.5 μg mL -1 of total chlorophyll) through transitions from high irradiance (1000 μmoles photosynthetically active radiation (PAR) m -2 s -1 ) to low irradiance (60 μmoles PAR m -2 s -1 ), and conversely from low to high irradiance. Canthaxanthin and zeaxanthin accumulation are among the most rapid modulation responses when cultures are shifted from low to high irradiance. The violaxanthin, antherazanthin, and zeaxanthin (VAZ) pool is ~3-fold higher in high-light cultures, suggesting that the VAZ cycle combined with a dramatic reduction in chlorophyll levels are among the major mechanisms used in Picochlorum celeri to efficiently acclimate to high-irradiance levels. Responsive pigment modulation was also observed in denser cultures (~0.65 g L –1 ) grown under a diel cycle (pond-mimicking conditions). Furthermore, this research provides unique insights into the dynamics of pigment modulation and photoacclimation in response to changing irradiance in a biotechnologically promising alga and will inform future pigment engineering strategies to further improve light capture and biomass accumulation.
Procedures for measuring the air mass zero (AM0) current versus voltage characteristics and calculating the efficiency are discussed. The various factors influencing the determination of the efficiency include the I-V measurement system, reference cell calibration, standard reporting conditions, area measurement, light source characteristics, temperature measurement and control, and the measurement procedures. Each of these sources contributes to the precision index and bias limit which is combined to obtain the total uncertainty in the efficiency. These factors are discussed as well as how to minimize differences in the reported AM0 efficiency of a given PV cell between various laboratories.
This study investigates marine and continental stratocumulus (Sc) cloud properties obtained from an automated implementation of a multispectral photometer retrieval. Photometer methods simultaneously retrieve cloud optical depth (τ) and cloud droplet effective radius (r e ), with estimates for liquid water path (LWP) calculated on the availability of those quantities. These applied methods evaluate retrieved cloud properties for Sc identified during a recent 6 year period over the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) program sites in Oklahoma, USA (SGP) and in the Azores, Portugal (ENA). Modest agreement in key quantity retrievals is found between the routine photometer products and multisensor collocated profiling references. Cumulative breakdowns contingent on cloud thickness indicate increases in all retrieved quantities in thicker clouds, with larger discrepancies in the relative performance between the retrievals collected in the presence of drizzle. Under continental cloud conditions, the clouds of a similar thickness and r e to those sampled under marine conditions report a factor of 1.5 larger τ and LWP. An r 2 ≅0.65 is found between photometer τ retrievals and shadowband radiometer measurements, with photometer retrievals reporting a high (relative) bias. The τ intercomparisons indicate that variability between retrievals is a factor of three larger than errors reported from individual retrieval input perturbation tests. Photometer r e retrievals suggest a low r 2 (< 0.1) having a standard deviation ≅ 3 µm when compared to ARM baseline multi-sensor radar/radiometer references (accounting for offsets in the cloud droplet number concentration assumptions of the latter). However, photometer LWP calculations remain relatively unbiased in non-drizzling conditions, with errors O (50 g m −2 ) and r 2 ≅0.5 to collocated radiometer and interferometer references. Additional sensitivity tests for island influences on marine Sc properties suggest that while island-influenced winds may promote larger cloud LWP or thickness, the influence could be within retrieval method uncertainty and/or collocated instrument variability.
We explored the utility of ground-based highly accelerated life testing (HALT) on epitaxial lift-off (ELO) triple-junction coverglass interconnected cells (CICs) after exposure to simulated Martian dust storms. Dust storm impingement was replicated by sandblasting CICs with Mars dust simulant replicating conditions similar to the weather conditions reported by the Viking landers. We observed that even in cases when there are no observable open circuit voltage (VOC) losses, the minority carrier lifetime is reduced. Short circuit current (JSC) losses can be recovered upon cleaning, suggesting JSC losses are not linked to permanent damage, like cell cracking. This suggests a permanent degradation could be determined by quantifying the difference between recoverable and non-recoverable power loss. We mined field data from the Mars Exploration Rover, Opportunity and extracted a degradation rate to compare to our experimental data. We found exceptional agreement between 4.9 Martian years of mined field data (9.4%) and the irreversible damage observed in our HALT experiment (9.7%). We demonstrate that the laboratory method for exposing CICs to Martian dust storm conditions well represents the physical reality of long duration CIC operation on Mars.
With the goal of maximizing plant reliability and availability, complex systems such as nuclear power plants continuously monitor and record the performance and the health status of many components, assets, and systems. Such data may take the form of online monitoring data, condition reports, and maintenance reports and it carries the potential to provide system engineers with insights into anomalous behaviors or degradation trends as well as the possible causes behind them and to predict their direct consequences. The analysis of such data poses however few challenges. While some of these challenges are technical in nature (i.e., data are often distributed over several physical servers or databases), others are conceptual in nature (i.e., data elements come in different formats, numeric or textual), and measured values have different scales (e.g., vibration spectra and oil temperature). This paper directly tackles these challenges, and it focuses on the integration of all these data elements in order to assist plant system engineers in analyzing component, assets, and systems performances and optimize maintenance activities. This is performed by 1) extracting knowledge from textual data via technical language processing methods, and 2) quantifying system, asset, and component health from numeric condition-based data. We rely on model-based system engineering (MBSE) models of systems and assets to identify their architecture and functional (i.e., cause and effect) relations. Numeric and textual data elements are then associated with an MBSE graph element, based on their nature. This bonding of MBSE models and data elements constitutes a first-of-its-kind knowledge graph of a nuclear power plants system, with data elements being organized in a structured manner that enables system engineers to identify cause-effect trends in data elements and carry out appropriate actions in response.
Defects play a significant role in the material properties of carbon fibers (CF). Several defects result in the formation of sp 3 bonds in an otherwise sp 2 -dominant graphitic structure. Understanding the distribution of these defects within CF provides insight into their properties and the effect of manufacturing conditions. Reports showed time-of-flight secondary ion mass spectrometry (ToF-SIMS) is capable of characterizing the spatial distribution of sp 2 and sp 3 content in carbon materials. Here, ToF-SIMS was utilized to investigate the spatial distribution of sp 3 defects in T700, T1000, and M46 CF. M46 had the lowest sp 3 content. Center-to-edge analysis revealed that T700 CF had a gradient of sp 3 defects starting from the center and increasing to the edge, whereas M46 CF had a sudden increase in sp 3 defects roughly 1 μm from the edge. Comparatively, T1000 CF had a relatively uniform radial distribution of sp 3 defects, except for a newly identified sp 2 rich region at 0.8 μm from the center. This is hypothesized to originate from a skin–core structure that forms during CF manufacturing. As a result, this work demonstrates the utility of ToF-SIMS for characterizing the spatial distribution of sp 3 defects within CF, establishing new ways to understand CF formation.
Edge localized modes (ELMs) are triggered using deuterium pellets injected into plasmas with ITER-relevant low collisionality pedestals, and the resulting peak ELM energy fluence is reduced by approximately 25%–50% relative to natural ELMs destabilized at similar pedestal pressures. Cryogenically frozen deuterium pellets are injected from the low-field side of the DIII-D tokamak at frequencies lower than the natural ELM frequency, and heat flux is measured by infrared cameras. Ideal MHD pedestal stability calculations show that without pellet injection, these low collisionality pedestals were limited by their current density (peeling-limited) rather than their pressure gradient (ballooning-limited). ELM triggering success correlates strongly with pellet mass, consistent with the theory that a large pressure perturbation is required to trigger an ELM in low collisionality discharges that are far from the ballooning stability boundary. For sufficiently large pellets, both instantaneous and time-integrated ELM energy deposition measured by infrared cameras is reduced with respect to naturally occurring ELMs at the inner strike point, which is the position where it is largest for natural ELMs. Energy fluence at the outer strike point is less effected. Cameras observing both heat flux and D-alpha emission often find significant toroidally asymmetric striations in the outboard far scrape-off layer resulting from ELMs that are triggered by pellets. Toroidal asymmetries at the inner strike point are similar between natural and pellet-triggered ELMs, indicating that the reduction in peak heat flux and total fluence at that location is robust for the conditions reported here.
The commercial U.S. light-water reactor fleet has been operating at historical efficiency, reliability, and safety over the last decade. Nuclear power has the highest capacity factor of any other power generation technology while also serving as the largest baseload source for carbon-free energy. Despite this remarkable achievement, continued operations for many plants are threatened due to fierce electricity market competition and rising operations and maintenance costs of which continued maintenance of obsolete analog equipment is a contributor. The digital age and associated technologies are where the future lies in process control, and nuclear has yet to take full advantage of the capabilities offered therein. The Light Water Reactor Sustainability Program (LWRS) at Idaho National Laboratory (INL), sponsored by the Department of Energy, has a mission to help the light-water reactor fleet manage its foundational capabilities to continue providing safe and reliable carbon-free power. LWRS helps support that mission by providing scientific, technology-based solutions for advanced concepts of operations with a more viable business model that will allow the fleet to continue to operate at peak levels through extended plant operation. The LWRS Digitalization Project at INL seeks to leverage digital technologies to synthesize and transform work processes. We provide a state-of-the-art analysis of digitalized work processes in nuclear power and investigate ways in which researchers at INL and the nuclear industry can work together to identify what data to access, how to access it, what to do with the data, and most importantly, how to use the insights for decision-making across all levels within the business. Borne from these considerations, we present four guiding principles for digitalization: develop a coherent digitalization plan, apply human factors engineering, establish data governance, and anticipate unintended consequences. Together, these principles form a method that plants can use to effectively to digitalize nuclear industry work processes. Our guiding principles are informed by multiple knowledge sources. First, we document activities from the Work Digitalization Initiative, which was conceived as a means for nuclear organizations to help define and standardize the industry’s approach to digitalizing work. Second, we detail primary research conducted with industry professionals regarding drivers and barriers to digitalization adoption. We present survey results that demonstrate what the industry hopes to get out of digitalization and the ways that INL can continue to support the industry’s digital transformation. Third, we present a digitalization use case with industry partners NextAxiom Technology and Xcel Energy. The project objective was to transform the current condition report work process from paper to digital, incorporating digitalized principles. We report the development of the application and lessons learned. The accomplishments achieved by this research and development serve to identify critical needs for plant guidance in support of digitalization implementation and contribute to the knowledge and strategies available for utilities considering or undertaking digitalization.
Particle formation in pressurized oxy-fuel combustion can be fundamentally different from oxy-fuel combustion at atmospheric pressure. Under high pressures, the rate of char gasification with CO2 and H2O increases significantly and dominates the char reactions particularly at high temperatures. Also, the extent of fragmentation varies. This could result in a very different particle size distribution from that of air-fired combustion. To accurately obtain the particle size distribution in a pressurized oxy-fuel combustor without sampling bias, the particle measurement should be made at the system pressure. Very few published studies have accomplished this, and never under the conditions reported herein. In this work, we fire PRB coal in a 100 kWth staged pressurized oxy-fuel combustor (SPOC) under two pressures, 15 and 2 bara. A sampling probe (oil-cooled) is installed at the combustor outlet and the aerosol flow are sampled isokinetically. We utilize a state-of-the-art optical analyzer (Malvern Insitec) with a novel high-pressure and high-temperature flow cell to measure the particle size distribution and concentration in-situ in a sampled flow, which contains moist/corrosive flue gas under the process pressure and a controlled temperature that is kept above the dew point. The results show that the pressure can significantly influence the particle size distribution and concentration from the oxy-fuel combustor.
The formation of the main flue gas species (NOx, SOx, CO2, and CO) in pressurized oxy-fuel combustion can be fundamentally different from oxy-fuel combustion at atmospheric pressure. To accurately obtain the concentration of these gas species in a pressurized oxy-fuel combustor, a gas measurement which maintains the sampling pressure is needed. Very few published studies have accomplished this, and never under the conditions reported herein. In this work, we fire PRB coal in a 100 kWth staged pressurized oxy-fuel combustor (SPOC) under a pressure 15 bara. We utilize a state-of-the-art FTIR (Thermo Scientific Nicolet iS20) with a novel high-pressure gas cell that is under process pressure to measure the in-situ flue-gas concentration in a sampled flow. However, water vapor can significantly interfere with the FTIR measurement, particularly under pressure. To address this problem, we have developed a high-pressure nafion dryer to selectively remove the water vapor from the flue gas while retaining the flue gas species. This approach can significantly increase the signal-noise ratio for the FTIR. By integrating the nafion dryer and the high-pressure gas cell, we were able to successfully measure flue gas species at system pressure with the FTIR.