Results for “Extreme value analysis” — Page 4

DOE OSTI2024

Development of Ti 3 SiC 2 MAX phase tubular structures for solar receiver applications

Solar receiver tubes are key components of concentrating solar-thermal power (CSP) systems that harvest solar energy. For better efficiency, the Gen3 CSP receivers, which collect heat into a heat transfer fluid, require a temperature exceeding 700 °C during operation and need to perform under extreme conditions of high temperature and high thermal stress. Operators are seeking CSP designs using new high-temperature structural materials with high thermal conductivity and high creep resistance to achieve a design life of 30 years and thus help recover the plant capital cost sooner. MAX phase materials, which consist of an early transition metal element, an A-group element, and carbon or nitrogen, are expected to exhibit high creep resistance as well as high fracture toughness. Here, in this paper, we describe fabricating both (1) dense Ti 3 SiC 2 MAX phase disks and (2) short-length tubes using field-assisted sintering technology (FAST). First, the disk samples that we fabricated are fully dense and contain ≈90 % Ti 3 SiC 2 MAX phase materials and ≈10 % TiC phase materials. We determined a flexure strength of 519 ± 32 MPa by conducting a four-point bending test at room temperature with rectangular bar samples of ≈100 % density. The thermal conductivity of the Ti 3 SiC 2 MAX phase samples, measured by light flashing analysis, decreases linearly from a value of 41 W . m -1 . K -1 at room temperature to a value of 36 W . m -1 . K -1 at 650 °C. A solar reflectance measurement of the Ti 3 SiC 2 MAX phase revealed that, temperature increases from 400 to 1400 °C, thermal emittance increases from 0.39 to 0.49, while selectivity decreases from 1.8 to 1.4, respectively. Whereas the surface oxidized MAX phase samples after 100 h exposure to air at 1000 °C exhibit that of SiC. Next, we discuss fabrication of the crack-free Ti 3 SiC 2 MAX phase tubular structures accomplished by using FAST processing in graphite bedding. A Ti 3 SiC 2 MAX phase content of > 95 % with traceable ≈3% remaining TiC phase and ≈15 % porosity were demonstrated after high-temperature annealing. An average fracture strength of ≈250 MPa was determined with Ti 3 SiC 2 MAX phase tubes of ≈85 % density by diametral compression testing at room temperature. Our work demonstrated that using FAST processing to produce Ti 3 SiC 2 MAX phase tubular structures for CSP receiver applications is a viable approach.

14 SOLAR ENERGY↗

DOE OSTI2025

University of Hawai‘i, Shallow Geothermal Resources: Energy Technology Innovation Partnership Project (Final Report)

Scientists at Lawrence Berkeley National Laboratory (Berkeley Lab) have teamed up with the University of Hawai‘i at Manoa (UH Manoa) through the U.S. Department of Energy’s Energy Technology Innovation Partnership Project to evaluate the technological and market feasibility of shallow geothermal heat exchanger (GHE) technology. UH requested this analysis to evaluate opportunities in building cooling, energy efficiency, and emissions reduction applications in Hawai‘i. UH has an abundance of geologic and geothermal data and is looking to the national labs’ expertise to execute this analysis. UH is also interested in investigating policy, regulatory, and business conditions advantageous for implementation of a pilot project and more broad deployment of this technology in Hawai‘i. In many locations around the world, the demands for heating and cooling are roughly balanced over the course of the year, so GHEs do not cause significant long-term changes in subsurface temperature. This is not the case in Hawai’i, where the demand for heating is very small, meaning that, over time, GHEs will add heat to the subsurface. If temperatures increase significantly, GHE systems will not work as designed. Regional groundwater flow has the potential to sweep heated water away from boreholes, thereby maintaining the functionality of the GHE system. Significant regional groundwater flow requires two things: a sufficiently large driving hydraulic head gradient (usually closely related to surface topography), and sufficient porosity and permeability to enable groundwater to flow in large enough quantities to enable near-borehole temperatures to be maintained at ambient values. Hawai‘i’s volcanic terrain offers ample surface topographic variation. The lava itself shows an extremely large range of porosity and permeability, so sites with large enough values of these properties must be selected. Numerical modeling of coupled groundwater and heat flow can be used to determine how large is large enough. Primarily, closed-loop systems have been investigated. Other options considered are open-loop systems and using cool seawater as the chilling source. Project work investigated the feasibility of GHE technology at two scales. At the island scale, GIS layers of various attributes relevant for GHE were combined to develop an overall favorability map for employing GHE in Hawai‘i. At the local scale, a hydrogeologic model for the subsurface component of a closed-loop system was developed for the Stan Sheriff Center at the UH Manoa campus. This site is considered promising because the rock below and immediately downgradient of the borefield is highly permeable, consisting of a subsurface karst system (limestone containing high-permeability open channels), which is underlain by a thick, high-permeability fractured basalt. Moreover, the site is near the base of the Ko‘olau Range, providing a large hydraulic head gradient. Thus, groundwater flow through the site is expected to be large, enabling efficient removal of heated groundwater. A full-GHE-system model of the site was also developed, with a simplified representation of the subsurface, in which groundwater flow is not considered and heat transfer is purely by conduction. Using the building cooling load data provided by UH, simulation results show that with groundwater flow present, a GHE can operate successfully for at least 10 years, but with no groundwater flow, the subsurface begins to heat up after only one year of operation, making the GHE unviable within 2-6 years. The team also developed a techno-economic model for this site to compare the cost of cooling using a GHE system with the costs of operating the current air-conditioning system. The GHE system is advantageous economically if favorable tax incentives and interest rates can be obtained.

15 GEOTHERMAL ENERGY↗

DOE OSTI2025

Ultra-high temperature testing and performance of L-PBF C103

Additive Manufacturing (AM) of refractory alloys is gaining traction as a materials processing route for components subject to extreme temperature environments. Due to the low oxidation resistance of refractory alloys, novel methods for evaluating their elevated temperature performance must be developed. In this work, a Gleeble® 3800 thermomechanical load frame was modified to evaluate the mechanical properties of laser powder bed fusion (L-PBF) consolidated niobium alloy C103 ranging from room temperature (RT) to 1400 °C. The fixturing and sample geometry were designed to accommodate Joule heating and prevent damage to the test chamber. Oxidation of the samples was minimized via testing in vacuum level of 1E-5 Torr. Ultimate tensile strength (UTS), yield strength (YS), elongation, and strain-hardening behavior were determined as a function of temperature. L-PBF C103 presented an average UTS of ∼650 MPa and over 25 % elongation at RT. Above RT, the UTS and YS dropped then leveled off from 500 °C to 1000 °C with values ranging from ∼400 MPa to ∼460 MPa, which is consistent with dynamic strain aging observed in this class of alloys. The strength rapidly declined after 1200 °C to ∼150 MPa at 1400 °C. Fractography indicated ductile fractures for the C103 at all test temperatures, and Electron Backscatter Diffraction (EBSD) analysis revealed a textured microstructure and the presence of dynamic recrystallization within the necked region of the sample tested at 1400 °C.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2026

Calibration and Data Analysis of a Frequency Selectable Laser Source for CMB Detector Characterization

Cosmic Microwave Background (CMB) experiments study faint radiation left over from the early universe. The CMB was created when the universe became cool enough for light to travel freely through space, and today it gives scientists one of the earliest images of the universe. One important goal of modern CMB experiments is to measure this radiation with higher precision in order to search for evidence that supports the theory of cosmic inflation. To do this, scientists use extremely sensitive detectors that must be calibrated accurately. The Frequency Selectable Laser Source, or FLS, is a new calibration tool that can send selected frequencies to detectors and help measure their response. During my internship, I worked on the FLS after it returned to Fermilab from Chile, where it had been used to characterize detectors at the Simons Observatory. The system came back in parts, so the first part of my project was helping rebuild the optical and mechanical setup. After the system was rebuilt, we performed alignments to maximize the receiver photocurrent. We then collected calibration measurements over different frequency ranges, including 543 GHz to 568 GHz, 740 GHz to 766 GHz, and 60 GHz to 500 GHz. These measurements were used to check waterline calibration and reflectivity features and compare new data with previous data. Another major part of my project was learning Python so I could understand previous analysis code, modify it for new files, and write my own code to compare the mean response between datasets. The results showed that the new data was close to previous measurements and that waterline features near 556 GHz and 752 GHz were found within less than 1.5 GHz of the expected values. I also completed the reflectivity analysis for five prisms in two polarization orientations. In the original orientation, the results were consistent between the five prisms and close to values measured on a different system at the University of Chicago. I then collected a second set of measurements on my own with the polarization of the laser rotated by 90 degrees and compared them with the original data using the same Python workflow. The measured reflectivity increased for all five prisms in the new orientation, showing that the prism reflectivity depends on polarization. Future work will focus on using the FLS to characterize real CMB detectors.

Pumarino, Rafael [Unlisted]↗

DOE OSTI2026

Calibration and Data Analysis of a Frequency Selectable Laser Source for CMB Detector Characterization

Cosmic Microwave Background (CMB) experiments study faint radiation left over from the early universe. The CMB was created when the universe became cool enough for light to travel freely through space, and today it gives scientists one of the earliest images of the universe. One important goal of modern CMB experiments is to measure this radiation with higher precision in order to search for evidence that supports the theory of cosmic inflation. To do this, scientists use extremely sensitive detectors that must be calibrated accurately. The Frequency Selectable Laser Source, or FLS, is a new calibration tool that can send selected frequencies to detectors and help measure their response. During my internship, I worked on the FLS after it returned to Fermilab from Chile, where it had been used to characterize detectors at the Simons Observatory. The system came back in parts, so the first part of my project was helping rebuild the optical and mechanical setup. After the system was rebuilt, we performed alignments to maximize the receiver photocurrent. We then collected calibration measurements over different frequency ranges, including 543 GHz to 568 GHz, 740 GHz to 766 GHz, and 60 GHz to 500 GHz. These measurements were used to check waterline calibration and reflectivity features and compare new data with previous data. Another major part of my project was learning Python so I could understand previous analysis code, modify it for new files, and write my own code to compare the mean response between datasets. The results showed that the new data was close to previous measurements and that waterline features near 556 GHz and 752 GHz were found within less than 1.5 GHz of the expected values. I also completed the reflectivity analysis for five prisms in two polarization orientations. In the original orientation, the results were consistent between the five prisms and close to values measured on a different system at the University of Chicago. I then collected a second set of measurements on my own with the polarization of the laser rotated by 90 degrees and compared them with the original data using the same Python workflow. The measured reflectivity increased for all five prisms in the new orientation, showing that the prism reflectivity depends on polarization. Future work will focus on using the FLS to characterize real CMB detectors.

Pumarino Meza, Rafael [Unlisted, US; Fermilab]↗

DOE OSTI2026

Calibration and Data Analysis of a Frequency Selectable Laser Source for CMB Detector Characterization

Cosmic Microwave Background (CMB) experiments study faint radiation left over from the early universe. The CMB was created when the universe became cool enough for light to travel freely through space, and today it gives scientists one of the earliest images of the universe. One important goal of modern CMB experiments is to measure this radiation with higher precision in order to search for evidence that supports the theory of cosmic inflation. To do this, scientists use extremely sensitive detectors that must be calibrated accurately. The Frequency Selectable Laser Source, or FLS, is a new calibration tool that can send selected frequencies to detectors and help measure their response. During my internship, I worked on the FLS after it returned to Fermilab from Chile, where it had been used to characterize detectors at the Simons Observatory. The system came back in parts, so the first part of my project was helping rebuild the optical and mechanical setup. After the system was rebuilt, we performed alignments to maximize the receiver photocurrent. We then collected calibration measurements over different frequency ranges, including 543 GHz to 568 GHz, 740 GHz to 766 GHz, and 60 GHz to 500 GHz. These measurements were used to check waterline calibration and reflectivity features and compare new data with previous data. Another major part of my project was learning Python so I could understand previous analysis code, modify it for new files, and write my own code to compare the mean response between datasets. The results showed that the new data was close to previous measurements and that waterline features near 556 GHz and 752 GHz were found within less than 1.5 GHz of the expected values. I also completed the reflectivity analysis for five prisms in two polarization orientations. In the original orientation, the results were consistent between the five prisms and close to values measured on a different system at the University of Chicago. I then collected a second set of measurements on my own with the polarization of the laser rotated by 90 degrees and compared them with the original data using the same Python workflow. The measured reflectivity increased for all five prisms in the new orientation, showing that the prism reflectivity depends on polarization. Future work will focus on using the FLS to characterize real CMB detectors.

Pumarino Meza, Rafael [Unlisted, US; Fermilab]↗

DOE OSTI2025

SiC Receiver/Reactor by Additive Manufacturing for Concentrated Solar Thermocatalysis with Thermal Energy Storage (Final Technical Report - Public)

The direct use of solar thermal energy provides opportunities for low-cost heating sources for a variety of applications. Ultra-high temperatures around 1000°C are high value and highly useful for energy-demanding industries. Many materials cannot withstand these conditions. In the area of Sustainable Chemicals, further limitations on material stability exist. Combining state-of-the-art materials with new designs provides a promising pathway for harvesting solar thermal energy and performing high temperature chemical processes. However, conventional manufacturing limits the potential for design flexibility. In this project, Additive Manufacturing was combined with advanced materials and new chemical reactor designs. In addition, 24/7 energy is necessary for chemical processing, and designs for ultra-high temperature thermal storage were devised. Specifically, preliminary design of a novel solar thermal receiver was developed in this project and designed to work with thermocatalytic reactors for producing sustainable chemicals and fuels. An ultra-high temperature particle storage system and heat exchangers were proposed to transport ultra-hot air as thermal fluid for the system. On a broader scale, this system could be used to tap solar thermal energy for a centralized facility with capability of transferring that heat to various segments at a full range of temperatures to 1000°C. The project pushed the temperature boundaries past those in current use, and Additive Manufacturing was envisaged for fabricating the receiver to meet requirements of extreme environments. An extensive analysis of silicon carbide additive manufacturing was performed to compare the thermal and mechanical properties of complex geometries compared to conventional material and those manufactured via other methods. The Additive Manufacturing via Binder-Jet printing was optimized and characterized to provide high quality and reproducible components capable of withstanding the proposed extreme environments. The designs for the concentrating solar thermal cavity with ultra-hot air thermal fluid showed high performance in simulations, attributable to the complex optimized geometries of the 3D printed systems. The bright future of Additive Manufacturing with advanced materials developments should provide more options and even higher quality as the technology further develops. Current costs for Additive Manufacturing of advanced ceramics is relatively low, however post-processing of the materials for extreme environments is currently high. There is little industrial-scale infrastructure for these, but it is growing as niche applications become more mainstream. The results of the project can be translated into similar extreme environments for concentrating solar thermal energy as well as its integration with ultra-hot air thermal fluids. A number of industries that require ultra-high temperatures need to electrify or otherwise decarbonize for climate goals, and this project showed that theoretically there is a pathway to do so with direct concentrated solar thermal power.

10 SYNTHETIC FUELS↗

DOE OSTI2026

Optimizing enzymes for plastic upcycling using machine learning design and high throughput experiments

Plastic use is ubiquitous in the modern world, and polyethylene terephthalate (PET) is one of the most abundantly produced plastics (and the most highly produced polyester), with ~65 million metric tons manufactured annually. To the consumer, PET is likely most recognizable as the plastic used to make beverage bottles. Like many plastics, traditional mechanical or chemical means of PET deconstruction and upcycling are costly and inefficient. Because of these challenges, recycled plastic is generally of lower quality and is more expensive to produce than virgin plastic derived from petroleum. Ultimately, this results in most plastic ending up as waste. We view plastic waste as an underutilized resource which, with the development of more efficient and high-quality recycling processes, could (1) generate significant economic value while (2) decreasing petroleum usage and greenhouse gas emissions, as well as (3) minimizing its negative environmental and health impacts. Biocatalytic recycling, or biomanufacturing the basic building blocks of new plastic from plastic waste, is a promising approach to plastic reuse that complements existing recycling technologies. Recently, biological enzymes capable of breaking down PET have garnered significant attention as an attractive means of dealing with the plastic problem. These enzymes are currently undergoing pilot studies for implementation in industrial-scale enzyme-based recycling. However, there are significant limitations to current enzymes, including the need to perform costly pre-processing of the plastic waste before the enzymes are able to work. Further optimization of these enzymes is necessary to make these technologies competitive, and ultimately incentivise industry-wide adoption of this biology-based green recycling technology. n this work we demonstrate a means to design and generate performant biological enzymes, capable of efficiently deconstructing plastic waste. Specifically, we applied recent advances in artificial intelligence, machine learning, and statistical analysis to design new versions and discover natural enzymes capable of breaking down PET. We focused on optimizing key properties that are important for industrial-scale enzymatic recycling such as pH and thermotolerance. Normal testing of enzymatic plastic-deconstruction is extremely labor intensive and so through this work we also developed a robotic-assisted experimental pipeline capable of characterizing thousands of candidate enzymes. The results of this iterative, AI-guided, multi-discipline approach have led to increases in enzymatic breakdown of over 150X over starting enzymes. This work supports the rapidly developing and transformative field of biocatalytic solutions to environmental problems beyond the discovery and predictive understanding of enzymes for polymer recycling, and has wide implications for tackling numerous energy problems such as carbon capture and fixation (e.g., engineering carbon monoxide dehydrogenase and the rubisco-pathway), biomining (e.g., design of lanthanide-binding proteins) and biomanufacturing (e.g., lignin-deconstruction enzymes).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2024

Improved Subseasonal Forecasting of Extreme Polar Vortices Using Machine Learning

Our research was focused on forecasting the position and shape of the winter stratospheric polar vortex at a subseasonal timescale of 15 days in advance. To achieve this, we employed both statistical and neural network machine learning techniques. The analysis was performed on 42 winter seasons of reanalysis data provided by NASA giving us a total of 6,342 days of data. The state of the polar vortex for determined by using geometric moments to calculate the centroid latitude and the aspect ratio of an ellipse fit onto the vortex. Timeseries for thirty additional precursors were calculated to help improve the predictive capabilities of the algorithm. Feature importance of these precursors was performed using random forest to measure the predictive importance and the ideal number of precursors. Then, using the precursors identified as important, various statistical methods were tested for predictive accuracy with random forest and nearest neighbor performing the best. An echo state network, a type of recurrent neural network that features sparsely connected hidden layer and a reduced number of trainable parameters that allows for rapid training and testing, was also implemented for the forecasting problem. Hyperparameter tuning was performed for each methods using a subset of the training data. The algorithms were trained and tuned on the first 41 years of data, then tested for accuracy on the final year. In general, the centroid latitude of the polar vortex proved easier to predict than the aspect ratio across all algorithms. Random forest outperformed other statistical forecasting algorithms overall but struggled to predict extreme values. Forecasting from echo state network suggested a strong predictive capability past 15 days, but further work is required to fully realize the potential of recurrent neural network approaches.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

A Demonstration System for Geological Thermal Energy Storage of Concentrating Solar Thermal

Energy storage is increasingly necessary as variable energy technologies are deployed. Seasonal energy storage can shift energy generation from the summer to the winter, but these technologies must have extremely large energy capacities and low costs. Geological Thermal Energy Storage (GeoTES) is proposed as a solution for long-term energy storage [1]. Excess thermal energy can be stored in permeable reservoirs such as aquifers and depleted hydrocarbon reservoirs for several months. The energy capacity cost of GeoTES is very low which makes it suitable for both daily- and seasonal storage of Concentrating Solar Thermal (CST) energy, thus enabling CST to provide value to electricity markets and thermal energy off-takers. A CST-GeoTES demonstration system has been funded by the U.S. Department of Energy, Solar Energy Technology Office. In this article, we will describe this demonstration system and progress that has been made in its development. The demonstration system will comprise a 2 MWth parabolic trough with an 8m aperture developed by Gossamer Space Frames, seven wells, and a 100 kWe power cycle. The demonstration system will be deployed in Kern County, California by Premier Resource Management. A techno-economic model for CST-GeoTES systems has also been developed [3] and is applied to the demonstration system and its planned future expansion. The model integrates the output of specialist models of each subsystem, which enables the performance and cost of both the subsurface and surface systems to be captured. Off-design models enable the performance to be evaluated at each hour of the year, before being aggregated to evaluate the economic potential of CST-GeoTES. Initial analysis indicates that CST-GeoTES can provide long duration energy storage capabilities with low marginal costs of energy capacity - leading to a low value of Levelized Cost of Storage (LCOS) compared to alternative technologies, see Figure 2. In this article, we investigate the cost and performance of the specific demonstration site being developed by PRM and explore a range of operational profiles that can deliver different value streams, such as daily and seasonal storage, capacity, and resiliancy.

14 SOLAR ENERGY↗

DOE OSTI2025

Techno-Economic Analysis of Data-Driven and Transactive Approaches for Resilience Enhancement

As extreme weather events lead to more frequent power outages, understanding and enhancing grid resilience is critical to mitigating economic losses and non-energy impacts from service disruptions. Here, this study introduces a novel techno-economic analysis framework for evaluating resilience enhancement mechanisms. The framework combines grid response modeling with a co-simulation approach and valuation methodology to provide a comprehensive assessment. We apply this framework to a realistic case study of the Texas grid during Winter Storm Uri in February 2021. Two advanced resilience strategies are analyzed: a data-driven rolling outage mechanism and a transactive energy (TE) based allocation scheme. The rolling outage scheme selectively serves customers based on real-time curtailment needs, while the TE scheme allows customers to trade energy allocations according to their preferences. Our findings show that both the rolling outage and TE schemes significantly outperform conventional methods (i.e. controlled outages) by reducing the amount of energy not supplied to customers by 41% and 64%, respectively. These approaches also enhance flexibility and customer satisfaction, while improving energy utilization for greater resilience. Additionally, they maintain thermal comfort about 3.5 times better and substantially lower customer risk exposure. A key contribution of this study is addressing both utility and customer perspectives while considering both energy and non-energy impacts. The techno-economic analysis indicates that implementing these resilience enhancement strategies would incur an additional 1.1Bto1.6B in utility costs but has the potential to avoid 17.3Bto18B of customer losses as compared to existing solutions, thereby underscoring the value of investing in advanced resilience, as it provides significant societal benefits to customers.

42 ENGINEERING↗

DOE OSTI2025

Performance of Convection-Permitting and Convection-Parameterized Models in Reproducing the Extreme Precipitation Intensity Relationship with Surface Conditions

Here, this study investigates the warm-season extreme precipitation–temperature scaling relationship in CONUS404, a convection-permitting (4 km) Weather Research and Forecasting (WRF) Model simulation over the conterminous United States for the past four decades, and compares it with the WRF-Thermodynamic Global Warming (WRF-TGW) historical simulation at a coarser resolution (12 km) using parameterized convection. We also analyze the NCEP stage IV and NASA Integrated Multi-satellitE Retrievals for the Global Precipitation Measurement (IMERG) datasets as observational benchmarks. We examine how extreme precipitation intensity (EPI) varies with temperature and saturation deficit over representative regions based on hourly data. The stage IV and IMERG data show a similar pattern of EPI variation with temperature and saturation deficit, except that the EPI peak is lower in IMERG than in stage IV. Under dry and hot conditions, EPI decreases too rapidly with elevated saturation deficit in both CONUS404 and WRF-TGW compared to observations, but the performance of CONUS404 is superior to WRF-TGW. When the near-surface atmosphere is saturated or close to saturated, both CONUS404 and WRF-TGW produce higher peak values of EPI relative to the observational references; IMERG exhibits scaling rates close to the Clausius–Clapeyron (C–C) relationship, while CONUS404, WRF-TGW, and stage IV all demonstrate super-C–C scaling behaviors. Despite marked warming over the past four decades, in both CONUS404 and WRF-TGW, the scaling relationship between EPI and temperature in a saturated atmosphere remains stable and robust. This indicates a strong potential for the EPI–temperature scaling rate under saturation to be used as an emergent constraint in reducing uncertainties of future extreme precipitation projection.

Atmosphere↗

DOE OSTI2025

Fission Product Quantification and Burnup Analysis via Gamma Spectrometry of the AGR-5/6/7 TRISO Fuel Experiment

Five capsules containing varying configurations of TRISO fuel compacts were irradiated in the most recent Advanced Gas Reactor (AGR) TRISO test campaign, AGR-5/6/7. As part of the post-irradiation examination (PIE) of this work all the fuel compacts and capsule graphite holders were measured with the Precision Gamma Scanner (PGS) to determine isotopic activities and locations using gamma spectrometry. Measuring the compacts allowed for the comparison of physics model depletion calculations with the measured compact activity to validate models. These measurements also are used to find compacts of interest with low fission product retention that may be tested in subsequent PIE. Measurements of the holders can confirm fission product distribution and migration. Of the isotopes measured, Cs-137 and Cs-134 were used to estimate location of failed particles as well as determine a measured burnup estimation. Results from Capsule 1 compacts and the holder indicate many fuel particle failures occurred. There are high amounts of cesium in the holder near Stack 9 of Capsule 1 that corresponds to low fractions?measured-to-calculated (M/C) ratio?of cesium remaining in those compacts. All other capsules had cesium retention ratios near 1. The isotope 110mAg had less consistent results. Capsule 2 compacts exhibited a M/C of 0.20, much lower than anticipated for the temperatures these compacts underwent. Capsule 3 experienced much higher temperatures, >1300C and had an average M/C of 0.75. These are the opposite results than what was predicted by past AGR experiments for the relationship between temperature and isotope retention. Capsule 4 and 5 showed good fission product retention and agreement with the physics model predictions. The burnup results from the PGS measurements showed strong agreement between the physics models and the measured values. Using a ratio of Cs-134/Cs-137 to calculate the burnup match closely with the physics models. Additionally, the Cs-137 burnup results were less accurate but extremely close to the model results.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2025

CMB-S4: Foreground-cleaning Pipeline Comparison for Measuring Primordial Gravitational Waves

We compare multiple foreground-cleaning pipelines for estimating the tensor-to-scalar ratio, r, using simulated maps of the planned CMB-S4 experiment within the context of the South Pole Deep Patch. To evaluate robustness, we analyze bias and uncertainty on r across various foreground suites using map-based simulations. The foreground-cleaning methods include: a parametric maximum likelihood approach applied to auto- and cross-power spectra between frequency maps; a map-based parametric maximum-likelihood method; and a harmonic-space internal linear combination using frequency maps. We summarize the conceptual basis of each method to highlight their similarities and differences. To better probe the impact of foreground residuals, we implement an iterative internal delensing step, leveraging a map-based pipeline to generate a lensing B-mode template from the large aperture telescope frequency maps. Our results show that the performance of the three approaches is comparable for simple and intermediate-complexity foregrounds, with σ(r) ranging from 3–5 ×10 −4 . However, biases at the 1σ–2σ level appear when analyzing more complex forms of foreground emission. By extending the baseline pipelines to marginalize over foreground residuals, we demonstrate that contamination can be reduced to within statistical uncertainties, albeit with a pipeline-dependent impact on σ(r), which translates to a detection significance between 2σ and 4σ for an input value of r = 0.003. These findings suggest varying levels of maturity among the tested pipelines, with the auto- and cross-spectra-based approach demonstrating the best stability and overall performance. Moreover, given the extremely low noise levels, mutual validation of independent foreground-cleaning pipelines is essential to ensure the robustness of any potential detection.

astronomy data analysis↗

DOE OSTI2024

Advanced Laboratory and Field Arrays (ALFA)/Lab Collaboration Project (LCP) for Marine Energy (Final Scientific/Technical Report)

The objective of the Advanced Laboratory and Field Arrays (ALFA) project was to reduce the Levelized Cost of Energy (LCOE) of Marine and Hydrokinetic (MHK) energy by leveraging research, development, and testing capabilities at Oregon State University, University of Washington, and the University of Alaska, Fairbanks. ALFA is a project within the Pacific Marine Energy Center (PMEC; formerly NNMREC), a multi-institution entity with a diverse funding base that focuses on research and development for marine renewables. The ALFA project aimed to accelerate the development of next-generation arrays of wave energy conversion (WEC) and tidal energy conversion (TEC) devices through a suite of field-focused R&D activities spanning a broad range of strategic opportunity areas identified in the Funding Opportunity Announcement: • Device and/or array operation and maintenance (O&M) logistics development; • High-fidelity resource characterization and/or modeling technique development and validation; • Array-specific component technology development (e.g. moorings and foundations, transmission, and other offshore grid components); • Array performance testing and evaluation; and • Novel cost-effective environmental monitoring techniques and instrumentation testing and evaluation. The objective of the Lab Collaboration Project (LCP) was to accelerate the development of next-generation marine energy conversion systems. The LCP aimed to achieve these project objectives in collaboration with the national laboratories by: • Developing concept generation and assessment tools; • Improving access to existing testing resources; • Validating collision risk models between fish and turbines; and • Advancing analysis and simulation capabilities for wave-WEC interactions and PTO analysis in nonlinear ocean waves. The ALFA portion of the project was comprised of six overarching technical tasks: • Task 1: Debris Modeling, Detection and Mitigation; • Task 2: Autonomous Monitoring & Intervention; • Task 3: Resource Characterization for Extreme Conditions; • Task 4: Robust Models for Design of Offshore Anchoring and Mooring Systems; • Task 5: Performance Enhancement for Marine Energy Converter (MEC) Arrays; and • Task 6: Evaluating Sampling Techniques for MHK Biological Monitoring. The LCP was divided into four overarching technical tasks: • Task 7: Project Management and Reporting • Task 8: Novel Design and Assessment Methodologies for Wave Energy Converter Design (Wave- SPARC) • Task 9: Testing Access for Commercial Marine Renewable Energy Technology Developers • Task 10: Quantifying Collision Risk for Fish and Turbines • Task 11: Nonlinear Ocean Waves and PTO Control Strategy Each ALFA/LCP task listed above functioned as a separate and discreet project. A final Technical Report was written for each individual task and these reports were uploaded to OSTI, after receiving DOE approval. The following document is a compilation of each of these final, approved reports arranged as individual chapters.

13 HYDRO ENERGY↗

DOE OSTI2024

Effects of irradiation damage on the hardness and elastic properties of quaternary and high entropy transition metal diborides

Multi-principal component transition metal (TM) diborides represent a class of high-entropy ceramics (HECs) that have received considerable interest in recent years owing to their promising properties for extreme environment applications that include thermal/ environmental barriers, hypersonic vehicles, turbine engines, and next-generation nuclear reactors. While the addition of chemical disorder through the random distribution of TM elements on the cation sublattice has offered opportunities to tailor elastic stiffness and hardness, the effects of irradiation-induced structural damage on the physical properties of these complex materials have remained largely unexplored. To this end, changes in the hardness and elastic moduli of a high-entropy TM diboride (Hf 0.2 Nb 0.2 Ta 0.2 Ti 0.2 Zr 0.2 )B 2 and three of its quaternary subsets following irradiation with 10 MeV gold (Au) ions to fluences of up to 6 × 10 15 Au cm -2 are investigated at the micrometer and sub-micrometer length-scales via the dispersion of laser-generated surface acoustic waves (SAW) and nanoindentation, respectively. The nanoindentation measurements show that the TM diborides exhibit an initial increase in hardness following irradiation with energetic Au ions, with a subsequent decrease in hardness following further irradiation. One quaternary composition, (Hf 1/3 Ta 1/3 Ti 1/3 )B 2 , exhibits a notable exception to the trend and continues to exhibit an increase in hardness with ion irradiation fluence. Although differences in the absolute values of the effective elastic moduli obtained from the measured SAW dispersion and nanoindentation are observed (and attributed to microstructural variations at the measurement length-scale), both techniques yield similar trends in the form of an initial reduction and subsequent saturation in the elastic modulus with increasing ion irradiation fluence. The quaternary TM diboride (Hf 1/3 Ta 1/3 Ti 1/3 )B 2 again exhibits a departure from this trend. The high-entropy TM diboride (Hf 0.2 Nb 0.2 Ta 0.2 Ti 0.2 Zr 0.2 )B 2 exhibits the greatest recovery in hardness and modulus when irradiated to high ion fluences following initial changes at low fluence, indicating superior resistance to radiation-induced damage over its quaternary counterparts. Opportunities for designing HECs with superior hardness and modulus for enhanced radiation resistance (compared to their single constituent counterparts) by tailoring chemical disorder and bond character in the lattice are discussed.

36 MATERIALS SCIENCE↗