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DOE OSTI2021

Adaptive Site Management Strategies for the Hanford Central Plateau Groundwater

Adaptive site management (ASM) is a systematic and iterative management approach that can be used to expedite the remediation of large and/or complex sites. ASM is defined as a formal and systematic project or site management approach centered on rigorous site planning and a firm understanding of site conditions and uncertainties, using science and technology to routinely re-evaluate and prioritize site remedial actions and characterization activities. The goal of the approach is to create a framework of structured and continuous planning, implementation, and assessment processes that accommodates new information and changing site conditions to develop effective and efficient cleanup approaches that achieves the required outcome(s) while optimizing costs, cleanup timeframe, and performance. Central to ASM is an evolving conceptual site model (CSM). Over time, incremental reductions in uncertainty associated with the CSM will occur, while supporting continued progress toward site cleanup and closure through remedy optimization and evaluation. ASM has the potential to expedite cleanup for the Central Plateau area at Hanford through a planned and systematic approach for reducing uncertainty with targeted characterization activities, while continuing remediation activities that advance cleanup for key risk-driving contaminants. A core component of cleanup within the Central Plateau is the 200 West Pump-and-Treat (P&T) system. Even with an active P&T remedy, uncertainty exists with respect to plume distributions, total mass in the aquifer, and currently known continuing sources. Additional uncertainty is associated with multiple contaminant source locations in the vadose zone, which have the potential to create new groundwater plumes in the absence of any source control measures, although not all contaminant fluxes to groundwater will result in contaminant concentrations above cleanup levels. Collectively, these uncertainties need to be addressed in the CSM to support effective and efficient site progress toward cleanup goal(s). Other nontechnical factors that may warrant an ASM approach at the Hanford Central Plateau are associated with the formation of operable units (OUs) used to manage cleanup. With the exception of the 200-ZP-1 OU, the three remaining groundwater OUs only have interim action records of decision. Nine vadose zone source area OUs are also in the early stages of the remedial investigation and feasibility study process, with pending characterization and technology identification activities. A set of proposed site objectives for the Central Plateau are provided in this document as an initial consideration/example and basis for discussion for ASM implementation. These example site objectives were selected with the goal of maintaining protectiveness at the Columbia River through confinement of contaminant plumes within an administratively controlled area below existing surface waste sites and waste disposal facilities. Although site decision makers and regulators need to provide concurrence, these site objectives are used in this document to describe the elements of an ASM approach, including selection of interim objectives and a long-term adaptive management plan. Interim objectives are also defined to yield measurable incremental progress toward the overall site goals. This document identifies initial technical considerations for developing an ASM framework for the Central Plateau cleanup decisions. These considerations are intended to facilitate more specific decisions, such as objectives, near- and long-term actions, and performance metrics, to develop an overall approach that maintains protectiveness but recognizes the uncertainty, long timeframe, and technical challenges that need to be considered in selecting, implementing, and managing remediation at the Hanford Central Plateau.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2022

Calibration and Commissioning of the LSST

Understanding the nature of dark energy and dark matter remains one of the fundamental questions in physics today; impacting our understanding of particle physics, cosmology, and possibly theories of gravity. Given the scale and complexity of the next generation of cosmology experiments (e.g., the Rubin Observatory, the Euclid satellite mission, and the Roman space telescope) we are entering an era where statistical noise no longer determines the accuracy to which we can measure cosmological parameters. Our ability to control and correct for systematics will ultimately determine the scientific impact of these experiments. This award addressed the challenge of how we determine what limits the accuracy of our cosmological measures, what techniques are appropriate for measuring and calibrating the properties of galaxies to best constrain cosmological models, how to develop statistical techniques that are insensitive to systematic errors, and how to optimize survey strategies in order to minimize systematics while maximizing the speed at which an experiment can achieve its science objectives. In this final technical report for award DE-SC0011635 we describe a set of open-source frameworks that simulate the characteristics and properties of current and planned cosmology surveys and the application of these frameworks to the development of new methodologies for estimating the properties and distances to galaxies that are robust to noisy and incomplete data.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2023

Tuning anisotropic bonding via chemistry and pressure in layered pnictides and chalcogenides (Final Report)

The overarching goal of this research program, as originally delineated in the proposal “Tuning anisotropic bonding via chemistry and pressure in layered pnictides and chalcogenides” was to develop a predictive, chemistry-driven understanding of the impact of the phonon behavior on thermal properties of bulk layered materials. At finite temperatures, atomic vibrations (phonons) strongly impact the thermodynamics, thermal and electrical transport, and phase-switching properties of functional materials. In particular, soft phonon modes and strongly anharmonic potentials can have spectacular consequences, including structural phase transitions (for example in ferroelectrics and phase-change memory materials), metal-insulator transitions, and extreme thermal resistance preventing heat propagation. Bulk materials with highly-anisotropic bonding may provide unique strategies to induce soft-phonon modes and lattice instabilities. Recently, increasingly detailed investigations of the lattice dynamics in layered materials have been made possible by the advent of first-principles phonon calculations and advanced characterization techniques based on neutron and X-ray scattering. However, due to the lack of studies in which composition and bonding character are systematically varied, there are still fundamental questions regarding the impacts of anisotropic bonding and anharmonicity on lattice stability and thermal transport. One of the major goals of this research program is therefore to address this gap by coherently tuning bonding anisotropy and anharmonicity across families of related compounds. Such approaches have revealed new strategies for exploiting structural anisotropy in quasi-1D and 2D bulk materials to obtain tailored functional properties. This project systematically explored the lattice dynamics, phase stability, and transport properties in bulk layered materials by using both composition and applied pressure to tune the degree of bonding anisotropy and anharmonicity. To accomplish this work, we combined i) single-crystal growth of key material systems with tunable anisotropy, ii) in-situ high-temperature/high-pressure characterization of structure and phonons to probe bonding anisotropy and anharmonicity, including state-of-the-art inelastic X-ray scattering (IXS) and inelastic neutron scattering (INS), and iii) first-principles simulations leveraging large-scale computing to identify the fundamental origins of the observed effects, by relating atomic structure and dynamics to electronic orbital interactions. Finally, we modeled and verified the impact of the phonon behavior on thermal transport to identify new strategies for a-priori design of thermal conductivity. Our integrated collaborative approach helped to systematically unravel the effects of anisotropy and bonding anharmonicity on phonon transport, thermodynamics, and thermal properties of complex anisotropic materials.

30 DIRECT ENERGY CONVERSION↗

DOE OSTI2022

Tuning anisotropic bonding via chemistry and pressure in layered pnictides and chalcogenides. Final Report

36 MATERIALS SCIENCE↗

DOE OSTI2023

Robust highly durable solid oxide fuel cell cathodes – Improved materials compatibility & self-regulating surface chemistry

Solid oxide fuel cells (SOFCs) are electrochemical conversion devices that directly transform hydrogen or hydrocarbon fuels to electricity, with energy efficiencies as high as 90%, coupled with reduced emissions. Several factors, however, remain to be addressed when considering scale-up of SOFC technology, including the need to overcome decreased performance due to sluggish rates of the oxygen reduction reaction (ORR) at the cathode under reduced temperatures and susceptibility to degradation in performance from surface poisoning e.g. from chromia, while limiting the use of critical raw materials (lanthanides and transition metals) present in high performing mixed ionic electronic conducting electrodes like (La,Sr)CoO 3 (LSC). In this project we explored the key descriptors for determining ORR activity in SOFC electrodes and tried to recover performance degradation by applying them to SOFC electrodes. In order to do this, we first selected a model mixed ionic electronic conducting (MIEC) oxide, Pr-doped CeO 2 (Pr 0.1 Ce 0.9 O 2-δ , PCO), which is a chemically stable fluorite and free of inherent poison sources (e.g. Sr segregation in LSC) that potentially react with external impurities such as Cr-species vaporized from the interconnect. The three approaches originally planned in this project are as follows: 1) evaluation of scavenger exsolution characteristics, 2) study of scavengers gettering efficacy following Cr and Si poisoning and 3) integration of new compositions into porous electrodes. Among them, exceptional progress has been made in 2) and 3), especially understanding the role of surface infiltrants in impacting electrode performance and degradation of PCO materials. We found that the Smith acidity scale for binary oxides serves as a powerful descriptor for tuning and predicting the oxygen exchange kinetics on MIEC PCO surfaces. As a result, with infiltration with binary oxides, ranging from strongly basic (Li 2 O) to strongly acidic (SiO 2 ) onto the surface of porous PCO, it was possible to systematically vary the chemical surface exchange coefficient (k chem ) by 6 orders of magnitude! L i2 O increased k chem by nearly 1,000 times over that of pristine PCO, while SiO 2 decreased k chem by nearly the same factor. Strikingly, although the pre-exponential of k chem scales linearly with the acidity of the infiltrated binary oxide, there is nearly no change in the activation energy. With this insight, we attributed the origin of these dramatic changes in k chem values to the systematic increase and decrease in the surface electron density induced by infiltrated binary oxides. More interestingly, although both Cr 2 O 3 and SiO 2 were determined to be acidic by Smith, suggesting that this feature could likely be the primary reason that these compounds serve to poison the ORR on SOFC cathodes, the effect of poisoning could be subsequently tuned by adding multiple infiltrants and controlling their relative surface acidities. We also systematically examined the effect of serial infiltration of basic and acidic oxides. It turned out that serial infiltration of Li not only recovers approximately 20-fold degraded k chem of PCO by acidic Cr 2 O 3 but its k chem is enhanced even beyond that of the non-infiltrated PCO by more than three orders of magnitude. This was further verified with a screen-printing PCO symmetric cell in terms of the electrode performance (area-specific resistance, ASR) related to approach 3). These observations point to acidity as a key descriptor not only in tuning and predicting the ORR activity of SOFC cathodes that largely determines the overall performance of SOFC, but in mitigating and reactivating poisoned electrode performance. This work provides novel guidelines for making the electrode performance much more active and robust in SOFCs, which can further be applied to all applications requiring oxygen exchange reaction, such as electrolyzers, permeation membranes and gas sensors.

30 DIRECT ENERGY CONVERSION↗

DOE OSTI2023

Improving Dark Energy Constraints Using Low-Redshift Large-Scale Structures

The primary goal of this project was to improve constraints on dark energy measurements by improving our ability to extract cosmological information from low redshift large-scale structures. PI Clowe's project's primary aim was to reduce the bias in measurements of the masses of clusters of galaxies to a level where the evolution of the cluster mass function can be used in the Vera Rubin Observatory's Legacy Survey of Space and Time Dark Energy Science Collaboration survey to improve the accuracy of the measurement of dark energy and other cosmological parameters. Co-PI Seo's project studied observational systematics affecting large-scale clustering of galaxies, which will be used to improve dark energy constraints from the Dark Energy Spectroscopic Instrument (DESI). The cluster lensing project employed a series of simulations and observations of clusters of galaxies to test numerous potential systematic errors in cluster mass measurements using weak gravitational lensing as the accuracy of current weak lensing measurements are more than order of magnitude worse than what is required to use clusters of galaxies for accurate determination of dark energy parameters. PI Clowe and group developed and analyzed simulations to test for, and correct biases introduced in, the weak lensing measurement process. Finally, PI Clowe and group developed a method of detecting clusters using galaxy overdensities and applied the method to the BLISS and DES surveys. The success of spectroscopic dark energy mission such as the extended Baryon Oscillation Spectroscopic Survey (eBOSS) and the Dark Energy Spectroscopic Instrument (DESI) will depend on a thorough understanding of various observational systematics in the target density fluctuations that would give rise to spurious, non-cosmological signals. PI Seo and group developed a deep learning, artificial neural network (ANN) technique that modeled and mitigated such effects, aimed at deriving more robust galaxy clustering signals not only for the baryon acoustic oscillation feature and redshift-space distortions but also for primordial non-Gaussianity constraint.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

Improving NOvA's Sterile Neutrino Search with the Booster Neutrino Beam

The NOvA experiment’s most recent search for eV-scale sterile neutrinos is systematically limited in the region of parameter space where $\Delta m^2_{41} \gtrsim 1~\mathrm{eV}^2$. This region of parameter space is preferred by sterile neutrino interpretations of current experimental anomalies; improving sensitivity here is high-priority. When added directly into the fit, additional data samples which are subject to orthogonal systematic uncertainties act as in-situ constraints, breaking the degeneracy between systematic uncertainties and sterile-induced oscillations. The NOvA experiment consists of two functionally identical detectors, 14.6 mrad off-axis of the NuMI beam, with the Near Detector (Far Detector) 1 km (810 km) from the beam source. The Near Detector’s position on-site at Fermilab means that it is also able to observe neutrinos from a second neutrino beam, the BNB, 160 mrad off-axis. NOvA has been taking BNB data since 2015, but has not yet analysed these data. The BNB and NuMI are subject to different beam-related uncertainties, allowing us to leverage this sample as an in-situ constraint. This poster will present the current status, preliminary simulations, and potential additional uses of this unique experimental setup

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2024

Constructing Data-Driven Predictions at the Far Detector for NOvA's Neutrino Oscillation Analysis.

NOvA, is a two-detector, long-baseline neutrino oscillation experiment located at Fermilab, Batavia, IL, USA. It is designed primarily to constrain neutrino oscillation parameters using $\nu_\mu \ (\bar{\nu}_\mu)$ disappearance and $\nu_e \ (\bar{\nu}_e)$ appearance data. The Neutrinos at Main Injector (NuMI) beamline at Fermilab provides a high purity 900 KW intense beam of neutrinos and anti-neutrinos to NOvA. The NOvA Near Detector, located 100m underground and 1km away from the beam source, observes the un-oscillated $\nu_\mu \ (\bar{\nu}_\mu)$ and beam $\nu_e \ (\bar{\nu}_e)$ event spectrum. The Far Detector, located in Ash River, MN, USA, is 809 km from the ND and records the oscillated $\nu_e \ (\bar{\nu}_e)$ and the un-oscillated $\nu_\mu \ (\bar{\nu}_\mu)$ event spectrum. NOvA uses a data-driven technique called extrapolation to predict the expected number of $\nu_\mu \ (\bar{\nu}_\mu)$ and $\nu_e \ (\bar{\nu}_e)$ events at the Far Detector using the Near Detector data. The use of data from a functionally equivalent Near Detector provides a powerful constraint on the systematic uncertainties in NOvA neutrino oscillation analyses. As NOvA continues to add data statistics, a robust constraint on systematics becomes more crucial for neutrino oscillation analysis. The details of the NOvA neutrino oscillation analysis framework and how it constrains dominant systematic uncertainties using the Near Detector data will be discussed in this poster.

43 PARTICLE ACCELERATORS↗

DOE OSTI2024

Latest Three-Flavor Neutrino Oscillation Results from NOvA

NOvA, is a two-detector, long-baseline neutrino oscillation experiment located at Fermilab, Batavia, IL, USA. It aims to constrain neutrino oscillation parameters by analyzing $\nu_\mu (\bar{\nu}_\mu)$ disappearance and $\nu_e (\bar{\nu}_e)$ appearance data. The experiment uses the Neutrinos at Main Injector (NuMI) beamline at Fermilab, which delivers a high-purity 900 KW beam of neutrinos and anti-neutrinos. The detectors are functionally identical finely granulated liquid tracking calorimeters, both situated 14.6 mrad off-axis to the beam direction. The NOvA Near Detector (ND), situated 100 meters underground and 1 kilometer from the beam source, detects the un-oscillated $\nu_\mu (\bar{\nu}_\mu)$ and beam $\nu_e (\bar{\nu}_e)$ events. The Far Detector (FD), located in Ash River, MN, USA, 809 kilometers from the ND, records the oscillated $\nu_e (\bar{\nu}_e)$ and the un-oscillated $\nu_\mu (\bar{\nu}_\mu)$ events. NOvA employs an extrapolation technique to predict the expected events at the Far Detector based on the Near Detector data, thereby providing a significant constraint on systematic uncertainties in the oscillation analyses. As NOvA accumulates more data, controlling these systematic uncertainties becomes increasingly important. This talk will detail the NOvA neutrino oscillation analysis framework and its approach to minimizing dominant systematic uncertainties using Near Detector data. The latest three flavor neutrino oscillation results based on a neutrino-beam exposure of $26.60 \times 10^{20}$ POT and an anti-neutrino beam exposure of $12.50\times 10^{20}$ POT and a novel low energy $\nu_e$ sample, will also be presented.

Choudhary, Brajesh↗

DOE OSTI2025

Investigating Kinetic Mechanisms of Soot Formation in Plasma Pyrolysis of Methane via Active Learning (Final Technical Report)

Plasma pyrolysis of methane is an effective route for zero-carbon hydrogen production. Yet, soot generated from pyrolysis of hydrocarbons is detrimental to the climate and human health. There is ample experimental and theoretical evidence that suggests polycyclic aromatic hydrocarbons (PAHs) are the molecular precursors to soot particles. The reaction pathways of PAH formation are intricately dependent on a multitude of process parameters, whose kinetic mechanisms are not well-understood in plasma pyrolysis. This project aims to leverage advances in the kinetic modeling of soot formation in combustion, as well as in surrogate modeling and active learning, to systematically investigate the effects of process parameter on the kinetics of PAH formation in plasma pyrolysis of methane. To this end, we propose to use the PAH formation kinetics model developed by the PPPL/PU group based on the well-established ABF and HACA mechanisms, coupled with low-temperature plasma models. We will develop an active learning (AL) framework based on Bayesian optimization to systematically and data-efficiently explore the complex and multivariable parameter space of plasma pyrolysis in order to quantify the effects of plasma and feed parameters on the ABF and HACA kinetic pathways. AL is the branch of machine learning concerned with systematically querying samples from a system (experimental or computational) to train a data-driven model that maps design parameters to a performance criterion. We will use the data generated via AL to perform global sensitivity analysis, combined with uncertainty quantification, to elucidate the impact of different reaction pathways on minimizing formation of soot precursors. This study will result in an improved understanding of kinetics of PAH formation in plasma pyrolysis and can pave the way for more advanced mechanistic studies (e.g., soot nucleation mechanisms). Additionally, the findings will be useful for establishing practical strategies for increasing the pyrolysis efficiency and producing high-grade carbon for synthesis of nanomaterials.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2025

Grid Architecture Mapping to Understand Transformation (GAMUT): Concept Definition

The electric power system is undergoing significant transformation driven by changes in the generation mix, increasing reliance on information and communication technologies, evolving customer expectations, and a dynamic cyber-physical environment. To address these challenges, substantial investments will be made over the next decade to create a flexible, affordable, secure, reliable, and resilient electric system. In response, the U.S. Department of Energy's Office of Electricity is developing knowledge management tools aimed at systematically documenting technology pilots and demonstration projects. This initiative seeks to improve understanding of operating contexts, planning steps, and integration requirements for innovative grid technologies. The Department of Energy project leverages Grid Architecture principles to collect and organize insights into the interdependencies, requirements, and capabilities of various grid solutions. By employing a systematic approach, the project aims to perform a feasibility study for the development of a software tool that will support stakeholders, including regulators, transmission and distribution system operators, distributed energy resources aggregators, and technology providers. By offering a systematic, software-based framework to document technologies, understand their benefits and impacts, and inform deployment strategies, the proposed Grid Architecture Mapping to Understand Transformation (GAMUT) Tool is intended to reduce costs, enhance decision-making, and facilitate scaling and effective deployment of new technologies. The feasibility study will evaluate the technical and financial viability of the GAMUT Tool, identifying stakeholder needs and assessing risks and mitigation strategies. Ultimately, the GAMUT team aims to develop an initial minimal viable product, followed by staged improvements, to aid in the modernization of the electric grid, contributing to a more sustainable and resilient energy future.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2026

Electron Neutrino Selection for Neutrino Oscillation Searches in the SBN Program

The Short- Baseline Neutrino (SBN) Pprogram at Fermilab employs a near detector, SBND, and a far detector, ICARUS, to search for baseline-dependent changes to the measure muon neutrino disappearance and electron neutrino appearance and disappearance from the muon neutrino-dominated Booster Neutrino Beam flux. The use of the same liquid argon time projection chamber (LArTPC) technology in both detectors and the same neutrino beam enables a systematically well-constrained oscillation measurement, by leveraging the high statistics of O(10 million) neutrino interactions expected at SBND through 2027 to constrain flux and cross-section systematics. In this poster, we present high-statistics, high-purity electron neutrino selections in SBND and ICARUS and related electron shower energy calibration measurements in SBND enabled by the SPINE deep learning-based particle reconstruction framework. Furthermore, we discuss how these samples can enable high sensitivity to '3+1' sterile neutrino oscillations in a combined fit accounting for systematic uncertainties and correlations.

Oza, Nupur [Nevis Labs, Columbia U.; Columbia U.]↗

DOE OSTI2026

Search for muon neutrino disappearance with multi-topologically splitted Inclusive events at SBN

The Short-Baseline Neutrino (SBN) program at Fermilab searches for signatures of sterile neutrinos with mass-squared splittings at the O(1) eV2 scale, motivated by anomalies previously reported by the LSND and MiniBooNE experiments. We present a search for such signatures using the muon neutrino disappearance channel. This analysis exploits the large statistics of fully inclusive charged-current interactions collected by the SBND and ICARUS detectors to maximize sensitivity. The inclusive samples in both detectors are further subdivided into multiple exclusive topological channels, a strategy designed to enhance sensitivity by isolating differences in interaction-mode composition and reconstructed energy response. This multi-topology approach represents a novel analysis technique within SBN, enabling improved constraints on systematic uncertainties arising from neutrino flux, interaction modeling, and detector response. We will present comparisons of data with detailed predictions incorporating a comprehensive treatment of systematic uncertainties and constraints on the systematics obtained by the multi-topology method.

Yadav, Shweta [Texas U., Arlington]↗

DOE OSTI2026

Using AI to Reproduce Neutrino Cross Section Analysis - Prototyping the Neutrino Discovery Platform

The Neutrino Discovery Platform (NDP) aims to accelerate DUNE-era science by making the neutrino program's existing datasets analyzable through fast, reproducible, and auditable workflows. We report a working version of two of its layers, data curation and agentic orchestration, built and tested end to end on MINERvA open data. The guiding lesson throughout is that a cross section is a measurement, and not just a plotted shape, only if it carries a defensible systematic-uncertainty budget, a trustworthy unfolding, and a reproducible record. Using a single medium-energy playlist pair from the MINERvA open-data release (about $2.05\times10^{17}$ protons on target of data), we first reproduced the shapes of two published charged-current inclusive $\nu_\mu$ measurements through a complete extraction ladder: selection, background subtraction, D'Agostini unfolding, efficiency correction, and flux normalization. These shape-level reproductions ran and tracked the published results, but they lacked the systematic-uncertainty machinery that defines a MINERvA cross section. To supply it, we vendored and built the MINERvA Analysis Toolkit and developed a many-universe systematic-uncertainty tool that produces a portable covariance artifact, a parallel event-loop runner, and a per-run auditability harness. Validated against a published covariance release, the toolchain reproduces the released statistical, flux, and muon-energy-scale terms and shows that they account for roughly 63\% of the total variance, with the remainder unreleased. Using this same infrastructure, we then performed a measurement of our own design, the hadronic recoil-energy distribution of low-energy ($E_\nu<2.5$~GeV) charged-current inclusive events, and found data/simulation shape agreement of $\chi^2/\mathrm{ndf}=1.26$. Together these results show that the platform supports original physics and not only reproductions.

Breaux, Auto [Tulane U. (main)]↗

DOE OSTI2026

AI-driven Neutrino Beam Diagnostics for Next-Generation Neutrino Experiments

The accelerator-driven beam uncertainty limits oscillation measurements in long-baseline neutrino experiments. Spill-resolved beam diagnostics and real-time inference are necessary to address these neutrino flux systematics. As such, we present a machine-learning-based beam monitoring framework developed and validated using data from the T2K experiment. Our approach uses downstream, spill-by-spill muon monitor observables to predict upstream parameters such as proton beam position and width. We achieve high predictive accuracy on nominal runs, demonstrating robust baseline performance whether the model is trained on stable runs or systematically varied conditions. The framework is designed to be robust against domain shifts, allowing the neural network architectures and inference strategies developed with T2K data to be retrained and validated using LBNF simulations, with the goal of eventual deployment under real LBNF/DUNE operating conditions. This scalable approach to real-time beam inference offers a pathway toward reducing flux systematics for next-generation neutrino experiments such as DUNE.

Aney, Noah [Fermilab; U. Chicago (main)]↗

DOE OSTI2024

Evaluation of Uncertainties of Pressure Gain Measurements in Rotating Detonation Combustor

Experimentally measuring the pressure gain of a rotating detonation combustor through the method of equivalent available pressure is prone to many experimental uncertainties. A detailed analysis of sources of random and systematic uncertainties in the thrust and pressure gain is performed using data from a hydrogen/air-operated rotating detonation combustor. The combustor had an axial air inlet and a 50% exit constriction. The measured (negative) pressure gain values agree with the results in the literature for similar inlet-to-exit area ratios. The base drag correction on the centerbody was found to be the greatest source of uncertainty for the thrust. While thrust is the predominant source of random uncertainty in the pressure gain calculation, significant systematic errors can be committed due to the assumed exit Mach number. The impact of this assumption becomes more detrimental the closer to positive the measured pressure gain is. By experimentally evaluating the exit Mach number, the random and systematic uncertainty in pressure gain both decreased, indicating that this should be an essential step. A definitive demonstration of gain is challenging, given the assessed uncertainties, and recommendations are provided to increase the precision of the equivalent available pressure methodology.

Engineering↗

DOE OSTI2026

Characterization of the Polarization Beam Response of SPT-3G Using Point Sources

Precise measurements of cosmic microwave background (CMB) polarization require rigorous control of instrumental systematics. For the South Pole Telescope's third-generation camera (SPT-3G), which observes in three bands centered near 95, 150, and 220 GHz, accurate beam characterization is critical for interpreting the polarized mm-wave sky. We present direct measurements of SPT-3G's polarized beam response from observations of 100 bright extragalactic point sources. Previous SPT-3G power spectrum analyses introduced a phenomenological parameter, $β_{\rm pol}$, to describe the polarization preserved in beam sidelobes, and found evidence for significant depolarization from the requirement of inter-frequency polarization power spectrum consistency. Our direct measurements yield $β_{\rm pol}=0.89\pm0.10$ at 95 GHz, $1.08\pm0.10$ at 150 GHz, and $0.90\pm0.22$ at 220 GHz, indicating minimal sidelobe depolarization. We validate these results with systematic tests of posterior sampling versus bootstrap resampling, real-space versus Fourier-space analysis, temperature-to-polarization leakage handling, covariance determination, and source selection. Compared to values inferred from previous cosmological analyses, our results differ by an effective $1.3σ$. This apparent discrepancy is model dependent, because the point source analysis derives much of its $β_{\rm pol}$ constraining power from higher multipoles than the power spectrum analysis. These measurements therefore admit three explanations for the frequency-dependent residuals observed in the power spectrum analysis: a statistical fluctuation, the need for more sophisticated polarized beam models, or systematics other than beam depolarization.

de Haan, T. [KEK, Tsukuba]↗

DOE OSTI2022

Life-Cycle and Techno-Economic Assessment of Early-Stage Carbon Capture and Utilization Technologies—A Discussion of Current Challenges and Best Practices

The mitigation of climate change requires research, development, and deployment of new technologies that are not only economically viable but also environmentally benign. Systematic and continuous technology assessment from early technology maturity onwards allows assessment practitioners to identify economic and environmental characteristics. With this information, decision-makers can focus time and resources on the most promising technologies. A broad toolset for technology assessment exists—stretching from the well-established life cycle assessment (LCA) methodology to more loosely defined techno-economic analysis (TEA) methods and the increasingly popular principles of technology maturity assessment such as the concept of technology readiness levels (TRL). However, current technology assessment practice faces various challenges at early stages, resulting in a potential mismatch of study results and stakeholders' needs and an escalation of assessment effort. In this practice review, we outline current challenges in the interplay of LCA, TEA, and TRL and present best practices for assessing early-stage climate change mitigation technologies in the field of carbon capture and utilization (CCU). The findings help practitioners systematically identify the TRL of a technology and adapt technology assessment methodologies accordingly. We highlight the methodological challenges for practitioners when adapting the goal and scope, identifying benchmark technologies, creating a comprehensive inventory, comparing early stage to commercial stage, ensuring clarity of recommendations for decision-making under high uncertainty, and streamlining conventional LCA and TEA assessment approaches and provide actionable recommendations. Overall, this work contributes to identifying promising technologies faster and more systematically, accelerating the development of new technologies for climate change mitigation and beyond.

54 ENVIRONMENTAL SCIENCES↗