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Order-by-order uncertainties of nucleon-nucleon Wolfenstein amplitudes in chiral effective field theory

Quantum mechanical invariance principles dictate the most general operator structure that can be present in the nucleon-nucleon (NN) interaction. Five independent operators appear in the on-shell NN amplitude together with five corresponding coefficient functions. The usual choice for these coefficient functions is known as the NN Wolfenstein amplitudes. We analyze the order-by-order convergence of each of the five NN Wolfenstein amplitudes predicted by a semilocal coordinate space potential implementation of chiral effective field theory (𝜒⁢EFT). We do this at laboratory kinetic energies between 25 and 200 MeV for both neutron-proton and proton-proton scattering. Our analysis uses the Gaussian-process methods developed by the BUQEYE Collaboration to describe the contributions of each 𝜒⁢EFT order, and so yields truncation uncertainties for each Wolfenstein amplitude that are correlated across scattering angles. We combine information on the size of different orders in the EFT to infer the 𝜒⁢EFT breakdown scale for each amplitude, finding, on average, Λ 𝑏 between 750 and 800 MeV. Furthermore, with this choice of Λ 𝑏 , the EFT truncation uncertainties cover both higher-order results and empirical Wolfenstein amplitudes well for all orders other than the leading order.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS

Development of Scalable Coastal and Offshore Macroalgal Farming

The US DOE/ARPA-E MARINER program funded a four-year project to determine an optimal way to grow kelps in large, nearshore and offshore arrays for the eventual purpose of biofuel production with the goal of keeping the cost below $\$$80 USD per dry metric ton of kelp. This project specifically looked at how Saccharina latissima can be grown in the Gulf of Alaska to reach that goal. There were three major aspects of the research: 1) optimizing nursery production and seeding lines for outplanting, 2) designing an economical, modular outplanting structure and 3) developing methods to efficiently harvest the product. Farm designs were based on catenary structures and the use of spreader bars with variable spacing of grow lines and line types. The spacing of the grow lines makes a difference in the yield. Grow line spacing of ≥1.5m showed about a 50% increase in kg/m. There was no statistical difference in the growth of Saccharina latissima whether in the middle or the outside of the array, but the line type and perhaps line thickness can make a difference in yield. Sagging caused by the weight of the mature fronds resulted in lower growth at depth. Various harvesting approaches for mature kelps were tested by collaborating farmers. One promising innovation is the use of large bags for holding the freshly harvested fronds. Although the weight of the fronds on the growlines causes the lines to sink, the bags packed with the harvested fronds float, allowing for easy loading to the transfer vessel. Another advance in harvesting is a specially built harvest vessel, the Harvest Buddy, allowing a more mechanized and faster way to harvest. A significant aspect of this project was the TTO/T2M. Several different outreach activities were performed by the Alaska Fisheries Development Foundation and GreenWave. A techno-economic assessment (TEA) using our data has pointed to solutions to reach the $\$$80 goal. A second phase of this project involved the co-culture of two different species of kelps. Interest in farming kelps has grown beyond using kelp for food, feed or biofuels. There is considerable interest in generating biomass from seaweed for use in bioplastics and other products that would substitute for petroleum-derived products. For these uses to be viable, large amounts of biomass are needed. Very large kelp farms can be expensive to build and maintain, leading to the need to optimize the biomass per unit area. Although close spacing of growlines can lead to poor growth, a viable approach may be to grow two species of kelps together: one that hangs down and one that is buoyant, growing up. This system would increase the spacing in three dimensions. In Alaska, Saccharina latissima is commonly grown hanging down from longlines. One of the buoyant Alaskan kelps is Nereocystis luetkeana. Because there are commercial uses for wild-harvested Nereocystis in Alaska, we undertook a preliminary trial in Kodiak, Alaska that grew both Saccharina and Nereocystis in the same longline array. Closely spaced lines were seeded the first week of February 2023 and set at 3m below the surface. The arrays were harvested in late June 2023. Despite having 45% fewer grow-lines, the total yield of the Nereocystis on the combined arrays was statistically similar to the Nereocystis only arrays. Total yields were greatest on the combined arrays, followed by the Nereocystis only and Saccharina only arrays. These results may have significance for large scale macroalgal production.

09 BIOMASS FUELS

Atacama Cosmology Telescope: DR6 gravitational lensing and SDSS BOSS cross-correlation measurement and constraints on gravity with the 𝐸 𝐺 statistic

We derive new constraints on the 𝐸 𝐺 statistic as a test of gravity, combining the cosmic microwave background (CMB) lensing map estimated from Data Release 6 (DR6) of the Atacama Cosmology Telescope with Sloan Digital Sky Survey III Baryon Oscillation Spectroscopic Survey (SDSS BOSS) CMASS and LOWZ galaxy data. We develop an analysis pipeline to measure the cross-correlation between CMB lensing maps and galaxy data, following a blinding policy and testing the approach through null and consistency checks. By testing the equivalence of the spatial and temporal gravitational potentials, the 𝐸 𝐺 statistic can distinguish Λ⁢ CDM from alternative models of gravity. We find 𝐸 𝐺 ⁡(𝑧 eff = 0.555) = 0.3⁢1$^{+0.06}_{−0.05}$ for Atacama Cosmology Telescope (ACT) and CMASS data at 68.28% confidence level, and 𝐸 𝐺 ⁡(𝑧 eff = 0.316) = 0.4⁢9$^{+0.14}_{−0.11}$ for the ACT and LOWZ. Systematic errors are estimated to be 3% and 4%, respectively. Including CMB lensing information from Planck PR4 results in 𝐸 𝐺 ⁡(𝑧 eff = 0.555) = 0.3⁢4$^{+0.05}_{−0.05}$ with CMASS and 𝐸 𝐺 ⁡(𝑧 eff = 0.316) = 0.4⁢3$^{+0.11}_{−0.09}$ with LOWZ. These are consistent with predictions for the Λ⁢ CDM model that best fits the Planck CMB anisotropy and SDSS BOSS baryon acoustic oscillations (BAO), where 𝐸$^{GR}_{𝐺⁡}$(𝑧 eff =0.555) =0.401 ± 0.005 for CMB lensing combined with CMASS and 𝐸$^{GR}_{𝐺}$⁡(𝑧 eff = 0.316) = 0.452 ± 0.005 combined with LOWZ. We also find 𝐸 𝐺 to be scale independent, with probability to exceed >5%, as predicted by general relativity. The methods developed in this work are also applicable to improved future analyses with upcoming spectroscopic galaxy samples and CMB lensing measurements.

79 ASTRONOMY AND ASTROPHYSICS

In-Silico Design of Next Generation Cellulose-Derived Packaging Materials (CRADA Final Report)

Developing sustainable solutions for single-use packaging is an important objective to combat the environmental crisis of plastics pollution. Most embodiments of cellulose-based packaging materials, including CellophaneTM, are completely biodegradable in both terrestrial and marine environments. However, petroleum-derived alternatives offer some performance advantages for metrics such as moisture barriers and mechanical properties. This project leverages molecular dynamics simulation to investigate how molecular modifications to cellulose-based polymer assemblies impact their material properties. An important performance criterion for the modified materials was to retain biodegradability; thus, modifications by naturally occurring, biodegradable additives were the focus of this study. Specifically, we developed models with xylan and lignin of varying monomeric compositions into the cellulose matrix. The mechanical properties were investigated by performing stress-strain simulations, and the water barrier and hydrophobicity were investigated by simulating the water contact angle. Our findings indicate that the incorporation of xylan into the cellulose matrix tends to increase the mechanical properties with an optimal loading of ~27 wt%. We also predict that orienting the nanoscale directionality of the xylan chains such that they are perpendicular to the cellulose fibrils will dramatically increase mechanical strength. In contrast, the incorporation of lignin tends to weaken the composite at all loadings investigated. Simulations of water contact angle predicted that coating polymers on the surface of the cellulose assembly creates a more hydrophobic surface than incorporating them throughout the matrix. Of the coatings investigated, lignin resulted in the most hydrophobic surface, followed by pectin and keratin, which both imparted modest increases in hydrophobicity. Future experimental work done by Futamura will focus on designing material prototypes to capitalize on the predictions of performance enhancement obtained from molecular modeling. While substantial progress was made by the simulations performed in this project, there still exists a vast parameter space that we were unable to investigate, including branching, functional group decoration, and degree of polymerization of polymer additives. However, the methods developed in this initial investigation will facilitate more rapid evaluation of the impact of molecular characteristics on the performance of biopolymer composite materials and thereby accelerate future materials discovery efforts in this area.

36 MATERIALS SCIENCE

Artificial Soiling Replication of Field Losses on Commercial Photovoltaic Modules

Here, this study demonstrates the capabilities of an indoor artificial soiling approach developed to closely replicate the natural, cyclic soil accumulation processes in the field-dust suspension, deposition, and sedimentation/cementation-for a subtropical climate. In this work, a near-field environment is replicated in an artificial soiling cubic chamber through controlled regulation of humidity, temperature, dust type, and dust concentration, based on site-specific historical climate data. Two different models (MA and MB) of full-size commercial photovoltaic modules from a single manufacturer, installed side by side in the mid-Atlantic United States, were retrieved and subjected to artificial soiling experiments and various characterization measurements, including short-circuit current, colorimetry, reflectance, X-ray fluorescence, laser diffraction, and optical microscopy. Both in the field and in our improved field-representative artificial soiling tests, the MA model experienced roughly twice the soiling loss as the MB model. To closely replicate the field soiling losses for a site-specific climate, it is critical to include: 1) The use of field-collected dust with identical dust chemistry and particle distribution instead of standardized ISO 12103 Arizona Road dusts, 2) the use of only a small amount of field-collected dust inside the chamber during the deposition process (e.g., 0.15 g), and 3) the preconditioning of the surface coating for the partial/full dose of UV stress as experienced in the field during sunlight exposure and the abrasion as experienced in the field during regular module cleaning activities, if/as needed. The field-representative artificial soiling method developed here could potentially be adopted for rank ordering of various antisoiling coatings developed by researchers and industry stakeholders.

14 SOLAR ENERGY

Extreme Ultraviolet and Beyond Extreme Ultraviolet Lithography Using Amorphous Zeolitic Imidazolate Resists Deposited by Atomic/Molecular Layer Deposition

Amorphous zinc-imidazolate (aZnMIm) resists show potential to meet the demands for next-generation high-numerical aperture (high-NA) metal-containing extreme ultraviolet (EUV) resist materials, given their ease of deposition by atomic/molecular layer deposition (ALD/MLD) at thicknesses of 20 nm and below. Here, this study demonstrates that aZnMIm thin films, previously identified as high-resolution electron beam resists, can also function as negative-tone EUV photoresists. Water development achieves high sensitivity (5 mJ/cm 2 ) but leaves significant residue, while acetic acid development results in poor contrast. A hybrid approach─water followed by acetic acid─enables residue-free development with a sensitivity of 181 mJ/cm 2 . Dry development using 1,1,1,5,5,5-hexafluoroacetylacetone (hfacH) is also possible but shows lower sensitivity (375 mJ/cm 2 ) compared to wet development methods. EUV photoelectron spectroscopy (PES), reflectometry/EUV absorption, total electron yield (TEY), residual gas analysis (RGA), and time-of-flight secondary ion mass spectrometry (TOF-SIMS) were used to investigate the effects of EUV irradiation on aZnMIm resists. Reflectometry experiments reveal an aZnMIm EUV absorption coefficient of 6.2 μm –1 , while PES and TEY analyses show that, compared to poly(4-hydroxystyrene) (PHS), a polymer-based reference resist, aZnMIm emits more primary and secondary electrons but generates fewer slow electrons relative to its primary electron emission; its total electron yield is similar to that of poly(methyl methacrylate) (PMMA) resists. When exposed to EUV, aZnMIm predominantly outgasses H 2 , as determined by RGA. TOF-SIMS measurements demonstrate that high-dose EUV exposure only partially fragments the 2-methylimidazole (2MIm) organic linkers, unlike high-dose electron beam exposure, which is known to completely degrade them. Additionally, aZnMIm resists show promise for potential beyond EUV lithography (BEUVL) due to the presence of Zn, which provides higher sensitivity at a wavelength of 6.7 nm compared to other metal ions, such as Sn, that are currently used in the best-performing EUV metal–organic resists. TEY measurements demonstrate that aZnMIm emits nearly twice as many electrons as PHS at 6.7 nm. The BEUV TEY of aZnMIm also surpasses that of PMMA, poly(pentafluorostyrene), and poly(4-iodostyrene), with the latter two being known for their high EUV TEYs. This work provides insight into zeolitic imidazolate framework (ZIF)-based EUV and BEUV resists and highlights their potential for both wet and dry development.

lithography

A synthetic strategy for the preparation of alkoxy‐functionalized bis‐1,2,4‐triazinyl‐2,6‐pyridines

Heteroaryl-1,2,4-triazine complexants are commonly utilized in separation science for the selective chelation of minor An from Ln in simulated high-level waste. Furthermore, to facilitate access to relevant chemical entities for hypothesis-driven inquiry toward improved separations performance, a synthetic method to construct various alkoxy-complexant derivatives was required. In this work, a convergent synthetic strategy for the production of 3,3′- and 4,4′-tetraalkoxy-bis-1,2,4-triazinyl-2,6-pyridines from readily available starting materials via a dealkylation/alkylation/condensation approach is described. Synthetic method development, substrate scope, preliminary solubility, and hydrolytic stability data in various process-relevant diluents are reported herein.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH

Kinetic Investigation by Batch Processing of Film Growth during the Electrodeposition of Titanium from Ethaline

Titanium electrodeposition as a technological advance has been out of reach due to the poor film quality obtained when using previously developed methods. This study shows that the electrodeposition of Ti is possible and feasible from the deep eutectic solvent ethaline. Moreover, this study shows through batch analysis that this deposition has temperature-dependent aspects that alter the film deposition kinetics upon modest heating. This ultraviolet–visible spectroscopic study is highlighting the more facile reduction of Ti 4+ to Ti 3+ and then to Ti 2+ at elevated temperatures. Understanding the underlying kinetics of electrodeposition opens up new venues for the application of this important metal.

36 MATERIALS SCIENCE

Constraints on long-range forces in de Sitter space

The representation theory of de Sitter space admits partially massless (PM) particles, but whether such particles can participate in consistent interacting theories remains unclear. We investigate the consistency of theories containing PM fields, particularly when these fields are coupled to gravity. Our strategy exploits the fact that PM fields correspond to partially conserved currents on the spacetime boundary, which generate symmetries. These symmetries place stringent constraints on correlation functions of charged operators, allowing us to test the consistency of a proposed bulk spectrum. When the assumed operator content violates these constraints, the corresponding bulk theory is ruled out. Applying this framework, we show that, in four-dimensional de Sitter space, PM fields of spin 2 or 3 (at depth 0) cannot couple consistently to gravity: such couplings necessitate additional massive fields, which are inevitably non-unitary. In higher dimensions, however, the constraints can be satisfied without violating unitarity if further PM fields are included. The resulting structure leads to additional charge conservation laws, which suggests that consistency may ultimately require an infinite tower of higher-spin PM fields, akin to the situation for ordinary higher-spin symmetries. The methods developed here provide powerful constraints on possible long-range interactions in de Sitter space and delineate the landscape of consistent quantum field theories in cosmological spacetimes.

AdS-CFT Correspondence

SCALE inventory and reactivity analysis as part of the Hermes 2021 PSAR review

The readiness of SCALE for comprehensive studies of pebble-bed reactors has been demonstrated through detailed analysis of a fluoride salt–cooled, high-temperature pebble-bed reactor (PB-FHR). The methods developed for pebble-bed reactor modeling in SCALE, particularly for inventory generation, have proven effective in gaining insights into the reactor physics of this advanced reactor. Excellent agreement with another code package has been observed, further highlighting SCALE’s strong performance. The SCALE results supported the US Nuclear Regulatory Commission’s construction permit application review of the Hermes low-power PB-FHR demonstration reactor. A SCALE model of the Hermes reactor was developed at Oak Ridge National Laboratory using information from the Preliminary Safety Analysis Report (PSAR) and supplemented with publicly available data. SCALE reactivity coefficient simulations reproduced PSAR results within 1σ statistical uncertainties. Sensitivity studies emphasized the importance of graphite specifications for accurate keff predictions.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS

Evaluation of IrO 2 catalysts doped with Ti and Nb at industrially relevant electrolyzer conditions: A comprehensive study

A series of commercial Oxygen Evolution Reaction (OER) IrO 2 -based materials doped with acid-stable titanium and niobium species were comprehensively characterized by Brunauer-Emmett-Teller (BET), X-ray diffraction analysis (XRD), X-ray photoelectron spectroscopy (XPS), transmission electron microscopy (TEM) with energy dispersive spectroscopy (EDS), and X-ray Scattering. Electrocatalysts were integrated into Membrane Electrode Assembly (MEA) using a fabrication method developed under the US DOE H2NEW consortium. An electrolysis performance in a commercial setup as well as a laboratory screening system was performed at conditions relevant to industrial application. According to the comprehensive characterizations, the studied materials are closer to doped iridium oxides rather than core–shell structures. In an electrolysis cell, the IrO 2 /TiO x catalyst slightly outperforms the IrO 2 /NbO x based on the activity. It was demonstrated that the operation of electrolysis cells at elevated temperatures and the implementation of thinner Nafion-type membranes allows for substantially increased performance, which is consistent with the literature report. Finally, this work provides valuable baselines including characterization and performance for guiding future research in this direction.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH

Optimizing a chemical cleaning protocol to determine the nickel isotopic composition of ancient seawater from carbonates

Reconstructing the ancient marine cycle of Ni, a trace metal in the oceans essential to enzymes regulating the C, N, and O cycles, would inform how Ni bioavailability shaped early life. The Ni isotopic composition of seawater (δ 60 Ni SW ) through time could provide insight, but this approach requires sedimentary archives that faithfully record δ 60 Ni SW . Carbonates are an often-used record of seawater chemistry, but contaminants could bias the measured δ 60 Ni of bulk sediment. To isolate the true carbonate-bound δ 60 Ni signal, we optimized a chemical cleaning protocol designed to minimize non‑carbonate Ni contributions and maximize carbonate recovery. We analyzed ODP Site 1007 sediments and evaluated oxidative and reductive pre-cleaning steps and carbonate dissolution protocols. Our results show that only reductive cleaning significantly altered the subsequent carbonate leachate composition, lowering Ni/Ca ratios by up to 60% and δ 60 Ni values by as much as 0.4 ‰. In contrast, δ 60 Ni values were largely insensitive to premature carbonate dissolution during pre-cleaning or to partial leaching of silicates during carbonate dissolution, even at higher acid molarities or longer reaction times. We recommend an evidence-based protocol that removes hydro-soluble salts and clays, applies reductive cleaning and oxidative cleaning for certain sample compositions, and dissolves carbonate using 0.5 M acetic acid, adjusted to pH 5. Using these results, we infer a ∼ 0.9 ‰ Ni isotopic fractionation between chemically cleaned deep-water carbonates (+0.4 ± 0.1 ‰) and deep seawater. This method development is a key step toward accurately reconstructing ancient marine Ni cycles.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH

Constrained or unconstrained? Neural-network-based equation discovery from data

Throughout many fields, practitioners often rely on differential equations to model systems. Yet, for many applications, the theoretical derivation of such equations and/or the accurate resolution of their solutions may be intractable. Instead, recently developed methods, including those based on parameter estimation, operator subset selection, and neural networks, allow for the data-driven discovery of both ordinary and partial differential equations (PDEs), on a spectrum of interpretability. The success of these strategies is often contingent upon the correct identification of representative equations from noisy observations of state variables and, as importantly and intertwined with that, the mathematical strategies utilized to enforce those equations. Specifically, the latter has been commonly addressed via unconstrained optimization strategies. Representing the PDE as a neural network, we propose to discover the PDE (or the associated operator) by solving a constrained optimization problem and using an intermediate state representation similar to a physics-informed neural network (PINN). The objective function of this constrained optimization problem promotes matching the data, while the constraints require that the discovered PDE is satisfied at a number of spatial collocation points. We present a penalty method and a widely used trust-region barrier method to solve this constrained optimization problem, and we compare these methods on numerical examples. Our results on several example problems demonstrate that the latter constrained method outperforms the penalty method, particularly for higher noise levels or fewer collocation points. This work motivates further exploration into using sophisticated constrained optimization methods in scientific machine learning, as opposed to their commonly used, penalty-method or unconstrained counterparts. For both of these methods, we solve these discovered neural network PDEs with classical methods, such as finite difference methods, as opposed to PINNs-type methods relying on automatic differentiation. Here, we briefly highlight how simultaneously fitting the data while discovering the PDE improves the robustness to noise and other small, yet crucial, implementation details.

Data-driven discovery

Overview of oxygen opacity experiments at the National Ignition Facility and investigation of potential systematic errors

Experiments to measure oxygen opacity at stellar interior conditions have been performed at the National Ignition Facility in a Discovery Science campaign. These experiments utilize the Opacity-on-NIF platform with a sample comprised of O, Mg, and Si. The spectral data from the Opacity Spectrometer cover the 1000–2000 eV photon energy range showing bound-free continuum absorption from O and line absorption from Mg and Si. DANTE and the Gated X-ray Detector are employed to measure the sample plasma’s temperature and density, respectively. Initial data show lower transmission than expected by theoretical models, raising questions of whether potential background or data uniformity concerns could produce systematic errors in the inferred transmission. Here, we investigate three concerns thought to be important for the oxygen opacity data, including instrumental scattered background, sample self-emission non-uniformity, and backlight continuum non-uniformity. Additionally, we show the effect of a recently developed method to account for 2nd order crystal reflection. The total effect of these concerns on one experiment is found to be small compared to the observed difference between the inferred transmission and a model calculation at the inferred temperature and density. Thus, we conclude that these potential sources of systematic error cannot account for the observed difference, increasing the likelihood of a real effect due to the high temperature and density conditions. However, because this is only a single experiment, we cannot make a firm conclusion. More experiments measuring the opacity and necessary calibrations are needed to assess the reproducibility and uncertainty of this result.

79 ASTRONOMY AND ASTROPHYSICS

Rapid assessment of the creep rupture life of metals: A model enabling experimental design

Prediction of the creep rupture life of engineering metals is critical for qualification and design of new materials. The use of long-term creep tests and the need to quantify the performance variability in a priori similar systems hinder the rapid creep assessment of a given material. Therefore, it is essential to develop methods that can extrapolate the long-term performance of alloys and the associated variability from short-term experiments. To this end, this study introduces a new model which enables the estimation of the rupture life of a material for a given stress and temperature. This model relies on two components. First, a new relation for the minimum creep rate (MCR) of materials is introduced. It includes a stress dependent stress exponent allowing the model to capture the variation of MCR across a wide range of temperatures and stresses. Second, employing the Monkman-Grant (MG) law, we establish a relation between stress, temperature and creep rupture life. Together, these two elements yield a new closed-form mathematical expression for the Larson Miller parameter as a function of stress and temperature. This expression captures the creep rupture time for many metals (Gr91, Copper, Gr122 and 347H) and compares favorably with alternate empirical approaches. The model is then used to assess the minimum duration of creep rates necessary to qualify the material up to 100000h. Furthermore, it is found that depending on the material system, creep tests as few as five limited to 5000 h for steels (Gr91, Gr122, 347H) and 100 h for copper are sufficient to model creep lifetimes. Finally, using a Bayesian inference-based approach to calibrate the model, we demonstrate that variability in rupture life can be captured via the quantification of the uncertainty in the model parameters and extrapolated from a limited number of short to moderately short creep tests; thereby paving the way for accelerated creep testing.

36 MATERIALS SCIENCE

Extending wire-arc directed energy deposition using non-gravity aligned (NGA) torch methods

For standard Additive Manufacturing (AM) processes, traditional path planning typically relies on a 2.5-dimensional approach. In wire-arc directed energy deposition (DED), commonly referred to as wire-arc additive manufacturing (WAAM), this 2.5D approach inherently limits final near net shape due to the stair-step effect and restricts the maximum overhang angle achievable without part degradation. To achieve better near net shape and part quality, a 3D planning approach that modulates the tool tip position and angle without process changes is demonstrated in components containing up to 105° of unsupported overhang. The experimental methods are validated with half and fully enclosed cylinder sections containing 90° of overhang. The non-gravity aligned methods are then applied to a commercial WAAM system for a composite tool mold demonstrator part. As a result, the methods developed in this paper enable expansion of WAAM system capabilities to parts containing large overhangs without compromising the net shape or material structure of the resulting parts and without the need for a part positioner.

Additive manufacturing

Mu2e straw tube tracker gas flow quality control

Here, we present a tracker gas flow quality control method developed for the Mu2e straw tube tracker. Using time-dependent current measurements, we quantify the onset time of ionization gain induced by an 55 F source during gas exchange, which is correlated to the gas conductance in the straw. This allows for the identification of channels with inadequate flow. This approach is broadly applicable to other gaseous detectors that require high-channel-count screening.

Flow

An analysis of physics limited dispatch of nuclear renewable integrated energy systems using deep reinforcement learning and dynamic modeling

Previous approaches to dispatching nuclear integrated energy systems (NIES) have focused on the profitability and flexibility of these systems to operate on energy grids with highly variable pricing. However, due to the complexity involved in modeling and designing these systems, there has been less emphasis on ensuring that these dispatch strategies are physically achievable. It is imperative to develop methods that allow the system to remain within the desired NIES operating conditions and perform this based on realistic limited forecasted information. This research employs next generation artificial intelligence, namely deep reinforcement learning (DRL), and a dynamic system model written in Modelica to find a safe and profitable dispatch strategy for a solar nuclear hybrid design. The DRL agent is shown to find a novel dispatch strategy that manages both power ramping and power levels while respecting operational limits. This DRL-based dispatch is compared to other dispatching strategies including an optimal design solution from mixed integer linear programming (MILP). It is found that incorporating the physics of such a tightly coupled NIES limits the profitability of the MILP-based dispatch strategy. As a result, the MILP solution overestimates the design’s generated revenue. In contrast, DRL significantly reduces the number of breaches of safe operational conditions during energy arbitrage while maintaining profitability. Furthermore, this work paves the way for a more detailed assessment of NIES profitability and could be used to aid operator decisions on future NIES projects.

14 - SOLAR ENERGY