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DOE OSTI2022

Modeling land use and land cover change: using a hindcast to estimate economic parameters in gcamland v2.0

Abstract. Future changes in land use and cover have important implications for agriculture, energy, water use, and climate. Estimates of future land use and land cover differ significantly across economic models as a result of differences in drivers, model structure, and model parameters; however, these models often rely on heuristics to determine model parameters. In this study, we demonstrate a more systematic and empirically based approach to estimating a few key parameters for an economic model of land use and land cover change, gcamland. Specifically, we generate a large set of model parameter perturbations for the selected parameters and run gcamland simulations with these parameter sets over the historical period in the United States to quantify land use and land cover, determine how well the model reproduces observations, and identify parameter combinations that best replicate observations, assuming other model parameters are fixed. We also test alternate methods for forming expectations about uncertain crop yields and prices, including adaptive, perfect, linear, and hybrid approaches. In particular, we estimate parameters for six parameters used in the formation of expectations and three of seven logit exponents for the USA only. We find that an adaptive expectation approach minimizes the error between simulated outputs and observations, with parameters that suggest that for most crops, landowners put a significant weight on previous information. Interestingly, for corn, where ethanol policies have led to a rapid growth in demand, the resulting parameters show that a larger weight is placed on more recent information. We examine the change in model parameters as the metric of model error changes, finding that the measure of model fitness affects the choice of parameter sets. Finally, we discuss how the methodology and results used in this study could be used for other regions or economic models to improve projections of future land use and land cover change.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2016

TREAT Neutronics Analysis and Design Support, Part II: Multi-SERTTA-CAL

Experiment vehicle design is necessary in preparation for Transient Reactor Test (TREAT) facility restart and the resumption of transient testing to support Accident Tolerant Fuel (ATF) characterization and other future fuels testing requirements. Currently the most mature vehicle design is the Multi-SERTTA (Static Environments Rodlet Transient Test Apparatuses), which can accommodate up to four concurrent rodlet-sized specimens under separate environmental conditions. Robust test vehicle design requires neutronics analyses to support design development, optimization of the power coupling factor (PCF) to efficiently maximize energy generation in the test fuel rodlets, and experiment safety analyses. In integral aspect of prior TREAT transient testing was the incorporation of calibration experiments to experimentally evaluate and validate test conditions in preparation of the actual fuel testing. The calibration experiment package established the test parameter conditions to support fine-tuning of the computational models to deliver the required energy deposition to the fuel samples. The calibration vehicle was designed to be as near neutronically equivalent to the experiment vehicle as possible to minimize errors between the calibration and final tests. The Multi-SERTTA-CAL vehicle was designed to serve as the calibration vehicle supporting Multi-SERTTA experimentation. Models of the Multi-SERTTA-CAL vehicle containing typical PWR-fuel rodlets were prepared and neutronics calculations were performed using MCNP6.1 with ENDF/B-VII.1 nuclear data libraries; these results were then compared against those performed for Multi-SERTTA to determine the similarity and possible design modification necessary prior to construction of these experiment vehicles. The estimated reactivity insertion worth into the TREAT core is very similar between the two vehicle designs, with the primary physical difference being a hollow Inconel tube running down the length of the calibration vehicle. Calculations of PCF indicate that on average there is a reduction of approximately 6.3 and 12.6%, respectively, for PWR fuel rodlets irradiated under wet and dry conditions. Changes to the primary or secondary vessel structure in the calibration vehicle can be performed to offset this discrepancy and maintain neutronic equivalency. Current possible modifications to the calibration vehicle include reduction of the primary vessel wall thickness, swapping Zircaloy-4 for stainless steel 316 in the secondary containment, or slight modification to the temperature and pressure of the water environment within the primary vessel. Removal of some of the instrumentation within the calibration vehicle can also serve to slightly increase the PCF. Future efforts include further modification and optimization of the Multi-SERTTA and Multi-SERTTA-CAL designs in preparation of actual TREAT transient testing. Experimental results from both test vehicles will be compared against calculational results and methods to provide validation and support additional neutronics analyses.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2018

Dielectric-barrier-discharge plasma-assisted hydrogen diffusion flame. Part 1: Temperature, oxygen, and fuel measurements by one-dimensional fs/ps rotational CARS imaging

One-dimensional hybrid fs/ps CARS imaging provides single-laser-shot measurements of temperature, oxygen, and hydrogen in a plasma-assisted hydrogen diffusion flame. The coaxial dielectric-barrier-discharge burner collapses the Re ~50 hydrogen diffusion flame to within ~5 mm of the burner surface at an applied AC potential of 8.75 kV at 18 kHz, coinciding nicely with the full spatial extent of the 1D CARS measurements. Translating the burner through the measurement volume allowed for measurements at numerous radial locations in increments of 1 mm with a resolution of 140 µm × 30 µm × 600 µm, sufficient to resolve spatial gradients in this unsteady flame. Longer probe delays, required for improved dynamic range in regions of high temperature fluctuations, proved difficult to model as a result of a nontrivial decay in the O 2 Raman coherence arising from complexities associated with the triplet ground electronic state of the O 2 molecule. Oxygen linewidths were treated empirically using the observed O 2 coherence decay in spectra acquired from the product gases of lean, near-adiabatic H 2 /air flames stabilized on a Hencken flat-flame burner. While still leading to errors up to 10% at worst, the empirically determined Raman linewidth factors eliminated any systematic error in the O 2 /N 2 measurements with probe delay. Temperature measurements in the Hencken Burner flames proved to be insensitive to probe pulse delay, providing robust thermometry. Here, demonstration of this technique in both the canonical Hencken burner flames and a new DBD burner validates its effectiveness in producing multiple spatially resolved measurements in combustion environments. Measurements in the DBD burner revealed an unsteady, counterflow flattened flame structure near the fuel orifice which became unsteady as the reaction zone curves towards the surface for larger radial positions. Lastly, fluctuations in the fuel concentration were largest at the source, as the large, plasma-generated, unsteady external toroidal vortex that dominates the transport in this flame provides enhanced ventilation of the flame surface in close proximity to the fuel tube.

42 ENGINEERING↗

DOE OSTI2023

A Consistent Representation of Cloud Overlap and Cloud Subgrid Vertical Heterogeneity

Many global climate models underestimate the cloud cover and overestimate the cloud albedo, especially for low-level clouds. We determine how a correct representation of the vertical structure of clouds can fix part of this bias. We use the 1D McICA framework and focus on low-level clouds. Using Large Eddy Simulations results as reference, we propose a method based on exponential-random overlap that represents the cloud overlap between layers and the subgrid cloud properties over several vertical scales, with a single value of the overlap parameter. Starting from a coarse vertical grid, representative of atmospheric models, this algorithm is used to generate the vertical profile of the cloud fraction with a finer vertical resolution, or to generate it on the coarse grid but with subgrid heterogeneity and cloud overlap that ensures a correct cloud cover. Doing so we find decorrelation lengths are dependent on the vertical resolution, except if the vertical subgrid heterogeneity and interlayer overlap are taken into account coherently. We confirm that the frequently used maximum-random overlap leads to a significant error by underestimating the low-level cloud cover with a relative error of about 50%, that can lead to an error of SW cloud albedo as big as 70%. Not taking into account the subgrid vertical heterogeneity of clouds can cause a relative error of 20% in brightness, assuming the cloud cover is correct.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

The Atacama Cosmology Telescope: DR6 constraints on extended cosmological models

We use new cosmic microwave background (CMB) primary temperature and polarization anisotropy measurements from the Atacama Cosmology Telescope (ACT) Data Release 6 (DR6) to test foundational assumptions of the standard cosmological model, ΛCDM, and set constraints on extensions to it. We derive constraints from the ACT DR6 power spectra alone, as well as in combination with legacy data from the Planck mission. To break geometric degeneracies, we include ACT and Planck CMB lensing data and baryon acoustic oscillation data from DESI Year-1. To test the dependence of our results on non-ACT data, we also explore combinations replacing Planck with WMAP and DESI with BOSS, and further add supernovae measurements from Pantheon+ for models that affect the late-time expansion history. We verify the near-scale-invariance (running of the spectral index dn s /d ln k = 0.0062 ± 0.0052) and adiabaticity of the primordial perturbations. Neutrino properties are consistent with Standard Model predictions: we find no evidence for new light, relativistic species that are free-streaming (N eff = 2.86 ± 0.13, which combined with astrophysical measurements of primordial helium and deuterium abundances becomes N eff = 2.89 ± 0.11), for non-zero neutrino masses (∑m ν < 0.089 eV at 95% CL), or for neutrino self-interactions. We also find no evidence for self-interacting dark radiation (N idr < 0.134), or for early-universe variation of fundamental constants, including the fine-structure constant (α EM /α EM,0 = 1.0043 ± 0.0017) and the electron mass (m e /m e,0 = 1.0063 ± 0.0056). Our data are consistent with standard big bang nucleosynthesis (we find Y p = 0.2312 ± 0.0092), the COBE/FIRAS-inferred CMB temperature (we find T CMB = 2.698 ± 0.016 K), a dark matter component that is collisionless and with only a small fraction allowed as axion-like particles, a cosmological constant (w = -0.986 ± 0.025), and the late-time growth rate predicted by general relativity (γ = 0.663 ± 0.052). We find no statistically significant preference for a departure from the baseline ΛCDM model. In fits to models invoking early dark energy, primordial magnetic fields, or an arbitrary modified recombination history, we find H 0 = 69.9 +0.8 -1.5 , 69.1 ± 0.5, or 69.6 ± 1.0 km/s/Mpc, respectively; using BOSS instead of DESI BAO data reduces the central values of these constraints by 1–1.5 km/s/Mpc while only slightly increasing the error bars. In general, models introduced to increase the Hubble constant or to decrease the amplitude of density fluctuations inferred from the primary CMB are not favored over ΛCDM by our data.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2025

Periodic GFN1-xTB Tight Binding: A Generalized Ewald Partitioning Scheme for the Klopman–Ohno Function

A novel formulation is presented for the treatment of electrostatics in the periodic GFN1-xTB tight-binding model. Periodic GFN1-xTB is hindered by the functional form of the second-order electrostatics, which only recovers Coulombic behavior at large interatomic distances and lacks a closed-form solution for its Fourier transform. We address this by introducing a binomial expansion of the Klopman–Ohno function to partition short- and long-range interactions, enabling the use of a generalized Ewald summation for the solution of the electrostatic energy. This approach is general and is applicable to any damped potential of the form |R n + c| –m . Benchmarks on the X23 molecular crystal dataset and a range of prototypical bulk semiconductors demonstrate that this systematic treatment of the electrostatics eliminates unphysical behavior in the equation of state curves. In the bulk systems studied, we observe a mean absolute error in total energy of 35 meV/atom, comparable to the machine-learned universal force field, M3GNet, and sufficiently precise for structure relaxation. These results highlight the promising potential of GFN1-xTB as a universal tight-binding parametrization.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Quantum algorithms from fluctuation theorems: Thermal-state preparation

Fluctuation theorems provide a correspondence between properties of quantum systems in thermal equilibrium and a work distribution arising in a non-equilibrium process that connects two quantum systems with Hamiltonians H 0 and H 1 = H 0 + V. Building upon these theorems, we present a quantum algorithm to prepare a purification of the thermal state of H 1 at inverse temperature β ≥ 0 starting from a purification of the thermal state of H 0 . The complexity of the quantum algorithm, given by the number of uses of certain unitaries, is $\mathcal{O}$ (e β(ΔA - w l )/2 ), where ΔA is the free-energy difference between H 1 and H 0 , and w l is a work cutoff that depends on the properties of the work distribution and the approximation error ϵ > 0. If the non-equilibrium process is trivial, this complexity is exponential i β∥V∥, where ∥V∥ is the spectral norm of V. This represents a significant improvement of prior quantum algorithms that have complexity exponential in β∥H 1 ∥ in the regime where ∥V∥$\ll$ ∥H 1 ∥. The dependence of the complexity in ϵ varies according to the structure of the quantum systems. It can be exponential in 1/ϵ in general, but we show it to be sublinear in 1/ϵ if H 0 and H 1 commute, or polynomial in 1/ϵ if H 0 and H 1 are local spin systems. The possibility of applying a unitary that drives the system out of equilibrium allows one to increase the value of w l and improve the complexity even further. To this end, we analyze the complexity for preparing the thermal state of the transverse field Ising model using different non-equilibrium unitary processes and see significant complexity improvements.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2025

2024 Incubator Final Report: Active Hybrid Mooring

This Incubator project has defined and developed a representation of an active hybrid mooring (AHM) system in Simulink to assess whether the speed and accuracy of AHM is sufficient to warrant further investigation in a larger project. We first built a representative mooring system for the VolturnUS-S 15MW floating offshore wind turbine (FOWT) in 1,000-meter water depth to provide baseline loads and displacements needed in the AHM system, with the results showing off-the-shelf actuators would be practical. We then defined model configurations for the numerical and physical substructures, using standalone MoorDyn v2 with a novel input strategy and chained hydraulic actuators represented in Simulink Simscape, respectively. The remainder of the project has focused on verifying the existing models for speed and accuracy against OpenFAST simulations, increasing their complexity to enable six degree of freedom (6DOF) operation, and connecting the numerical and physical substructures into a single holistic model. The verification phase of the project has shown promising results, though further refinement is needed to resolve accuracy discrepancies and for robust performance across a wider range of metocean conditions. The numerical model we developed is computationally stable and operates faster than real time using a time step of 0.01 seconds or shorter, indicating the model is likely fast enough for our AHM design to operate successfully. Additionally, the Simscape model of a hydraulic actuator operates with less than 0.3% relative error when actuating mooring loads from an OpenFAST simulation of the VolturnUS-S 1,000-meter mooring system. The aforementined refinements will be performed in the next year as a Continuing Incubator, with key remaining tasks include programming the predictor-corrector loop to minimize movement error, testing against more complex nonlinear wave cases, and expanding to enable loads from connected shared mooring lines.

17 WIND ENERGY↗

DOE OSTI2020

Resolving atomic transport through iron oxide under irradiation using isotopic tracers

Structural materials in nuclear environments are exposed to complex and harsh conditions, including high temperatures, corrosive solutions, and irradiation. Material stability and likewise degradation are fundamentally controlled by atomic transport mechanisms. Here, we investigate the influence of radiation-induced, non-equilibrium point defect populations on mass transport within model oxide systems using isotopic tracers and atom probe tomography. An isotopically labelled hematite (a-Fe2O3) film was synthesized with 16O- and 18O-rich layers (>30nm and 10 nm, respectively) sequentially deposited via molecular beam epitaxy. One region of the film was proton irradiated to ~0.1 dpa at 450°C, and regions outside the beam spot provided a non-irradiated control of thermal annealing only. 3D APT was used to directly visualize the elemental and O-isotopic redistribution following both thermal and combined thermal and irradiation conditions. Complementary scanning transmission electron microscopy (STEM) was also employed to study the microstructural evolution. Error function fits of the 18O-concentration profiles enabled quantification of diffusion coefficients.

isotopic tracers, diffusion, proton irradiation, h↗

DOE OSTI2020

Leveraging 3D CAD and Virtual Reality in Design of the Calcine Disposition Project - 20512

Fluor Idaho's Calcine Disposition Project (CDP) is leveraging the power of three-dimensional (3D) visualization, light detection and ranging (Lidar), and virtual reality to improve designs and worker safety. With the use of computer-aided design (CAD) modeling software, the CDP has created 3D models of the facility and systems to aid in the design, development, and operation of its retrieval and transfer system. This by itself is nothing new and has been done in industry for years. The CDP project however is taking this a few steps farther with the use of Lidar and virtual reality software. The CRP is tasked with removing a radioactive granular material from stainless steel bins located in concrete vaults that were constructed in the late 1950's and early 1960's. While construction drawings are available, it is not certain that the drawings are as-built or how accurate they truly are. Part of the project requires precise placement of equipment on to bins around multiple pipe, electrical lines, and bin stiffeners. Relying solely on the existing drawings and models created from these drawings is highly risky and prone to failure. The first step to determine the precise location and orientation of all obstructions in the vault the project will use a Lidar system to scan the vault structure and precisely locate all vault and bin components. Once this information is obtained, the data will be integrated into the CAD model. The model will then be verified, and a true as-built model developed. Precise component location, size, and orientation will be used for final design and placement of retrieval components. The second step will be to take the verified 3D model and scan data and import it into virtual reality software creating a virtual world. While some work on the project requires all work to be completed remotely due to high radiation fields, some areas have low enough radiation levels that personnel can enter and perform work. With the use of a virtual reality headset, operators and technicians will be able to enter our virtual world and become familiar with the surroundings and perform work prior to ever entering the radiation environment. This training is expected to pay dividends by improving worker efficiency, reducing errors, and improving confidence that the work can be performed as expected. It will play a key aspect in as low as reasonably achievable (ALARA) principles. An additional aspect in using the Lidar scans and virtual environment, is that it will give engineers and managers an opportunity to revisit the facility, especially radiation areas, at any time to obtain design information and measurements that may be costly or impossible to obtain once the facility transitions into radiation operations. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2015

Status on the Development of a Modeling and Simulation Framework for the Economic Assessment of Nuclear Hybrid Energy Systems

An effort to design and build a modeling and simulation framework to assess the economic viability of Nuclear Hybrid Energy Systems (NHES) was undertaken in fiscal year 2015 (FY15). The purpose of this report is to document the various tasks associated with the development of such a framework and to provide a status on its progress. Several tasks have been accomplished. First, starting from a simulation strategy, a rigorous mathematical formulation has been achieved in which the economic optimization of a Nuclear Hybrid Energy System is presented as a constrained robust (under uncertainty) optimization problem. Some possible algorithms for the solution of the optimization problem are presented. A variation of the Simultaneous Perturbation Stochastic Approximation algorithm has been implemented in RAVEN and preliminary tests have been performed. The development of the software infrastructure to support the simulation of the whole NHES has also moved forward. The coupling between RAVEN and an implementation of the Modelica language (OpenModelica) has been implemented, migrated under several operating systems and tested using an adapted model of a desalination plant. In particular, this exercise was focused on testing the coupling of the different code systems; testing parallel, computationally expensive simulations on the INL cluster; and providing a proof of concept for the possibility of using surrogate models to represent the different NHES subsystems. Another important step was the porting of the RAVEN code under the Windows™ operating system. This accomplishment makes RAVEN compatible with the development environment that is being used for dynamic simulation of NHES components. A very simplified model of a NHES on the electric market has been built in RAVEN to confirm expectations on the analysis capability of RAVEN to provide insight into system economics and to test the capability of RAVEN to identify limit surfaces even for stochastic constraints. This capability will be needed in the future to enforce the stochastic constraints on the electric demand coverage from the NHES. The development team gained experience with many of the tools that are currently envisioned for use in the economic analysis of NHES and completed several important steps. Given the complexity of the project, preference has been given to a structural approach in which several independent efforts have been used to build the cornerstone of the simulation framework. While this is good approach in establishing such a complex framework, it may delay reaching more complete results on the performance of analyzed system configurations. The integration of the previously reported exergy analysis approach was initially proposed as part of this milestone. However, in reality, the exergy-based apportioning of cost will take place only in a second stage of the implementation since it will be used to properly allocate cost among the different NHES subsystems. Therefore, exergy does not appear at the level of the main drivers in the analysis framework; the latter development of the base framework is the focus of this report.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2019

From the Arctic to the tropics: multi-biome prediction of leaf mass per area using leaf reflectance

Leaf-mass-per-area (LMA) is a key plant trait, reflecting tradeoffs between leaf photosynthetic function, longevity, and structural investment. Capturing spatial and temporal variability in LMA has been a long-standing goal of ecological research and is an essential component for advancing Earth system models. Despite the substantial variation in LMA within and across Earth's biomes, an efficient, globally generalizable approach to predict LMA is still lacking. In this work, we explored the capacity to predict LMA from leaf spectra across much of the global LMA trait space, with values ranging from 17 g m -2 to 393 g m -2 . Our dataset contained leaves from a wide range of biomes from the high Arctic to the tropics, included broad- and needle-leaf species, and upper and lower canopy (i.e. sun and shade) growth environments. Here we demonstrate the capacity to rapidly estimate LMA using only spectral measurements across a wide range of species, leaf age, and canopy position, from diverse biomes. Our model captures LMA variability with high accuracy and low error (R 2 =0.89; RMSE=15.45 g m -2 ). Lastly, our finding highlights that the leaf economic spectrum is mirrored by the leaf optical spectrum paving the way for this technology to predict the diversity of LMA in ecosystems across global biomes.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Uncertainty-Guided Prediction Horizon of Phase-Resolved Ocean Wave Forecasting Under Data Sparsity: Experimental and Numerical Evaluation

Accurate short-term wave forecasting is critical for the safe and efficient operation of marine structures that rely on real-time, phase-resolved ocean wave information for control and monitoring purposes (e.g., digital twins). These systems often depend on environmental sensors (e.g., waverider buoys, wave-sensing LIDAR). Challenges arise when upstream sensor data are missing, sparse, or phase-shifted due to drift. This study investigates the performance of two machine learning models, time-series dense encoder (TiDE) and long short-term memory (LSTM), for forecasting phase-resolved ocean surface elevations under varying degrees of data degradation. We introduce the τ-trimming algorithm, which adapts the prediction horizon based on uncertainty thresholds derived from historical forecasts. Numerical wave tank (NWT) and wave basin experiments are used to benchmark model performance under short- and long-term data masking, spatially coarse sensor grids, and upstream phase shifts. Results show under a 50% probability of upstream data loss, the τ-trimmed TiDE model achieves a 46% reduction in error at the most upstream target, compared to 22% for LSTM. Furthermore, phase misalignment in upstream data introduces a near-linear increase in forecast error. Under moderate model settings, a ±3 s misalignment increases the mean absolute error by approximately 0.5 m, while the same error is accumulated at ±4 s using the more conservative approach. These findings inform the design of resilient, uncertainty-aware wave forecasting systems suited for realistic offshore sensing environments.

42 ENGINEERING↗

DOE OSTI2020

The impact of the fiducial cosmology assumption on BAO distance scale measurements

ABSTRACT Standard analysis pipelines for measurements of Baryon Acoustic Oscillations (BAO) in galaxy surveys make use of a fiducial cosmological model to guide the data compression required to transform from observed redshifts and angles to the measured angular and radial BAO peak positions. In order to remove any dependence on the fiducial cosmology from the results, all models compared to the data should mimic the compression and its dependence on the fiducial model. In practice, approximations are made when testing models: (1) There is assumed to be no residual dependence on the fiducial cosmology after reconstruction, (2) differences in the distance–redshift relationship are assumed to match a linear scaling, and (3) differences in clustering between true and fiducial models are assumed to be removed by the free parameters used to null the non-BAO signal. We test these approximations using the current standard measurement procedure with a set of halo catalogues from the aemulus suite of N-body simulations, which span a range of wCDM cosmological models. We focus on reconstruction of the primordial BAO and locating the BAO. For the range of wCDM cosmologies covered by the aemulus suite, we find no evidence for systematic errors in the measured BAO shift parameters α∥ and α⊥ to $\lt 0.1\%$. However, the measured errors $\sigma _{\alpha _{\parallel }}$ and $\sigma _{\alpha _{\bot }}$ show a notable absolute increase by up to +0.001 and +0.002, respectively, in the case that the fiducial cosmology does not match the truth. These effects on the inferred BAO scale will be important, given the precision of measurements expected from future surveys including DESI, Euclid, and WFIRST.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2023

Improving Subsurface Stress Characterization for Carbon Dioxide Storage Projects by Incorporating Machine Learning Techniques

The overall objective of this project is to develop a framework for reliable characterization and prediction of the state of stress in the overburden and underburden (including the basement) in CO 2 storage reservoirs using machine learning and integrated geomechanics and geophysical methods. Specifically, we propose to develop workflow encompassing of technologies and/or methods to predict stress and pressure changes due to CO 2 injection in an active tertiary recovery site and their impacts on subtle fault activation, fractures and occurrence of microseismic events and compare responses to field observations. In this project, we anticipate using dataset from the Farnsworth field Unit (FWU) which is operated by Purdure Petroleum. A novel elastic-waveform VSP inversion technique will be used to estimate high-resolution spatial and temporal changes of elastic moduli in CO 2 storage reservoirs, which will be combined with velocity-stress relationship derived from laboratory tests to obtain subsurface pressure and stress. Clustered microseismic data will be jointly inverted for improved focal mechanisms. Least-squares reverse-time migration of microseismic waveform data will be performed to directly image fracture/fault zones. Additionally, a deep neural network machine learning technique with convolutional and recurrent layers will be used for learning the spectro-temporal structures in microseismic waveforms. The results of this geotechnical data analysis will be integrated to develop a high-resolution 3D mechanical earth model extending from the overburden sealing formations to the underburden including the basement. Mechanical properties will be derived through integration of mechanical logs, tests, available results from chemo-mechanical laboratory tests, and elastic inversion of seismic data using a combination of Bayesian and stochastic methods as well as machine learning technique. Failure features (faults/fractures) will be represented and/or modeled based on seismic and core data analysis. A transient hydrodynamic-geomechanical model will be developed through coupling with the calibrated FWU reservoir simulation model. The full physics coupled model will be used to train a reduced order proxy model using machine learning algorithm for estimating stress which will then be used with appropriate constitutive relationships and forward seismological models to simulate pressure changes and induced microseismicity. An advanced optimization framework will be developed to perform a history match to minimize error between field observations and simulated. The history matched proxy model will be verified against the full-physics equivalent. The field observations that will be used in the coupled model calibration process include pressure/stress inverted from VSP, moment magnitude from microseismic analysis, real time downhole pressure measurements, production and injection data. Parameter sensitivity and uncertainty analysis will be performed to characterize the impact of model parameter uncertainty on stress estimates. The proposed project will have significant impact on future field implementation of the proposed technology. Because the project field site is an ongoing CO 2 EOR development, the value of the new technology will be demonstrated in an operational context and evaluated as a viable risk mitigation strategy. Cost/benefit will be evaluated together with the various commercial incentives for CO 2 sequestration available to oil and gas operators. The extensive available dataset and ongoing data acquisition under the SWP Phase III work plan provides flexibility for investigation of multiple approaches and reduces technical risk.

58 GEOSCIENCES↗

DOE OSTI2023

Non-singlet quark helicity $\mathrm{PDF}$s of the nucleon from pseudo-distributions

The non-singlet helicity quark parton distribution functions (PDFs) of the nucleon are determined from lattice QCD, by jointly leveraging pseudo-distributions and the distillation spatial smearing paradigm. A Lorentz decomposition of appropriately isolated space-like matrix elements reveals pseudo-distributions that contain information on the leading-twist helicity PDFs, as well as an invariant amplitude that induces an additional z 2 contamination of the leading-twist signal. An analysis of the short-distance behavior of the space-like matrix elements using matching coefficients computed to next-to-leading order (NLO) exposes the desired PDF up to this additional z 2 contamination. Due to the non-conservation of the axial current, we elect to isolate the helicity PDFs normalized by the nucleon axial charge at the same scale μ 2 . The leading-twist helicity PDFs as well as several sources of systematic error, including higher-twist effects, discretization errors, and the aforementioned z 2 contaminating amplitude are jointly determined by characterizing the computed pseudo-distribution in a basis of Jacobi polynomials. The Akaike Information Criterion is exploited to effectively average over distinct model parameterizations and cuts on the pseudo-distribution. Encouraging agreement is observed with recent global analyses of each non-singlet quark helicity PDF, notably a rather small non-singlet anti-quark helicity PDF for all quark momentum fractions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2026

Updating PV and Battery Bill Savings Calculations for Net Billing: New Best Practices for Input Data and Uncertainty

Jurisdictions are increasingly adopting compensation structures for distributed PV and PV-battery systems that price exported energy lower than energy consumed onsite (net billing rates). Standard methods for calculating the bill savings from PV and PV-battery systems were developed for net metering structures, and applying these same methods to net billing structures (such as using Typical Meteorological Year weather with actual year load) introduces bias errors that underestimate PV-battery system bill savings by between 1.5\% and 9\%, depending on the utility rate. We assess the magnitude of these errors and compare them to other sources of uncertainty when estimating the bill savings from PV and PV-battery systems under more complex utility rates.

14 SOLAR ENERGY↗

DOE OSTI2019

Pathway Complexity in the Stacking of Imine-Linked Macrocycles Related to Two-Dimensional Covalent Organic Frameworks

Interlayer interactions play an important role in the formation of two-dimensional covalent organic frameworks (2D COFs), yet the effects of monomer structure on COF formation, crystallinity, and susceptibility to exfoliation are not well understood. Here we probe these effects by studying the stacking behavior of imine-linked macrocycles that represent discrete models of 2D COFs. Specifically, macrocycles based on terephthaldehyde (PDA) or 2,5-dimethoxyterephthaldehyde (DMPDA) stack upon cooling molecularly dissolved solutions. Both macrocycles assemble cooperatively with similar Delta H-e values of -97 kJ/mol and -101 kJ/mol, respectively, although the DMPDA macrocycle assembly process showed a more straightforward temperature dependence. Density functional theory calculations of the stacking of PDA macrocycles suggested two stable configurations that were close in energy. Circular dichroism spectroscopy performed on macrocycles bearing chiral side chains revealed a helix reversion process for the PDA macrocycles that was not observed for the DMPDA macrocycles. Given the structural similarity of these monomers, these findings demonstrate that the stacking processes associated with nanotubes derived from these macrocycles, as well as for the corresponding COFs, are complex and susceptible to kinetic traps, casting doubt on the relevance of thermodynamic arguments for improving materials quality. Rather, a deeper understanding of the mechanism of supramolecular polymerization and its interplay with polymerization and error correction during COF synthesis is needed for improved control of the crystallinity and morphology of these emerging materials.

Wang, Shiwei↗