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DOE OSTI2021

Pore-Scale Dynamics of Liquid CO2–Water Displacement in 2D Axisymmetric Porous Micromodels Under Strong Drainage and Weak Imbibition Conditions: High-Speed μPIV Measurements

Resolving pore-scale transient flow dynamics is crucial to understanding the physics underlying multiphase flow in porous media and informing large-scale predictive models. Surface properties of the porous matrix play an important role in controlling such physics, yet interfacial mechanisms remain poorly understood, in part due to a lack of direct observations. This study reports on an experimental investigation of the pore-scale flow dynamics of liquid CO 2 and water in two-dimensional (2D) circular porous micromodels with different surface characteristics employing high-speed microscopic particle image velocimetry (μPIV). The design of the micromodel minimized side boundary effects due to the limited size of the domain. The high-speed μPIV technique resolved the spatial and temporal dynamics of multiphase flow of CO 2 and water under reservoir-relevant conditions, for both drainage and imbibition scenarios. When CO 2 displaced water in a hydrophilic micromodel (i.e., drainage), unstable capillary fingering occurred and the pore flow was dominated by successive pore-scale burst events (i.e., Haines jumps). When the same experiment was repeated in a nearly neutral wetting micromodel (i.e., weak imbibition), flow instability and fluctuations were virtually eliminated, leading to a more compact displacement pattern. Energy balance analysis indicates that the conversion efficiency between surface energy and external work is less than 30%, and that kinetic energy is a disproportionately smaller contributor to the energy budget. This is true even during a Haines jump event, which induces velocities typically two orders of magnitude higher than the bulk velocity. These novel measurements further enabled direct observations of the meniscus displacement, revealing a significant alteration of the pore filling mechanisms during drainage and imbibition. While the former typically featured burst events, which often occur only at one of the several throats connecting a pore, the latter is typically dominated by a cooperative filling mechanism involving simultaneous invasion of a pore from multiple throats. This cooperative filling mechanism leads to merging of two interfaces and releases surface energy, causing instantaneous high-speed events that are similar, yet fundamentally different from, burst events. Finally, pore-scale velocity fields were statistically analyzed to provide a quantitative measure of the role of capillary effects in these pore flows.

Li, Yaofa↗

DOE OSTI2024

Weak Scale Supersymmetry Emergent from the String Landscape

Superstring flux compactifications can stabilize all moduli while leading to an enormous number of vacua solutions, each leading to different 4−d laws of physics. While the string landscape provides at present the only plausible explanation for the size of the cosmological constant, it may also predict the form of weak scale supersymmetry which is expected to emerge. Rather general arguments suggest a power-law draw to large soft terms, but these are subject to an anthropic selection of a not-too-large value for the weak scale. The combined selection allows one to compute relative probabilities for the emergence of supersymmetric models from the landscape. Models with weak scale naturalness appear most likely to emerge since they have the largest parameter space on the landscape. For finetuned models such as high-scale SUSY or split SUSY, the required weak scale finetuning shrinks their parameter space to tiny volumes, making them much less likely to appear compared to natural models. Probability distributions for sparticle and Higgs masses from natural models show a preference for Higgs mass mh∼125 GeV, with sparticles typically beyond the present LHC limits, in accord with data. From these considerations, we briefly describe how natural SUSY is expected to be revealed at future LHC upgrades. This article is a contribution to the Special Edition of the journal Entropy, honoring Paul Frampton on his 80th birthday.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2024

Efficient First-Order Algorithms for Large-Scale, Non-Smooth Maximum Entropy Models with Application to Wildfire Science

Maximum entropy (MaxEnt) models are a class of statistical models that use the maximum entropy principle to estimate probability distributions from data. Due to the size of modern data sets, MaxEnt models need efficient optimization algorithms to scale well for big data applications. State-of-the-art algorithms for MaxEnt models, however, were not originally designed to handle big data sets; these algorithms either rely on technical devices that may yield unreliable numerical results, scale poorly, or require smoothness assumptions that many practical MaxEnt models lack. In this paper, we present novel optimization algorithms that overcome the shortcomings of state-of-the-art algorithms for training large-scale, non-smooth MaxEnt models. Our proposed first-order algorithms leverage the Kullback–Leibler divergence to train large-scale and non-smooth MaxEnt models efficiently. For MaxEnt models with discrete probability distribution of n elements built from samples, each containing m features, the stepsize parameter estimation and iterations in our algorithms scale on the order of O(mn) operations and can be trivially parallelized. Moreover, the strong ℓ1 convexity of the Kullback–Leibler divergence allows for larger stepsize parameters, thereby speeding up the convergence rate of our algorithms. To illustrate the efficiency of our novel algorithms, we consider the problem of estimating probabilities of fire occurrences as a function of ecological features in the Western US MTBS-Interagency wildfire data set. Our numerical results show that our algorithms outperform the state of the art by one order of magnitude and yield results that agree with physical models of wildfire occurrence and previous statistical analyses of wildfire drivers.

Physics↗

DOE OSTI2023

Multi-Scale Characterization of Porosity and Cracks in Silicon Carbide Cladding after Transient Reactor Test Facility Irradiation

Silicon carbide (SiC) ceramic matrix composite (CMC) cladding is currently being pursued as one of the leading candidates for accident-tolerant fuel (ATF) cladding for light water reactor applications. The morphology of fabrication defects, including the size and shape of voids, is one of the key challenges that impacts cladding performance and guarantees reactor safety. Therefore, quantification of defects’ size, location, distribution, and leak paths is critical to determining SiC CMC in-core performance. This research aims to provide quantitative insight into the defect’s distribution under multi-scale characterization at different length scales before and after different Transient Reactor Test Facility (TREAT) irradiation tests. A non-destructive multi-scale evaluation of irradiated SiC will help to assess critical microstructural defects from production and/or experimental testing to better understand and predict overall cladding performance. X-ray computed tomography (XCT), a non-destructive, data-rich characterization technique, is combined with lower length scale electronic microscopic characterization, which provides microscale morphology and structural characterization. This paper discusses a fully automatic workflow to detect and analyze SiC-SiC defects using image processing techniques on 3D X-ray images. Following the XCT data analysis, advanced characterizations from focused ion beam (FIB) and transmission electron microscopy (TEM) were conducted to verify the findings from the XCT data, especially quantitative results from local nano-scale TEM 3D tomography data, which were utilized to complement the 3D XCT results. In this work, three SiC samples (two irradiated and one unirradiated) provided by General Atomics are investigated. The irradiated samples were irradiated in a way that was expected to induce cracking, and indeed, the automated workflow developed in this work was able to successfully identify and characterize the defects formation in the irradiated samples while detecting no observed cracking in the unirradiated sample. These results demonstrate the value of automated XCT tools to better understand the damage and damage propagation in SiC-SiC structures for nuclear applications.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2021

ForSE: A GAN-based Algorithm for Extending CMB Foreground Models to Subdegree Angular Scales

We present ForSE (Foreground Scale Extender), a novel Python package that aims to overcome the current limitations in the simulation of diffuse Galactic radiation, in the context of cosmic microwave background (CMB) experiments. ForSE exploits the ability of generative adversarial neural networks (GANs) to learn and reproduce complex features present in a set of images, with the goal of simulating realistic and non-Gaussian foreground radiation at subdegree angular scales. This is of great importance in order to estimate the foreground contamination to lensing reconstruction, delensing, and primordial B-modes for future CMB experiments. We applied this algorithm to Galactic thermal dust emission in both total intensity and polarization. Our results show how ForSE is able to generate small-scale features (at 12') having as input the large-scale ones (80'). The injected structures have statistical properties, evaluated by means of the Minkowski functionals, in good agreement with those of the real sky and which show the correct amplitude scaling as a function of the angular dimension. Furthermore, the obtained thermal dust Stokes Q and U full-sky maps as well as the ForSE package are publicly available for download.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2021

Two Year Cosmology Large Angular Scale Surveyor (CLASS) Observations: Long Timescale Stability Achieved with a Front-end Variable-delay Polarization Modulator at 40 GHz

The Cosmology Large Angular Scale Surveyor (CLASS) is a four-telescope array observing the largest angular scales (2≲ ℓ ≲ 200) of the cosmic microwave background (CMB) polarization. These scales encode information about reionization and inflation during the early universe. The instrument stability necessary to observe these angular scales from the ground is achieved through the use of a variable-delay polarization modulator as the first optical element in each of the CLASS telescopes. Here, we develop a demodulation scheme used to extract the polarization timestreams from the CLASS data and apply this method to selected data from the first 2 yr of observations by the 40 GHz CLASS telescope. These timestreams are used to measure the 1/f noise and temperature-to-polarization (T → P) leakage present in the CLASS data. We find a median knee frequency for the pair-differenced demodulated linear polarization of 15.12 mHz and a T → P leakage of <3.8 × 10 -4 (95% confidence) across the focal plane. We examine the sources of 1/f noise present in the data and find the component of 1/f due to atmospheric precipitable water vapor (PWV) has an amplitude of 203 ± 12 µK RJ $\sqrt{{s}}$ for 1 mm of PWV when evaluated at 10 mHz; accounting for ~17% of the 1/f noise in the central pixels of the focal plane. In conclusion, the low levels of T → P leakage and 1/f noise achieved through the use of a front-end polarization modulator are requirements for observing of the largest angular scales of the CMB polarization by the CLASS telescopes.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2023

The Aemulus Project. V. Cosmological Constraint from Small-scale Clustering of BOSS Galaxies

We analyze clustering measurements of BOSS galaxies using a simulation-based emulator of two-point statistics. We focus on the monopole and quadrupole of the redshift-space correlation function, and the projected correlation function, at scales of 0.1 ~ 60 h -1 Mpc. Although our simulations are based on wCDM with general relativity (GR), we include a scaling parameter of the halo velocity field, γ f , defined as the amplitude of the halo velocity field relative to the GR prediction. We divide the BOSS data into three redshift bins. After marginalizing over other cosmological parameters, galaxy bias parameters, and the velocity scaling parameter, we find fσ 8 (z = 0.25) = 0.413 ± 0.031, fσ 8 (z = 0.4) = 0.470 ± 0.026, and fσ 8 (z = 0.55) = 0.396 ± 0.022. Compared with Planck observations using a flat Lambda cold dark matter model, our results are lower by 1.9σ, 0.3σ, and 3.4σ, respectively. These results are consistent with other recent simulation-based results at nonlinear scales, including weak lensing measurements of BOSS LOWZ galaxies, two-point clustering of eBOSS LRGs, and an independent clustering analysis of BOSS LOWZ. All these results are generally consistent with a combination of ${\gamma }_{f}^{1/2}{\sigma }_{8}\approx 0.75$. We note, however, that the BOSS data is well fit assuming GR, i.e., γf = 1. We cannot rule out an unknown systematic error in the galaxy bias model at nonlinear scales, but near-future data and modeling will enhance our understanding of the galaxy–halo connection, and provide a strong test of new physics beyond the standard model.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

Multizone Modeling of Black Hole Accretion and Feedback in 3D GRMHD: Bridging Vast Spatial and Temporal Scales

Simulating accretion and feedback from the horizon scale of supermassive black holes (SMBHs) out to galactic scales is challenging because of the vast range of scales involved. Elaborating on H. Cho et al., we describe and test a "multizone" technique, which is designed to tackle this difficult problem in three-dimensional general relativistic magnetohydrodynamic (GRMHD) simulations. While short-timescale variability should be interpreted with caution, the method is demonstrated to be well-suited for finding dynamical steady states over a wide dynamic range. We simulate accretion on a nonspinning SMBH ($a\ast$ = 0) using initial conditions and the external galactic potential from a large-scale galaxy simulation and achieve a steady state over eight decades in radius. As found in H. Cho et al., the density scales with radius as ρ ∝ r –1 inside the Bondi radius R B , which is located at R B = 2 × 10 5 r g (≈60 pc for M87), where r g is the gravitational radius of the SMBH; the plasma-β is ~ unity, indicating an extended magnetically arrested state; the mass accretion rate $\dot{M}$ is ≈1% of the analytical Bondi accretion rate ${\dot{M}}_{{\rm{B}}};$ and there is continuous energy feedback out to ≈100R B (or beyond > kpc) at a rate $\approx 0.02\dot{M}{c}^{2}$. Surprisingly, no ordered rotation in the external medium survives as the magnetized gas flows to smaller radii, and the final steady solution is very similar to when the exterior has no rotation. Using the multizone method, we simulate GRMHD accretion over a wide range of Bondi radii, R B ~ 10 2 –10 7 r g , and find that $\dot{M}/{\dot{M}}_{{B}}\approx {({R}_{{B}}/6\,{r}_{g})}^{-0.5}$.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2025

A Measurement of the Largest-scale CMB E -mode Polarization with CLASS

We present measurements of large-scale cosmic microwave background E-mode polarization from the Cosmology Large Angular Scale Surveyor 90 GHz data. Using 115 det-yr of observations collected through 2024 with a variable-delay polarization modulator, we achieved a polarization sensitivity of 82 μK arcimin, comparable to Planck at similar frequencies (100 and 143 GHz ). The analysis demonstrates effective mitigation of systematic errors and addresses challenges to large-angular-scale power recovery posed by time-domain filtering in maximum-likelihood map-making. A novel implementation of the pixel-space transfer matrix is introduced, which enables efficient filtering simulations and bias correction in the power spectrum using the quadratic cross-spectrum estimator. Overall, we achieved an unbiased time-domain filtering correction to recover the largest angular scale polarization, with the only power deficit, arising from map-making nonlinearity, being characterized as <3%. Through cross-correlation with Planck, we detected the cosmic reionization at 99.4% significance and measured the reionization optical depth τ = $0.053^{+0.018}_{-0.019}$, marking the first ground-based attempt at such a measurement. At intermediate angular scales (ℓ > 30), our results, both independently and in cross-correlation with Planck, remain fully consistent with Planck’s measurements.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2025

A species scale-driven breakdown of effective field theory in time-dependent string backgrounds

We present a novel way in which effective field theory (EFT) can break down in cosmological string backgrounds depending on the behavior of the quantum gravity cutoff in infinite distance limits, known as the species scale $Λ_s$. Namely, EFT can break down if the species scale $Λ_s$ falls off so rapidly as the Friedmann-Robertson-Walker (FRW) scale factor grows from some initial value $a_i$ to some final value $a_f$ that the physical momentum of an initial Hubble-sized perturbation $\sim H_i^{-1}$ grows to exceed the species scale. For EFT to remain valid, a new condition $H_i \frac{a_i}{a_f} \ll Λ_{s,f}$ must hold, which is distinct from Trans-Planckian conditions discussed in the literature. Using the universal relation $\frac{\nabla m}{m} \cdot \frac{\nabla Λ_s}{Λ_s} = \frac{1}{d-2}$ in the infinite distance limits of moduli space where $m$ is the mass scale of the lightest tower and $\nabla$ measures variations with respect to the canonical metric on moduli space, we show that spatially flat FRW solutions in the string landscape violate this condition or at best marginally satisfy it. However, we find that sufficiently large negative spatial curvature always avoids a breakdown. To avoid EFT breakdown, we derive an upper bound on the duration of quasi-de Sitter expansion that classically evolves to decelerated expansion. Our bound is proportional to the Trans-Planckian Censorship Conjecture (TCC) bound, with the advantage that it applies to any FRW solution in the string landscape. Finally, we distinguish EFT breakdown from TCC violation, the latter being a quantum gravity constraint rather than an EFT limitation. Perhaps our most surprising finding is that in any flat FRW solution that develops a weakly coupled string at future infinity the EFT inevitably breaks down.

Cosmology and Nongalactic Astrophysics (astro-ph.C↗

DOE OSTI2024

Design of a Meso-Scale Test of a Fracture Thermal Energy Storage (FTES) System

This paper will present the characterization, scaling, and design of an intermediate-scale field test of a fracture thermal energy storage system (FTES). Seasonal storage of thermal energy has the potential to both significantly reduce the total energy requirements for heating and cooling of buildings, but also allow for the flexibility to store thermal energy from intermittent sources. With approximately half of global energy consumption currently being used for heating and cooling, this represents an important path to reducing greenhouse gas (GHG) emissions. The concept of FTES is to drill two or more wells into a low permeability formation, generally at a depth of less than a few hundred meters, and then generate hydraulic fractures to create flow paths for water to circulate between the wells. Hot or cold thermal energy can then be stored in the surrounding rock mass by circulating hot or cold water through the fractures, which will heat or cool the rock mass. To recover the stored energy, ambient temperature water can be then circulated through the fractures, which will then be heated or cooled by the rock mass. Fractures inherently have a very large ratio of surface area to volume. This allows for very high heat fluxes to and from the rock mass to be achieved despite the relatively low thermal conductivity of most geologic formations. Because large fractures can be made with low-cost equipment and with only inexpensive and environmentally safe materials such as water and sand, the cost to construct even large FTES systems is expected to be quite low. This paper will present what the performance requirements, size, and operating conditions of a full-scale system to operate a commercial building. The paper will describe how these full-scale system characteristics will be used as a design basis for an intermediate-scale FTES test to be conducted at the Sanford Underground Research Facility (SURF) in Lead, SD.

Burghardt, Jeffrey A.↗

DOE OSTI2026

EXERGETIC: De-Risking Next-Generation Resilient Geothermal Hybrids via At-Scale Evaluation Using Virtual Emulation Digital Twin Environment for Efficient Operation

The DOE-GTO-funded project, award number 5.1.2.12, entitled "EXERGETIC - De-risking Next Generation Resilient Geothermal Hybrids via at-Scale Evaluation Using a Virtual Emulation Digital Twin Environment for Efficient Operation," advances the solution to these challenges by developing and validating a geothermal co-emulation environment implemented at the National Laboratory of the Rockies (NLR)'s Advanced Research on Integrated Energy Systems (ARIES) platform. This framework enables the de-risking of next-generation geothermal and geothermal hybrid systems through high-fidelity modeling, real-time digital emulation, advanced control strategies, and techno-economic assessment. The project focused on geothermal hybrid configurations that integrate geothermal power plants with concentrated solar power and underground thermal energy storage, enabling enhanced efficiency, flexibility, and grid support capabilities. The main goal of this project was the development of a geothermal digital co-emulation environment to demonstrate the technical and economic value of geothermal hybrid systems and their contribution to grid stability and flexibility. The EXERGETIC framework combined physics-based models, controls, and real assets at ARIES, including digital real-time simulators (DRTS), a 20-MW-scale controllable grid interface (CGI), and a 2-MW conventional generator. Detailed transient models were developed for the key subsystems of a hybrid geothermal plant, including parabolic trough solar collectors, reservoir thermal energy storage (RTES), and a binary Organic Rankine Cycle (ORC) power plant. The ORC model explicitly captured thermal inertia and off-design operation and integrated control strategies to dynamically respond to electric load profiles. The models were validated against published experimental and numerical studies, demonstrating strong agreement and confirming the accuracy and robustness of the modeling approach. The resulting digital twin represents geothermal-solar-storage systems at multiple scales (1 MW to 100 MW) and enables realistic emulation of grid-connected operation. The control architecture allows the geothermal resource to provide stable baseload generation, while solar and stored thermal energy supply flexible, dispatchable support during periods of high demand or variable grid conditions. A key contribution of the EXERGETIC project is the demonstration that geothermal hybrid systems can be designed to be active grid assets rather than passive baseload generators. Using the ARIES platform, the digital twin was evaluated under multiple grid scenarios, including load following, voltage support at the distribution level, and frequency response at the transmission level. Results show that hybrid geothermal systems can respond effectively to dynamic grid conditions, providing inertia-like behavior, primary frequency support, and voltage regulation through coordinated control. In addition to the performance and grid services capability analysis of geothermal and hybrid geothermal systems, the EXERGETIC project also focused on scalability and techno-economic analysis of geothermal hybrid plants. In particular, for the scalability analysis, machine-learning (ML)-based surrogate models were trained using data generated from the geothermal digital twin under different grid-connected scenarios and plant capacities. These ML models demonstrated strong interpolation and extrapolation capabilities across plant sizes, accurately reproducing both steady-state and transient responses with very low errors. Regarding the techno-economic analysis, plant performance results were integrated with cost models for hybrid geothermal systems, and the levelized cost of electricity (LCOE) was used as the main economic metric to evaluate system performance across a range of system capacities, solar shares, solar multiples, and storage durations. Results indicate that economies of scale significantly reduce geothermal LCOE as plant capacity increases, with large-scale systems (25-100 MW) achieving substantially lower costs than small plants. Hybridization with solar thermal energy and storage further improves economic performance by increasing capacity utilization and enabling flexible dispatch. In addition, thermal storage plays a critical role in reducing LCOE by maximizing geothermal, solar, and stored energy resources. In summary, the results from this project demonstrate that geothermal hybrid systems represent a promising alternative for increasing the energy conversion efficiency of geothermal technologies, contributing to the preservation of geothermal resources, and supporting the transition of geothermal plants from traditional baseload resources into flexible, resilient, and cost-competitive energy conversion technologies.

15 GEOTHERMAL ENERGY↗

DOE OSTI2020

Multiphase Reacting Flow Simulations and Optimization of Commercial-Scale Aerobic Bioreactors

Aerobic bioreactors are widely used in the synthesis of value-added products in pharmaceutical and biotechnology industries, wherein microbial bioreactions aid in the conversion of sugars to macromolecules. These reactors are also being actively investigated as a cost-effective pathway for the production of low-value commodities such as biofuels and animal feed. Reactor scale-up is one of the important challenges when designing these systems. Gas and liquid phase transport, mass-transfer, and mixing physics at large length scales can significantly affect microbial conversion rates, particularly when the microbial reaction requires a narrow set of conditions. These phenomena are difficult to study in small-scale bench-top reactors that are typically well-mixed. Predictive computational fluid dynamics (CFD) based simulations can therefore aid in the design and optimization of these reactors. This work presents multiphase Euler-Euler CFD simulations of commercial-scale (~ 500 m3) aerobic bioreactors. Our mathematical model treats the gas and liquid as interpenetrating phases. This approach reduces the computational complexity of tracking individual gas bubbles that are several orders of magnitude smaller than reactor dimensions. We solve the Reynolds averaged Navier-Stokes (RANS) multiphase equations that account for phase and chemical species transport, interphase mass and momentum transfer and uses a phenomenological model for oxygen uptake by microbes. We use a customized solver derived from open-source CFD toolbox, OpenFOAM, to perform these simulations, which has been validated against small-scale reactors in our previous work. This work examines the performance of three different reactor designs, viz. bubble column reactor, airlift reactor with an internal draft tube, and a stirred-tank reactor with Rushton impellers. Reactor oxygen mass-transfer coefficient, gas hold-up, and oxygen distribution are critically analyzed among reactors, and sensitivity studies pertaining to gas flow rates and reactor geometry will be presented.

09 BIOMASS FUELS↗

DOE OSTI2020

Computationally-Aided Design of a Small-Scale Radioactive Waste Glass Melter

To provide mission support to the Hanford Waste Immobilization and Treatment Plant for the vitrification of legacy nuclear tank waste, a reduced-scale vitrification pilot system is being designed to process simulated and actual radioactive tank wastes. The tank waste will be separated into high-level waste (HLW) and low-activity waste (LAW) fractions, where the majority by mass (~90%) is LAW and by activity (>95%) is HLW. The first tank waste to be processed at the WTP will be LAW. Since Hanford tank waste and the resultant melter feed compositions are known to vary widely, pilot-scale operations are essential to identify potential problems, provide needed data, confirm assumptions, and determine impacts to full-scale melters and off-gas systems from these different feeds. In addition, the reduced-scale melter system must be capable of quickly providing results to operations without the typically high costs of radioactive operations and provide an engineering platform in close proximity to local operations staff. The objective is to produce similar process conditions to those encountered in the full-scale LAW melters and minimize the volume of radioactive waste necessary for the evaluations. To this end, melter design features are being explored to increase production without significantly increasing surface area, melter glass volumes or compromising data quality. In support of these objectives, a set of computational fluid dynamic models have been developed to provide insight into the flow patterns within these small melters and evaluate design features to increase production without significantly increasing glass inventory. Computed velocities were evaluated at the interface between the cold cap and the molten glass pool and within the bulk glass pool. A method was developed to correlate results to an estimated melt rate and down-select design features that produce the highest gains.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2020

Computationally-Aided Design of a Small-Scale Radioactive Waste Glass Melter

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2020

Large-Scale Solar Development: A Playbook for Southwest Virginia

his playbook is an introductory guide for local governments to facilitate large-scale solar projects in Southwest Virginia. In a region that has a long history of energy production, solar technologies offer enormous potential for economic development and job growth. Large-scale solar can take many forms, including rooftop or ground-mounted installations at local corporate offices, nonprofit organizations, or schools. It can also encompass utility-scale projects over many acres on former agricultural or timberlands, mined lands, or industrial sites. Regardless of the type of project, solar is a widely popular, cost-competitive energy choice that helps create sustainable and prosperous communities. This playbook is directed to municipal and county governments that have an essential role to play in encouraging large-scale solar projects. The first section provides an overview of state and national trends, including recent state legislation that will impact local oversight of solar development. This is followed by an overview of the solar project approval process from a developer’s perspective. The next section is an overview of the state and local permitting process for solar projects, followed by other development considerations such as local tax revenue options, financing incentives, and considerations for solar on brownfields and previously mined lands. The playbook concludes with a step-by-step guide for local governments to facilitate large-scale solar development.This playbook is part of the Solar Workgroup of Southwest Virginia’s effort to bring solar energy and associated jobs to the region. Over the past few years, the workgroup has met with stakeholder groups and crafted a strategy for local solar energy development. The workgroup has collaborated with cities and counties to bring SolSmart designation to eight counties and cities, implemented group purchase campaigns for commercial solar, and led research efforts.

14 SOLAR ENERGY↗

DOE OSTI2021

A Modularized Urban Scale Building Energy Modeling Framework Designed with An Open Mind

In recent years, physics-based building energy modeling (BEM) has started being used to evaluate the performance of buildings in the context of connected communities and on an urban scale to study their aggregated energy use, interactions, and impacts on the energy supply infrastructure and environment. The development of urban-scale BEM solutions needs extensive effort. Existing attempts tend to focus on different aspects of BEM on an urban scale, such as collecting as-built building data from different information sources, integrating geometry modeling with geographic information systems (GISs), representing operational and occupancy profiles, automating workflow, processing and visualizing the results, and conducting large-scale simulations. Urban-scale BEM development would benefit from multi-disciplinary research areas and from an open platform to adopt advancements on data sources and tools. For these purposes, this research proposes a modularized bottom-up model creation and simulation framework that is built on the state-of-the-art BEM tools and can accommodate different building stock data. This framework uses a standardized schema to describe building design and operational characteristics, and it can be instantiated from different building survey datasets with heterogeneous structures. The paper demonstrates how thousands of surveyed buildings from the 2012 U.S. Energy Information Administration’s Commercial Buildings Energy Consumption Survey (CBECS) were one-to-one converted to EnergyPlus models through the schema and the model generation process, then simulated with distributed computing, and their results are summarized.

Lei, Xuechen↗

DOE OSTI2022

The Modeling of the Synfuel Production Process: Process models of Fischer-Tropsch production with electricity and hydrogen provided by various scales of nuclear plants

Synthetic fuels (synfuels), also known as electro-fuels (E-fuels), are hydrocarbon fuels produced from waste CO2 streams and water electrolysis, with electricity as the primary source of energy. To achieve substantial reductions in greenhouse gas (GHG) emissions, electricity sources must release zero carbon or near-zero carbon, as is the case with solar, wind, hydro, and nuclear power. Nuclear power is one of the largest and steadiest domestic sources of clean energy in the United States. Moreover, nuclear power has the potential to produce hydrogen economically for less than $2/kg, reaching the DOE near-term target price. Thus, using nuclear power to produce synfuels has the unique potential to significantly reduce the GHG emissions of hydrocarbon fuels production and end-use applications. Fisher-Tropsch or FT fuel (a mixture of naphtha, jet fuel, and diesel) is of great interest because it is a drop-in fuel that can be blended with conventional petroleum counterparts and is compatible with existing infrastructure. By using the ASPEN Plus model, this report develops FT fuel production models on three scales, corresponding to nuclear plants with capacities of 1000 MWe, 437 Mwe, and 100 MWe, respectively. The FT model case with energy from a 437-MWe nuclear plant is used as a baseline case. This report summarizes the baseline ASPEN Plus model results with a detailed mass and energy analysis. Our modeled facility produces 507 MT/day (185,000 gal/day) of FT fuel by converting 255 MT/day of hydrogen and 1,580 MT/day of CO2. The FT fuel production energy efficiency from hydrogen and electricity energy inputs is 70% (lowerheating-value or LHV-based). Including the high-temperature electrolyzer in the system boundary, the FT fuel production LHV efficiency from electricity and thermal energy inputs is 51%, considering 39.8 kWh/kg of electricity and 6.86 kWh/kg of thermal energy use from a nuclear plant for hydrogen production. The FT production efficiency can potentially be increased by further integrating the heat exchange between nuclear plant and FT process, and this study is underway. The carbon conversion ratio in the baseline case is 99%, with process CO2 capture and recirculation and oxy-combustion using the oxygen by-product from water electrolysis. The hydrogen consumption is 1.38 kg/gal-FT fuel and the CO2 consumption is 8.56 kg/gal-FT fuel in the baseline case. With different FT production scales determined by the nuclear plant capacity, the FT model was scaled using the same operating parameters, which led to the same conversion efficiency regardless of scale. However, the different FT plant scales will impact the economics of FT fuel production; this impact will be examined in the next phase of this study.

Zang, Guiyan↗