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DOE OSTI2021

Methods for Delivery and Distribution of Amendments for Subsurface Remediation: A Critical Review

The ability to reliably deliver and widely distribute remedial amendments through the subsurface environment is of paramount importance to achieve clean-up objectives for contaminated sediments and groundwater for protection of sensitive environmental habitats and natural resources. A wide range of amendment types, delivery techniques, and subsurface access methods are available. However, the applicability of these approaches is dependent on a multitude of site-specific factors and conditions. In this review, an overview of amendment types (i.e., liquid, gas, and solids) and access/distribution methods is provided, along with discussion of the maturity level (low, medium, or high), advantages, and limitations that relate to the potential effectiveness of each approach in the context of site-specific factors (subsurface geology, geochemistry, contaminant properties, etc.). Each amendment type and delivery approach are further evaluated for applicability to the following subsurface target zones: saturated, unsaturated, and perched water, with specific focus on high and low permeability variants of each zone. The review highlights a critical need for field-tested approaches targeting unsaturated and perched water zones, as well as low-permeability regions within all subsurface regions. The intent of this review is to provide critical information and insight into how amendments can be delivered, emplaced, and/or distributed effectively in the subsurface environment to effectively manage subsurface contamination.

Muller, Katherine A.↗

DOE OSTI2021

Upscaling Reactive Transport and Clogging in Shale Microcracks by Deep Learning

Fracture networks in shales exhibit multiscale features. A rock system may contain a few main fractures and thousands of microcracks, whose length and aperture are orders of magnitude smaller than the former. It is computationally prohibitive to resolve all the fractures explicitly for such multiscale fracture networks. One traditional approach is to model the small-scale features (e.g., microcracks in shales) as an effective medium. Although this fracture-matrix conceptualization significantly reduces the problem complexity, there are classes of physical processes that cannot be accurately upscaled by effective medium approximations, e.g., microcrack clogging during mineral reactions. Here, we employ deep learning in place of effective medium theory to upscale physical processes in small-scale features. Specifically, we consider reactive transport in a fracture-microcrack network where microcracks can be clogged by precipitation. A deep learning multiscale algorithm is developed, in which the microcracks are upscaled as a wall boundary condition of the main fractures. The wall boundary condition is constructed by recurrent neural networks, which take concentration histories as input and predict the solute transport from main fractures to microcracks. The deep learning multiscale algorithm is firstly employed in specific scenarios, then a general model is developed which can work under various conditions. The new approach is validated against fully resolved simulations and an analytical solution, providing a reliable and efficient solution for problems that cannot be upscaled by effective medium models.

58 GEOSCIENCES↗

DOE OSTI2023

A deep learning upscaling framework: Reactive transport and mineral precipitation in fracture-matrix systems

Pore-scale modeling has limited applicability at large scales due to its high computational cost. One common approach to upscale pore-scale models is the use of effective medium theories, which homogenize small-scale features in a porous structure and characterize the medium by macroscale properties (e.g., permeability) and equations (e.g., Darcy’s law). However, there are classes of physical processes for which effective medium approximations may become inaccurate, e.g., mineral precipitation and clogging during reactive transport. We have developed a deep learning upscaling framework, in which pore-scale modeling is directly employed in macroscale systems, without relying on effective medium approximations. The upscaling framework is first developed for general multiscale systems and then applied to modeling reactive transport with mineral precipitation in the altered layer in fracture-matrix structures. Solute transport from the fractures to the matrix is modeled as a wall boundary condition for the fractures, which, in turn, is predicted by recurrent neural networks using the concentration histories at the fracture-matrix boundary. Specifically, we consider a meter-scale fracture network embedded in sandstones, where the smallest feature is at the micron scale. Here the proposed framework allows us to span five orders of magnitude in length scales by capturing mineral precipitation in the altered layer of the rock matrix at the pore scale across the entire meter-scale fracture network.

42 ENGINEERING↗

DOE OSTI2024

Advancing the understanding of energy-energy correlators in heavy-ion collisions

We investigate the collinear limit of the energy-energy correlator (EEC) in a heavy-ion context. First, we revisit the leading-logarithmic (LL) resummation of this observable in vacuum following a diagrammatic approach. We argue that this route allows to naturally incorporate medium-induced effects into the all-orders structure systematically. As an example, we show how the phase-space constraints imposed by the static medium on vacuum-like emissions can be incorporated into the LL result by modifying the anomalous dimensions. On the fixed-order side, we calculate the $\mathcal{O}$(α s ) expansion of the in-medium EEC for a γ → $q\overline{q}$ splitting with arbitrary kinematics including, for the first time, subleading colour corrections. When comparing this result to previously used approximations in the literature, we find up to $\mathcal{O}$(1) deviations in the regime of interest for jet quenching signatures. Energy loss effects are also quantified and further suppress the EEC at large angles. These semi-analytic studies are complemented with a phenomenological study using the jet quenching Monte Carlo JetMed. Finally, we argue that the imprint of medium-induced effects in energy-energy correlators can be enhanced by using an alternative definition that takes as input Lund primary declusterings instead of particles.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2020

Conservation Voltage Reduction (CVR) via Two-Timescale Control in Unbalanced Power Distribution Systems

Voltage control devices are employed in power distribution systems to reduce the power consumption by operating the system closer to the lower acceptable voltage limits; this technique is called conservation voltage reduction (CVR). The different modes of operation for system’s legacy devices (with binary control) and new devices (e.g. smart inverters with continuous control) coupled with variable photovoltaic (PV) generation results in voltage fluctuations which makes it challenging to achieve CVR objective. This paper presents a two-timescale control of feeder’s voltage control devices to achieve CVR that includes (1)a centralized controller operating in a slower time-scale to coordinate voltage control devices across the feeder and (2) local controllers operating in a faster timescale to mitigate voltage fluctuations due to PV variability. The centralized controller utilizes a three-phase optimal power flow model to obtain the decision variables for both legacy devices and smart inverters. The local controllers operate smart inverters to minimize voltage fluctuations and restore nodal voltages to their reference values by adjusting the reactive power support. The proposed approach is validated using the IEEE-123 bus (medium-size) and R3-12.47-2 (large-size) feeders. It is demonstrated that the proposed approach is effective in achieving the CVR objective for unbalanced distribution systems.

optimal control, distributed generation, fluctuati↗

DOE OSTI2023

Impact of the chiral asymmetry and a magnetic field on the passage of an energetic test parton in a QCD medium

We study the dependence of soft contribution to the energy loss of a test parton moving with a high velocity on the chiral imbalance and magnetic field in the QCD medium. A semiclassical approach is adopted to estimate the parton energy loss that takes into account the back-reaction on the parton due to the polarization effects of the QCD medium while traversing through the medium. We find that the motion of the parton is sensitive to the chiral asymmetry in the medium. Further, we investigate the effect of magnetic field-induced anisotropy on the energy transfer between the moving parton and the medium. Our results show that the energy loss of the parton is strongly influenced by the strength of the magnetic field as well as the relative orientation of the motion of the parton and the direction of the magnetic field in the medium.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2025

Selective Recovery of Critical Minerals from Simulated Electronic Wastes Via Reaction‐Diffusion Coupling

Abstract Atom‐ and energy‐efficient chemical separations are urgently needed to meet the surging demand for critical materials that has strained supply chains and threatened environmental damage. In this study, we used reaction‐diffusion coupling to separate iron, neodymium, and dysprosium ions from model feedstocks of permanent magnets, which are typically found in electronic wastes. Feedstock solutions were placed in contact with a hydrogel loaded with potassium hydroxide and/or dibutyl phosphate, resulting in complex precipitation patterns as the various metal ions diffused into the reaction medium. Specifically, we observed the precipitation of up to 40 mM of iron from the feedstock, followed by the enrichment of 73 % dysprosium, and the extraction of >95 % neodymium product at a further distance from the solution‐gel interface. We designed a series of experiments and simulations to determine the relevant ion diffusivities, D Nd =5.4×10 −10 and D Dy =5.1×10 −10 m 2 /s, and precipitation rates, k Nd =1.0×10 −5 and k Dy =5.0×10 −3 m 9 mol −3 s −1 , which enabled a numerical model to be established for predicting the distribution of products in the reaction medium. Our proof‐of‐concept study validates reaction‐diffusion coupling as an effective and versatile approach for critical materials separations, without relying on ligands, membranes, resins, or other specialty chemicals.

Wang, Qingpu [Physical and Computational Sciences ↗

DOE OSTI2026

Phononic Casimir Effect in Planar Materials

The phononic Casimir effect between planar objects is investigated by deriving a formalism from the quantum partition function of the system following multiscattering approach. This fluctuation-induced coupling is mediated by phonons modeled as an effective elastic medium. We find that excitations with three types of polarizations arise from the resolved boundary conditions, however the coupling is dominated by only one of these degrees of freedom due to exponential suppression effects in the other two. Here, the obtained scaling laws and dependence on materials properties and temperature suggest effective pathways of interaction control. Scenarios of materials combinations are envisioned where the phononic Casimir effect is of similar order as the standard Casimir interaction mediated by electromagnetic fluctuations.

Acoustic phonons↗

DOE OSTI2024

Demystifying group-4 polyolefin hydrogenolysis catalysis: Gaseous propane hydrogenolysis mechanism over the same catalysts

A kinetic/mechanistic investigation of gaseous propane hydrogenolysis over the single-site heterogeneous polyolefin depolymerization catalysts AlS/ZrNp 2 and AlS/HfNp 2 (AlS = sulfated alumina, Np = neopentyl), is use to probe intrinsic catalyst properties without the complexities introduced by time- and viscosity-dependent polymer medium effects. In a polymer-free automated plug-flow catalytic reactor, propane hydrogenolysis turnover frequencies approach 3,000 h −1 at 150 °C. Both catalysts exhibit approximately linear relationships between rate and [H 2 ] at substoichiometric [H 2 ] with rate law orders of 0.66 ± 0.09 and 0.48 ± 0.07 for Hf and Zr, respectively; at higher [H 2 ], the rates approach zero-order in [H 2 ]. Reaction orders in [C 3 H 8 ] and [catalyst] are essentially zero-order under all conditions, with the former implying rapid, irreversible alkane binding/activation. This rate law, activation parameter, and DFT energy span analysis support a scenario in which [H 2 ] is pivotal in one of two plausible and competing rate-determining transition states—bimolecular metal-alkyl bond hydrogenolysis vs. unimolecular β-alkyl elimination. The Zr and Hf catalyst activation parameters, ΔH ‡ = 16.8 ± 0.2 kcal mol −1 and 18.2 ± 0.6 kcal mol −1 , respectively, track the relative turnover frequencies, while ΔS ‡ = −19.1 ± 0.8 and −16.7 ± 1.4 cal mol −1 K −1 , respectively, imply highly organized transition states. These catalysts maintain activity up to 200 °C, while time-on-stream data indicate multiday activities with an extrapolated turnover number ~92,000 at 150 °C for the Zr catalyst. This methodology is attractive for depolymerization catalyst discovery and process optimization.

03 NATURAL GAS↗

DOE OSTI2022

An analysis of the hybrid internal mass modeling approach in EnergyPlus

Accurate simulation of building system dynamics is particularly important for understanding building energy flexibility. Among all dynamics in a building, a zone temperature’s variation is especially important, as it significantly affects a building’s electricity load profile when its heating, ventilating, and air conditioning (HVAC) system is controlled with on/off cycles or setpoint reset strategies. To accurately simulate a zone temperature’s dynamics, internal mass needs to be modeled carefully. In this paper, we compare the two internal mass modeling approaches provided by EnergyPlus, i.e., internal mass object and zone air capacitance multiplier, to better understand their impacts on zone temperature simulation. Real building zone temperature dynamic data from small- and medium-sized office buildings are analyzed and compared with simulated data. In particular, we illustrate the effectiveness of a hybrid method of the two EnergyPlus modeling approaches, which yields more realistic zone temperature dynamics, especially when the zone is conditioned with heat pump systems with on/off cycling.

Chen, Zhelun↗

DOE OSTI2024

Radiative corrections for factorized jet observables in heavy ion collisions

I look at the renormalization of the medium structure function and a medium induced jet function in a factorized cross section for jet substructure observables in Heavy Ion collisions. This is based on the formalism developed in [1], which uses an Open quantum system approach combined with the Effective Field Theory (EFT) for forward scattering to derive a factorization formula for jet observables which work as hard probes of a long lived dilute Quark Gluon Plasma (QGP) medium. I show that the universal medium structure function that captures the observable independent physics of the QGP has both rapidity and UV anomalous dimensions that appear due to medium induced Bremsstrahlung. The resulting Renormalization Group (RG) equations correspond to the BFKL equation and the running of the QCD coupling respectively. I present the first results for the numerical impact of resummation using these RG equations on the mean free path of the jet in the medium. I also briefly discuss the prospects of extending this formalism for a short lived dense medium.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2025

Comparative Economic Analysis Between Bioenergy and Forage Types of Switchgrass for Sustainable Biofuel Feedstock Production: A Data Envelopment Analysis and Cost–Benefit Analysis Approach

ABSTRACT The capacity to produce switchgrass efficiently and cost‐effectively across diverse environments can be pivotal in achieving the short‐ and medium‐term Sustainable Aviation Fuel targets set by the U.S. Department of Energy. This study evaluated the economic performance of forage‐ and bioenergy‐type switchgrass cultivars and their response to N fertilization under diverse marginal environments across the US Midwest that included Illinois (IL), Iowa (IA), Nebraska (NE), and South Dakota (SD). Data Envelopment Analysis (DEA) was used to evaluate the efficiency of 23 Decision‐Making Units (DMUs)—cultivar types and N fertilization rate combinations—while a cost–benefit analysis calculated their profitability over 5 years. Results showed that two energy‐type cultivars—“Independence” and “Liberty”—were superior economically to the forage cultivars. Independence performed best with the highest profit margin when fertilized at 56 kg N ha −1 , particularly in the US hardiness zone 6a (Urbana, IL). Liberty exhibited the highest profit margins in hardiness zone 5b (Madrid, IA, and Ithaca, NE) at 56 kg N ha −1 and showed exceptional profitability with 28 kg N ha −1 in hardiness zone 6b (Brighton, IL). Switchgrass cultivar “Carthage” showed better efficiency score and profitability results in hardiness zone 4b (South Shore, SD) at 56 kg N ha −1 . The profit trends observed in current study sites may indicate broader patterns across similar US hardiness zones. This study provides valuable insights for decision‐makers to optimize input strategies for biomass production of bioenergy switchgrass to meet renewable energy demands.

Arshad, Muhammad Umer [Department of Crop Sciences↗

DOE OSTI2021

Neural-network model for force prediction in multi-principal-element alloys

Atomistic simulations can provide useful insights into the physical properties of multi-principal-element alloys. However, classical potentials mostly fail to capture key quantum (electronic-structure) effects. Here we present a deep 3D convolutional neural network (3D CNN) based framework combined with a voxelization technique to design interatomic potentials for chemically complex alloys. We highlight the performance of the 3D CNN model and its efficacy in computing potentials using the medium-entropy alloy TaNbMo. In order to provide insights into the effect of voxel resolution, we implemented two approaches based on the inner and outer bounding boxes. An efficient 3D CNN model, which is as accurate as the density-functional theory (DFT) approach, for calculating potentials will provide a promising schema for accurate atomistic simulations of structure and dynamics of general multi-principle element alloys.

36 MATERIALS SCIENCE↗

DOE OSTI2022

A Reliable, Cost-Effective Transformerless Medium-Voltage Inverter for Grid Integration of Combined Solar and Energy Storage

The goal of this project is to utilize an innovative holistic power electronic inverter design approach, which can leverage best-in-class silicon carbide (SiC) power modules, novel multi-level power electronic circuits, high frequency transformers, switching sequence based control and co-designed electro-thermal management methods, to realize a 300 kW transformerless medium-voltage (MV) inverter system. The system cost of the inverter is considered as a primary design objective alongside high power density, efficiency, low electromagnetic interference (EMI) and long lifespan. This design-oriented research activity, especially the proposed multi-objective optimization approach, will have broad impacts in holistic power electronic system design methods and in technologies that can be commercialized into a wide variety of wide bandgap power electronic applications.

14 SOLAR ENERGY↗

DOE OSTI2020

Light element ($$Z=1,2$$) production from spontaneous ternary fission of $$^{252}$$Cf

Abstract The yields of light elements ( $$Z=1,2$$ Z = 1 , 2 ) obtained from spontaneous ternary fission of $$^{252}$$ 252 Cf are treated within a nonequilibrium approach, and the contribution of unstable nuclei and excited bound states is taken into account. These light cluster yields may be used to probe dense matter, and to infer in-medium corrections such as Pauli blocking which is determined by the nucleon density. Continuum correlations are calculated from scattering phase shifts using the Beth-Uhlenbeck formula, and the effect of medium modification is estimated. The relevant distribution is reconstructed from the measured yields of isotopes. This describes the state of the nucleon system at scission and cluster formation, using only three Lagrange parameters which are the nonequilibrium counterparts of the temperature and chemical potentials, as defined in thermodynamic equilibrium. We concluded that a simple nuclear statistical equilibrium model neglecting continuum correlations and medium effects is not able to describe the measured distribution of H and He isotopes. Moreover, the freeze-out concept may serve as an important ingredient to the nonequilibrium approach using the relevant statistical operator concept.

Röpke, G.↗

DOE OSTI2023

High-Precision Spectroscopy of 20 O Benchmarking Ab Initio Calculations in Light Nuclei

The excited states of unstable 20 O were investigated via γ-ray spectroscopy following the 19 O(d, p) ⁢20 O reaction at 8 A⁢ MeV. By exploiting the Doppler shift attenuation method, the lifetimes of the $2^+_2$ and $3^+_1$ states were firmly established. From the γ-ray branching and E⁢2/M⁢1 mixing ratios for transitions deexciting the $2^+_2$ and $3^+_1$ states, the B⁡(E⁢2) and B⁡(M⁢1) were determined. Various chiral effective field theory Hamiltonians, describing the nuclear properties beyond ground states, along with a standard USDB interaction, were compared with the experimentally obtained data. Such a comparison for a large set of γ-ray transition probabilities with the valence space in medium similarity renormalization group ab initio calculations was performed for the first time in a nucleus far from stability. It was shown that the ab initio approaches using chiral effective field theory forces are challenged by detailed high-precision spectroscopic properties of nuclei. Finally, the reduced transition probabilities were found to be a very constraining test of the performance of the ab initio models.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2023

Decision-making Framework to Support the End-of-Life Management of High-Activity Radioactive Sources

Sealed radioactive sources are used for an extremely wide range of purposes, including as radiation sources in various nuclear facilities, universities, hospitals, biomedical and industrial applications, as well as for geological prospecting and exploration. The proper management of these sealed radioactive sources once they have reached their end-of-life is still a global challenge. Very few field-tested Mobile Hot Cells (MHC) exist in the world to support the end-of-life management of disused high-activity radioactive sources. One of the critical challenges that a source recovery team encounters on each site is to find adequate space, and access to that space to complete the staging and recapture process with a MHC; this process is tedious, uncertain, and time-consuming. Therefore, it is essential to understand the planning and management of the MHC setup and takedown. Currently, there isn't an single capable planning tool that will provide an effective medium to plan, inform, educate, and communicate knowledge about the environment where the MHC will be deployed. We present a novel approach for the planning and management of the deployment of the MHC to several different sites that relies on technology. Furthermore, this planning tool will support collaboration, promote information sharing, and foster better decision making processes, resulting in a more efficient, and reliable setup and source recovery with the MHC.

61 RADIATION PROTECTION AND DOSIMETRY↗

DOE OSTI2024

Strategic Qualitative Risk Assessment of Thousands of Legacy Wells within the Area of Review (AoR) of a Potential CO2 Storage Site

The subsurface confinement of anthropogenic carbon dioxide (CO2) demands robust risk assessment methodologies to identify potential leakage pathways. Legacy wells within the Area of Review (AoR) represent one potential leakage pathway. Robust methodologies require enormous amounts of data, which are not available for many old legacy wells. This study strategically categorizes 4386 legacy wells within the AoR of a potential CO2 storage site in the Illinois basin and identifies the high-risk wells by leveraging publicly available data—reports and well logs submitted to state regulatory agencies. Wells were categorized based on their proximity to the injection well location, depth, the mechanical integrity of well barriers, and the accessibility to these wells throughout the project lifecycle. Wells posing immediate risks were identified, guiding prioritized corrective actions and monitoring plans. Out of 4386 wells, 54 have high priority for corrective action, 10 have medium priority, and the remainder are of low priority. Case study results from the Illinois basin demonstrate the effectiveness and applicability of this approach, to assess the risk associated with legacy wells within the AoR of potential CO2 storage site, strategically categorizing over 4000 such wells despite data limitations.

Arbad, Nachiket (ORCID:0000000215353656)↗