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At least 361 records · Page 20

The cementitious barriers partnership experimental programs and software advancing DOE's waste disposal/tank closure efforts - 15436

The U.S. Department of Energy Environmental Management (DOE-EM) Office of Tank Waste Management sponsored Cementitious Barriers Partnership (CBP) is chartered with providing the technical basis for implementing cement-based waste forms and radioactive waste containment structures for long-term disposal. DOE needs in this area include the following to support progress in final treatment and disposal of legacy waste and closure of High-Level Waste (HLW) tanks in the DOE complex: - Long-term performance predictions and - Flow sheet development and flow sheet enhancements - Conceptual designs for new disposal facilities The DOE-EM Cementitious Barriers Partnership is producing software and experimental programs resulting in new methods and data needed for end-users involved with environmental cleanup and waste disposal. Both the modeling tools and the experimental data have already benefited the DOE sites in the areas of performance assessments by increasing confidence backed up with modeling support, leaching methods, and transport properties developed for actual DOE materials. In 2014, the CBP Partnership released the CBP Software Toolbox - 'Version 2.0' which provides concrete degradation models for: 1) sulfate attack, 2) carbonation, 3) chloride initiated rebar corrosion, and includes constituent leaching. These models are applicable and can be used by both DOE and the Nuclear Regulatory Commission (NRC) for service life and long-term performance evaluations and predictions of nuclear and radioactive waste containment structures across the DOE complex (Figure 1) including Future SRS salt-stone and HLW tank performance assessments and special analyses - Hanford site HLW tank closure projects and other projects in which cementitious barriers are required - The Advanced Simulation Capability for Environmental Management (ASCEM) project which requires source terms from cementitious containment structures as input to their flow simulations - Regulatory reviews of DOE performance assessments - Nuclear Regulatory Commission reviews of commercial nuclear power plant (NPP) structures which are part of the overall US Energy Security program to extend the service life of NPPs In addition, the CBP experimental programs have had a significant impact on the DOE complex by providing specific data unique to DOE sodium salt wastes at Hanford and SRS which are not readily available in the literature. Two recent experimental programs on cementitious phase characterization and on technetium (Tc) mobility have provided significant conclusions as summarized below: Recent mineralogy characterization discussed in this paper illustrates that sodium salt waste form matrices are somewhat similar to but not the same as those found in blended cement matrices which to date have been used in long-term thermodynamic modeling and contaminant sequestration as a first approximation. Utilizing the CBP generated data in long-term performance predictions provides for a more defensible technical basis in performance evaluations. - In addition, recent experimental studies related to technetium mobility indicate that conventional leaching protocols may not be conservative for direct disposal of Tc- containing waste forms in vadose zone environments. These results have the potential to influence the current Hanford supplemental waste treatment flow sheet and disposal conceptual design. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Structural and Computational Assessment of the Influence of Wet-Chemical Post-Processing of the Al-Substituted Cubic Li 7 La 3 Zr 2 O 12

Li 7 La 3 Zr 2 O 12 (LLZO) and related compounds are considered as promising candidates for future all-solid-state Li-ion battery applications. Still, the processing of those materials into thin membranes with the right stoichiometry and crystal structure is difficult and laborious. The sensitivity of the Li-ion conductive garnets against moisture and the associated Li + /H + cation exchange makes their processing even more difficult. Formulation of suitable polymer/ceramic hybrid solid state electrolytes could be a prosperous way to reach the future large scale production of solid state Li-ion batteries. In fact, solvent mediated and/or slurry based wet-processing of the LLZO, e.g., tape-casting, could result in irreversible Li-ion loss of the pristine material due to Li + /H + cation exchange. The concomitant structural changes and loss in functionality in terms of Li-ion conductivity are the results of the above process. As such, in the present work a systematic study on the chemical stability and structural retention of Al-substituted LLZO in different solvents is reported. It was found that Li + /H + exchange in LLZO occurs upon solvent immersion, and its magnitude is dependent on the availability of –OH functional groups of the solvent molecules. As a result, a larger degree of Li + /H + exchange causes higher increase of the lattice parameter of the LLZO, determined by synchrotron diffraction analyses. The expansion of the cubic unit cell was ascertained, when Li + was replaced by H + in the host lattice, by ab initio computational studies. The application of the most common solvent as dispersion medium, i.e., high purity water, causes the most significant Li + /H + exchange and, therefore, structural change, while acetonitrile was proven to be the best suitable solvent for wet postprocessing of LLZO. Finally, computational calculations suggested that the Li + /H + exchange could result in diminished ionic, i.e., mixed Li + –H + , conductivity due to the insertion of protons with lower mobility than that of Li-ions.

36 MATERIALS SCIENCE↗

Selection Metric for Photovoltaic Materials Screening Based on Detailed-Balance Analysis

The success of recently discovered absorber materials for photovoltaic applications has been generating increasing interest in systematic materials screening over the last years. However, the key for a successful materials screening is a suitable selection metric that goes beyond the Shockley-Queisser theory that determines the thermodynamic efficiency limit of an absorber material solely by its band-gap energy. Here, we develop a selection metric to quantify the potential photovoltaic efficiency of a material. Our approach is compatible with detailed balance and applicable in computational and experimental materials screening. We use the complex refractive index to calculate radiative and nonradiative efficiency limits and the respective optimal thickness in the high mobility limit. We also compare our model to the widely applied selection metric by Yu and Zunger [Phys. Rev. Lett. 108, 068701 (2012)] with respect to their dependence on thickness, internal luminescence quantum efficiency, and refractive index. Finally, the model is applied to complex refractive indices calculated via electronic structure theory.

14 SOLAR ENERGY↗

Localization of phonons in mass-disordered alloys: A typical medium dynamical cluster approach

The effect of disorder on lattice vibrational modes has been a topic of interest for several decades. In this article, we employ a Green's function based approach, namely, the dynamical cluster approximation (DCA), to investigate phonons in mass-disordered systems. Detailed benchmarks with previous exact calculations are used to validate the method in a wide parameter space. An extension of the method, namely, the typical medium DCA (TMDCA), is used to study Anderson localization of phonons in three dimensions. We show that, for binary isotopic disorder, lighter impurities induce localized modes beyond the bandwidth of the host system, while heavier impurities lead to a partial localization of the low-frequency acoustic modes. For a uniform (box) distribution of masses, the physical spectrum is shown to develop long tails comprising mostly localized modes. The mobility edge separating extended and localized modes, obtained through the TMDCA, agrees well with results from the transfer matrix method. A reentrance behavior of the mobility edge with increasing disorder is found that is similar to, but somewhat more pronounced than, the behavior in disordered electronic systems. Our work establishes a computational approach, which recovers the thermodynamic limit, is versatile and computationally inexpensive, to investigate lattice vibrations in disordered lattice systems.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

MRDIS Standalone Central Alarm Station

The MRDIS Standalone Central Alarm Station(MRDIS-CAS} is a software system for receiving, storing, and reviewing radiation data collected by the Mobile Radiation Detection and Identification System (MRDIS}, a mobile radiation scanning system developed for use in foreign ports for the DOE Megaports Initiative. It is designed to run on one of the on board computers in the MRDIS cab. It will collect, store, and display data from the MRDIS without the need for wireless communications or centralized server technology. It is intended to be a lightweight replacement for a distributed Megaports communication system in ports where the necessary communications infrastructure does not exist for a full Megaports communications system.

Source record↗

CrossSim Inference Manual v2.0

Neural networks are largely based on matrix computations. During forward inference, the most heavily used compute kernel is the matrix-vector multiplication (MVM): $W \vec{x} $. Inference is a first frontier for the deployment of next-generation hardware for neural network applications, as it is more readily deployed in edge devices, such as mobile devices or embedded processors with size, weight, and power constraints. Inference is also easier to implement in analog systems than training, which has more stringent device requirements. The main processing kernel used during inference is the MVM.

97 MATHEMATICS AND COMPUTING↗

Toward Chirality-Encoded Domain Wall Logic

Nonvolatile logic networks based on spintronic and nanomagnetic technologies have the possibility to create high-speed, ultralow power computational architectures. This work investigates the feasibility of “chirality-encoded domain wall logic,” a nanomagnetic logic architecture where data are encoded by the chiral structures of mobile domain walls in networks of ferromagnetic nanowires and processed by the chiral structures' interactions with geometric features of the networks. High-resolution magnetic imaging is used to test two critical functionalities: the inversion of domain wall chirality at tailored artificial defect sites (logical NOT gates) and the chirality-selective output of domain walls from 2-in-1-out nanowire junctions (common operation to AND/NAND/OR/NOR gates). The measurements demonstrate both operations can be performed to a good degree of fidelity even in the presence of complex magnetization dynamics that would normally be expected to destroy chirality-encoded information. Together, these results represent a strong indication of the feasibility of devices where chiral magnetization textures are used to directly carry, rather than merely delineate, data.

36 MATERIALS SCIENCE↗

RETRO RX

RETRO Rx is an R&D 100 Gold Award-winning suite of tools that provides a new class of analytics in the space between traditional epidemiological models and unanalyzed spreadsheets of data. Unlike traditional models, these tools provide analysts, scientists, practitioners, and decision makers a way to easily and effectively do sophisticated analyses using a simple user interface. AIDO guides users at the early stages of a disease outbreak by comparing the current parameters to historic outbreaks. RED Alert constructs a broad historical picture of disease incidence (recent outbreak included) to detect disease reemergence at its earliest stages, locally and globally. RETRO Rx compiles data and presents analysis in a clear, concise visual format to support disease mitigation and prevention planning. Both are available currently as web-based apps. A prototype of the RED Alert mobile app with enhanced functionality is available for beta testing and AIDO mobile app development is planned.

59 BASIC BIOLOGICAL SCIENCES↗

Low-Temperature Annealing of Nanoscale Defects in Polycrystalline Graphite

Polycrystalline graphite contains multi-scale defects, which are difficult to anneal thermally because of the extremely high temperatures involved in the manufacturing process. In this study, we demonstrate annealing of nuclear graphite NBG-18 at temperatures below 28 °C, exploiting the electron wind force, a non-thermal stimulus. High current density pulses were passed through the specimens with a very low-duty cycle so that the electron momentum could mobilize the defects without heating the specimen. The effectiveness of this technique is presented with a significant decrease in electrical resistivity, defect counts from X-ray computed tomography, Raman spectroscopy, and nanoindentation-based mechanical characterization. Such multi-modal evidence highlights the feasibility of nanoscale defect control at temperatures about two orders of magnitude below the graphitization temperature.

Liu, Gongyuan↗

PeakQC: A Software Tool for Omics-Agnostic Automated Quality Control of Mass Spectrometry Data

Mass spectrometry is broadly employed to study complex molecular mechanisms in various biological and environmental fields, enabling 'omics' research such as proteomics, metabolomics, and lipidomics. As study cohorts grow larger and more complex with dozens to hundreds of samples, the need for robust quality control (QC) measures through automated software tools becomes paramount to ensure the integrity, high quality, and validity of scientific conclusions from downstream analyses and minimize the waste of resources. Since existing QC tools are mostly dedicated to proteomics, automated solutions supporting metabolomics are needed. To address this need, we developed the software PeakQC, a tool for automated QC of MS data that is independent of omics molecular types (i.e., omics-agnostic). It allows automated extraction and inspection of peak metrics of precursor ions (e.g., errors in mass, retention time, arrival time) and supports various instrumentations and acquisition types, from infusion experiments or using liquid chromatography and/or ion mobility spectrometry front-end separations and with/without fragmentation spectra from data-dependent or independent acquisition analyses. Diagnostic plots for fragmentation spectra are also generated. Here, in this paper, we describe and illustrate PeakQC’s functionalities using different representative data sets, demonstrating its utility as a valuable tool for enhancing the quality and reliability of omics mass spectrometry analyses.

47 OTHER INSTRUMENTATION↗

A new efficient grain growth model using a random Gaussian-sampled mode filter

This paper presents the use of a Gaussian neighborhood mode filter for predicting grain growth in a manner similar to the solutions obtained by a Monte Carlo Potts model. This flexible grain growth model can quickly utilize modern, computationally optimized data science strategies on graphics processing units to simulate grain growth up to 100 times faster than the state-of-the-art, publicly available Monte Carlo Potts model. We show that, given the correct neighborhood, the mode filter can replicate normal grain growth in two or three dimensions. In addition, the paper briefly demonstrates the ability to model limited anisotropic in grain boundary energy and mobility. Anisotropic grain boundary energy is modeled by defining a weighted mode filter operation. Anisotropic grain boundary mobility is modeled by scaling and orienting the Gaussian neighborhood in a particular direction.

Anisotropy↗

Applying Hanford Tank Mixing Data to Define Pulse Jet Mixer Operation

Pulse jet mixed (PJM) process vessels are being developed for storing, blending, and chemical processing of nuclear waste slurries at the Waste Treatment and Immobilization Plant (WTP) to be built at Hanford, Washington. These waste slurries exhibit variable process feed characteristics including Newtonian to non-Newtonian rheologies over a range of solids loadings. Waste feed to the WTP from the Hanford Tank Farms will be accomplished via the Waste Feed Delivery (WFD) system which includes million-gallon underground storage double-shell tanks (DSTs) with dual-opposed jet mixer pumps. Experience using WFD type jet mixer pumps to mobilize actual Hanford waste in DSTs may be used to establish design threshold criteria of interest to pulse jet mixed process vessel operation. This paper describes a method to evaluate the pulse jet mixed vessel capability to process waste based on information obtained during mobilizing and suspending waste by the WFD system jet mixer pumps in a DST. Calculations of jet velocity and wall shear stress in a specific pulse jet mixed process vessel were performed using a commercial computational fluid dynamics (CFD) code. The CFD-modelled process vessel consists of a 4.9-m- (16-ft-) diameter tank with a 2:1 semi-elliptical head, a single, 10-cm (4-in.) downward facing 60-degree conical nozzle, and a 0.61-m (24-in.) inside diameter PJM. The PJM is located at 70% of the vessel radius with the nozzle stand-off-distance 14 cm (6 in.) above the vessel head. The CFD modeled fluid velocity and wall shear stress can be used to estimate vessel waste-processing performance by comparison to available actual WFD system process data. Test data from the operation of jet mixer pumps in the 23-m (75-ft) diameter DSTs have demonstrated mobilization, solid particles in a sediment matrix were moved from their initial location, and suspension, mobilized solid particles were moved to a higher elevation in the vessel than their initial location, of waste solids. Jet mixer pumps were used in Hanford waste tank 241-AZ-101, and at least 95% of the 0.46-m (18-in.) deep sediment, with a shear strength of 1,500 to 4,200 Pa, was mobilized. Solids with a median particle size of 43 μm, 90th percentile of 94μm, were suspended in tank 241-AZ-101 to at least 5.5 m (216 in.) above the vessel bottom. Analytical calculations for this jet mixer pump test were used to estimate the velocities and wall shear stress that mobilized and suspended the waste. These velocities and wall shear stresses provide design threshold criteria which are metrics for system performance that can be evaluated via testing. If the fluid motion in a specific pulse jet mixed process vessel meets or exceeds the fluid motion of the demonstrated performance in the WFD system, confidence is provided that that vessel will similarly mobilize and suspend those solids if they were within the WTP. The single PJM CFD-calculated jet velocity and wall shear stress compare favorably with the design threshold criterion estimated for the tank 241-AZ-101 process data. Therefore, for both mobilization and suspension, the performance data evaluated from the WFD system testing increases confidence that the performance of the pulse jet mixed process vessels will be sufficient to process that waste even if that waste is not fully characterized.

mixing' slurry↗

Microgrid Integration with High Performance Computing Systems for Microreactor Operation

Multiple nuclear microreactor concepts are currently being developed across several sizes and fuel types with high performance computing (HPC) systems anticipated to be end-users of the power. Nuclear microreactors are small in size, portable, produce less than 10 MW electric, operate autonomously, and have a refueling interval of as many as 10 years. However, their load-follow is also generally limited to 10%/minute or worse whereas the power variance in HPC systems easily exceeds this constraint under normal operations. This study explores an approach that requires no load-follow from the microreactor but integrates the HPC system with a microgrid built from commercial-off-the-shelf components. Three typical HPC architectures are explored in the context of microgrid operation in this study. Components of power quality and transient response are empirically measured for five different HPC load-follow response levels using a self-contained mobile datacenter connected to the microgrid capable of integration with a nuclear microreactor.

microgrids↗

The CanBikeCO Mini Pilot: Procedure and Preliminary Results

In fall 2020, the Colorado Energy Office, as part of the State of Colorado's "Can Do Colorado" initiative, initiated a project aimed at encouraging energy-efficient transportation during the COVID-19 pandemic. The initial mini-pilot provided e-bikes to 13 low-income households under an individual ownership model. This report assesses the impact of providing this additional mobility option on the travel behavior of participants. It also outlines the lessons learned from deploying a continuous monitoring platform to track the travel behavior. These lessons will influence the evaluation component for the full pilot, which will cover multiple geographic regions, start in summer 2021, and run for 2 years. The continuous data collection was enabled by a customized version of the open-source e-mission platform, called CanBikeCO, configured with a behavioral gamification feature. The Colorado Energy Office used this system to collect a unique data set consisting of 3 months of partially automated travel diaries, combining sensed and surveyed data and linked with demographic information, from 12 participants. The data collection process worked well overall: users generally liked the app, appreciated the game, and did not complain about battery life. The long tracking period introduced behavioral challenges in user engagement, which we plan to address using repeated patterns and automated status checks for the full pilot. The analysis results, based on the subset of trips with user-reported labels (68%), indicate that the e-bike was the dominant commute mode share (31%), in sharp contrast to the census bicycle commute mode share (<1%). E-bike trips primarily replaced single-occupancy vehicle (SOV) trips (28%), followed closely by walking (24%) and regular bike (20%). The non-motorized mode replacement corresponds to lower travel time and increased productivity enabled by the program. The emissions impact analysis of the program, computed using trip-level energy intensity factors, indicates savings of 1,367 lbs. of CO2. Although the results are strongly positive, the narrow demographic profile of study participants, their limited mobility alternatives, and nonuniform labeling indicate caution in broader interpretation. These preliminary results do suggest that such programs, supported by real-time education and support from program managers, can simultaneously meet equity and sustainability goals. The planned full pilot, addressing the data collection challenges and broadening the geographic scope, will provide additional insights into the generality of this approach.

ADVANCED PROPULSION SYSTEMS↗

Pore-scale CFD simulations of clay mobilization in natural porous media due to fresh water injection

The present work investigates mechanisms of permeability impairment as a result of low-salinity fluid injection into brine-saturated porous media containing dispersible clays. Here, we present a computational fluid dynamics model at the pore-scale to simulate detachment, migration and straining of fine particles in porous media. The model uses an immersed boundary method to simulate the motion of clay fines in a fluid. In addition to the hydrodynamic forces, we model the Derjaguin-Landau-Verwey-Overbeek forces (DLVO) between clay fines and grains. Our simulations show the impact of the injected fluid's salinity and velocity on the concentration of clay fines retained on the grain surface. We see clay particles dislodging from the grain surface in clusters of up to 12 particles. Our simulation results also demonstrate clogging of narrow pore spaces by the detached particles from the grain surfaces.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Implications of stop-and-go traffic on training learning-based car-following control

Learning-based car-following control (LCC) of connected and autonomous vehicles (CAVs) is gaining significant attention with the advancement of computing power and data accessibility. While the flexibility and large model capacity of model-free architecture enable LCC to potentially outperform the model-based car-following (CF) model in improving traffic efficiency and mitigating congestion, the generalizability of LCC for traffic conditions different from the training environment/dataset is not well-understood. Herein, this study seeks to explore the impact of stop-and-go traffic in the training dataset on the generalizability of LCC. It uses the characteristics of lead vehicle trajectories to describe stop-and-go traffic, and links the theory of identifiability (i.e., obtaining a unique parameter estimation result using sensor measurements) to the generalizability of behavior cloning (BC) and policy-based deep reinforcement learning (DRL). Correspondingly, the study shows theoretically that: (i) stop-and-go traffic can enable the property of identifiability and enhance the control performance of BC-based LCC in different traffic conditions; (ii) stop-and-go traffic is not necessary for DRL-based LCC to generalize to different traffic conditions; (iii) DRL-based LCC trained with only constant-speed lead vehicle trajectories (not sufficient to ensure identifiability) can be generalized to different traffic conditions; and (iv) stop-and-go traffic increases variance in the training dataset, which improves the convergence of parameter estimation while negatively impacting the convergence of DRL to the optimal control policy. Numerical experiments validate the above findings, illustrating that BC-based LCC entails comprehensive training datasets for generalizing to different traffic conditions, while DRL-based LCC can achieve generalization with simple free-flow traffic training environments. This further suggests DRL as a more promising and cost-effective LCC approach to reduce operational costs, mitigate traffic congestion, and enhance safety and mobility, which can accelerate the deployment and acceptance of CAVs.

33 ADVANCED PROPULSION SYSTEMS↗