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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 199 records · Page 11

Model-based economic analysis under uncertainty for PFAS treatment by granular activated carbon and ion exchange technologies

Recent drinking water regulations have imposed the need for per- and polyfluoroalkyl substances (PFAS) remediation. In response, treatment facilities may be required to retrofit existing treatment schemes to treat PFAS below maximum contaminant levels (MCLs). Adsorption technologies such as granular activated carbon (GAC) and ion exchange (IX) have been demonstrated to be effective; however, there are limited techno-economic metrics available which provide guidance on technology selection and design for diverse PFAS-containing source water conditions. Process systems engineering (PSE) tools which can traditionally perform these analyses are hindered by the data availability, model validity, and understanding of treatment phenomena for emerging contaminants. This work employs published data regressions, statistical models, process models, techno-economic analyses, and other process systems tools in a model-based uncertainty framework to consider the limitations of emerging contaminant research. Through this analysis framework, economic results are provided as probabilistic distributions based on the uncertainty of the models and diverse conditions that treatment facilities experience.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Event driven readout architecture with non-priority arbitration for radiation detectors

A novel event driven readout architecture, EDWARD (Event Driven with Access and 8 Reset Decoder) architecture, for highly granular pixel detectors is presented. It incorporates, inter alia, an asynchronous arbitration tree based on Seitz' arbiters, removing the need for an imposed prioritization scheme. It also provides protection against glitches during readout. The system allows not only reading pixel activities, but also retrieving additional data, both analog and digital, from the pixels. A novel in-channel logic allows the entire readout process to be split into consecutive phases for additional flexibility. All operations are controlled by only one edge of the clock signal, seen as an acknowledge token, so there is no dead time between readouts.

47 OTHER INSTRUMENTATION↗

Large Scale Granulator Development Designed to Process Reclaimed Feedstock for Sustainable Additive Manufacturing Applications

This CRADA between UT-Battelle, LLC (Contractor) and re:3D Inc. (Participant) aims to develop an affordable large-scale granulator system designed to process reclaimed plastic feedstock suitable for additive manufacturing applications. The 24-month project will focus on testing, prototyping, and optimizing a shredder/granulator system. This project also focuses on the processing steps (e.g. washing and sorting) that can convert waste plastics, like discarded water bottles, into flake/granules which can be 3D printed using re:3D’s Fused Granular Fabrication (FGF) 3D printers. If successful, this could enable more localized 3D printing using recycled plastics, reducing waste and feedstock costs.

Wang, Peter [Oak Ridge National Laboratory (ORNL),↗

Quantum Computing for AI-based Design and Optimization of Electric Motors

Knowledge-based artificial intelligence and hierarchical fuzzy logic offer an interpretable framework for electricvehicle motor preliminary design, but their computational burden grows with linguistic granularity and coupled design-space size. This paper presents a reduced quantum reformulation of the hierarchical fuzzy inference of air-gap flux density, a representative level-one motor-design parameter. Starting from the published electric-vehicle motor-design framework, a three-term fuzzy prototype is constructed from the original inference structure. The reduced model is then reformulated as a modular quantum register-oracle system, in which each hierarchical subrelation is encoded as a block oracle and evaluated through superpositionbased candidate-label testing. The proposed modular quantum formulation reproduces the reduced classical prototype after block fusion. A resource analysis shows that the reduced modular system requires seven qubits per block and twenty-two qubits in a straightforward four-block implementation. Finally, a crossovercomplexity model is derived to identify the regime in which quantum candidate search may become favorable relative to hierarchical fuzzy inference. The results show that no quantum advantage should be claimed for the present one-output reduced benchmark, but that a plausible crossover emerges for larger joint candidate spaces and higher linguistic granularity. The work therefore establishes a technically consistent starting point for future quantum-assisted electric-vehicle motor-design optimization.

Kumar, Praveen [ORNL] (ORCID:0000000291877857)↗

Development of Chromium and Sulfur Getter for Solid Oxide Fuel Cell (SOFC) System

Under the “real world” SOFC operating conditions, gaseous Cr and S species coexist in air stream. The combined Cr and S effect on the electrochemical poisoning of candidate LSM and LSCF electrodes has been investigated. Electrochemical and structural analysis revealed that the combined Cr and S interactions with the LSCF electrode remains significantly different from those of the individual Cr and S interactions. S reacts with the surface SrO accompanied by morphological changes whereas the hexavalent gaseous Cr species mainly deposit at the LSCF/GDC interface as is the case with Cr-only poisoning. For LSM electrode, the combined interactions of Cr and S remains similar to the sum of individual Cr and S effects as SO 2 reacts with Sr-rich regions of the bulk LSM, while Cr deposits at the electrochemically active sites. The use of getter, consisting of alkaline earth and transition metal oxides, has been proposed as a cost-effective approach to mitigate electrode poisoning. SrMnO 3 (SMO) is suggested as a robust getter material for the co-capture of airborne gaseous S and Cr species entering high-temperature electrochemical systems. The honeycomb getter forms, covered with SMO nanoparticles, were fabricated using dip coating. The SMO getter successfully maintained the electrochemical activity of LSM under the presence of gaseous Cr and S species, validating the efficacy of the getter. Post-test characterization revealed that the absorption of S and Cr contaminants led to the elongation of granular SMO particles, forming SrO nanorods and SrCrO 4 whiskers leaving Mn oxides underneath where inward-migrating Cr reside, indicating the high mutual affinity of Sr and Mn. The growth of reaction products during the long term exposure favors continued absorption of incoming S and Cr contaminants. The Mn 2 O 9 dimers, existing on the surface, are considered to help absorb S and Cr impurities, along with the Sr-terminated surface. The SMO getter also displays robust stability in humid environments at high temperatures without phase transformation or hydrolysis, fulfilling the requirement for operation in high-temperature electrochemical systems.

30 DIRECT ENERGY CONVERSION↗

An investigation into the effects of cyclic strain rate on the high cycle and very high cycle fatigue behaviors of wrought and additively manufactured Inconel 718

Additive Manufacturing (AM) has increasingly been used to fabricate parts in aerospace applications, which may require service lives beyond ten-million cycles due to the imposed high loading frequencies. Understanding the very high cycle fatigue (VHCF) behavior of these additive manufactured (AM) parts is an important step towards their design and qualification processes. This study focuses on the high cycle fatigue (HCF) and VHCF behaviors of both wrought and laser beam-powder bed fusion (LB-PBF) fabricated Inconel 718 in machined/polished surface condition, emphasizing on the influence of test frequency (i.e., cyclic strain rate). Uniaxial, fully-reversed force- and stress-controlled fatigue tests were conducted utilizing a servo-hydraulic and an ultrasonic test system operating at 5 Hz and 20 kHz, respectively, on wrought as well as LB-PBF vertically and diagonally built specimens. Fatigue cracks in the majority of the specimens were found to initiate from intra-granular slip bands near or at the surface, which gives rise to strong anisotropy in fatigue resistance in LB-PBF specimens due to the presence of columnar grains along the build directions. Longer fatigue lives were obtained at 20 kHz, which was ascribed to possibly lower-than-intended stresses applied in the ultrasonic tests. The corrected stress-life fatigue data at 20 kHz were found to converge to the one obtained from conventional testing at 5 Hz, implying no effect of cyclic strain rate on the fatigue behavior of Inconel 718 regardless of the fabrication process. The findings of this work confirm the use of ultrasonic fatigue testing to expedite generation of AM materials data to keep up with the current demand; however, the applied stress may need to be corrected.

36 MATERIALS SCIENCE↗

CG-Kit: Code Generation Toolkit for performant and maintainable variants of source code applied to Flash-X hydrodynamics simulations

CG-Kit is a new Code Generation tool-Kit that we have developed as a part of the solution for portability and maintainability for multiphysics computing applications. The development of CG-Kit is rooted in the urgent need created by the shifting landscape of high-performance computing platforms and the algorithmic complexities of a particular large-scale multiphysics application: Flash-X. To efficiently use computing resources on a heterogeneous node, an application must have a map of computation to resources and a mechanism to move the data and computation to the resources according to the map. Most existing performance portability solutions are focussed on abstracting the expression of computations so that a unified source code can be specialized to run on different resources. However, such an approach is insufficient for a code like Flash-X, which has a multitude of code components that can be assembled in various permutations and combinations to form different instances of applications. Similar challenges apply to any code that has composability, where a single specified way of apportioning work among devices may not be optimal. Additionally, use cases arise where the optimal control flow of computation may differ for different devices while the underlying numerics remain identical. This combination leads to unique challenges including handling an existing large code base in Fortran and/or C/C++, subdivision of code into a great variety of units supporting a wide range of physics and numerical methods, different parallelization techniques for distributed and shared memory systems and accelerator devices, and heterogeneity of computing platforms requiring coexisting variants of parallel algorithms. All of these challenges demand that scientific software developers apply existing knowledge about domain applications, algorithms, and computing platforms to determine custom abstractions and granularity for code generation. There is a critical lack of tools to tackle those problems. CG-Kit is designed to fill this gap by providing a user with the ability to express their desired control flow and computation-to-resource map in the form a pseudocode-like recipe. It consists of standalone tools that can be combined into highly specific and, we argue, highly effective portability and maintainability toolchains. Here we present the design of our new tools: parametrized source trees, control flow graphs, and recipes. The tools are implemented in Python. They are agnostic to the programming language of the source code targeted for code generation. In conclusion, we demonstrate the capabilities of the toolkit with two examples, first, multithreaded variants of the basic AXPY operation, and second, variants of parallel algorithms within a hydrodynamics solver, called Spark, from Flash-X that operates on block-structured adaptive meshes.

Algorithmic portability↗

Enhancement of Two Heterogeneous Reactions in the Production of the Medical Isotope 188 W

We report the efficiency of heterogeneous reactions is influenced by kinetic conditions with an emphasis on reactants in different phases to have effective interactions. Optimal interactions of reactants rely on the rational design of the equipment and engineering parameters for the reaction process, especially for the process on a large scale. 188 W production at the Oak Ridge National Laboratory is such an example. In processing the irradiated 186 W metal target for the 188 W product, two of the heterogeneous reactions are essential ones: (1) the gas–solid reaction of O 2 + W to form WO 3 and (2) the gas–liquid reaction of OsO 4 being absorbed by the NaOH sorbent. Better understanding of the two reactions has led to revisions to the design of the quartz reaction vessel (gas–solid reaction) and the scrubbing system (gas–liquid reaction). The optimized quartz vessel resulted in less heating hours, whereas a more efficient OsO 4 scrubbing system ensured that all volatile OsO 4 was qualitatively captured.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Electric Vehicle and Infrastructure Systems Modeling in Washington D.C. and Baltimore

This report documents the Argonne-Exelon effort to develop and utilize an agent-based model (ATEAM) of charging demand and infrastructure expansion applicable to the Washington, DC–Baltimore, MD consolidated metropolitan area. This study extends the ATEAM model time horizon to 10 years (from 2020 to 2030), expands agent behavior modeling capabilities, incorporates more granular and extensive empirical data on charging behavior, and analyzes charging needs for a much larger population of PEVs, in keeping with regional goals for significant adoption of ZEVs. With given targets for annual BEV adoption, five scenarios were developed to examine public infrastructure needs and resulting charging load, considering different home charging availabilities, as well as different PEV consumer profiles and public charging infrastructure deployment strategies. Scenario results show that if new chargers (both L2 and DCFC) are spread more widely (as with ubiquitous deployment strategies), there will be less variation in the number of chargers added to each census tract in the study area. More importantly, widespread public charging infrastructure with ubiquitous deployment strategies reduces unmet charging demand and improves charging success, even with heavy reliance on public charging. About 80 percent of BEV drivers can charge on their first attempt in scenarios with ubiquitous deployment strategies. Moreover, widespread public charging infrastructure better meets the demand for more charging, and in return, increases BEV adoption. Low home charging availability produces higher charging loads in public locations, especially during the early morning (around 8:00 a.m.) and late afternoon (around 6:00 p.m.). The evening peak load indicates that drivers are taking advantage of public charging before heading home. Study results also indicate that even with 20 percent home charging availability in 2030, just 20 percent of drivers attempt to charge on a given day. With their relatively high electric range (200+ miles), the BEVs expected to be on the road in 2030 can handle daily commutes without re-charging for a couple of days.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Electrochemical reduction of per- and polyfluorinated alkyl substances (PFAS): is it possible? Applying experimental and quantum mechanical insights from the reductive defluorination literature

Remediation of per- and polyfluorinated alkyl substances (PFAS) in global water systems is a critical human and environmental health challenge facing society. PFAS consumption is associated with a litany of adverse health effects, and our knowledge of these dangers is still evolving. Current techniques to remove PFAS from water include adsorption to media (e.g. granular activated carbon, ion-exchange resin), nanofiltration, and reverse osmosis. However, these processes create a concentrated PFAS residual that requires further management. Destructive techniques are therefore needed to detoxify these residuals. Oxidative techniques have garnered the most attention (e.g. supercritical water oxidation, electrochemical oxidation) but are energy intensive and potentially form toxic by-products. As an alternative, several groups have researched advanced reduction processes that form aqueous electrons, but these processes are still chemical and energy intensive (e.g. ultraviolet/SO 3 2− , electron beam). This concise review therefore focuses on whether electrochemical reduction — a chemical-free, modular process — could be technically feasible for PFAS destruction.

King, Jacob F.↗

Solidification of REDC Organics For Disposal As Solid Waste

The Radiochemical Engineering Development Center (REDC) generates various liquid organic wastes from processing irradiated targets to recover heavy elements. In the past, these organics were discharged to the Oak Ridge National Laboratory (ORNL) liquid low-level waste (LLLW) system, along with the aqueous waste. Because of a reduction in aqueous LLLW from other ORNL generators and an increase in the radionuclide concentration, particularly 238 Pu, in the REDC organic waste stream, the organics can no longer be discharged to the LLLW system. The plan is to solidify the liquid organic waste for disposal as solid waste. Solidifying the organic liquids using PM-199 Organoclay ® would produce solid waste forms with no free liquid, which should qualify for disposal at the Waste Isolation Pilot Plant. Granular Organoclay can be added to the organic waste solutions until there is a dry layer on top of the liquid and then allowed to cure for a few hours to produce a solid wasteform.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

ComStock Measure Documentation: Fan Static Pressure Reset for Multizone Variable Air Volume Systems

This report assesses the potential for nationwide adoption of a duct static pressure reset in MZ VAV systems in appropriate applications. Building on the 3-year End-Use Load Profiles project to calibrate and validate the U.S. Department of Energy’s ResStock™ and ComStock™ models, this work produces national datasets that enable cities, states, utilities, and other stakeholders to answer a broad range of questions regarding their commercial building stock. ComStock is a highly granular, bottom-up model that uses various data sources, statistical sampling methods, and advanced building energy simulations to estimate the annual sub-hourly energy consumption of the commercial building stock across the United States. The “baseline” model intends to represent the U.S. commercial building stock as it existed in 2018. The methodology of the baseline model is discussed in the ComStock Reference Documentation. The goal of this work is to develop energy efficiency and demand flexibility measures that cover market-ready technologies and study their mass-adoption impact on the baseline building stock. “Measures” refers to various “what-if” scenarios that can be applied to buildings. The results for the baseline and measure scenario simulations are published in public datasets that provide insights into building stock characteristics, operational behaviors, utility bill impacts, and annual and sub-hourly energy usage by fuel type and end use. This report describes the modeling methodology for a single ComStock measure scenario—Fan Static Pressure Reset for Multizone Variable Air Volume (VAV) Systems—and briefly introduces key results. The full public dataset can be accessed on the ComStock data lake or via the Data Viewer at comstock.nrel.gov. The public dataset enables users to create custom aggregations of results for their use case (e.g., filter to a specific county or building type).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Universal behavior in fragmenting brittle, isotropic solids across material properties

A bonded particle model is used to explore how variations in the material properties of brittle, isotropic solids affect critical behavior in fragmentation. To control material properties, a model is proposed which includes breakable two- and three-body particle interactions to calibrate elastic moduli and mode I and mode II fracture toughnesses. In the quasistatic limit, fragmentation leads to a power-law distribution of grain sizes which is truncated at a maximum grain mass that grows as a nontrivial power of system size. In the high-rate limit, truncation occurs at a mass that decreases as a power of increasing rate. A scaling description is used to characterize this behavior by collapsing the mean-square grain mass across rates and system sizes. Consistent scaling persists across all material properties studied, although there are differences in the evolution of grain size distributions with strain as the initial number of grains at fracture and their subsequent rate of production depend on Poisson's ratio. Importantly, this evolving granular structure is found to induce a unique rheology where the ratio of the shear stress to pressure, an internal friction coefficient, decays approximately as the logarithm of increasing strain rate. The stress ratio also decreases at all rates with increasing strain as fragmentation progresses and depends on elastic properties of the solid.

36 MATERIALS SCIENCE↗

Improving Trustworthiness of Data-Driven Power Grid Contingency Analysis With Bayesian Residual Graph Neural Networks

The evolving energy landscape requires novel tools to efficiently perform contingency analysis and reliability assessment of power grids, potentially in real-time. The high computational cost of traditional power flow solvers limits their applicability in practice. Machine learning (ML) surrogates such as deep neural networks (NNs) accelerate power flow solvers computations, enabling high-order contingency analysis and real-time decision-making by learning highly nonlinear functions and integrating grid topology via graph architectures. However, (graph) NNs lack predictive power away from training data and do not provide predictive confidence estimates. Here, we present a Bayesian residual graph NN that integrates knowledge from low-fidelity data via residual training and embeds granular quantification of uncertainties, improving trustworthiness critical for high-consequence decision-making. Applying Bayesian concepts to NNs is challenging due to the high-dimensionality of both the parameter space, complicating derivation of a meaningful prior, and the output space in large grid systems, requiring enhanced techniques to assess the predicted high-dimensional uncertainties. Our contributions include: (1) Deriving a prior for fully connected and graph NNs that leverages low-fidelity data to guide mean predictions and appropriately control prior predictive uncertainty. (2) Integrating this prior within an ensembling with anchoring scheme for efficient approximate posterior inference. (3) Deriving enhanced metrics to assess accuracy of both the mean and uncertainty predictions in high dimensions, appropriately accounting for correlations propagated through graph layers. The resulting Bayesian residual graph NN is tested on a contingency analysis task for 14-bus and 118-bus grids.

24 - POWER TRANSMISSION AND DISTRIBUTION↗

Voronoi cell analysis: The shapes of particle systems

Many physical systems can be studied as collections of particles embedded in space, often evolving in time. Natural questions arise concerning how to characterize these arrangements—are they ordered or disordered? If they are ordered, how are they ordered and what kinds of defects do they possess? Voronoi tessellations, originally introduced to study problems in pure mathematics, have become a powerful and versatile tool for analyzing countless problems in pure and applied physics. Here we explain the basics of Voronoi tessellations and the shapes that they produce and describe how they can be used to characterize many physical systems.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Evaluation of Lost Circulation Material Sealing for Geothermal Drilling

Lost circulation is a pervasive problem in geothermal wells that can create prohibitive costs during drilling. The main issue with treatment is that the mechanism of plug formation is poorly understood. Here we applied two experimental approaches to characterize the clogging effectiveness of different materials. Fracture flow tests with different geometries were conducted with various individual materials and mixtures at relevant conditions. A high-temperature flow loop system was also developed to inject single- and mixed-material plugs into a gravel pack with a non-uniform geometry to compare with the fracture tests. The fracture tests revealed that single materials tended to form no plug or an unstable plug, while mixtures of materials were uniformly better at sealing fractures. Gravel pack tests at high temperatures show most of the materials are intact but degraded. The fibrous materials can create partial or unstable plugs in the gravel pack, but mixed-material plugs are far more effective at clogging. Both test types suggest that (1) mixed materials are more effective at blocking fluid flow and (2) fibrous materials seal fracture openings better, while granular materials seal inside fractures or pore throats better. Further research is needed to study the long-term stability of different plug configurations.

clogging tests↗