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At least 973 records · Page 54

A Model of Grain Boundary Complexion Transitions and Grain Growth in Yttria-Doped Alumina

In this work, we present a physically-parameterized microstructure evolution model for the Yttria-doped alumina system. Yttria-doped alumina is a well-known ceramic system which undergoes first-order phase-like transitions at grain boundaries, which can radically alter interface properties. The change in interfacial properties in turn can radically change microstructure outcomes during processing, including the induction of abnormal grain growth modes. In this work, we develop a simulation that evolves alumina microstructure as a function of yttria concentration and temperature. In the window studied, we achieve strong agreement with reviewed experimental results in identifying the windows for large grains, small grains, abnormal grain growth, and complexion transition kinetics. We then apply the model to study and demonstrate how the possible inclusion of second-phase particles or uneven solute distribution profiles will impact microstructure evolution. It is found that particles do not significantly affect abnormal grain growth in the window studied (but do lead to reduced grain size through pinning effects). It is found that even modest amounts of solute inhomogeneity will result in substantial changes in microstructure outcomes, frequently leading to clusters of abnormal grains. This model largely corroborates the expectations and hypotheses made from recent experimental studies in oxide-doped alumina systems. Further, it is found that there exists a peak transition fraction for the system at which abnormal grain size tends to be maximized.

Grain Growth, Grain Boundary Complexion, abnormal ↗

Mesoscopic-scale complexity in macroscopically-uniform plastic flow of an Al 0.3 CoCrFeNi high-entropy alloy

The concept of a smooth and homogeneous plastic flow of solids is nowadays constantly challenged by various observations of the self-organization of crystal defects on mesoscopic scales pertaining, e.g., to acoustic emission or the evolution of the local strain field. Such investigations would be of particular interest for High-Entropy Alloys (HEAs) characterized by extremely complex microstructures. However, the complexity of their deformation has been only studied in relation to the jerky flow. The present work explores a mesoscale complexity of the macroscopically-smooth plastic flow of an Al 0.3 CoCrFeNi alloy. Here, an inclusive approach involving various experimental methods and complementary nonlinear analyses allowed to reveal transitions between distinct dynamical regimes, which may be assimilated with noises of different colors, in particular the blue noise that is rarely observed in complex systems, and various kinds of reddened behavior. Such findings provide significant new insights into the micro/macro transition in the deformation behavior of HEAs.

36 MATERIALS SCIENCE↗

The use of teledentistry in facilitating oral health for older adults: A scoping review

Teledentistry is used in many countries to provide oral health care services. However, using teledentistry to provide oral health care services for older adults is not well documented. This knowledge gap needs to be addressed, especially when accessing a dental clinic is not possible and teledentistry might be the only way for many older adults to receive oral health care services. Nine databases were searched and 3,396 studies were screened using established eligibility criteria. Included studies were original research or review articles in which the intervention of interest was delivered to an older adult population (≥ 60 years) via teledentistry. The authors followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Review criteria. Nineteen studies were identified that met the criteria for inclusion. Only 1 study was from the United States. Seven studies had results focusing on older adult participants only, with most of those conducted in elder care facilities. The remainder consisted of studies with mixed-age populations reporting distinct results or information for older adults. The included studies used teledentistry, in both synchronous and asynchronous modes, to provide services such as diagnosis, oral hygiene promotion, assessment and referral of oral emergencies, and postintervention follow-up. Teledentistry comprises a variety of promising apps. Lastly, the authors identified and described uses, promising possibilities, and limitations of teledentistry to improve the oral health of older adults.

60 APPLIED LIFE SCIENCES↗

Synergy of tensile strength and high cycle fatigue properties in a novel additively manufactured Al-Ni-Ti-Zr alloy with a heterogeneous microstructure

Alloy design strategies in additive manufacturing (AM) to achieve grain refinement and terminal eutectic solidification have been introduced to engineer Al alloys having microstructural hierarchy and heterogeneity. Such alloy design strategies enable crack-free builds with an expanded AM processing window and pushed the strength limit in Al alloys. However, fatigue performance of Al alloys made by AM is restricted by the presence of process induced defects and its stochasticity. In this work, tensile and high cycle fatigue (HCF) behavior of a novel Al-Ni-Ti-Zr alloy with a heterogeneous microstructure is studied in the as-built condition, supplemented by detailed microstructural and mechanical characterization. Excellent strength-ductility synergy of 342 MPa and 16% failure strain achieved in the alloy was associated with the microstructural attributes that pertain to the novel alloy. Additionally, the alloy showed excellent HCF performance with a fatigue endurance limit to ultimate tensile strength ratio of 0.29 in flexural fatigue mode. The study revealed the existence of multiple crack retardation mechanisms and favorable crack propagation pathways through the fine-grained regions which enabled good fatigue performance to the alloy. Further, a probabilistic model has been used to estimate the fatigue life of the alloy as a function of the stochastic microstructure by utilizing the statistical distribution of pores, solid-state inclusions, and grains in the AM Al alloy. Finally, the model parametric trends are consistent with the experimental observations.

36 MATERIALS SCIENCE↗

Additively manufactured Al-Ce-Ni-Mn alloy with improved elevated-temperature fatigue resistance

Here, the high cycle fatigue behavior of an additively manufactured (AM) Al-10.5Ce-3.1Ni-1.2Mn wt% alloy was evaluated at 350 °C. The measured fatigue strength of 50 MPa at this temperature is comparable to the most fatigue resistant wrought Al alloys (2618-T6 and 7079-T6) at 315 °C. Refinement of pore populations through advanced AM processing in the examined alloy led to oxide inclusions becoming dominant fatigue crack initiation sites. The distribution of microstructural features that determine crack initiation was measured by X-ray computed tomography and served as input to make fatigue strength model predictions with various methodologies. A Monte-Carlo based approach that was previously applied to predict the fatigue strength of cast aluminum alloys through pore size distributions yielded accurate predictions for the fatigue strength of this AM alloy. Given the tunability of defect distributions in AM alloys, the sensitivity of the Al-Ce-Ni-Mn alloy fatigue behavior to defect distributions and outstanding elevated-temperature fatigue resistance of this alloy; the results together suggest the possibility of a new generation of fatigue-resistant alloys produced by the additive manufacturing route.

36 MATERIALS SCIENCE↗

Load balancing for multi-beam additive manufacturing systems

As powder bed fusion (PBF) additive manufacturing (AM) becomes a more mature field, system configurations are gradually moving away from the classic single heat source, layer-by-layer system configurations towards unconventional system configurations that offer higher throughput. Higher throughput systems allow PBF systems to be considered for a larger variety of industrial applications. However, the inclusion of multiple heat sources, or beams, also increases the complexity of the control schemes needed. For multi-beam systems with overlapping fields of view, the distribution of workload, or load balancing, across these beams directly affects the total print time for a build. Additionally, the probability of any beam failing in a multi-beam system increases with the number of beams. While manual methods of load balancing and dealing with beam failures are reasonable for current generation multi-beam systems, as system configurations become more complex, manual methods will become prohibitively inefficient. Here, this paper introduces two different ways to load balance multi-beam systems of various configuration types, regardless of their complexity, which are highly performant. A consequence of this performance is the enablement of on-the-fly load balancing in the event a beam fails, thus improving system robustness.

36 MATERIALS SCIENCE↗

Process-structure-property relationships for droplet-on-demand liquid-metal-jetted parts

Liquid metal jetting droplet-on-demand additive manufacturing is an attractive alternative to industry-standard, laser-based metal additive manufacturing techniques that use powder feedstocks and produce large heat affected zones. Liquid metal jetting provides a low feedstock footprint, minimal materials waste, less contamination and inclusions from feedstock, and is compatible with a large range of materials. However, little has been reported on the liquid metal jetting process-structure-property relationships that are crucial to understanding how to consistently print high quality metal parts. We investigate the effects of build plate temperature, infill pattern, and track raster rate on the macro- and microstructure, density, hardness, and tensile strength of metal parts created with our custom droplet-on-demand setup using pure tin feedstock as a surrogate for more relevant structural materials. We found that although the build plate temperature had the largest influence on the structure and properties, the infill pattern is an important factor for optimal structural integrity. It was observed that the track raster rate influenced track-to-track porosity and should be considered in toolpath development. Despite printing in ambient air, we could not identify oxide on the surface or in the bulk of the parts and saw no adverse effects on microstructure or tensile performance. The results and methods of this study will help guide future work in optimizing the liquid metal jetting process to reliably print parts using any liquid metal jetting system for a wide variety of metal feedstocks.

36 MATERIALS SCIENCE↗

Modeling powder spreadability in powder-based processes using the discrete element method

Powder-bed fusion (PBF) processes refer to a subset of Additive Manufacturing (AM) techniques where powder is spread on the build-plate before melting (by a laser or electron beam). While PBF processes are attractive due to their ability for realizing complex structures that are either difficult or impossible to create through conventional means, the parts fabricated with these techniques can exhibit defects such as pores, inclusions, and excessive surface roughness. To minimize these defects, much research has been dedicated towards process maturation by optimizing laser or electron beam parameters. However, these developmental efforts typically do not address the recoating process where achieving dense and uniform layers of powder is a necessity for ensuring process repeatability and part quality. While the recoating process can be studied through experimentation, the dynamics of particle movement are difficult to analyze experimentally. Therefore, here, in this study, powder spreading in PBF was simulated through the Discrete Element Method (DEM) to elucidate the mechanisms that control powder-bed quality. Utilizing the Buckingham Pi theorem, a dimensionless metric referred to as the spreading index is developed that combines powder-bed density, roughness, and particle size to assess the quality of powder layers. The formulated spreading index is then related to several dimensionless quantities that provide insight into the mechanisms dominating powder spreading in PBF. The DEM simulations conducted in this work focused on the scenario where powder is spread onto an existing powder bed and revealed that a reduction in the recoating velocity causes an increase in the spreading index while little to no impact on the spreading index was observed when varying layer thickness from 30 μm to 75 μm.Particle size effects on the powder-bed quality were also investigated.

36 MATERIALS SCIENCE↗

Nuclear β − -decay with statistical de-excitation

he accurate description of nuclear β − -decay has far-reaching consequences for applications spanning nuclear reactors to the creation of heavy elements in astrophysical environments. We present the nuclear particle spectra associated with the β -decay of neutron-rich nuclei calculated with the well benchmarked coupled Quasi-particle Random Phase Approximation and Hauser–Feshbach (QRPA+HF) model. This approach begins with the population of the daughter nucleus via semi-microscopic Gamow-Teller or First-Forbidden strength distributions (QRPA) and follows the statistical de-excitation (HF) until the initial available excitation energy is exhausted. At each stage of de-excitation the emission by neutrons and $γ$-rays is considered obeying quantum mechanical selection rules. For completeness we also provide parsed Auger and Internal Conversion (IC) electron spectra from Evaluated Nuclear Data Files (ENDF). Our results are tabulated and provided in parsable ASCII formatted tables that are suitable for inclusion in various applications.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Stochastic fracture generation and thermo-hydro-mechanical modeling in an equivalent continuum framework for enhanced geothermal systems

Enhanced geothermal systems (EGS) involve fracturing low permeability material to establish well connectivity and then injecting and circulating fluid into the fractured subsurface for geothermal power production. Changes in fracture aperture from contraction of the cooling matrix rock may alter network connectivity and risk thermal short-circuiting. Thermo-hydro-mechanical (THM) models are a useful tool to study these processes. However, as fracture networks are complex, and data may be limited, fracture networks in THM models are often stochastically generated. Given reliance on stochastic fracture networks and THM modeling to represent the subsurface and assess productivity of EGS, increased understanding of the influence of such statistically derived fracture networks on flow and heat transport in THM models is needed. Here, a new fracture process model is developed in the reactive transport code PFLOTRAN to stochastically generate fracture families and simulate changes in fracture aperture over time due to temperature changes of the rock matrix. Sixty-four different fracture networks ranging from well to poorly-connected, are modeled in PFLOTRAN with and without mechanical processes (THM vs TH). Results indicate that for well-connected fracture networks, thermal short-circuiting is less of a concern due to the abundance of available alternative flowpaths. For poorly-connected fracture networks, inclusion of mechanical processes showed steep thermal drawdown coincident with increase in fracture aperture along developing colder flowpaths, demonstrating the risk of thermal short-circuiting. Simulations with additional, larger fractures engineered to establish connectivity in a poorly-fractured subsurface, indicate that while stochastic variation of fracture orientation of the background network had limited influence, such variation in the engineered fractures significantly affected flow and heat transport.

Discrete fracture networks (DFN)↗

Neutron thermalization in nuclear graphite: A modern story of a classic moderator

Graphite has been of great interest since the dawn of the nuclear era. In this work, we will focus on the thermal neutron scattering of two types of nuclear graphite that have different microstructures, namely, the historic PGA which has a very anisotropic medium-grained needle coke, and the new G347A which is a near-isotropic fine-grained graphite. We report the results of room temperature inelastic neutron scattering measurements for the scattering function, double differential scattering cross-section, and phonon density of states. The obtained results are discussed in conjunction with results extracted from first-principles lattice dynamics simulations of crystalline graphite, using the incoherent approximation and by also including the coherent-one phonon contribution. Excellent agreements have been found between the measured and calculated scattering functions and phonon densities of states. The inclusion of the coherent-one phonon scattering shows a significant improvement of the calculated scattering functions, double differentials, and inelastic scattering cross-sections. We also highlight the physical concerns about the current thermal neutron scattering ENDF/B-VIII of nuclear graphite library and its corresponding phonon density of states. This work aims to provide a new presentation of neutron thermalization by graphite and offers a new set of high quality experimental and computational data for consideration.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

A digital twin approach to system-level fault detection and diagnosis for improved equipment health monitoring

Automating the task of fault detection and diagnosis is crucial in the effort to reduce the operation and maintenance cost in the nuclear industry. This paper describes a physics-based approach for system-level diagnosis in thermal-hydraulic systems in nuclear power plants. The inclusion of physics information allows for the creation of virtual sensors, which provide improved fault diagnosis capability. The physics information also serves to better constrain diagnostic solutions to the physical domain. As a demonstration, various test cases for fault diagnosis in a high-pressure feedwater system were considered. The use of virtual sensors allows constructing performance models for two first-point feedwater heaters which would not have been possible otherwise due to the limited sensor set. Real-time plant data provided by a utility partner were used to assess the diagnostic approach. The detection of an abnormal event immediate after a plant startup pointed to faulty behaviors in the two first-point feedwater heaters. Further, this double-blind fault diagnosis was subsequently confirmed by the plant operator. In addition, several simulated sensor fault events demonstrated the capability of our algorithms in detecting and discriminating sensor faults.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Generation of localized reactor point kinetics parameters using coupled neutronic and thermal fluid models for pebble-bed reactor transient analysis

The systems analysis of anticipated operating occurrences and design basis accidents for pebble-bed reactor systems requires knowledge of neutron point kinetics equations (PKE) parameters. Typically, the generation of PKE parameters is performed in a global manner using standalone neutronics calculations, without the inclusion of thermal fluid distributions. We utilize Griffin and Pronghorn for generating global and local PKE parameters which includes the use of thermal fluid distributions to account for localized effects. This work establishes a methodology for calculating PKE parameters for a pebble bed reactor with a coupled neutronics/thermal fluids analysis. PKE parameters generated on a global and local basis are compared against a diffusion solve for a typical load-following transient. Locally-generated neutron kinetic parameters are able to reduce the maximum error in the transient power level from 5% to below 1.5%; along with this, bulk temperature errors were reduced from 12 K to 4 K.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

High-fidelity simulations of the run-in process for a pebble-bed reactor

Pebble-bed reactors (PBRs) rely on a continual feed of fuel pebbles being cycled through the core. As a result, they require a “run-in” period in order to reach an equilibrium state. The run-in period for a PBR is a complex, time-dependent problem that requires the injection of new fuel, different types of fuel, and power increases. This complexity in the run-in makes it important to capture the physical processes in order to generate an accurate representation. The present work details the creation of a high-fidelity Monte Carlo methodology for analyzing the run-in and subsequent approach to equilibrium for PBRs. The methodology entails a Python module wrapped around Serpent so as to perform neutronics calculations, move pebbles, refuel the core, and discharge pebbles, thereby modeling the explicit behavior of the PBR run-in. Further, three run-in simulations (a constant temperature profile, a linear temperature profile, and a constant temperature profile using control rods) were examined in order to identify the key physical phenomena present in the run-in process. Utilizing kugelpy, we found the inclusion of a temperature profile to be important for accurately capturing a discharge burnup (around 141 MWd/kg), a consistent k-eff (around 1.005), and an average pebble power (around 2.5 kW/pebble) that all fall within acceptable limits.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Source term analysis of FeCrAl accident tolerant fuel using MELCOR

It has been established that incremental improvements in beyond design basis accident performance can be achieved through accident tolerant fuel (ATF). However, they have the potential to recover margin with respect to conventional fuel and therefore enhance plant economics through uprate or cycle length increase. To realize this potential, it is necessary to quantify the reduction in source term due to use of ATF, and correspondingly how this is affected by increasing the cycle length and/or burnup. This requires development of a risk informed analysis methodology for ATF under high burnup conditions, which is being developed within LWRS. To this end, a MELCOR simulation of FeCrAl ATF in a recovered Large Break LOCA (LBLOCA) scenario has been developed, using a model based on the Zion Pressurized Water Reactor (PWR). The new user defined material capability, along with the inclusion of detailed neutronics- and depletion-derived parameters such as core power distribution, decay heat behavior, and fission product inventories, allows a more detailed simulation of FeCrAl clad material properties and behavior than has previously been possible using MELCOR. These detailed FeCrAl results were compared with a zircaloy clad model to investigate the differences between the two clad types and quantify the benefits of FeCrAl ATF with an 18-month cycle. Next, the fuel cycle with ATF was extended to 24 months, to determine whether any additional safety margin provided by FeCrAl ATF could be leveraged to implement high burnup FeCrAl-clad fuel while retaining the same operating and safety limits as current zircaloy-clad fuel. For the particular scenario analyzed, the delay to fuel failure from using ATF was of the same order as the LOCA recovery time, and hence significant in reducing fission product release, with the 24-month FeCrAl core performing better than the 18-month zircaloy core. It is noted that for other transients, the reduction in release due to using FeCrAl may be less significant. Furthermore, the material model developed here can be used in such further studies in support of determining the overall source term.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Dynamic Linking of Upstream Energy and Freight Demands for Bio and Fossil Energy Pathways in the Global Change Analysis Model

Comprehensive study of the environmental impacts associated with demand for an energy resource or carrier in any one sector requires a full consideration of the direct and indirect impacts on the rest of the regional and global energy system. It is important to consider the energy that is consumed in producing primary energy resources and energy consumed in transporting these energy resources internationally and domestically in order to produce a complete picture of these impacts. Biofuels are especially complex since they have feedbacks not just to the energy system but also to regional and global crop markets. Different modeling and analysis strategies have been applied to consider these impacts, which occur “upstream” of final energy consumption, with some success. Traditional life cycle models allow for rich technological detail in linking upstream impacts of energy demand with downstream final consumption; however, they cannot by themselves represent dynamic economic feedbacks across multiple sectors and regions over time. Computable general equilibrium (CGE) modeling does account for economic feedback among all sectors and regions; however, CGE modeling does not lend itself to physical representation of technological detail. Partial equilibrium (PE) modeling is a heterogeneous category describing economic models that focus on a subset of the economy, and they differ in coverage and ease in incorporating more sectors and economic links. In this study, we present a strategy for dynamically including the direct and indirect impacts of energy demand with physical and technology detail by explicitly adding these upstream energy and transportation links to GCAM, a PE model of global energy, land use, and emissions. We incorporate the following inter-sectoral linkages: energy inputs to crop production, energy inputs to fossil resource production, and freight transport requirements of energy and agricultural commodities. We assess the implications of explicitly including these links by measuring the global impacts of increased corn ethanol demand in the United States with and without these links included. Although the net global impact of the upstream links on energy and emissions are relatively modest in the scenarios we studied, the inclusion of these links illustrates interesting trade-offs in energy and transportation demand among fossil fuel and agriculture sectors. These sectoral interactions suggest that this level of modeling detail could be important in evaluating future analytical questions.

Sampedro Martinez de Estivariz, Jon↗

Incorporation of market signals for the optimal design of post combustion carbon capture systems

Recent studies have shown that fossil generators equipped with post-combustion carbon capture (PCC) systems are needed to reduce the cost of deep decarbonization. Such generators need to be flexible and responsive to grid conditions, particularly in a high variable renewable energy (VRE) environment. In this work, we evaluate the net present value (NPV) of retrofitting an existing natural gas combined cycle (NGCC) unit with a flexible PCC system while incorporating market signals from a high VRE grid. We use our industrial partner’s NGCC configuration as representative of existing NGCC units and Svante’s rapid-temperature swing adsorption (TSA) for PCC. Because of its ability to rapidly startup/shutdown and ramp-up/ramp-down, the chosen capture technology is very attractive for load-following operations. For a given set of market signals, we formulate a two-stage stochastic multi-period optimization problem, under the price-taker assumption, to simultaneously optimize the design of the capture system and operation of the entire plant. Rigorous models for the NGCC unit, PCC system, and compression system are developed using commercial process simulators and validated with either plant or vendor data. For computational tractability, we develop surrogate/reduced-order models for use in the optimization problem. The surrogate model for the NGCC plant is constructed by linearizing the rigorous dynamic model at 75% load, while data-driven nonlinear surrogate models for the capture and compression systems are constructed using simulation data from the rigorous models. The optimization problem, formulated as a mixed integer bilinear program, is implemented in the IDAES® integrated platform and solved to global optimality using Gurobi 9.5. Using this formulation, we determine the profitability of retrofitting an existing NGCC unit with the chosen capture system for multiple regions in the U.S. under two scenarios with different carbon prices. Importantly, the results show that the optimal decision strongly depends on the region and on the carbon price, thereby demonstrating the importance of the inclusion of market signals in the design process.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Multi-facility analysis using metered power data to quantify MRI energy use and utility bill costs across scanner operating modes

This study quantifies the energy consumption of magnetic resonance imaging (MRI) scanners across discrete operating modes during routine clinical workflows, based solely on electrical power measurements. Although previous studies have investigated MRI energy consumption within single hospitals or specific clinical settings, this research provides a broader and more systematic analysis. Researchers analyzed electrical power data and applied a previously developed semi-automatic method for identifying MRI operating modes using load duration curves for 20 MRI scanners across four different U.S. healthcare facilities, encompassing outpatient, inpatient, and mixed-use clinical settings. A key innovation is the inclusion of localized hourly utility rates to estimate costs, a parameter absent in prior literature. Key findings indicate significant variability in energy and cost profiles between weekdays and weekends. Scanner characteristics, including magnet strength, manufacturer, vintage, location, and clinical setting, influenced average daily energy consumption and power thresholds for operating modes. Notably, the clinical setting of a scanner predominantly determines its energy use. For example, the scanners in outpatient facilities consumed more energy. The breakdown of energy usage and costs by operating modes showed scanners spend between 61% and 93% of their time in nonproductive modes, with one outlier spending 34%. Average daily energy use for the scanners in the study ranged from 160 to 1069 kWh, with energy costs ranging from $\$$9 to $\$$149. This study uses an existing framework to quantify MRI energy behavior, leading to insights that can enable improved performance and cost savings across different healthcare environments.

24 POWER TRANSMISSION AND DISTRIBUTION↗