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Impurities in Primary Coolant Salt of FHRs: Chemistry, Impact, and Removal Methods
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Sensitivity analysis of hydraulic conductivity and Manning'snparameters lead to new method to scale effective hydraulic conductivity across model resolutions
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An Fe-Ni-Cr embedded atom method potential for austenitic and ferritic systems: An Fe-Ni-Cr embedded atom method potential for austenitic and ferritic systems
Fe-Ni-Cr stainless-steels are important structural materials because of their superior strength and corrosion resistance. Atomistic studies of mechanical properties of stainless-steels, however, have been limited by the lack of high-fidelity interatomic potentials. Here in this paper, using density functional theory as a guide, we have developed a new Fe-Ni-Cr embedded atom method potential. We demonstrate that our potential enables stable molecular dynamics simulations of stainless-steel alloys at high temperatures, accurately reproduces the stacking fault energy—known to strongly influence the mode of plastic deformation (e.g., twinning vs. dislocation glide vs. cross-slip)—of these alloys over a range of compositions, and gives reasonable elastic constants, energies, and volumes for various compositions. The latter are pertinent for determining short-range order and solute strengthening effects. Our results suggest that our potential is suitable for studying mechanical properties of austenitic and ferritic stainless-steels which have vast implementation in the scientific and industrial communities.
Ferroelectric Phase Content in 7 nm Hf (1- x ) Zr x O 2 Thin Films Determined by X-Ray-Based Methods
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Mercury Concentrations in the Two-Toed Amphiuma ( Amphiuma means ) and the Lesser Siren ( Siren intermedia ): Validating Non-lethal Sampling Methods in Southeastern Aquatic Salamanders
The global decline of amphibians is a major conservation issue. Many stressors are recognized for this decline including exposure to environmental contaminants. Mercury (Hg) is an environmental contaminant that bioaccumulates in wildlife and can cause a variety of negative impacts across taxa, including amphibians. Amphiuma and Siren spp. can comprise a large portion of biomass within their respective ecosystems, and thus, likely serve as important predators or prey in wetland communities. However, due to their cryptic nature, little is known about their ecology, diet, and accumulation potential. Here, we sought to validate a non-lethal sampling method to quantify total mercury (THg) in two enigmatic species of aquatic salamanders: the two-toed amphiuma (Amphiuma means) and the lesser siren (Siren intermedia). We examined relationships between THg content in lethal (whole-body) and non-lethal (tail clip) samples. Tail clips were significant predictors of whole body THg (all p < 0.001), explaining 84-89% of variation in whole body THg. Average whole-body THg (mg/kg did not significantly differ between the two species (p = 0.97), and overall, they had similar whole body THg content (LESI = 0.330 ± 0.04, n = 18; AMME = 0.333 ± 0.07, n = 11). To our knowledge, these data represent the first reported Hg burdens in A. means and S. intermedia.
Overlapping domain decomposition based exponential time differencing methods for semilinear parabolic equations
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Chapman–Enskog Analyses on the Gray Lattice Boltzmann Equation Method for Fluid Flow in Porous Media
The gray lattice Boltzmann equation (GLBE) method has recently been used to simulate fluid flow in porous media. It employs a partial bounce-back of populations (through a fractional coefficient θ, which represents the fraction of populations being reflected by the solid phase) in the evolution equation to account for the linear drag of the medium. Several particular GLBE schemes have been proposed in the literature and these schemes are very easy to implement; but there exists uncertainty about the need for redefining the macroscopic velocity as there has been no systematic analysis to recover the Brinkman equation from the various GLBE schemes. Rigorous Chapman–Enskog analyses are carried out to show that the momentum equation recovered from these schemes can satisfy Brinkman equation to second order in ϵ only if θ=O(ϵ) in which ϵ is the ratio of the lattice spacing to the characteristic length of physical dimension. The need for redefining macroscopic velocity is shown to be scheme-dependent. When a body force is encountered such as the gravitational force or that caused by a pressure gradient, different forms of forcing redefinitions are required for each GLBE scheme.
A High-Throughput Method to Define Additive Manufacturing Process Parameters: Application to Haynes 282
This paper demonstrates how an analytical and experimental method can be used to rapidly define the 45 additive manufacturing settings for a new alloy where the process parameters were previously unknown. A nickel-based superalloy, Haynes 282, was chosen for the analysis. An experimental matrix of focused processing parameters was predicted with a dimensionless number and 100 samples were printed using the Selective Laser Melting technique. High-throughput measurements validated the predicted process conditions needed to achieve desired density and hardness. The whole process was completed in 16 hours. The new technique was confirmed with analytical processing maps adopted by the metal additive manufacturing community. With the predicted set of process parameters, microstructural characterizations and tensile testing were used to confirm the predictions. The resultant as-fabricated microstructures have refined length scales of both microsegregation and secondary phase distributions. As a result, the mechanical properties were comparable within the predicted processing window and exhibited high strength and high ductility.
Energy flexibility of residential buildings: A systematic review of characterization and quantification methods and applications
With building electric demand becoming increasingly dynamic, and a growing percentage of intermittent renewable power generation from solar photovoltaics and wind turbines, the power grid is facing increasing challenge to manage the real time balance between the supply and demand. With advancements in smart sensing and metering, smart appliances, electric vehicles, and energy storage technologies, demand side management of residential buildings can help the grid to improve stability by optimizing flexible loads. This paper reviews recent studies on residential building demand side management, with a focus on characterization and quantification of energy flexibility covering various types of flexible loads, metrics, methods, and applications. The reviewed studies showed four levels of applications: building level (45%), district or community level (29%), system level (19%), and building sector level (7%). Shifting loads is the dominant flexibility type in 60% of applications, followed by shedding (19%), generation (16%), and modulating (6%). Depending on the technology and application scope, flexible operations have a wide range of performance, with peak power reductions of 1%~65%, energy savings up to 60%, operational cost reduction of 1%~48%, and greenhouse gas emission reductions of up to29%. More than half (51%) of the studies employed control strategies to achieve flexibility; among those 72% used optimal controls, while 28% used rule-based controls. About 58% of the studies used mathematical formulation to quantify energy flexibility. Most studies were based on simulation, while less than 15% of the studies had measurements from experiments or field tests. The review reveals research opportunities to address significant gaps in the existing literature: (1) establishing a common definition and performance metrics for energy flexibility of buildings that are technology and application agnostic, (2) developing an ontology to standardize representation of flexibility resources for interoperability, (3) integrating occupant impacts into the quantification and optimization of energy flexibility, and (4) developing requirements and credits of energy flexibility in building energy codes and standards. Findings from the review can inform future research and development of energy flexible buildings which are essential to a reliable and resilient power grid.
Immobilization of LiCl-Li2O pyroprocessing salt wastes in chlorosodalite using glass-bonded hydrothermal and salt-occlusion methods
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Application of regression, variance, and density based global sensitivity methods to integrated VERA-CS and BISON simulations [Application of regression, variance, and density based global sensitivity methods to integrated VERA-CS and BISON simulations]
Uncertainty quantification (UQ) and sensitivity analyses (SA) are performed for coupled simulations between VERA-CS, a coupled pin resolved neutron transport and subchannel thermal hydraulics code, and the fuel performance code BISON. The interface between VERA-CS and BISON is performed in a multiphysics environment known as the LOCA Toolkit for U.S. light water reactors (LOTUS) currently under development at Idaho National Laboratory (INL). A focus is placed on using a variety of SA measures, including two regression based (Pearson and Spearman), one variance based (Sobol indices), and three moment independent measures (Delta moment independent measures with L 1 , L 2 , and L ∞ norms). The problem under inspection is a single assembly depletion case for three fuel cycles. The figures of merit are the minimum departure from nucleate boiling ratio (MDNBR), maximum fuel centerline temperature (MFCT), and gap conductance at peak power (GCPP). SA results show MDNBR to be linear with consistent rankings throughout the fuel cycles. MFCT is linear, but with a change in rankings at the switch from open gap to closed gap models. GCPP is nonlinear at intermediate states that coincide with the onset of contact between fuel and cladding. Furthermore, these nonlinear states allow for the showcasing of higher order SA measures over first order methods.
Pseudodiagonalization Method for Accelerating Nonlinear Subspace Diagonalization in Density Functional Theory
In density functional theory, each self-consistent field (SCF) nonlinear step updates the discretized Kohn-Sham orbitals by solving a linear eigenvalue problem. The concept of pseudodiagonalization is to solve this linear eigenvalue problem approximately, and specifically utilizing a method involving a small number of Jacobi rotations that takes advantage of the good initial guess to the solution given by the approximation to the orbitals from the previous SCF iteration. The approximate solution to the linear eigenvalue problem can be very rapid, particularly for those steps near SCF convergence. Here, we adapt pseudodiagonalization to finite-temperature and metallic systems, where partially-occupied orbitals must be individually resolved with some accuracy. We apply pseudodiagonalization to the subspace eigenvalue problem that arises in Chebyshev-filtered subspace iteration. In tests on metallic and other systems for a range of temperatures, we show that pseudodiagonalization achieves similar rates of SCF convergence to exact diagonalization.
Enabling Efficient and Accurate Computational Studies of MOF Reactivity via QM/MM and QM/QM Methods
Electronic structure calculations can provide unique insight into metal–organic framework (MOF) reactivity and defect formation. Such calculations can be broadly categorized as utilizing either periodic or cluster models, each with their respective advantages and disadvantages. In the present study, we demonstrate how multiscale methods can leverage the advantages of both approaches to enable high levels of accuracy and computational efficiency in studies of MOF reactivity. Using defect formation in a zeolitic imidazolate framework (ZIF) as a prototypical example, we benchmark a quantum mechanics/molecular mechanics (QM/MM) scheme that enables highly efficient cluster-based calculations on MOFs. We demonstrate the importance of correctly accounting for the influence of both dative bond cleavage in the QM cluster and long-range mechanical coupling to the bulk to achieving accurate QM/MM studies of MOFs. We subsequently leverage these cluster models in a QM/QM scheme that goes beyond standard DFT to yield “gold-standard” correlated wave function results on MOFs at modest computational cost. Crucially, we find several cases in which the incorporation of these correlated corrections yields qualitatively important corrections over conventional DFT values.