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At least 469 records · Page 26

Assessing MP2 frozen natural orbitals in relativistic correlated electronic structure calculations

The high computational scaling with the basis set size and the number of correlated electrons is a bottleneck limiting applications of coupled cluster algorithms, in particular for calculations based on two- or four-component relativistic Hamiltonians, which often employ uncontracted basis sets. This problem may be alleviated by replacing canonical Hartree–Fock virtual orbitals by natural orbitals (NOs). Here, in this paper, we describe the implementation of a module for generating NOs for correlated wavefunctions and, in particular, second order Møller–Plesset perturbation frozen natural orbitals (MP2FNOs) as a component of our novel implementation of relativistic coupled cluster theory for massively parallel architectures [Pototschnig et al. J. Chem. Theory Comput. 17, 5509, (2021)]. Our implementation can manipulate complex or quaternion density matrices, thus allowing for the generation of both Kramers-restricted and Kramers-unrestricted MP2FNOs. Furthermore, NOs are re-expressed in the parent atomic orbital (AO) basis, allowing for generating coupled cluster singles and doubles NOs in the AO basis for further analysis. By investigating the truncation errors of MP2FNOs for both the correlation energy and molecular properties—electric field gradients at the nuclei, electric dipole and quadrupole moments for hydrogen halides HX (X = F–Ts), and parity-violating energy differences for H 2 Z 2 (Z = O–Se)—we find MP2FNOs accelerate the convergence of the correlation energy in a roughly uniform manner across the Periodic Table. It is possible to obtain reliable estimates for both energies and the molecular properties considered with virtual molecular orbital spaces truncated to about half the size of the full spaces.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Insight into the deformation features and capacity loss mechanisms of lithium-ion pouch cells under spherical indentation conditions

Mechanical deformation under extreme conditions is one of the important reasons for the failure of lithium-ion batteries in automotive application. However, the deformation features and component failure of lithium-ion cells to external loading has never been a design consideration. Here, in this study, we conduct spherical indentation tests on a dozen of lithium-ion cells with different capacities under different control mode conditions to investigate their deformation features and capacity loss mechanisms. The experimental results show that, under mechanical deformation conditions, internal faults of cells occur in stages, and energy accumulation and sudden release are two key processes of cell's mechanical failure. The cells' state of charge is the main factor affecting their thermal runaway behaviors. In addition, a finite element model is developed to simulate the deformation features and the failure mechanism of key components of lithium-ion pouch cells; the 3D x-ray computed tomography is employed to demonstrate its internal configuration. With this model, the force-strain response, the deformation features as well as the size of the failure area of lithium-ion cells under spherical indentation conditions are accurately predicted. In 3D x-ray computed tomography images, unique mud cracks in cooper current collector are observed, and the influence mechanisms of the isolated fragments on the cell capacities are revealed. These results may provide useful information for the mechanical structure design of the components of lithium-ion pouch cells.

25 ENERGY STORAGE↗

The microbiome structure of decomposing plant leaves in soil depends on plant species, soil pore sizes, and soil moisture content

Microbial communities are known as the primary decomposers of all the carbon accumulated in the soil. However, how important soil structure and its conventional or organic management, moisture content, and how different plant species impact this process are less understood. To answer these questions, we generated a soil microcosm with decomposing corn and soy leaves, as well as soil adjacent to the leaves, and compared it to control samples. We then used high-throughput amplicon sequencing of the ITS and 16S rDNA regions to characterize these microbiomes. Leaf microbiomes were the least diverse and the most even in terms of OTU richness and abundance compared to near soil and far soil, especially in their bacterial component. Microbial composition was significantly and primarily affected by niche (leaves vs. soil) but also by soil management type and plant species in the fungal microbiome, while moisture content and pore sizes were more important drivers for the bacterial communities. The pore size effect was significantly dependent on moisture content, but only in the organic management type. Overall, our results refine our understanding of the decomposition of carbon residues in the soil and the factors that influence it, which are key for environmental sustainability and for evaluating changes in ecosystem functions.

16S rDNA↗

The Surface Chemistry and Structure of Colloidal Lead Halide Perovskite Nanocrystals

Since the initial discovery of colloidal lead halide perovskite nanocrystals, there has been significant interest placed on these semiconductors because of their remarkable optoelectronic properties, including very high photoluminescence quantum yields, narrow size- and composition-tunable emission over a wide color gamut, defect tolerance, and suppressed blinking. These material attributes have made them attractive components for next-generation solar cells, light emitting diodes, low-threshold lasers, single photon emitters, and X-ray scintillators. While a great deal of research has gone into the various applications of colloidal lead halide perovskite nanocrystals, comparatively little work has focused on the fundamental surface chemistry of these materials. While the surface chemistry of colloidal semiconductor nanocrystals is generally affected by their particle morphology, surface stoichiometry, and organic ligands that contribute to the first coordination sphere of their surface atoms, these attributes are markedly different in lead halide perovskite nanocrystals because of their ionicity. Herein, emerging work on the surface chemistry of lead halide perovskite nanocrystals is highlighted, with a particular focus placed on the most-studied composition of CsPbBr 3 . We begin with an in-depth exploration of the native surface chemistry of as-prepared, 0-D cuboidal CsPbBr 3 nanocrystals, including an atomistic description of their surface termini, vacancies, and ionic bonding with ligands. We then proceed to discuss various post-synthetic surface treatments that have been developed to increase the photoluminescence quantum yields and stability of CsPbBr 3 nanocrystals, including the use of tetraalkylammonium bromides, metal bromides, zwitterions, and phosphonic acids, and how these various ligands are known to bind to the nanocrystal surface. To underscore the effect of post-synthetic surface treatments on the application of these materials, we focus on lead halide perovskite nanocrystal-based light emitting diodes, and the positive effect of various surface treatments on external quantum efficiencies. We also discuss the current state-of-the-art in the surface chemistry of 1-D nanowires and 2-D nanoplatelets of CsPbBr 3 , which are more quantum confined than the corresponding cuboidal nanocrystals but also generally possess a higher defect density because of their increased surface area-to-volume ratios.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Anthropogenic extremely low volatility organics (ELVOCs) Govern the Growth of Molecular Clusters over the Southern Great Plains during the Springtime

New particle formation (NPF) and growth govern cloud condensation nuclei (CCN) concentrations in many regions. The mechanisms governing the nucleation of molecular clusters vary substantially in different regions of the atmosphere. Additionally, the growth of these clusters from ~2 to 20 nm sizes is often governed by the availability of extremely low volatility organic vapours (ELVOCs). While the pathways to ELVOC formation from the oxidation of biogenic monoterpenes with ozone is better understood, the chemical and mechanistic pathways for ELVOC formation from oxidation of anthropogenic organics are not well understood. We integrate measurements and three-dimensional regional model simulations with the Weather Research and Forecasting Model coupled to chemistry (WRF-Chem) to understand the processes governing new particle formation and growth and secondary organic aerosol (SOA) formation during the Holistic Interactions of Shallow Clouds, Aerosols and Land Ecosystems (HI-SCALE) field campaign at the Southern Great Plains (SGP) observatory in Oklahoma, and contrast it with a site within the Bankhead National Forest (BNF), Alabama in Southeast USA, where 5-year long measurements will begin in 2024. Simulations show that nucleation rates are at least an order of magnitude higher at SGP compared to BNF during the springtime days (April 28 and May 14, 2016), largely due to lower H2SO4 concentrations at BNF, which are needed for nucleation. In addition, the larger CS at BNF (compared to SGP) increase the loss of molecular clusters by coagulation to pre-existing particles. Among the 8 different nucleation mechanisms in WRF-Chem, we find that the amine+H2SO4 nucleation mechanism dominates at the SGP site, while the pure organic ion induced nucleation mechanism dominates over BNF. Through various WRF-Chem sensitivity simulations, we find that anthropogenic ELVOCs are critical for explaining the growth of newly formed particles and the resulting number size distribution observed near the surface at the SGP site during the daytime. In addition, we show that treating organic particles as semisolid, with strong diffusion-limited uptake of organic vapours, brings model predictions into closer agreement with the observed evolution of particle size distribution. Simulations also predict that anthropogenic SOA, formed by the oxidation of aromatic volatile organic compounds (VOCs), is the dominant organic aerosol component at SGP, while biogenic SOA dominates particle composition at the BNF site in Southeast USA on these days.

Shrivastava, ManishKumar B.↗

Tempering stochastic density functional theory

Here, we introduce a tempering approach with stochastic density functional theory (sDFT), labeled t-sDFT, which reduces the statistical errors in the estimates of observable expectation values. This is achieved by rewriting the electronic density as a sum of a "warm" component complemented by "colder" correction(s). Since the warm component is larger in magnitude but faster to evaluate, we use many more stochastic orbitals for its evaluation than for the smaller-sized colder correction(s). This results in a significant reduction in the statistical fluctuations and systematic deviation compared to sDFT for the same computational effort. We demonstrate the method's performance on large hydrogen-passivated silicon nanocrystals, finding a reduction in the systematic deviation in the energy by more than an order of magnitude, while the systematic deviation in the forces is also quenched. Similarly, the statistical fluctuations are reduced by factors of ≈4-5 for the total energy and ≈1.5-2 for the forces on the atoms. Since the embedding in t-sDFT is fully stochastic, it is possible to combine t-sDFT with other variants of sDFT such as energy-window sDFT and embedded-fragmented sDFT.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The magnetic gradient scale length explains why certain plasmas require close external magnetic coils

Abstract The separation between the last closed flux surface of a plasma and the external coils that magnetically confine it is a limiting factor in the construction of fusion-capable plasma devices. This plasma-coil separation must be large enough so that components such as a breeding blanket and neutron shielding can fit between the plasma and the coils. Plasma-coil separation affects reactor size, engineering complexity, and particle loss due to field ripple. For some plasmas it can be difficult to produce the desired flux surface shaping with distant coils, and for other plasmas it is infeasible altogether. Here, we seek to understand the underlying physics that limits plasma-coil separation and explain why some configurations require close external coils. In this paper, we explore the hypothesis that the limiting plasma-coil separation is set by the shortest scale length of the magnetic field as expressed by the ∇ B tensor. We tested this hypothesis on a database of > 40 stellarator and tokamak configurations. Within this database, the coil-to-plasma distance compared to the minor radius varies by over an order of magnitude. The magnetic scale length is well correlated to the coil-to-plasma distance of actual coil designs generated using the REGCOIL method (Landreman 2017 Nucl. Fusion 57 046003). Additionally, this correlation reveals a general trend that larger plasma-coil separation is possible with a small number of field periods.

Physics↗

Summary of 2020 edge-plasma modeling for FNSFand plans for 2021

This year, following the study of liquid-wall options, our edge-plasma modeling has returned to analyzing issues associated with a solid tungsten-wall, Fusion Nuclear Science Facility (FNSF)-size device, primarily using the 2D UEDGE plasma/neutral transport code. The focus is to predict plasma/neutral heat and particle fluxes to various wall components and determine the concentration of injected and wall-sputtered impurities that reach the core plasma region. Our models have been advanced in a number of areas compared to the initial modeling done in the 2017 timeframe: this year we include each individual charge-state of impurity ions instead of assuming a fixed concentration of impurities relative to the deuterium-tritium (DT) fuel plasma, including the interaction between inner and outer divertor legs. Here edge fueling of the impurity and pumping in the private-flux region is incorporated. Increasingly detailed atomic-physics rate files for impurity radiation have been compared, as well as the role of molecules. The impact of spatial variation of the turbulence-driven radial plasma transport is considered to contribute to the understanding of the heat-flux-limit effects of choosing a double-null or single-null divertor configuration. Detailed plasma/neutral wall fluxes, densities, and temperatures have been provided to the ERO group for their more detailed studies of wall sputtering and near-surface impurity transport.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Ductile coatings on additive manufactured components

A method of forming a coated component using an additive manufacturing system including building a body portion of the component on a build plate. An outer surface of the body portion can include an indentation resulting from the additive manufacturing system. The method further includes performing at least one post-build process on the body portion. The method yet further includes forming a coating layer on an outer surface of the processed body portion. The coating layer may surround a portion of the body component and may impregnate the indentation. A thickness of the coating layer may be a function of at least one of surface roughness, size of the indentation, or a diameter of particles used to build the additive manufactured bracket.

Racca, Stephen D.↗

Evaluation of Second Target Station Target Streaming for the Preliminary Design of the Target Assembly

This report documents the analysis of dose rate fields from a combination of two sources stemming from the target system of the Oak Ridge National Laboratory (ORNL) Spallation Neutron Source (SNS) Second Target Station (STS). This analysis supports the target drive components’ lifetime estimates and conventional facilities’ preliminary design. The two sources detailed in this report are the radiation generated by the proton beam incident on the target and the activated cooling water in the pipes at the top of the target assembly. The analysis considers the STS target system in operational configuration, with all shielding in place. The dose rate fields are calculated in the target drive room and through the target drive room ceiling. This report calculates the thickness necessary for the target drive room’s high-density concrete ceiling to meet the 0.25 mrem/hr dose limit requirement in the high bay directly above the target drive room. In addition to sizing the target drive room ceiling, this report includes details of the dose field surrounding the target drive assembly to estimate the deposited dose in the target drive assembly components resulting from both streaming and decay of activated water. Prompt neutrons and gammas generated by the proton beam incident on the target primarily stream along the gaps between the target assembly and core vessel shielding. Because the models and analysis detailed in this report are based on the STS preliminary design, future analysis is needed to support the STS final design.

43 PARTICLE ACCELERATORS↗

Analysis of Cutter Blade Wear in Rotary Shear Mills

Following development of an analytical abrasive wear model to predict wear of components in a rotary shear mill, the team used a finite element analysis (FEA) approach to calculate forces and loads acting on particles responsible for abrasive wear. The analytical model related critical rotary shear process parameters (shear geometry and rotational speed) to critical material attributes of inorganic mineral species in feedstock (density, size, and aspect ratio) and substrate (hardness and elastic modulus) that enabled us to model the wear of shear cutters in a rotary shear milling system developed by Forest Concepts. With proper knowledge of the forces acting between abrasive particles and cutter components built into it, the model can accurately predict wear of the cutters and provides a quality by design (QbD) approach to predict component reliability based on scientific engineering principles in lieu of trial-and-error approaches. During this reporting period, researchers at Oak Ridge National Laboratory applied an FEA package to simulate the local stresses and forces between an abrasive silica particle and two rotary shear cutters as the distance between the cutters decreases. The output of the FEA was used to provide more accurate projections of the loads applied to the particles in the analytical wear model. Comparison of the FEA force calculations are in good agreement with the loads assumed in the analytical predictions.

36 MATERIALS SCIENCE↗

Role of Fe in long-range ordered Ni 2 Cr precipitates in Ni-Cr-Fe model alloys during isothermal aging

The precipitation of new phases during long-term service at elevated temperatures is a concern for the thermal stability of engineering alloys. In Ni-Cr-based alloys, e.g., Alloy 690, the formation of long-range ordered Ni 2 Cr causes embrittlement and may impact the lifetime of nuclear power plant components. In this work, we quantify the formation and evolution of Ni 2 Cr precipitation in eleven Ni-Cr-Fe model alloys with 0, 5, 7, and 10wt % Fe contents, and with Ni/Cr atomic ratios of 1.8, 2.0, 2.2, 2.4. These alloys were isothermally aged up to 10,000h at temperatures between 330 and 475°C. The alloys were characterized by synchrotron-based x-ray diffraction and Vickers hardness testing to quantify Ni 2 Cr precipitate size, and the impact of precipitate size on the mechanical properties as a function of Fe content. After 10,000 h of aging at 475°C and 418°C, the formation of Ni 2 Cr was observed in all alloys with 0 and 5wt % Fe. After 10,000h of aging at 418°C, Ni 2 Cr precipitates were also observed in the 7wt % Fe containing Ni/Cr=2.0 sample. Further, no clear evidence of Ni 2 Cr was observed in any of the 10wt % Fe samples at any time and temperature combination. We find that the face-centered cubic matrix lattice contraction and Vickers hardness are correlated with the Ni 2 Cr formation. The greatest change in hardness and lattice contraction occurs in stoichiometric alloys (Ni/Cr=2.0) with 0wt % Fe at 475°C. The rate of change in the material properties for the 5wt % Fe alloys is reduced, however the magnitude of changes is similar to 0wt % Fe alloys. A precipitation hardening model developed for Ni-Cr alloys based on critical resolved shear stress with weakly coupled dislocations shows a clear link between Ni 2 Cr precipitate size and hardness. This trend held across all alloys with Ni 2 Cr formation regardless of Fe concentration. This important structure-property relationship can potentially help define Ni-Cr-Fe-based component lifetimes directly through an understanding of how Ni 2 Cr formation impacts mechanical properties as a function of Fe content.

36 MATERIALS SCIENCE↗

Imaging of Calibrated Defects in Additively Manufactured Materials: Pulsed Thermal Tomography Nondestructive Examination of Additively Manufactured Reactor Materials and Components

Additive manufacturing (AM, or 3D printing) for commercial nuclear energy applications is an emerging method for cost-efficient manufacturing aimed at replacing aging nuclear reactor parts and reducing costs for new construction. Known material flaws in AM include low-density regions consisting of non-sintered powder, which have to be detected to ensure the safety of long-term performance nuclear reactor components. Currently, limited options are available for nondestructive evaluation (NDE), either during or post manufacturing. As a solution to NDE of AM, we are developing pulsed thermal imaging which is non-contact, one-sided, and scalable to arbitrary size and shape of the AM parts. Pulsed thermography (PT) system utilizes a high intensity flash lamp to rapidly heat surface of sample, and a high sensitivity fast-frame megapixel infrared (IR) camera to capture data of surface temperature variations. The acquired data cube consists of a stack of surface temperature images taken at different times. Information about material internal defects is extracted by analyzing the data cube. This report provides results of preliminary performance evaluation of pulsed thermal imaging capability in detection of imprinted flaws in AM metallic structures. The flaws were introduced into AM parts as imprinted hemispherical low density regions, consisting of trapped un-sintered metallic powder. Specimens for developed for this study consisted of AM stainless steel 316 and Inconel 718 plates. The diameters of imprinted defects varied from 1mm to 8mm, and their depths below the plate flat surface varied between 1mm and 6mm. Pulsed thermal tomography (PTT) processes the measured data cube to obtain 3D reconstructions of material effusivity using a unique inversion algorithm developed at Argonne. PTT has been previously used in imaging of similar size flat bottom hole (FBH) simulated defects in stainless steel 316 and Inconel 718 specimens. In the study involving AM specimens, PTT imaging results have shown that 1mm-diameter defects located 1mm and 2mm below the surface of specimens were detectable. Larger size defects were detectable at greater depth. We also explored an alternative approach to detection of material flaws in PT data cube, which is using neural learning-based approach to blind source separation. Detection of small material defects requires finding features in the data cube which have signal contrast levels approaching sensitivity limit of IR camera. In this study, an optimized Neural Learning based Blind Source Separation (NLBSS) algorithm, including Principal Component Analysis (PCA), and Independent Component Analysis (ICA) is demonstrated to automatically extract principal temporal and spatial features of thermography frames to enhance flaw detection. By using the NLBSS algorithm, material internal defects can be automatically detected. Furthermore, this processing approach compensates for experimental thermal imaging artifacts, such as noise and uneven heating. By merging artificial intelligence with phtotothermics, the NDE system detects internal calibrated defects of various sizes and depths in AM nuclear-grade metallic alloys.

36 MATERIALS SCIENCE↗

Effect of stoichiometry and hydration level on water domain size and transport in poly(aryl piperidinium) alkaline anion-exchange membranes

Alkaline water electrolysis holds promise in decarbonizing the global economy by enabling renewable hydrogen production with non-precious group metal catalysts. Anion exchange membranes are an important component of alkaline water electrolyzers and would ideally be durable while allowing for high hydroxide conductivity. The poly(aryl piperidinium) (PAP) class of polymers has attracted recent interest due to their good mechanical robustness and high ionic conductivity. Here, in this work, we perform atomistic molecular dynamics (MD) simulations of several PAP polymers at experimentally relevant hydration levels and polymer ion exchange capacities (IECs) to gain nanoscale insight into their properties and to help elucidate the trade-offs that result from tuning the IECs through the polymer stoichiometry. Our MD-predicted macroscopic polymer properties were found to be in good agreement with experimentally available polymer swelling ratios, water-occupied volumes, X-ray scattering, and ionic conductivities. The models show that for hydration levels greater than 8H 2 O per cation a single water cluster will form that percolates through the system. The growth in water cluster size results in large polymer swelling, the creation of larger channels with widths of 7 Å or larger, and nanophase separation between the hydrophilic domains and the polymer with characteristic length scales of approximately 20–30 Å. The experimentally observed lack of a strong X-ray scattering peak at low wavevectors can be explained by a cancellation between the polymer-polymer/water-water and polymer-water correlations and not a loss in nanophase separation. The overlap in coordination environments of the hydroxide oxygen and polymer nitrogen atoms implies that vehicular diffusion between cationic groups could play a role in hydroxide transport. The polymers' hydroxide and water diffusion constants increase by approximately an order of magnitude between hydration levels of 8 and 20H 2 O per cation. However, there are diminishing returns in hydroxide diffusion constant once the IEC exceeds 2.4 meq/g.

08 HYDROGEN↗

Effect of Specimen Thickness on Fracture Toughness and Plane Stress to Plane Strain Transition in Medium-Density Polyethylene

This study investigates the effect of specimen thickness on fracture toughness and the transition from plane stress to plane strain conditions in Medium-Density Polyethylene (MDPE) using Single Edge Notched Bend (SENB) specimens. Three thickness groups (7.5 mm, 9.0 mm, and 12.1 mm) were tested following ASTM D5045 protocol. Conditional stress intensity factors (KQ) increased from 2.2 MPavm to 2.8 MPavm with increasing thickness, demonstrating significant size dependency. Confocal microscopy revealed a 34% reduction in maximum crack tip opening displacement (CTOD) from 0.478 mm to 0.314 mm as thickness increased, with plastic zone lateral extent decreasing by 32%. This quantitative evidence validates Irwin's theoretical prediction of plastic zone size transition from plane stress r_y˜ (1/2p) (K_I/s_y )^2 to plane strain conditions r_y˜ (1/6p) (K_I/s_y )^2.Scanning electron microscopy confirmed progressive suppression of shear lips and evolution from ductile tearing with extensive polymer chain drawing in thin specimens to localized crazing in thick specimens. Despite all specimens satisfying the ASTM D5045 criterion (B = 2.5(KQ/s_y )^2 ) ,residual shear lips persisted even in the thickest specimens, demonstrating that nominal size requirements alone are insufficient for achieving complete plane strain conditions in highly ductile polymers. The findings emphasize the necessity of integrated analytical and morphological assessment for valid fracture toughness characterization, with critical implications for life assessment and integrity prediction in thick-section polymer components such as natural gas distribution pipelines.

Medium-Density Polyethylene↗

Fatigue of laser powder bed fusion processed 17-4 stainless steel using prior process exposed powder feedstock

The rapid pace of development seen in the metal additive manufacturing (AM) process of laser powder-bed fusion (LPBF) requires in-step advances in processes qualification to enable full-scale adoption. This particularly applies to quantifying how powder feedstock conditions impact end-component quality. Here this study examines how in-machine 17-4 stainless steel powder feedstocks are affected by prior LPBF processes, and how these effects impact subsequent builds. Examinations of powder morphology, chemistry, flowability, and rheology were conducted to characterize the powder conditions. The resultant effects of powder feedstock condition on produced component quasi-static tensile and high-cycle fatigue properties were analyzed. Fatigue life was analyzed using a reliability modeling approach that enabled a robust statistical comparison of life. Powder characteristics were found to evolve with powder exposure to prior LPBF processes, particularly in the extremes of powder size distribution and measures of bulk flow. No significant effects of these changes on tensile properties were observed. Reliability modeling methods, including the lognormal and Weibull distributions as well as the empirical survival function, are shown to be effective tools for modeling fatigue variability in LPBF manufactured components. Through these tools, fatigue life was found to be invariant with changes in powder condition.

42 ENGINEERING↗

Limitations of traditional tools for beyond design basis external hazard PRA

Probabilistic risk assessment (PRA) is being used increasingly by the nuclear industry for safety during normal operations as well as for the protection against external hazards. Computation of total risk in an external hazard PRA is dependent on hazard assessment, fragility assessment, and systems analysis. A systems analysis for propagation of component fragilities is conducted using event and fault trees. The event and fault trees for an actual power plant can be fairly large in size, which imposes computational challenges. Hence, certain assumptions are employed for computational efficiency. These assumptions typically represent the conditions imposed during the design basis (DB) scenario. The traditional PRA tools based on these assumptions are also widely applied to perform risk assessment in the context of beyond design basis (BDB) scenarios. However, some of these assumptions may not be valid for certain BDB scenarios. In addition, the probability of dependent failures also increases in BDB scenarios due to common cause failures (CCF) which usually results from design modifications, human errors, etc. In this manuscript, a simple and a relatively more complex illustrative examples are used to show the limitation of these assumptions in the numerical quantification of risk for the case of BDB conditions. Case studies with CCF events across multiple fault trees are also presented to illustrate the effect of these assumptions when traditional approach is used in BDB risk assessment. It is shown that the assumptions are valid for the case of DB conditions but may lead to excessively conservative risk estimates in the case of BDB conditions. Finally, a Bayesian network based top-down algorithm is proposed as an alternative tool for accurate numerical quantification of total risk in systems analysis.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Cloud Process Coupling and Time Integration in the E3SM Atmosphere Model

Abstract In this study, we find significant sensitivity to the choice of time step for the Energy Exascale Earth System Model's atmospheric component, leading to large decreases in the magnitude of cloud forcing when the time step is reduced to 10 s. Reducing the time step size for the microphysics increases precipitation, leading to a drying of the atmosphere and an increase in surface evaporation. This effect is amplified when the microphysics is substepped together with other cloud physics processes. Coupling the model's dynamics and physics more frequently reduces cloud fraction at lower altitudes, while producing more cloud liquid at higher altitudes. Reducing the deep convection time step also reduces low cloud mass and cloud fraction. Together, these results suggest that cloud physics in a global circulation model can depend strongly on time step and, in particular, on the frequency with which cloud‐related processes are coupled with each other and with the model dynamics.

54 ENVIRONMENTAL SCIENCES↗