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SIERRA/Aero User Manual (V.5.10)

SIERRA/Aero is a compressible fluid dynamics program intended to solve a wide variety compressible fluid flows including transonic and hypersonic problems. This document describes the commands for assembling a fluid model for analysis with this module, henceforth referred to simply as Aero for brevity. Aero is an application developed using the SIERRA Toolkit (STK). The intent of STK is to provide a set of tools for handling common tasks that programmers encounter when developing a code for numerical simulation. For example, components of STK provide field allocation and management, and parallel input/output of field and mesh data. These services also allow the development of coupled mechanics analysis software for a massively parallel computing environment.

97 MATHEMATICS AND COMPUTING↗

SIERRA/Aero Theory Manual - V.5.10

SIERRA/Aero is a compressible fluid dynamics program intended to solve a wide variety compressible fluid flows including transonic and hypersonic problems. This document describes the commands for assembling a fluid model for analysis with this module, henceforth referred to simply as Aero for brevity. Aero is an application developed using the SIERRA Toolkit (STK). The intent of STK is to provide a set of tools for handling common tasks that programmers encounter when developing a code for numerical simulation. For example, components of STK provide field allocation and management, and parallel input/output of field and mesh data. These services also allow the development of coupled mechanics analysis software for a massively parallel computing environment.

42 ENGINEERING↗

FGR 13 Dose Conversion Factor Files

The purpose of this document is to discuss the construction of two MACCS dose conversion factor (DCF) files in some detail, an older file created in 2007 named FGR13DCF.inp and a newer file created in 2018 called FGR13GyEquiv_RevA.inp. Very briefly, the difference between the two files is that the older file follows the standard conventions of assigning a radiation weighting factor of 20 for alpha radiation for all tissues and organs; whereas, the newer file complies with the FGR 13 health effects modeling and uses modified radiation weighting factors (referred to as relative biological effectiveness (RBE) factors) for alpha radiation of 10 for breast and of 1 for red bone marrow. During an intermediate period the creation of these two DCF files, a file called FGR13GyEquiv was created and used for the SOARCA calculations. This file was not released to the MACCS user community, but it is also discussed briefly in this document. DCF files are used by MACCS to convert air and ground radionuclide concentrations to doses to an organ or to the whole body. The MACCS calculation considers duration and shielding factor for each exposure pathway including cloudshine, groundshine, inhalation, and ingestion. Dose coefficients for cloudshine and groundshine are expressed as dose rates; dose coefficients for inhalation and ingestion are expressed as committed doses. In this document, dose coefficients (newer ICRP terminology) is used to describe the values contained in dose conversion factor (older ICRP terminology) files.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗

BSEC VPRM 10m Hourly Biogenic Fluxes in Baltimore (2021)

Model outputs from the Vegetation Photosynthesis and Respiration Model (VPRM: version from Horne et al. in prep). Model remote sensing inputs come from Sential 2-derived EVI and LSWI. Model meteorological inputs for two-meter air temperature and shortwave incoming come from the BSEC WRF 2021 Control Run (Foust, W. 2023). Plant functional Types (PFTs) are spatially classified using the Chesapeake Bay Program 2018 land use land cover product. The final biogenic flux (µmol CO2 m^-2 s^-1) outputs of NEE, RESP, and GEE are a weighted average based on the portion of PFTs within the cell. Individual PFT outputs are saved inside PFT directories (e.g., Crops, Grass, etc.) inside the specific month directory. Model outputs are denoted as a negative flux into the land system (i.e., photosynthesis) and a positive flux as a net release into the overlying atmosphere. Respiration (RESP) fluxes are positive and combine heterotrophic (only soil) and autotrophic sources. Gross ecosystem exchange (GEE) is a negative flux driven by only photosynthetic activity from vegetation, and the Net ecosystem exchange (NEE) is the sum of the two (i.e., NEE=RESP+GEE). Data Characteristics Spatial Resolution: 10m Temporal Resolution: Hourly File Format: VPRM_ _BSEC. .tif (Hour is in UTC) For more information on the model results, please email Jason Horne (jph6488@psu.edu). References: Foust, W. (2023). BSEC WRF 2021 Control Run Output (v0.1.0) [Data set]. MSD-LIVE Data Repository. https://data.msdlive.org/records/m0e6m-vvq17

Baltimore↗

LIDAR, Point Clouds, and their Archaeological Applications

It is common in contemporary archaeological literature, in papers at archaeological conferences, and in grant proposals to see heritage professionals use the term LIDAR to refer to high spatial resolution digital elevation models and the technology used to produce them. The goal of this chapter is to break that association and introduce archaeologists to the world of point clouds, in which LIDAR is only one member of a larger family of techniques to obtain, visualize, and analyze three-dimensional measurements of archaeological features. After describing how point clouds are constructed, there is a brief discussion on the currently available software and analytical techniques designed to make sense of them.

DEM↗

Projected Changes in Temperature and Precipitation Over the United States, Central America, and the Caribbean in CMIP6 GCMs

The Coupled Model Intercomparison Project Phase 6 (CMIP6) dataset is used to examine projected changes in temperature and precipitation over the United States (U.S.), Central America and the Caribbean. The changes are computed using an ensemble of 31 models for three future time slices (2021–2040, 2041–2060, and 2080–2099) relative to the reference period (1995–2014) under three Shared Socioeconomic Pathways (SSPs; SSP1-2.6, SSP2-4.5, and SSP5-8.5). The CMIP6 ensemble reproduces the observed annual cycle and distribution of mean annual temperature and precipitation with biases between – 0.93 and 1.27 °C and – 37.90 to 58.45%, respectively, for most of the region. However, modeled precipitation is too large over the western and Midwestern U.S. during winter and spring and over the North American monsoon region in summer, while too small over southern Central America. Temperature is projected to increase over the entire domain under all three SSPs, by as much as 6 °C under SSP5-8.5, and with more pronounced increases in the northern latitudes over the regions that receive snow in the present climate. Annual precipitation projections for the end of the twenty-first century have more uncertainty, as expected, and exhibit a meridional dipole-like pattern, with precipitation increasing by 10–30% over much of the U.S. and decreasing by 10–40% over Central America and the Caribbean, especially over the monsoon region. Seasonally, precipitation over the eastern and central subregions is projected to increase during winter and spring and decrease during summer and autumn. Over the monsoon region and Central America, precipitation is projected to decrease in all seasons except autumn. The analysis was repeated on a subset of 9 models with the best performance in the reference period; however, no significant difference was found, suggesting that model bias is not strongly influencing the projections.

54 ENVIRONMENTAL SCIENCES↗

Explicit ions/implicit water generalized Born model for nucleic acids

>The ion atmosphere around highly charged nucleic acid molecules plays a significant role in their dynamics, structure, and interactions. Here we utilized the implicit solvent framework to develop a model for the explicit treatment of ions interacting with nucleic acid molecules. The proposed explicit ions/implicit water model is based on a significantly modified generalized Born (GB) model and utilizes a non-standard approach to define the solute/solvent dielectric boundary. Specifically, the model includes modifications to the GB interaction terms for the case of multiple interacting solutes—disconnected dielectric boundary around the solute-ion or ion-ion pairs. A fully analytical description of all energy components for charge-charge interactions is provided. The effectiveness of the approach is demonstrated by calculating the potential of mean force for Na + –Cl – ion pair and by carrying out a set of Monte Carlo (MC) simulations of mono- and trivalent ions interacting with DNA and RNA duplexes. We report the monovalent (Na + ) and trivalent (CoHex 3+ ) counterion distributions predicted by the model are in close quantitative agreement with all-atom explicit water molecular dynamics simulations used as reference. Expressed in the units of energy, the maximum deviations of local ion concentrations from the reference are within k B T . The proposed explicit ions/implicit water GB model is able to resolve subtle features and differences of CoHex distributions around DNA and RNA duplexes. These features include preferential CoHex binding inside the major groove of the RNA duplex, in contrast to CoHex biding at the “external” surface of the sugar-phosphate backbone of the DNA duplex; these differences in the counterion binding patters were earlier shown to be responsible for the observed drastic differences in condensation propensities between short DNA and RNA duplexes. MC simulations of CoHex ions interacting with the homopolymeric poly(dA·dT) DNA duplex with modified (de-methylated) and native thymine bases are used to explore the physics behind CoHex-thymine interactions. The simulations suggest that the ion desolvation penalty due to proximity to the low dielectric volume of the methyl group can contribute significantly to CoHex-thymine interactions. Compared to the steric repulsion between the ion and the methyl group, the desolvation penalty interaction has a longer range and may be important to consider in the context of methylation effects on DNA condensation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Charged-cell periodic DFT simulations via an impurity model based on density embedding: Application to the ionization potential of liquid water

Calculations of charged systems in periodic boundary conditions (PBC) are problematic because there are spurious interactions between the charges in different periodic images that can affect the physical picture. In addition, the intuitive limit of Coulomb interactions decaying to zero as the interacting charges are placed at infinite separation no longer applies, and for example total energies become undefined. Leveraging subsystem density functional theory (also known as density embedding) we define an impurity model that embeds a finite neutral or charged subsystem within an extended (infinite) surrounding subsystem. The combination of the impurity model and a consistent choice of the Coulomb reference provides us with an algorithm for evaluating the ionization potential (IP) in extended systems. Additionally, we demonstrate our approach in a pilot calculation of the IP of liquid water, based on a configuration from a prior ab initio molecular dynamics (AIMD) simulation of liquid water (Genova et al., J. Chem. Phys. 2016, 144, 234105). The calculations with the impurity model capture the broadening on the ionization energies introduced by the interactions between the water molecules. Furthermore, the calculated average IP value (10.5 eV) compare favorably to experiments (9.9-10.06 eV) and very recent simulations based on the GW approximation (10.55 eV), while at the same time outperforming density embedding calculations carried out with a naïve handling of the electrostatic interactions (about 7 eV).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The baryonic self similarity of dark matter

The cosmological simulations indicates that dark matter halos have specific self-similar properties. However, the halo similarity is affected by the baryonic feedback. By using momentum-driven winds as a model to represent the baryon feedback, an equilibrium condition is derived which directly implies the emergence of a new type of similarity. The new self-similar solution has constant acceleration at a reference radius for both dark matter and baryons. This model receives strong support from the observations of galaxies. The new self-similar properties imply that the total acceleration at larger distances is scale-free, the transition between the dark matter and baryons dominated regime occurs at a constant acceleration, and the maximum amplitude of the velocity curve at larger distances is proportional to M {sup 1/4}. These results demonstrate that this self-similar model is consistent with the basics of modified Newtonian dynamics (MOND) phenomenology. In agreement with the observations, the coincidence between the self-similar model and MOND breaks at the scale of clusters of galaxies. Some numerical experiments show that the behavior of the density near the origin is closely approximated by a Einasto profile.

79 ASTRONOMY AND ASTROPHYSICS↗

Machine Learning Application to Assess Occurrence and Saturations of Methane Hydrate in Marine Deposits Offshore India

Artificial Neural Networks (ANN) were used to assess methane hydrate occurrence and saturation in marine sediments offshore India. The ANN analysis classifies the gas hydrate occurrence into three types: methane hydrate in pore space, methane hydrate in fractures, or no methane hydrate. Further, predicted saturation characterizes the volume of gas hydrate with respect to the available void volume. Log data collected at six wells, which were drilled during the India National Gas Hydrate Program Expedition 02 (NGHP-02), provided a combination of well log measurements that were used as input for machine learning (ML) models. Well log measurements included density, porosity, electrical resistivity, natural gamma radiation, and acoustic wave velocity. Combinations of well logs used in the ML models provide good overall balanced accuracy (0.79 to 0.86) for the prediction of the gas hydrate occurrence and good accuracy (0.68 to 0.92) for methane hydrate saturation prediction in the marine accumulations against reference data. The accuracy scores indicate that the ML models can successfully predict reservoir characteristics for marine methane hydrate deposits. In conclusion, the results indicate that the ML models can either augment physics-driven methods for assessing the occurrence and saturation of methane hydrate deposits or serve as an independent predictive tool for those characteristics.

58 GEOSCIENCES↗

E3SM‐Arctic: Regionally Refined Coupled Model for Advanced Understanding of Arctic Systems Interactions

Earth system models are essential tools for climate projections, but coarse resolutions limit regional accuracy, especially in the Arctic. Regionally refined meshes (RRMs) enhance resolution in key areas while maintaining computational efficiency. This paper provides an overview of the United States (U.S.) Department of Energy's (DOE's) Energy Exascale Earth System Model version 2.1 with an Arctic RRM, hereafter referred to as E3SMv2.1-Arctic, for the atmosphere (25 km), land (25 km), and ocean/ice (10 km) components. We evaluate the atmospheric component and its interactions with land, ocean, and cryosphere by comparing the RRM (E3SM2.1-Arctic) historical simulations (1950–2014) with the uniform low-resolution (LR) counterpart, reanalysis products, and observational data sets. The RRM generally reduces biases in the LR model, improving simulations of Arctic large-scale mean fields, such as precipitation, atmospheric circulation, clouds, atmospheric river frequency, and sea ice thickness. However, it introduces a seasonally dependent surface air temperature bias, reducing the LR cold bias in summer but enhancing the LR warm bias in winter, which contributes to the underestimated winter sea ice area and volume. Radiative feedback analysis shows similar climate feedback strengths in both model configurations, with the RRM exhibiting a more positive surface albedo feedback and contributing to a stronger surface warming than LR. These findings underscore the importance of high-resolution modeling for advancing our understanding of Arctic climate changes and their broader global impacts, although some persistent biases appear to be independent of model resolution at 10–100 km scales.

Energy Exascale Earth System Model (E3SM)↗

Initial Core Physics and Safety Analyses Supporting the Versatile Test Reactor

The Versatile Test Reactor (VTR) is a proposed integrated facility for investigations into the behavior of fuels and materials subjected to high, fast neutron fluxes prototypical of fast reactor environments. Detailed design of the reactor is currently being performed by a group of U.S. National Laboratories, including Argonne National Laboratory. The current design of the reactor is a 300 MW sodium-cooled pool-type fast reactor fueled with ternary U-20Pu-10Zr metallic fuel. This report documents reactor core physics and preliminary safety analyses that have been performed. The reference VTR core has 313 assembly positions, 66 of which contain fuel assemblies. The remaining assembly positions are loaded with reflector, shield, control rod duct, and test assemblies. Ten positions are available in the reference design for experimental or test assemblies, however the VTR will support test assemblies in any position in the core for alternate core loadings. The performance of the reference VTR core has been assessed for an assumed equilibrium cycle. The core power distribution and reactivity feedback coefficients have been calculated. Preliminary assessments of the reactivity coefficients have shown that each of them results in a negative reactivity change for increasing temperatures. Safety analysis of a VTR layout has been performed using the SAS4A/SASSYS-1 fast reactor safety analysis code. A model has been developed to represent the current core design and a reference heat transport system design. The model has been used to simulate and perform analysis of protected and unprotected loss of heat sink, station blackout, and transient overpower accident scenarios. These scenarios represent the three main ways to perturb the reactor core, through changes to the core inlet temperature, mass flow rate, or reactivity insertions and are credible bounding scenarios for the evaluated transient categories. The results of these simulations have been assessed against simplified criteria for Anticipated Operational Occurrences for the protected transients and for Beyond Design Basis Events for the unprotected transients. Because the primary heat transport system is able to transition quickly and effectively to natural circulation and because the shutdown heat removal system provides sufficient heat rejection capability, large margins for all criteria were predicted for all protected transients. Large margins were also predicted for the unprotected loss of heat sink and station blackout transients due to the strong negative reactivity feedbacks generated by the core. Because of the high power density in the reactor, smaller fuel melting margins are predicted for the unprotected transient overpower accident.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Neutron Multiplicity Counting Moments for Fissile Mass Estimation in Scatter-Based Neutron Detection Systems

Neutron multiplicity counting (NMC) techniques are widely used for nuclear materials accountability and international safeguards applications to quantitatively evaluate characteristic properties pertaining to fissile material. Mathematical models for NMC moments have been previously derived for systems that use capture-based detectors; however, these models are not applicable when scatter-based detectors are used because of “neutron cross talk.” Neutron cross talk occurs when a single neutron scatters and deposits energy above threshold into multiple detectors causing spurious increase in multiplicity counts; this, in turn, has caused fissile mass to be overestimated when not treated. In this paper, we propose new mathematical models derived from point kinetics to correct for neutron cross-talk effects up to any arbitrary order N, where N denotes the maximum number of counts a single neutron can cause. The new models were used to estimate the fissile mass of plutonium metal and oxide samples with effective 240 Pu mass ranging from 2.5 to 250 g. The adequacy of the models was confirmed using simulations of a conceptual scatter-based neutron multiplicity counter (e.g., organic scintillators) using MCNPX v2.7e with the PoliMi fission event generating extension. The fissile mass estimates with no correction for neutron cross-talk events yielded an average relative deviation from the true 240 Pu eff mass of 55.94% and 84.56% for metal and oxide samples, respectively. When neutron cross-talk events of order N = 2 are included in the model, the fissile mass estimates yielded an average relative deviation of 11.89% for metal and 13.21% for oxide samples. Accounting for neutron cross-talk events of order N = 3 resulted in fissile mass estimates with an average relative deviation of 9.58% and 10.51% for metal and oxide samples, respectively. These mass estimates were compared to a reference case (i.e., no neutron crosstalk effects) that yielded an average relative deviation of 6.81% and 4.77% for metal and oxide samples, respectively. In conclusion, the discrepancy between the estimates from the proposed model and the reference case is attributed to the assumed value of N, which sets a finite upper bound on the order of cross-talk events the model treats (i.e., the model for N = 3 assumes that a neutron will never cause more than three counts).

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

The role of density-dependent and –independent processes in spawning habitat selection by salmon in an Arctic riverscape

Density-dependent (DD) and density-independent (DI) habitat selection is strongly linked to a species’ evolutionary history. Determining the relative importance of each is necessary because declining populations are not always the result of altered DI mechanisms but can often be the result of DD via a reduced carrying capacity. Here, we developed spatially and temporally explicit models throughout the Chena River, Alaska to predict important DI mechanisms that influence Chinook salmon spawning success. We used resource-selection functions to predict suitable spawning habitat based on geomorphic characteristics, a semi-distributed water-and-energy balance hydrologic model to generate stream flow metrics, and modeled stream temperature as a function of climatic variables. Spawner counts were predicted throughout the core and periphery spawning sections of the Chena River from escapement estimates (DD) and DI variables. In addition, we used isodar analysis to identify whether spawners actively defend spawning habitat or follow an ideal free distribution along the riverscape. Aerial counts were best explained by escapement and reference to the core or periphery, while no models with DI variables were supported in the candidate set. Moreover, isodar plots indicated habitat selection was best explained by ideal free distributions, although there was strong evidence for active defense of core spawning habitat. These results are surprising, given salmon commonly defend spawning resources, and are likely due to competition occurring at finer spatial scales than addressed in this study.

54 ENVIRONMENTAL SCIENCES↗

Metrics as tools for bridging climate science and applications

In climate science and applications, the term “metric” is used to describe the distillation of complex, multifaceted evaluations to summarize the overall quality of a model simulation, or other data product, and/or as a means to quantify some response to climate change. Metrics provide insights into the fidelity of processes and outcomes from climate models and can assist with both differentiating models' representation of variables or processes and informing whether models are “fit for purpose.” Metrics can also provide a valuable reference point for co-production of knowledge between climate scientists and climate impact practitioners. Although continued metric developments enable model developers to better understand the impacts of decisions made in the model design process, metrics also have implications for the characterization of uncertainty and facilitating analyses of underlying physical processes. As a result, comprehensive evaluation with multiple metrics enhances usability of climate information by both scientific and stakeholder communities. Here, this paper presents examples of insights gained from the development and appropriate use of metrics, and provides examples of how metrics can be used to engage with stakeholders and inform decision-making.

54 ENVIRONMENTAL SCIENCES↗

A global ensemble of ocean wave climate projections from CMIP5-driven models

This dataset, produced through the Coordinated Ocean Wave Climate Project (COWCLIP) phase 2, represents the first coordinated multivariate ensemble of 21st Century global wind-wave climate projections available (henceforth COWCLIP2.0). COWCLIP2.0 comprises general and extreme statistics of significant wave height (H S ), mean wave period (T m ), and mean wave direction (θ m ) computed over time-slices 1979–2004 and 2081–2100, at different frequency resolutions (monthly, seasonally and annually). The full ensemble comprising 155 global wave climate simulations is obtained from ten CMIP5-based state-of-the-art wave climate studies and provides data derived from alternative wind-wave downscaling methods, and different climate-model forcing and future emissions scenarios. The data has been produced, and processed, under a specific framework for consistency and quality, and follows CMIP5 Data Reference Syntax, Directory structures, and Metadata requirements. Technical comparison of model skill against 26 years of global satellite measurements of significant wave height has been undertaken at global and regional scales. This new dataset provides support for future broad scale coastal hazard and vulnerability assessments and climate adaptation studies in many offshore and coastal engineering applications.

Science & Technology - Other Topics↗

Effect of Accurate Modeling of Converter Interfaced Generation (CIG) on a Practical Bulk Power System

With increased penetration of converter interfaced generation (CIG) in power systems, it becomes imperative to adequately model them in both steady-state and dynamic simulations. There are several modeling approaches and simulation platforms for CIG. In addition, it is noted that suitability of modeling approaches and models is also dependent on the system conditions. However, their suitability has yet to be systematically analyzed, and this becomes a challenge in the industry without a systemic method. To tackle these challenges, in this paper, we first develop a methodology for identifying the maximum penetration of aggregated rooftop sources that can be represented as negative loads in both the steady state and dynamic analysis. Then we verify the suitability of positive-sequence performance-based model and detailed electromagnetic transient (EMT) model for utility-scale PV plants under different fault conditions. Based on the results, we perform dynamic simulations on a large practical system with both positive-sequence transient stability(TS) and EMT-TS hybrid simulation. Our study shows that positive-sequence performance based PV plant model is more suitable for study cases with faults relatively far away from the point of connection, and that positive-sequence models and TS simulation approach can produce comparable results with reference to EMT-TS hybrid simulation for normally-cleared single-line-to-ground faults, but the inadequacy of positive-sequence based model and simulation approach becomes obvious for prolonged-tripping of unbalanced faults in proximity of the PV plants.

Huang, Qiuhua↗

1:50 Scale Testing of Three Floating Wind Turbines at MARIN and Numerical Model Validation Against Test Data

The primary goal of the basin model test program discussed herein is to properly scale and accurately capture physical data of the rigid body motions, accelerations and loads for different floating wind turbine platform technologies. The intended use for this data is for performing comparisons with predictions from various aero-hydro-servo-elastic floating wind turbine simulators for calibration and validation. Of particular interest is validating the floating offshore wind turbine simulation capabilities of NREL’s FAST open-source simulation tool. Once the validation process is complete, coupled simulators such as FAST can be used with a much greater degree of confidence in design processes for commercial development of floating offshore wind turbines. The test program subsequently described in this report was performed at MARIN (Maritime Research Institute Netherlands) in Wageningen, the Netherlands. The models considered consisted of the horizontal axis, NREL 5 MW Reference Wind Turbine (Jonkman et al., 2009) with a flexible tower affixed atop three distinct platforms: a tension leg platform (TLP), a spar-buoy modeled after the OC3 Hywind (Jonkman, 2010) and a semi-submersible. The three generic platform designs were intended to cover the spectrum of currently investigated concepts, each based on proven floating offshore structure technology. The models were tested under Froude scale wind and wave loads. The high-quality wind environments, unique to these tests, were realized in the offshore basin via a novel wind machine which exhibits negligible swirl and low turbulence intensity in the flow field. Recorded data from the floating wind turbine models included rotor torque and position, tower top and base forces and moments, mooring line tensions, six-axis platform motions and accelerations at key locations on the nacelle, tower, and platform. A large number of tests were performed ranging from simple free-decay tests to complex operating conditions with irregular sea states and dynamic winds.

17 WIND ENERGY↗