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

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Impact of Detailed Parameter Modeling of Open-Cycle Gas Turbines on Production Cost Simulation: Preprint

Flexible resources are increasingly important as variable renewable energy deployment in the power system increases. Although many systems are transitioning away from fossil fuels, open-cycle gas turbines are likely to play an important balancing role for some time, thus requiring accurate modeling of their operational parameters. This paper explores the impact of detailed representation of three operational parameters - start- up costs, run-up rates, and forced outage rates - in the production cost model of a system as it adopts higher levels of wind and solar. Using PLEXOS simulations of the NREL-118 bus test system, the study examines how more detailed parameter modeling affects outcomes such as the number of start-ups and shutdowns, ramping and total generation costs for open-cycle gas turbines, as renewable energy levels increase. The results suggest the value of detailed parameter modeling and continued research on combustion turbines' ability to provide flexibility.

economic dispatch↗
DOE OSTI2011

Modeling Impact-Induced Reactivity Changes Using DAG-MCNP5

There is a long literature studying the criticality of space reactors immersed in water/sand after a launch accident; however, most of these studies evaluate nominal or uniformly compacted system configurations. There is less research on the reactivity consequences of impact, which can cause large structural deformation of reactor components that can result in changes in the reactivity of the system. Predicting these changes is an important component of launch safety analysis. This paper describes new features added to the DAG-MCNP5 neutronics code that allow the criticality analysis of deformed geometries. A CAD-based solid model of the reactor geometry is used to generate an initial mesh for a structural mechanics impact calculation using the PRONTO3D/PRESTO continuum mechanics codes. Boundary conditions and material specifications for the reactivity analysis are attached to the solid model that is then associated with the initial mesh representation. This geometry is then updated with the deformed finite element mesh to perturb node coordinates. DAG-MCNP5 was extended to accommodate two consequences of the large structural deformations: dead elements representing fracture, and small overlaps between adjacent volumes. The dead elements are removed during geometry initialization and adjustments are made to conserve mass. More challenging, small overlaps where adjacent mesh elements contact cause the geometric queries to become unreliable. A new point membership test was developed that is tolerant of self-intersecting volumes, and the particle tracking algorithm was adjusted to enable transport through small overlaps. These new features enable DAG-MCNP5 to perform particle transport and criticality eigenvalue calculations on both deformed mesh geometry and CAD geometry with small geometric defects. Detailed impact simulations were performed on an 85-pin space reactor model. In the most realistic model that included NaK coolant and water in the impact simulation, the eigenvalue was determined to increase 2.7% due to impact.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
NASA NTRS2000

The Impact of Detailed Snow Physics on the Simulation of Snow Cover and Subsurface Thermodynamics at Continental Scales

The three-layer snow model is coupled to the global catchment-based Land Surface Model (LSM) of the NASA Seasonal to Interannual Prediction Project (NSIPP) project, and the combined models are used to simulate the growth and ablation of snow cover over the North American continent for the period 1987-1988. The various snow processes included in the three-layer model, such as snow melting and re-freezing, dynamic changes in snow density, and snow insulating properties, are shown (through a comparison with the corresponding simulation using a much simpler snow model) to lead to an improved simulation of ground thermodynamics on the continental scale.

Stieglitz, Marc↗
DOE OSTI2016

Impact of High Performance Computing on the Detailed Simulation of Subsurface Flow and Contaminant Transport Using eSTOMP - 16341

The ability to model subsurface processes at the field-scale is essential to site closure and remedial action decisions. Field-scale models often require high-performance computing to meet the computational demands associated with complex systems, model calibration, and uncertainty quantification. eSTOMP, a parallel version of STOMP, is an analytical tool that meets the need for investigating coupled processes in the subsurface involving regional multi-fluid flow and biogeochemistry. The scalability of eSTOMP makes it ideal for simulating contaminant and geochemical reactive transport when long run times result from execution of a serial code. To demonstrate the impact of high-performance computation on subsurface analyses, the application of eSTOMP is presented for two sites. The first site involves uranium surface complexation within a highly dynamic, variably saturated flow field. The use of this model in conjunction with continued field monitoring is expected to provide a rigorous basis for developing operational strategies for field remediation and for defining defensible remediation endpoints. The second site involves the long-term dissolution of low-level radioactive glass emplaced within a near-surface repository. The waste form release rate is evaluated by modeling the basic physical and chemical processes that are known to control the waste form dissolution behavior, including pH and composition of the fluid contacting the glass. Simulations demonstrate that glass dissolution rates vary both in time and as a function of position within the disposal system, and that a 'leach rate' or radionuclide release rate parameter can only be estimated after identifying these impacts in a dynamic system. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

MPEX AI Digital Twins

All magnetically confined plasma fusion power plant concepts (Tokamak, Spherical Tokamak, Stellarator, Mirror, ...) must exhaust the heat and plasma from the core confinement region to the material walls. The primary channel for this exhaust is through a plasma divertor which directs plasma along open magnetic field lines to a material target. The Material Plasma Exposure eXperiment (MPEX) illustrated in Figure 1, is a high-power, steady-state linear plasma device designed to produce the plasma material interaction (PMI) conditions of the divertor of future magnetic confinement fusion power plants: energy flux 20MW/m 2 , ion fluence 1031/m 2 , pulse duration 106 sec. These goals of plasma exposure in MPEX are well beyond those achieved in magnetic fusion experimental devices. Successfully achieving these high power steady state conditions for long pulses requires operational control of the heating and particle sources and the plasma flux to the walls and target. The MPEX AI Hot Spot Controller, proposed in this project, will help achieve the operational milestones of MPEX. The MPEX device will begin commissioning at the end of FY26. A smaller proto-MPEX was operated for 14,666 plasma discharges and will resume operation in September of 2025 as proto-MPEX-lite, with reduced capability, to test a new window for the Helicon plasma source. The proto-MPEX data has undergone surrogate modeling with machine learning methods (R. Archibald, 2022 IEEE International Conference on Big Data). This proto-MPEX data will be used to begin development of the AI digital twins described in this white paper. The scientific mission of MPEX is to qualify materials of different composition for use in the high energy and plasma flux conditions of a fusion power plant. The materials exposed in MPEX will in some cases be exposed to high neutron fluxes at other ORNL facilities to measure the changes to their PMI properties. The targets exposed in MPEX will be transported under vacuum to a Surface Analysis Station (SAS). The SAS will be equipped with the following diagnostics: Focused Ion Beam (FIB) for trench milling, 100-400 angstrom resolution scanning electron microscope (SEM), surface mapping x-ray spectrometer, high resolution camera, and a future upgrade to a laser induced breakdown spectroscopy quadruple mass spectrometer (LIBS-QMS). The MPEX experiments will generate diverse pre- and post-exposure measurement data of detailed material properties down to the crystal grain level in 3D for post-exposure assessment of PMI damage (e.g. cracking, melting, erosion and redeposition of the material). Physics models for the PMI, and how the material composition and manufacturing impact its performance under high energy plasma exposure, need to be validated with MPEX data to guide the selection of new candidate materials. Our vision for the MPEX AI Digital Twins project is to supply experimental and physics model simulation data to train Artificial Intelligence (AI) models for data processing, analysis, operational control, PMI and materials simulation to maximize the scientific output of the MPEX device. Ultimately, an AI digital twin of MPEX material assessment metrics for tested and synthetic material types with simulated PMI will be trained by the AI Modeling Teams on the experimental and physics simulation data submitted to the American Science Cloud by this project. A purely empirical search for the best material is inefficient given the finite number of samples that can be tested on MPEX. In order to expand the material properties database for training the MPEX Material Assessment AI Digital Twin, and to gain physics understanding of the PMI processes, physics models of the material properties and PMI processes are required. The physics simulations provide detailed simulation data, like impact angles for plasma ions, sputtering yields, transport of the ionized sputtered target material in the plasma, and redeposition locations. This simulation data expands the measurement data for deeper physics understanding. The experimental data is essential to validate the PMI and material structure simulation models. The validated models can then be used to generate new simulation data of MPEX material assessments for synthetic material compositions that have not been exposed in MPEX. These predictive simulations, plus the whole experimental dataset, will be used to train the MPEX Material Assessment AI Digital Twin allowing a rapid generative AI search for new materials with reduced PMI damage by interpolating the domain of the training set. These new optimum materials can be simulated with the physics codes and/or tested in MPEX. The ability of AI neural networks to interpolate multi-dimensional parameter spaces and generate virtual data is exploited for a more efficient search for optimum materials. The advent of the Transformational AI Models Consortium (TAIMC) is an opportunity to engage with state of the art private and public AI developers to achieve the goals of the AI digital twins and AI accelerated physics models proposed in this project. Our partners at ORNL from the Advance Scientific Computing Research (ASCR) organization will collaborate in accelerating the integrated plasma material interaction simulation framework. This simulation framework will provide a platform for generating simulation data across a range of physical fidelities, including hybrid methods that produce multi-fidelity results. This data will be leveraged for AI model development, both for generation of surrogates and the automation of simulation campaigns. A part of the research below will include collaborative efforts with the TAIMC to (i) adapt data storage approaches to ensure AI-readiness, (ii) provide a protypical exemplar to inform and exercise constructed workflows, and (iii) generate and share data, using the TAIMC unified AI data standard, for foundational models that will be trained from multiple sources across the DOE complex. We will also collaborate with the TAIMC, as well as the planned AI modeling teams, to develop approaches for reducing the cost of data generation. These include tailored multi-fidelity approaches as well as fine-tuning strategies to augment general, large-scale foundational models.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2014

The Marriage of Residential Energy Codes and Rating Systems: Conflict Resolution or Just Conflict?

After three decades of coexistence at a distance, model residential energy codes and residential energy rating systems have come together in the 2015 International Energy Conservation Code. At the October, 2013, International Code Council’s Public Comment Hearing, a new compliance path based on an Energy Rating Index was added to the IECC. Although not specifically named in the code, RESNET’s HERS rating system is the likely candidate Index for most jurisdictions. While HERS has been a mainstay in various beyond-code programs for many years, its direct incorporation into the most popular model energy code raises questions about the equivalence of a HERS-based compliance path and the traditional IECC performance compliance path, especially because the two approaches use different efficiency metrics, are governed by different simulation rules, and have different scopes with regard to energy impacting house features. A detailed simulation analysis of more than 15,000 house configurations reveals a very large range of HERS Index values that achieve equivalence with the IECC’s performance path. This paper summarizes the results of that analysis and evaluates those results against the specific Energy Rating Index values required by the 2015 IECC. Based on the home characteristics most likely to result in disparities between HERS-based compliance and performance path compliance, potential impacts on the compliance process, state and local adoption of the new code, energy efficiency in the next generation of homes subject to this new code, and future evolution of model code formats are discussed.

Residential, Energy, Rating systems, HERS, 2015 IE↗
NASA NTRS1988

Computer modeling of large asteroid impacts into continental and oceanic sites: Atmospheric, cratering, and ejecta dynamics

Numerous impact cratering events have occurred on the Earth during the last several billion years that have seriously affected our planet and its atmosphere. The largest cratering events, which were caused by asteroids and comets with kinetic energies equivalent to tens of millions of megatons of TNT, have distributed substantial quantities of terrestrial and extraterrestrial material over much or all of the Earth. In order to study a large-scale impact event in detail, computer simulations were completed that model the passage of a 10 km-diameter asteroid through the Earth's atmosphere and the subsequent cratering and ejecta dynamics associated with impact of the asteroid into two different targets, i.e., an oceanic site and a continental site. The calcuations were designed to broadly represent giant impact events that have occurred on the Earth since its formation and specifically represent an impact cratering event proposed to have occurred at the end of Cretaceous time. Calculation of the passage of the asteroid through a U.S. Standard Atmosphere showed development of a strong bow shock that expanded radially outward. Behind the shock front was a region of highly shock compressed and intensely heated air. Behind the asteroid, rapid expansion of this shocked air created a large region of very low density that also expanded away from the impact area. Calculations of the cratering events in both the continental and oceanic targets were carried to 120 s. Despite geologic differences, impacts in both targets developed comparable dynamic flow fields, and by approx. 29 s similar-sized transient craters approx. 39 km deep and approx. 62 km across had formed. For all practical purposes, the atmosphere was nearly completely removed from the impact area for tens of seconds, i.e., air pressures were less than fractions of a bar out to ranges of over 50 km. Consequently, much of the asteroid and target materials were ejected upward into a near vacuum. Effects of secondary volcanism and return of the ocean over hot oceanic crater floor could also be expected to add substantial solid and vaporized material to the atmosphere, but these conditions were not studied.

Roddy, D. J.↗
NASA NTRS2012

Characterization and Analysis of Triaxially Braided Polymer Composites under Static and Impact Loads

In order to design impact resistant aerospace components made of triaxially-braided polymer matrix composite materials, a need exists to have reliable impact simulation methods and a detailed understanding of the material behavior. Traditional test methods and specimen designs have yielded unrealistic material property data due to material mechanisms such as edge damage. To overcome these deficiencies, various alternative testing geometries such as notched flat coupons have been examined to alleviate difficulties observed with standard test methods. The results from the coupon level tests have been used to characterize and validate a macro level finite element-based model which can be used to simulate the mechanical and impact response of the braided composites. In the analytical model, the triaxial braid unit cell is approximated by using four parallel laminated composites, each with a different fiber layup, which roughly simulates the braid architecture. In the analysis, each of these laminated composites is modeled as a shell element. Currently, each shell element is considered to be a smeared homogeneous material. Simplified micromechanics techniques and lamination theory are used to determine the equivalent stiffness properties of each shell element, and results from the coupon level tests on the braided composite are used to back out the strength properties of each shell element. Recent improvements to the model include the incorporation of strain rate effects into the model. Simulations of ballistic impact tests have been carried out to investigate and verify the analysis approach.

Goldberg, Robert K.↗
NASA NTRS1992

M and D SIG progress report: Laboratory simulations of LDEF impact features

Laboratory impact experiments are needed to understand the relationship between a measured penetration hole diameter and associated projectile dimension in the thermal blankets of experiment A0178, which occupied some 16 sq. m. These blankets are composed of 125 micron thick Teflon that has an Ag/enconel second mirror surface, backed by organic binder and Chemglaze paint for a total thickness of some 170 microns. While dedicated experiments are required to understand the penetration behavior of this compound target in detail, we report here on impact simulations sponsored by other projects into pure Teflon and aluminum targets. These experiments will allow first order interpretations of impact features on the Long Duration Exposure Facility (LDEF), and they will serve as guides for dedicated experiments that employ the real LDEF blankets, both exposed and unexposed, for a refined understanding of the LDEF's collisional environment. We employed a light gas gun to launch soda-lime glass spheres from 50 to 3200 microns in diameter that impacted targets of variable thickness. Penetration measurements are given.

Horz, Friedrich↗
DOE OSTI2013

EFFECT OF MASKED REGIONS ON WEAK-LENSING STATISTICS

Sky masking is unavoidable in wide-field weak-lensing observations. We study how masks affect the measurement of statistics of matter distribution probed by weak gravitational lensing. We first use 1000 cosmological ray-tracing simulations to examine in detail the impact of masked regions on the weak-lensing Minkowski Functionals (MFs). We consider actual sky masks used for a Subaru Suprime-Cam imaging survey. The masks increase the variance of the convergence field and the expected values of the MFs are biased. The bias then compromises the non-Gaussian signals induced by the gravitational growth of structure. We then explore how masks affect cosmological parameter estimation. We calculate the cumulative signal-to-noise ratio (S/N) for masked maps to study the information content of lensing MFs. We show that the degradation of S/N for masked maps is mainly determined by the effective survey area. We also perform simple {chi}{sup 2} analysis to show the impact of lensing MF bias due to masked regions. Finally, we compare ray-tracing simulations with data from a Subaru 2 deg{sup 2} survey in order to address if the observed lensing MFs are consistent with those of the standard cosmology. The resulting {chi}{sup 2}/n{sub dof} = 29.6/30 for three combined MFs, obtained with the mask effects taken into account, suggests that the observational data are indeed consistent with the standard {Lambda}CDM model. We conclude that the lensing MFs are a powerful probe of cosmology only if mask effects are correctly taken into account.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Automatic Imagery Data Analysis for Proactive Computer-Based Workflow Management during Nuclear Power Plant Outages

This report is being submitted for the task “Final Report” of DOE NEUP Project 15-8121 “Automatic Imagery Data Analysis for Proactive Computer-Based Workflow Management during Nuclear Power Plant Outages.” Typical nuclear power plant (NPP) outages always involve thousands of maintenance and refueling activities and a large number of workers in limited workspaces, while having tight schedules and zero-tolerance for accidents. During an outage, thousands of workers will be working in various workspaces across the NPP. High outage costs and expensive delays (approximately 1.5 million dollars of loss per day of delay) in NPP maintenance demand tight outage schedules. In packed workspaces, an automatic system that monitors human behaviors in real-time and provides insights about current and pending schedule deviations from the plan is critical for ensuring: 1) effective collaboration among workers and worker teams from different trades; 2) less waste of time and resources due to the lack of situational awareness; and 3) proactive outage project control. The overall goal of this project is to test the hypothesis that real-time imagery-based object tracking and spatial analysis, as well as human behavior modeling of outage participants, will significantly improve the efficiency of outage control while lowering the rates of accidents and incidents. Three objectives of this project are: 1) Establish real-time object tracking and spatiotemporal analysis methods that automatically assess the productivity of field activities and detect anomalous spatiotemporal relationships among activities that cause inefficiencies and risks; 2) Establish realtime human tracking and human factor modeling methods for automatically diagnosing unexpected actions of and interactions between outage participants, those which cause inefficient collaborations between Advanced Outage Control Center (AOCC), satellite outage centers, NPP workers, and maintenance service providers; and 3) Test the proposed automated object tracking, human behavior modeling, and spatiotemporal analysis methods in outage control case studies in order to characterize the effectiveness of automated imagery-data-driven methods in proactively improving the efficiency and safety of workflows in outage coordination and risk management. Recent studies of detailed human behavior monitoring on construction sites have examined the potential of applying advanced computer vision algorithms in detecting and tracking anomalous workers (i.e., workers who do not wear hard hats or safety vests) for ensuring job site safety. Some studies of human factor studies revealed the importance of modeling detailed interactions between individuals within and across teams in better understanding the impact of human in proactive project control. Other studies in the construction domain have developed computational simulation frameworks that formalize detailed spatiotemporal interactions between tasks in order to simulate the impacts of individual tasks on the performance of workflows. While integrated analyses that combine human factor assessment, as well as image processing and simulation, are in demand for effective decision-making, limited studies have examined the potential of such integrated analyses in NPP outage control. This research project has examined an automatic outage monitoring and control system that integrates human factor analysis, computer vision techniques, and simulation methods in order to enable engineers to better understand the interactions between humans, resources, and workflows during outage processes. The project aims at providing NPP maintenance agencies insights into more efficient use of limited resources in extending the life of a nuclear plant, as well as reducing waste while ensuring sufficient generation of electricity. This study is significant for the safety of nuclear plants, sustainable electricity generation for livable communities, and cost savings for maintaining electricity infrastructures in the United States.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

The track-length extension fitting algorithm for energy measurement of interacting particles in liquid argon TPCs and its performance with ProtoDUNE-SP data

This paper introduces a novel track-length extension fitting algorithm for measuring the kinetic energies of inelastically interacting particles in liquid argon time projection chambers (LArTPCs). The algorithm finds the most probable offset in track length for a track-like object by comparing the measured ionization density as a function of position with a theoretical prediction of the energy loss as a function of the energy, including models of electron recombination and detector response. The algorithm can be used to measure the energies of particles that interact before they stop, such as charged pions that are absorbed by argon nuclei. The algorithm's energy measurement resolutions and fractional biases are presented as functions of particle kinetic energy and number of track hits using samples of stopping secondary charged pions in data collected by the ProtoDUNE-SP detector, and also in a detailed simulation. Additional studies describe the impact of the dE/dx model on energy measurement performance. The method described in this paper to characterize the energy measurement performance can be repeated in any LArTPC experiment using stopping secondary charged pions.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Detailed Simulations of a Three-Stage Supercritical Carbon Dioxide Axial Compressor with a Focus on the Shrouded Stator Cavities Flow

This paper describes the findings of detailed simulations performed to investigate the impact of seal teeth cavity leakage flow on the aerodynamic and thermal performance of a three-stage supercritical CO 2 axial compressor. The study compares a shrouded stator configuration (with cavities) to a cantilevered stator configuration (without cavities) to highlight their differences. High-fidelity computational fluid dynamics simulations were performed using non-linear harmonic (NLH) and mixing plane assumptions, considering various possible rotor/stator interface configurations for mixing plane calculations. The key performance parameters for each case were compared, and the best-performing configuration selected for further analysis. The individual stage performance parameters are also examined and compared between the cantilevered and shrouded configurations. It was observed that in the shrouded case, the leakage flow enters the cavity downstream of the stator trailing edge and gets entrained into the primary flow upstream of the stator, leading to boundary layer changes at the hub and degradation of stator and downstream rotor performance. Vortical flow structures were also observed in the stator wells, which tended to change the flow angles around the region, thereby affecting mixing and velocity distribution, resulting in a slight deterioration of compressor performance. Additionally, the study examines windage heating due to shear work from rotating walls, including the seal teeth surface. The amount of shear work done on the leakage flow and the corresponding rise in fluid temperature were quantified, tabulated, and further compared with a simple analytical model, showing good agreement between them and, hence, validating the numerical approach used.

42 ENGINEERING↗
DOE OSTI2017

Turbulent Flow Simulation at the Exascale: Opportunities and Challenges Workshop: August 4-5, 2015, Washington, D.C.

This report details the impact exascale will bring to turbulent-flow simulations in applied science and technology. The need for accurate simulation of turbulent flows is evident across the DOE applied-science and engineering portfolios, including combustion, plasma physics, nuclear-reactor physics, wind energy, and atmospheric science. The workshop brought together experts in turbulent-flow simulation, computational mathematics, and high-performance computing. Building upon previous ASCR workshops on exascale computing, participants defined a research agenda and path forward that will enable scientists and engineers to continually leverage, engage, and direct advances in computational systems on the path to exascale computing.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Model-based data center cooling controls comparative co-design

This article presents a comparative simulation-based control logic design process. It uses the Control Description Language (CDL) and the ASHRAE Guideline 36 high-performing building control sequences with the Modelica Buildings Library (MBL) to demonstrate a comparative analysis of two control designs for a data center chilled water plant. Details include a description of the closed-loop plant and control design methodology, including sizing and parameterization, base and alternative (Guideline 36) control logic with software implementation structure, and outline of the simulation experimentation process. The selected control designs are paired with comparable chilled water plant configurations. The models include a chiller, a water-side economizer, and an evaporative cooling tower. The plant provides cooling at 27ºC zone supply air temperature to a data center in Sacramento, CA. The comparative simulation results examined the impacts of a selected control logic detail, and present an example model-based design application. Overall, the simulation results showed a 25% annual and a 18% summer energy use reduction for alternative controls. This shows that simulation-based control logic design performance evaluation can improve energy efficiency and resilience aspects of system controls at large.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2017

Systematic Biases in Weak Lensing Cosmology with the Dark Energy Survey

This thesis sets out a practical guide to applying shear measurements as a cosmological tool. We first present one of two science-ready galaxy shape catalogues from Year 1 of the Dark Energy Survey (DES Y1), which covers 1500 square degrees in four bands $griz$, with a median redshift of $0.59$. We describe the shape measurement process implemented by the DES Y1 imshape catalogue, which contains 21.9 million high-quality $r$-band bulge/disc fits. In Chapter 3 a new suite of image simulations, referred to as Hoopoe, are presented. The Hoopoe dataset is tailored to DES Y1 and includes realistic blending, spatial masks and variation in the point spread function. We derive shear corrections, which we show are robust to changes in calibration method, galaxy binning and variance within the simulated dataset. Sources of systematic uncertainty in the simulation-based shear calibration are discussed, leading to a final estimate of the $1\sigma$ uncertainties in the residual multiplica tive bias after calibration of 0.025. Chapter 4 describes an extension of the analysis on the Hoopoe simulations into a detailed investigation of the impact of galaxy neighbours on shape measurement and shear cosmology. Four mechanisms by which neighbours can have a non-negligible influence on shear measurement are identified. These effects, if ignored, would contribute a net multiplicative bias of $m \sim 0.03 - 0.09$ in DES Y1, though the precise impact will depend on both the measurement code and the selection cuts applied. We use the cosmological inference pipeline of DES Y1 to explore the cosmological implications of neighbour bias and show that omitting blending from the calibration simulation for DES Y1 would bias the inferred clustering amplitude $S_8 \equiv \sigma_8 (\omegam /0.3)^{0.5}$ by $1.5 \sigma$ towards low values. Finally, we use the Hoopoe simulations to test the effect of neighbour-induced spatial correlations in the multiplicative bias. We find the cosmo logical impact to be subdominant to statistical error at the! current level of precision. Another major uncertainity in shear cosmology is the accuracy of our ensemble redshift distributions. Chapter 5 presents a numerical investigation into the combined constraining power of cosmic shear, galaxy clustering and their cross-correlation in DES Y1, and the potential for internal calibration of redshift errors. Introducing a moderate uniform bias into the redshift distributions used to model the weak lensing (WL) galaxies is shown to produce a $> 2\sigma$ bias in $S_8$. We demonstrate that this cosmological bias can be eliminated by marginalising over redshift error nuisance parameters. Strikingly, the cosmological constraint of the combined dataset is largely undiminished by the loss of prior information on the WL distributions. We demonstrate that this implicit self-calibration is the result of complementary degeneracy directions in the combined data. In Chapter 6 we present the preliminary results of an investigation into galaxy intrin sic alignments. Using the DES Y1 data, we show a clear dependence in alignment amplitude on galaxy type, in agreement with previous results. We subject these findings to a series of initial robustness tests. We conclude with a short overview of the work presented, and discuss prospects for the future.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Consequences of Giant Impacts on Early Uranus for Rotation, Internal Structure, Debris, and Atmospheric Erosion

Here, we perform a suite of smoothed particle hydrodynamics simulations to investigate in detail the results of a giant impact on the young Uranus. We study the internal structure, rotation rate, and atmospheric retention of the post-impact planet, as well as the composition of material ejected into orbit. Most of the material from the impactor's rocky core falls in to the core of the target. However, for higher angular momentum impacts, significant amounts become embedded anisotropically as lumps in the ice layer. Furthermore, most of the impactor's ice and energy is deposited in a hot, high-entropy shell at a radius of ~3 R ⊕ . This could explain Uranus' observed lack of heat flow from the interior and be relevant for understanding its asymmetric magnetic field. We verify the results from the single previous study of lower resolution simulations that an impactor with a mass of at least 2 M ⊕ can produce sufficiently rapid rotation in the post-impact Uranus for a range of angular momenta. At least 90% of the atmosphere remains bound to the final planet after the collision, but over half can be ejected beyond the Roche radius by a 2 or 3 M ⊕ impactor. This atmospheric erosion peaks for intermediate impactor angular momenta (~3 × 10 36 kg m 2 s –1 ). Rock is more efficiently placed into orbit and made available for satellite formation by 2 M ⊕ impactors than 3 M ⊕ ones, because it requires tidal disruption that is suppressed by the more massive impactors.

79 ASTRONOMY AND ASTROPHYSICS↗