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At least 757 records · Page 42

Design-Space Exploration for Inverse-Design of Wind Turbine Blades Using Data-Driven Methods

The state-of-the-practice aerodynamic design methods for wind turbine blades is typically based on Blade-Element Momentum (BEM) theory using a pre-designed frozen family of airfoils. The airfoils are themselves typically designed using panel methods. The design of the next-generation of large flexible rotors will need to capture the non-linear aerodynamics and three-dimensional flow to reduce the levelized cost of wind energy. Data-driven methods for aerodynamic design using data generated by computational fluid dynamics offer an attractive alternative to BEM-based methods that captures the non-linear aerodynamics of the component airfoils as well as the root and tip sections. In this work, we develop and demonstrate a framework to "smartly" explore the relevant design space in combination with an appropriate automated CFD pipeline to evaluate the aerodynamics of each design. The design-space exploration framework uses appropriate perturbations to the airfoil shape and induction profile from a baseline shape in combination with the inverse-design using BEM. The resulting designs are evaluated using an automated CFD pipeline using the in-house CFD solver framework "Mercury". We perform verification and validation to establish the capability of the Mercury framework to predict the aerodynamic performance of wind turbines. The CFD simulation of the perturbed blade shapes are optimized to restart from the converged baseline simulation to reduce the computational time. Finally, we demonstrate the design-space exploration technique for the design of the outboard section and the full rotor using perturbations to the shape and operating conditions of the NREL 5-MW turbine.

aerodynamic design methods↗

Intelligent fault management for the Space Station active thermal control system

The Thermal Advanced Automation Project (TAAP) approach and architecture is described for automating the Space Station Freedom (SSF) Active Thermal Control System (ATCS). The baseline functionally and advanced automation techniques for Fault Detection, Isolation, and Recovery (FDIR) will be compared and contrasted. Advanced automation techniques such as rule-based systems and model-based reasoning should be utilized to efficiently control, monitor, and diagnose this extremely complex physical system. TAAP is developing advanced FDIR software for use on the SSF thermal control system. The goal of TAAP is to join Knowledge-Based System (KBS) technology, using a combination of rules and model-based reasoning, with conventional monitoring and control software in order to maximize autonomy of the ATCS. TAAP's predecessor was NASA's Thermal Expert System (TEXSYS) project which was the first large real-time expert system to use both extensive rules and model-based reasoning to control and perform FDIR on a large, complex physical system. TEXSYS showed that a method is needed for safely and inexpensively testing all possible faults of the ATCS, particularly those potentially damaging to the hardware, in order to develop a fully capable FDIR system. TAAP therefore includes the development of a high-fidelity simulation of the thermal control system. The simulation provides realistic, dynamic ATCS behavior and fault insertion capability for software testing without hardware related risks or expense. In addition, thermal engineers will gain greater confidence in the KBS FDIR software than was possible prior to this kind of simulation testing. The TAAP KBS will initially be a ground-based extension of the baseline ATCS monitoring and control software and could be migrated on-board as additional computation resources are made available.

Hill, Tim↗

Development of machine learning framework for interface force closures based on bubble tracking data

Interfacial force closures in the two-fluid model play a critical role for the predictive capabilities of void fraction distribution. However, the practices of interfacial force modeling have long been challenged by the inherent physical complexity of the two-phase flows. The rapidly expanding computational capabilities in the recent years have made high-fidelity data from the interface-captured direct numerical simulation become more available, and hence potential for data-driven interfacial force modeling has prevailed. In this work, we established a data-driven modeling framework integrated to the HZDR multiphase Eulerian-Eulerian framework for computational fluid dynamics simulations. The data-driven framework is verified in a benchmark problem, where a feedforward neural network managed to capture the non-linear mapping between bubble Reynolds number and drag coefficient and reproduce the void distribution resulting from the baseline model in the test case. The second focus is on utilizing the bubble tracking data set to form a closure for the bubble drag in the turbulent bubbly flow, in which the drag coefficient is set to be correlated with the bubble Reynolds number and the Eötvös number. Pseudo-steady state filtering in the Frenet Frame was carried out to obtain the drag coefficient from the turbulent bubbly flow data. The performance of the data-driven drag model is also examined through a case study, where improvement of model’s prediction near-wall is regarded necessary. In conclusion, discussion and further plans of investigation are provided.

42 ENGINEERING↗

Assessing Reservoir Depositional Environments to Develop and Quantify Improvements in CO 2 Storage Efficiency. A Reservoir Simulation Approach

The storage potential and fluid movement within formations are dependent on the unique hydraulic characteristics of their respective depositional environments. Storage efficiency (E) quantifies the potential for storage in a geologic depositional environment and is used to assess basinal or regional CO 2 storage resources. Current estimates of storage resources are calculated using common E ranges by lithology and not by depositional environment. The objectives of this project are to quantify E ranges and identify E enhancement strategies for different depositional environments via reservoir simulation studies. The depositional environments considered include deltaic, shelf clastic, shelf carbonate, fluvial deltaic, strandplain, reef, fluvial and alluvial, and turbidite. Strategies considered for enhancing E include CO 2 injection via vertical, horizontal, and deviated wells, selective completions, water production, and multi-well injection. Conceptual geologic and geocellular models of the depositional environments were developed based on data from Illinois Basin oil fields and gas storage sites. The geologic and geocellular models were generalized for use in other US sedimentary basins. An important aspect of this work is the development of conceptual geologic and geocellular models that reflect the uniqueness of each depositional environment. Different injection well completions methods were simulated to investigate methods of enhancing E in the presence of geologic heterogeneity specific to a depositional environment. Modeling scenarios included horizontal wells (length, orientation, and inclination), selective and dynamic completions, water production, and multiwell injection. A Geologic Storage Efficiency Calculator (GSECalc) was developed to calculate E from reservoir simulation output. Estimated E values were normalized to diminish their dependency on fluid relative permeability. Classifying depositional environments according to normalized baseline E ranges ranks fluvial deltaic and turbidite highest and shelf carbonate lowest. The estimated average normalized baseline E of turbidite, and shelf carbonate depositional environments are 42.5% and 13.1%, with corresponding standard deviations of 11.3%, and 3.10%, respectively. Simulations of different plume management techniques suggest that the horizontal well, multi-well injection with brine production from blanket vertical producers are the most efficient E enhancement strategies in seven of eight depositional environments; for the fluvial deltaic depositional environment, vertical well with blanket completions is the most efficient. This study estimates normalized baseline E ranges for eight depositional environments, which can be used to assess the CO 2 storage resource of candidate formations. This study also improves the general understanding of depositional environment’s influence on E. The lessons learned and results obtained from this study can be extrapolated to formations in other US basins with formations of similar depositional environments, which should be used to further refine regional and national storage resource estimates in future editions of the Carbon Utilization and Storage Atlas of the United States. Further study could consider the economic feasibility of the E enhancement strategies identified here.

01 COAL, LIGNITE, AND PEAT↗

Final Report for ALCC Allocation: Predictive Simulation of Complex Flow in Wind Farms

This report documents work performed using ALCC computing resources granted under a proposal submitted in February 2016, with the resource allocation period spanning the period July 2016 through June 2017. The award allocation was 10.7 million processor-hours at the National Energy Research Scientific Computing Center. The simulations performed were in support of two projects: the Atmosphere to Electrons (A2e) project, supported by the DOE EERE office; and the Exascale Computing Project (ECP), supported by the DOE Office of Science. The project team for both efforts consists of staff scientists and postdocs from Sandia National Laboratories and the National Renewable Energy Laboratory. At the heart of these projects is the open-source computational-fluid-dynamics (CFD) code, Nalu. Nalu solves the low-Mach-number Navier-Stokes equations using an unstructured- grid discretization. Nalu leverages the open-source Trilinos solver library and the Sierra Toolkit (STK) for parallelization and I/O. This report documents baseline computational performance of the Nalu code on problems of direct relevance to the wind plant physics application - namely, Large Eddy Simulation (LES) of an atmospheric boundary layer (ABL) flow and wall-modeled LES of a flow past a static wind turbine rotor blade. Parallel performance of Nalu and its constituent solver routines residing in the Trilinos library has been assessed previously under various campaigns. However, both Nalu and Trilinos have been, and remain, in active development and resources have not been available previously to rigorously track code performance over time. With the initiation of the ECP, it is important to establish and document baseline code performance on the problems of interest. This will allow the project team to identify and target any deficiencies in performance, as well as highlight any performance bottlenecks as we exercise the code on a greater variety of platforms and at larger scales. The current study is rather modest in scale, examining performance on problem sizes of O(100 million) elements and core counts up to 8k cores. This will be expanded as more computational resources become available to the projects.

17 WIND ENERGY↗

Climate adaptation and sustainability in switchgrass: exploring plant-microbe-soil interactions across continental scale environmental gradients

Less carbon-intensive energy sources are needed to reduce greenhouse gas emissions and their predicted role in climate change. There is growing interest in the potential of biofuels for meeting this need. A critical question is whether large-scale biofuel production can be sustainable over the time scales needed to mitigate our carbon debt from fossil fuel consumption. The carbon balance and ultimately the sustainability of biofuel feedstock production is the result of complex climate-coupled interactions between carbon fixation, sequestration, and release through combustion. Similarly, the long-term productivity of biofuels depends on the environmental factors limiting plant growth. These factors are often related to soil resources which involve complex interactions at the plant-microbe-soil interface impacting their availability and cycling. Our collaborative project addressed sustainable switchgrass (Panicum virgatum) production by exploring Plant Systems, Plant-Microbiome Interactions, and Ecosystem Processes through the integrating lens of Multi-Scale Modeling. Our research was based on detailed characterization of genetically diverse switchgrass genotypes planted in common gardens across a continental latitudinal gradient. The underlying theme of our Plant Systems research was the use of locally adapted plant material to explore plant function, to understand the mechanistic basis of environmental interactions, and to discover the plant genes important for adaptation and sustainability in the face of climate change. Our Plant-Microbiome Interaction project characterized the microbial communities associated with switchgrass using genomic tools. Our Ecosystem Processes research focused on carbon cycle responses at the ecosystem level using stand level plantings. Finally, our Multi-Scale Modeling helped to define conditions of a sustainable biofuel system and identify key tradeoffs between genetic diversity, productivity, and ecosystem services. Genome-wide association analyses were used to identify alleles that contribute to successful establishment and biomass production across North America. Together, our work provided a baseline analyses of the potential of switchgrass as a biofuel feedstock. Our project resulted in a number of successful outcomes. First, we were successful in collecting switchgrass germplasm across the species range, propagating the material, and establishing common garden experiments across the species range. In collaboration with DOE JGI, we successfully assembled the first tetraploid switchgrass genome and published this resource with an analyses of the genetic basis local adaptation from our gardens (Lowry et al. 2019, Lovell et al. 2021). The gardens were used to characterize the genetic architecture for a number of important plant phenotypes. Our project also conducted extensive sampling and sequencing to characterize the bacterial and fungal associates of switchgrass roots and leaves. We showed that host genotype, location, and harvesting practices can play a role in microbiome assembly (Singer et al. 2019 & 2022, Van Wallendael et al. 2020 & 2022, Edwards et al. 2023). Our ecosystem processes work created baseline dataset of carbon and nutrient cycling in realistic stand plantings of switchgrass. Data from this experiment provided new insight into the role of plant traits, phenology, and local environments in ecosystem processes like soil respiration, net-ecosystem exchange, and dynamics of soil and plant nutrients (Ricketts et al. 2023). Finally, our crop modelling experiments help to characterize the sensitivity of common modeling frameworks to parameters, identify key limiters of productivity across large geographic scales, and leverage patterns of local adaptation in prediction. Ultimately, these studies help to identify critical plant-microbe-soil traits that may be manipulated, through breeding or agronomic management, to improve the sustainability of biofuel feedstocks.

09 BIOMASS FUELS↗

Real-time simulation of the TF30-P-3 turbofan engine using a hybrid computer

A real-time, hybrid-computer simulation of the TF30-P-3 turbofan engine was developed. The simulation was primarily analog in nature but used the digital portion of the hybrid computer to perform bivariate function generation associated with the performance of the engine's rotating components. FORTRAN listings and analog patching diagrams are provided. The hybrid simulation was controlled by a digital computer programmed to simulate the engine's standard hydromechanical control. Both steady-state and dynamic data obtained from the digitally controlled engine simulation are presented. Hybrid simulation data are compared with data obtained from a digital simulation provided by the engine manufacturer. The comparisons indicate that the real-time hybrid simulation adequately matches the baseline digital simulation.

Szuch, J. R.↗

A global geodetic reference frame from Lageos ranging (SL5.1AP)

A summary of the results obtained for a new comprehensive geodetic parameter solution from the analysis of Lageos laser ranging data for the period May 1976 to the end of 1982 is presented. Estimates of each component of the polar motion and earth rotation, the station coordinates, the value of the earth's gravitational constant GM, and the elements of the Lageos orbit comprise this SL5.1AP solution. The results differ from previously published values primarily through incorporation of more rigorous dynamic models for the ocean and solid earth tides. The precision of the geodetic parameters are on average 5-marc sec polar motion, 0.2-ms length of day, better than 5-cm center-of-mass geodetic positioning, 3-cm global baselines, and 2-cm regional baselines. An assessment of the contribution of systematic errors in the interstation distance determination is presented.

Smith, D. E.↗

Multi-Tethered Space-Based Interferometers: Particle System Model

Dynamics models are presented for a class of space-based interferometers comprised of multiple component bodies, interconnected in various arrangements, by low-mass flexible tethers of variable length. The tethered constellations are to perform coordinated rotational scanning accompanied by baseline dimensional changes, as well as spin axis realignments and spin-up/spin-down maneuvers. The mechanical idealization is a system of N point masses interconnected by massless tethers of variable length. Both extensible and inextensible tethers are considered. Expressions for system angular and linear momenta are developed. The unrestricted nonlinear motion equations are derived via Lagranges equations. Rheonomic constraints are introduced to allow prescribed motion of any degrees of freedom, and the associated physical forces are determined. The linearized equations of motion are obtained for the steady rotation of a system with extensible tethers of constant unstrained length.

Gates, Stephen S.↗

In-Flight Suppression of a Destabilized F/A-18 Structural Mode Using the Space Launch System Adaptive Augmenting Control System

NASA's Space Launch System (SLS) Flight Control System (FCS) includes an Adaptive Augmenting Control (AAC) component which employs a multiplicative gain update law to enhance the performance and robustness of the baseline control system for extreme off nominal scenarios. The SLS FCS algorithm including AAC has been flight tested utilizing a specially outfitted F/A-18 fighter jet in which the pitch axis control of the aircraft was performed by a Non-linear Dynamic Inversion (NDI) controller, SLS reference models, and the SLS flight software prototype. This paper describes test cases from the research flight campaign in which the fundamental F/A-18 airframe structural mode was identified using frequency-domain reconstruction of flight data, amplified to result in closed loop instability, and suppressed in-flight by the SLS adaptive control system.

Wall, John H.↗

A Small Spacecraft Swarm Deployment and Stationkeeping Strategy for Sun-Earth L1 Halo Orbits

Spacecraft orbits about the Sun-Earth librarian point L1 have been of interest since the 1950s. An L1 halo orbit was first achieved with the International Sun-Earth Explorer-3 (ISEE-3) mission, and similar orbits around Sun-Earth L1 were achieved in the Solar and Heliospheric Observatory (SOHO), Advanced Composition Explorer (ACE), Genesis, and Deep Space Climate Observatory (DSCOVR) missions. With recent advancements in CubeSat technology, we envision that it will soon be feasible to deploy CubeSats at L1. As opposed to these prior missions where one large satellite orbited alone, a swarm of CubeSats at L1 would enable novel science data return, providing a topology for intersatellite measurements of heliophysics phenomena both spatially and temporally, at varying spatial scales.The purpose of this iPoster is to present a flight dynamics strategy for a swarm of numerous CubeSats orbiting Sun-Earth L1. The presented method is a coupled, two-part solution. First, we present a deployment strategy for theCubeSats that is optimized to produce prescribed, time-varying intersatellite baselines for the purposes of collectingmagnetometer data as well as radiometric measurements from cross-links. Second, we employ a loose controlstrategy that was successfully applied to SOHO and ACE for minimized stationkeeping propellant expenditure. Weemphasize that the presented solution is practical within the current state-of-the-art and heritage CubeSat technology,citing capabilities of CubeSat designs that will launch on the upcoming Exploration Mission 1 (EM-1) to lunar orbitsand beyond. Within this iPoster, we present animations of the simulated deployment strategy and resulting spacecrafttrajectories. Mission design parameters such as total v required for long-term station keeping andminimum/maximum/mean spacecraft separation distances are also presented.

Optimal control↗

Development and Validation of a Slosh-Based Ullage Collapse Model

Ullage collapse modeling is an essential tool for the success of spacecraft powered by cryogenic propellants. The degree of ullage collapse can have a major impact on the design of cryogenic propellant tanks as well as the mission’s concept of operations. Additional commodities (e.g., helium gas for pressure control) and their quantities are dependent on the amount of heat transfer and phase change of propellants expected during flight. Currently, high-fidelity computational fluid dynamics (CFD) with heat transfer and phase change is the most accurate method for predicting ullage collapse. CFD simulations of this kind, however, can become very costly for problems requiring large domains, long simulation times, or significant liquid motion. Consequently, there is a need for a reduced order model to provide fast responses which can be used in engineering design decisions. The proposed numerical model is a nodal approach, augmented by outputs from CFD analyses that are generated rapidly and reliably. These outputs include transient values for liquid-vapor interface area, interface velocity, and liquid position using a volume of fluid (VoF) method. There are several benefits of combining a nodal approach with slosh predictions from CFD simulations: leveraging of the Loci/STREAM-VoF solver that has been validated in high-g and low-g environments, rapid modeling of VoF with isothermal propellant simplifications and relatively coarse meshes, and improved model predictions from the nodal tool. The nodal approach, informed by the slosh predictions from CFD, assumes uniform conditions in the liquid and gas domains. Modifications to account for temperature stratification in the liquid and gas may be implemented as a future improvement. Thermodynamic changes within the tank are solved at user-defined timesteps. First, impacts due to mass entering or leaving the control volume are captured. Second, heat transfer impacts are accounted for by tracking the volume of the gas which has been contacted by liquid in that timestep and rebalancing the internal energy. Finally, phase change is approximated using the area and velocity of the interface. The tank conditions are re-computed by conserving mass and energy. Calibration of the model to several test flights and experiments are required to baseline the predictive power and uncertainty. The final product will enable designers and engineers to create quick-turnaround predictions for ullage collapse and inform design feasibility.

Computational Fluid Dynamics↗

A History of Full-Scale Aircraft and Rotorcraft Crash Testing and Simulation at NASA Langley Research Center

This paper summarizes 2-1/2 decades of full-scale aircraft and rotorcraft crash testing performed at the Impact Dynamics Research Facility (IDRF) located at NASA Langley Research Center in Hampton, Virginia. The IDRF is a 240-ft.-high steel gantry that was built originally as a lunar landing simulator facility in the early 1960's. It was converted into a full-scale crash test facility for light aircraft and rotorcraft in the early 1970 s. Since the first full-scale crash test was preformed in February 1974, the IDRF has been used to conduct: 41 full-scale crash tests of General Aviation (GA) aircraft including landmark studies to establish baseline crash performance data for metallic and composite GA aircraft; 11 full-scale crash tests of helicopters including crash qualification tests of the Bell and Sikorsky Advanced Composite Airframe Program (ACAP) prototypes; 48 Wire Strike Protection System (WSPS) qualification tests of Army helicopters; 3 vertical drop tests of Boeing 707 transport aircraft fuselage sections; and, 60+ crash tests of the F-111 crew escape module. For some of these tests, nonlinear transient dynamic codes were utilized to simulate the impact response of the airframe. These simulations were performed to evaluate the capabilities of the analytical tools, as well as to validate the models through test-analysis correlation. In September 2003, NASA Langley closed the IDRF facility and plans are underway to demolish it in 2007. Consequently, it is important to document the contributions made to improve the crashworthiness of light aircraft and rotorcraft achieved through full-scale crash testing and simulation at the IDRF.

Jackson, Karen E.↗

Insights into Waterflooding in Hydrocarbon-Bearing Nanochannels of Varying Cross Sections from Mesoscopic Multiphase Flow Simulations

Waterflooding is one of the geotechnique used to recover fuel sources from nanoporous geological formations. The scientific understanding of the process that involves the multiphase flow of nanoconfined fluids, however, has lagged, mainly due to the complex nanopore geometries and chemical compositions. To enable benchmarked flow of nanoconfined fluids, the architected geomaterials, such as synthesized mesoporous silica with tunable pore shapes and surface chemical properties, are used for designing and conducting experiments and simulations. This work uses a modified many-body dissipative particle dynamics (mDPD) model with accurately calibrated parameters to perform parametric flow simulations for studying the influences of waterflooding driven power, pore shape, surface roughness, and surface wettability on the multiphase flow in heptane-saturated silica nanochannels. Remarkably, up to 80\% reduction in the effective permeability is found for water-driven heptane flow in a baseline 4.5 nm-wide slit channel, when compared with the Hagen–Poiseuille equation. In the 4.5 nm-wide channels with architected surface roughness, the flow rate is found either higher or lower than the baseline case, depending on the shape and size of cross-sections. High wettability of the solid surface to water is essential for achieving high recovery of heptane, regardless of surface roughness. When the solid surface is less wetting or non-wetting to water, the existence of an optimal waterflooding driven power is found to allow for the highest possible recovery. A detailed analysis on the evolution of the transient water-heptane interface in those nanochannels is presented to elucidate the underlying mechanisms that impact or dictate the multiphase flow behaviors.

58 GEOSCIENCES↗

THE NOT-SO-MASSIVE BLACK HOLE IN THE MICROQUASAR GRS1915+105

We present a new dynamical study of the black hole X-ray transient GRS1915+105 making use of near-infrared spectroscopy obtained with X-shooter at the Very Large Telescope. We detect a large number of donor star absorption features across a wide range of wavelengths spanning the H and K bands. Our 24 epochs covering a baseline of over 1 yr permit us to determine a new binary ephemeris including a refined orbital period of P = 33.85 {+-} 0.16 days. The donor star radial velocity curves deliver a significantly improved determination of the donor semi-amplitude which is both accurate (K{sub 2} = 126 {+-} 1 km s{sup -1}) and robust against choice of donor star template and spectral features used. We furthermore constrain the donor star's rotational broadening to vsin i = 21 {+-} 4 km s{sup -1}, delivering a binary mass ratio of q = 0.042 {+-} 0.024. If we combine these new constraints with distance and inclination estimates derived from modeling the radio emission, a black hole mass of M{sub BH} = 10.1 {+-} 0.6 M{sub Sun} is inferred, paired with an evolved mass donor of M{sub 2} = 0.47 {+-} 0.27 M{sub Sun }. Our analysis suggests a more typical black hole mass for GRS1915+105 rather than the unusually high values derived in the pioneering dynamical study by Greiner et al. Our data demonstrate that high-resolution infrared spectroscopy of obscured accreting binaries can deliver dynamical mass determinations with a precision on par with optical studies.

79 ASTRONOMY AND ASTROPHYSICS↗

Thermal Analysis of a Solid Particle Light-Trapping Planar Cavity Receiver Using Computational Fluid Dynamics

Concentrated solar power (CSP) is one of the most effective ways of harnessing solar power to create efficient, durable, and resilient energy systems. This study entails thermal modeling and analysis of a novel central tower receiver configuration. This receiver uses solid particles as the heat transfer fluid (HTF), a promising option for third-generation CSP systems. The configuration considered here is the light-trapping planar cavity receiver (LTPCR) introduced by the National Renewable Energy Laboratory. While heat transfer studies of various LTPCR subsystems have been done, system-level thermal analysis of the LTPCR receiver has not been attempted. This study also presents important sensitivity analyses of the operating parameters of the CSP system, which can help guide the design of future central tower receivers. This study employs Ansys Fluent as a computational fluid dynamics (CFD) tool to model fluid dynamics and heat transfer in the receiver, intending to quantify its thermal performance. The model seamlessly integrates Monte Carlo ray tracing data, which generates absorbed solar flux profiles from the heliostat field design, with the heat transfer characteristics of the fluidized particle bed. This unified model is designed to accurately predict the thermal behavior of the LTPCR. Analysis of preliminary results reveals that the primary loss mechanisms are radiative and natural convective losses, in that order. Based on observations from a baseline case, several strategies are suggested and numerically tested. These solutions include selective cooling of high-temperature regions and manipulation of particle bed parameters. Selective cooling of high-temperature regions reduced the peak temperature by 151 degrees C and decreased thermal losses by 0.9%. Improving the particle-wall heat transfer coefficient (P-W HTC) of the particle bed decreased the thermal losses by 1.7% and decreased the peak temperatures by 57 degrees C. Decreasing the particle inlet temperature (PIT) also reduced thermal losses by 3.5% and decreased peak temperatures by 29 degrees C. Compounding these strategies improved the thermal losses of the receiver from 13.5% in the baseline case to 7.5%. Additionally, the study explores the variation in thermal performance across different locations of the receiver, where a variation of thermal losses from 12.9% to 17.3% is found. This allows a comprehensive evaluation of potential improvements in efficiency and temperature management.

computational fluid dynamics↗

Distribution of centrality measures on undirected random networks via the cavity method

The Katz centrality of a node in a complex network is a measure of the node’s importance as far as the flow of information across the network is concerned. For ensembles of locally tree-like undirected random graphs, this observable is a random variable. Its full probability distribution is of interest but difficult to handle analytically because of its “global” character and its definition in terms of a matrix inverse. Leveraging a fast Gaussian Belief Propagation-Cavity algorithm to solve linear systems on tree-like structures, we show that i) the Katz centrality of a single instance can be computed recursively in a very fast way, and ii) the probability P ( K ) that a random node in the ensemble of undirected random graphs has centrality K satisfies a set of recursive distributional equations, which can be analytically characterized and efficiently solved using a population dynamics algorithm. We test our solution on ensembles of Erdős-Rényi and Scale Free networks in the locally tree-like regime, with excellent agreement. The analytical distribution of centrality for the configuration model conditioned on the degree of each node can be employed as a benchmark to identify nodes of empirical networks with over- and underexpressed centrality relative to a null baseline. We also provide an approximate formula based on a rank- 1 projection that works well if the network is not too sparse, and we argue that an extension of our method could be efficiently extended to tackle analytical distributions of other centrality measures such as PageRank for directed networks in a transparent and user-friendly way.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

High Fidelity BWR Fuel Simulations

This report describes the Consortium for Advanced Simulation of Light Water Reactors (CASL) work conducted for completion of the Thermal Hydraulics Methods (THM) Level 3 milestone THM.CFD.P13.03: High Fidelity BWR Fuel Simulation. High fidelity computational fluid dynamics (CFD) simulation for Boiling Water Reactor (BWR) was conducted to investigate the applicability and robustness performance of BWR closures. As a preliminary study, a CFD model with simplified Ferrule spacer grid geometry of NUPEC BWR Full-size Fine-mesh Bundle Test (BFBT) benchmark has been implemented. Performance of multiphase segregated solver with baseline boiling closures has been evaluated. Although the mean values of void fraction and exit quality of CFD result for BFBT case 4101-61 agreed with experimental data, the local void distribution was not predicted accurately. The mesh quality was one of the critical factors to obtain converged result. The stability and robustness of the simulation was mainly affected by the mesh quality, combination of BWR closure models. In addition, the CFD modeling of fully-detailed spacer grid geometry with mixing vane is necessary for improving the accuracy of CFD simulation.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗