Spatially Adaptive Stochastic Methods for Mesoscopic Fluid-Structure Interactions in Complex Geometries.
Abstract not provided.
Hu, Jonathan Joseph↗
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Reducing COmputational Complexity in Moment of Fluid Interface Reconstruction
Abstract not provided
97 MATHEMATICS AND COMPUTING↗
Fluid-structure interactions in compressible cavity flows
Experiments were performed to understand the complex fluid-structure interactions that occur during aircraft internal store carriage. A cylindrical store was installed in a rectangular cavity having a length-to-depth ratio of 3.33 and a length-to-width ratio of 1. The Mach number ranged from 0.6 to 2.5 and the incoming boundary layer was turbulent. Fast-response pressure measurements provided aeroacoustic loading in the cavity, while triaxial accelerometers provided simultaneous store response. Despite occupying only 6% of the cavity volume, the store significantly altered the cavity acoustics. The store responded to the cavity flow at its natural structural frequencies, and it exhibited a directionally dependent response to cavity resonance. Specifically, cavity tones excited the store in the streamwise and wall-normal directions consistently, whereas a spanwise response was observed only occasionally. Also, the streamwise and wall-normal responses were attributed to the longitudinal pressure waves and shear layer vortices known to occur during cavity resonance. Although the spanwise response to cavity tones was limited, broadband pressure fluctuations resulted in significant spanwise accelerations at store natural frequencies. As a result, the largest vibrations occurred when a cavity tone matched a structural natural frequency, although energy was transferred more efficiently to natural frequencies having predominantly streamwise and wall-normal motions.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
Assessing the combined influence of fluid-rock interactions on reservoir properties and injectivity during CO 2 storage in saline aquifers
Complex fluid-rock interactions can occur during the injection of carbon dioxide (CO 2 ) into saline aquifers for sequestration, which may affect CO 2 injectivity and storage capacity. A comprehensive reactive transport model is established to analyze salt precipitation, CO 2 -water-rock geochemical reactions, and their effects on reservoir physical properties and injectivity. In addition, sensitivity analyses are conducted to investigate the main factors that affect fluid-rock interactions and injectivity with relevance for site selection for CO 2 storage. Results show that the back flow of formation water not only affects the salt precipitation but also affects the CO 2 -water-rock geochemical reactions, resulting in salt and calcite precipitations mainly occurring in the dry-out zone. However, most of the mineral dissolution/precipitation caused by CO 2 -water-rock reaction occurs in the two-phase and aqueous-phase zones, and their effect on reservoir porosity and permeability are small. A considerable amount of sodium chloride precipitates in the dry-out zone as brine is drawn by capillary action into this zone, with significant consequences for porosity, permeability and injectivity. The injection rate, salinity, capillary pressure–saturation relationships, and reservoir permeability strongly affect the distribution of salt precipitation. Finally, moderate injection rates, salinities, capillary pressures, and permeabilities all lead to favorable CO 2 injectivity.
54 ENVIRONMENTAL SCIENCES↗
Advanced Supercritical Carbon Dioxide Brayton Cycle Development
Fluids operating in the supercritical state have promising characteristics for future high efficiency power cycles. In order to develop power cycles using supercritical fluids, it is necessary to understand the flow characteristics of fluids under both supercritical and two-phase conditions. In this study, a Computational Fluid Dynamic (CFD) methodology was developed for supercritical fluids flowing through complex geometries. A real fluid property module was implemented to provide properties for different supercritical fluids. However, in each simulation case, there is only one species of fluid. As a result, the fluid property module provides properties for either supercritical CO 2 (S-CO 2 ) or supercritical water (SCW). The Homogeneous Equilibrium Model (HEM) was employed to model the two-phase flow. HEM assumes two phases have same velocity, pressure, and temperature, making it only applicable for the dilute dispersed two-phase flow situation. Three example geometries, including orifices, labyrinth seals, and valves, were used to validate this methodology with experimental data. For the first geometry, S-CO 2 and SCW flowing through orifices were simulated and compared with experimental data. The maximum difference between the mass flow rate predictions and experimental measurements is less than 5%. This is a significant improvement as previous works can only guarantee 10% error. In this research, several efforts were made to help this improvement. First, an accurate real fluid module was used to provide properties. Second, the upstream condition was determined by pressure and density, which determines supercritical states more precise than using pressure and temperature. For the second geometry, the flow through labyrinth seals was studied. After a successful validation, parametric studies were performed to study geometric effects on the leakage rate. Based on these parametric studies, an optimum design strategy for the see-through labyrinth seals was proposed. A stepped labyrinth seal, which mimics the behavior of the labyrinth seal used in the Sandia National Laboratory (SNL) S-CO 2 Brayton cycle, was also tested in the experiment along with simulations performed. The rest of this study demonstrates the difference of valves' behavior under supercritical fluid and normal fluid conditions. A small-scale valve was tested in the experiment facility using S-CO 2 . Different percentages of opening valves were tested, and the measured mass flow rate agreed with simulation predictions. Two transients from a real S-CO 2 Brayton cycle design provided the data for valve selection. The selected valve was studied using numerical simulation, as experimental data is not available.
42 ENGINEERING↗
Generating a heated fluid using an electromagnetic radiation-absorbing complex
A vessel including a concentrator configured to concentrate electromagnetic (EM) radiation received from an EM radiation source and a complex configured to absorb EM radiation to generate heat. The vessel is configured to receive a cool fluid from the cool fluid source, concentrate the EM radiation using the concentrator, apply the EM radiation to the complex, and transform, using the heat generated by the complex, the cool fluid to the heated fluid. The complex is at least one of consisting of copper nanoparticles, copper oxide nanoparticles, nanoshells, nanorods, carbon moieties, encapsulated nanoshells, encapsulated nanoparticles, and branched nanostructures. Further, the EM radiation is at least one of EM radiation in an ultraviolet region of an electromagnetic spectrum, in a visible region of the electromagnetic spectrum, and in an infrared region of the electromagnetic spectrum.
36 MATERIALS SCIENCE↗
Self-assembly of {alpha}-helical polypeptides driven by complex coacervation.
Reported is the ability of alpha-helical polypeptides to self-assemble with oppositely-charged polypeptides to form liquid complexes while maintaining their alpha-helical secondary structure. Coupling the alpha-helical polypeptide to a neutral, hydrophilic polymer and subsequent complexation enables the formation of nanoscale coacervate-core micelles. While previous reports on polypeptide complexation demonstrated a critical dependence of the nature of the complex (liquid versus solid) on chirality, the alpha-helical structure of the positively charged polypeptide prevents the formation of beta-sheets, which would otherwise drive the assembly into a solid state, thereby, enabling coacervate formation between two chiral components. The higher charge density of the assembly, a result of the folding of the alpha-helical polypeptide, provides enhanced resistance to salts known to inhibit polypeptide complexation. The unique combination of properties of these materials can enhance the known potential of fluid polypeptide complexes for delivery of biologically relevant molecules.
chirality↗
Room-temperature polariton quantum fluids in halide perovskites
Abstract Quantum fluids exhibit quantum mechanical effects at the macroscopic level, which contrast strongly with classical fluids. Gain-dissipative solid-state exciton-polaritons systems are promising emulation platforms for complex quantum fluid studies at elevated temperatures. Recently, halide perovskite polariton systems have emerged as materials with distinctive advantages over other room-temperature systems for future studies of topological physics, non-Abelian gauge fields, and spin-orbit interactions. However, the demonstration of nonlinear quantum hydrodynamics, such as superfluidity and Čerenkov flow, which is a consequence of the renormalized elementary excitation spectrum, remains elusive in halide perovskites. Here, using homogenous halide perovskites single crystals, we report, in both one- and two-dimensional cases, the complete set of quantum fluid phase transitions from normal classical fluids to scatterless polariton superfluids and supersonic fluids—all at room temperature, clear consequences of the Landau criterion. Specifically, the supersonic Čerenkov wave pattern was observed at room temperature. The experimental results are also in quantitative agreement with theoretical predictions from the dissipative Gross-Pitaevskii equation. Our results set the stage for exploring the rich non-equilibrium quantum fluid many-body physics at room temperature and also pave the way for important polaritonic device applications.
42 ENGINEERING↗
Multi-dimensional rheology-based two-phase model for sediment transport and applications to sheet flow and pipeline scour
Sediment transport is fundamentally a two-phase phenomenon involving fluid and sediments; however, many existing numerical models are one-phase approaches, which are unable to capture the complex fluid-particle and inter-particle interactions. In the last decade, two-phase models have gained traction; however, there are still many limitations in these models. For example, several existing two-phase models are confined to one-dimensional problems; in addition, the existing two-dimensional models simulate only the region outside the sand bed. This paper develops a new three-dimensional two-phase model for simulating sediment transport in the sheet flow condition, incorporating recently published rheological characteristics of sediments. The enduring-contact, inertial, and fluid viscosity effects are considered in determining sediment pressure and stresses, enabling the model to be applicable to a wide range of particle Reynolds number. A k − ε turbulence model is adopted to compute the Reynolds stresses. In addition, a novel numerical scheme is proposed, thus avoiding numerical instability caused by high sediment concentration and allowing the sediment dynamics to be computed both within and outside the sand bed. The present model is applied to two classical problems, namely, sheet flow and scour under a pipeline with favorable results. For sheet flow, the computed velocity is consistent with measured data reported in the literature. For pipeline scour, the computed scour rate beneath the pipeline agrees with previous experimental observations. However, the present model is unable to capture vortex shedding; consequently, the sediment deposition behind the pipeline is overestimated. Sensitivity analyses reveal that model parameters associated with turbulence have strong influence on the computed results.
42 ENGINEERING↗
Ring Model Development and Validation for Prismatic HTGR Core Thermal-hydraulics and Safety Analysis
Because of the complex core geometry, prismatic high temperature gas-cooled reactors (prismatic HTGRs) often exhibit complex thermal fluid behaviors during both normal operating and transient conditions. Most HTGR designs rely on passive safety system for decay heat removal, such as the reactor cavity cooling system (RCCS). During postulated accidents like Pressurized Conduction Cooldown (PCC) event, the decay heat is first radially transferred from the core region to the reactor vessel outer surface, then to the RCCS cooling panels. The peak fuel temperature is controlled by heat transfer mechanisms with two distinctive characteristic length scales, i.e., the core-wise effective heat conduction and local heat conduction in the fuel pellet scale. As both length scales are essential to determine the fuel temperature, from the modeling perspective, computer codes must be able to capture heat transfer in both scales. This is challenging for both computational fluid dynamics (CFD) tools because of extremely large amount of computation resources required, and for system analysis codes because of the challenge to model the complex core geometry. Under the support of DOE-NE’s Nuclear Energy Advanced Modeling and Simulation (NEAMS) program, efforts have been pursued to support HTGR technology development and its modeling and simulation needs. There is a particular need for advanced modeling and simulation tools to predict thermal-fluid behavior during safety-related transients. In our previous studies, the ring model was adopted in SAM and further developed to simulate the normal operating condition and a PCC event using the MHTGR-350 design of General Atomics as the reference design. This current work represents a continuation of these previous efforts, and the focus is to critically review and examine simplifications and assumptions made to develop the ring model, and to perform code validation using experimental data from an integral-effect test facility, the High Temperature Test Facility (HTTF) at the Oregon State University. In this study, the test PG-27 from the HTTF test suite was selected for code validation purpose. The test PG-27 is a transient test designed to simulate the PCC event of the MHTGR design. Very good agreements between SAM prediction and experimental measurements were found in both coolant and solid structure temperatures during the transient.
21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
MAST Propellant and Delivery System Design Methods
A Mars Aerospace Taxi (MAST) concept and propellant storage and delivery case study is undergoing investigation by NASA's Element Design and Architectural Impact (EDAI) design and analysis forum. The MAST lander concept envisions landing with its ascent propellant storage tanks empty and supplying these reusable Mars landers with propellant that is generated and transferred while on the Mars surface. The report provides an overview of the data derived from modeling between different methods of propellant line routing (or "lining") and differentiate the resulting design and operations complexity of fluid and gaseous paths based on a given set of fluid sources and destinations. The EDAI team desires a rough-order-magnitude algorithm for estimating the lining characteristics (i.e., the plumbing mass and complexity) associated different numbers of vehicle propellant sources and destinations. This paper explored the feasibility of preparing a mathematically sound algorithm for this purpose, and offers a method for the EDAI team to implement.
Taxi↗
Application of parallel distributed Lagrange multiplier technique to simulate coupled Fluid-Granular flows in pipes with varying Cross-Sectional area
Fluid-granular flows are common phenomena in nature and industry. Here, an efficient computational technique based on the distributed Lagrange multiplier method is utilized to simulate complex fluid-granular flows. Each particle is explicitly resolved on an Eulerian grid as a separate domain, using solid volume fractions. The fluid equations are solved through the entire computational domain, however, Lagrange multiplier constrains are applied inside the particle domain such that the fluid within any volume associated with a solid particle moves as an incompressible rigid body. The particle–particle interactions are implemented using explicit force-displacement interactions for frictional inelastic particles similar to the DEM method with some modifications using the volume of an overlapping region as an input to the contact forces. Here, a parallel implementation of the method is based on the SAMRAI (Structured Adaptive Mesh Refinement Application Infrastructure) library.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
Construction of a Fluid Flowfield from Discrete Point Data using Machine Learning
Many verification and validation procedures in aerospace engineering involve the comparison of computational fluid dynamics (CFD) data to experimental results from sources like wind tunnel tests. However, an incongruity exists between the data available from these sources: flow visualization is available by default in computational data, whereas in most experimental setups the available data is far more discrete and far more limited: integrated forces and moments, discrete pressure and temperature probes, etc. When differences exist between quantities of interest like lift and drag coefficients, the lack of full-field flow data from the experiments complicates most attempts to reconcile why the different data sources disagree. To this end, a shallow neural network, constrained by certain fluid flow properties, was trained to approximate flow field snapshots given only discrete data like that available in a wind tunnel test. The constructed snapshots, even for complex incompressible fluid flows, were found to agree at the large scales with the true flow fields. With this tool, researchers can more readily and easily understand why quantities of interest differ between their experimental and computational datasets. This in turn improves the resulting data's uncertainty measures.
Yury Lebedev↗
Construction of a Fluid Flowfield from Discrete Point Data using Machine Learning
Many verification and validation procedures in aerospace engineering involve the comparison of computational fluid dynamics (CFD) data to experimental results from sources like wind tunnel tests. However, an incongruity exists between the data available from these sources: flow visualization is available by default in computational data, whereas in most experimental setups the available data is far more discrete and far more limited: integrated forces and moments, discrete pressure and temperature probes, etc. When differences exist between quantities of interest like lift and drag coefficients, the lack of full-field flow data from the experiments complicates most attempts to reconcile why the different data sources disagree. To this end, a shallow neural network, constrained by certain fluid flow properties, was trained to approximate flow field snapshots given only discrete data like that available in a wind tunnel test. The constructed snapshots, even for complex incompressible fluid flows, were found to agree at the large scales with the true flow fields. With this tool, researchers can more readily and easily understand why quantities of interest differ between their experimental and computational datasets. This in turn improves the resulting data's uncertainty measures.
Yury Lebedev↗
Fastrac Rocket Engine Combustion Chamber Acoustic Cavities
A three dimensional modal analysis was performed using finite fluid elements. The analysis shows four distinct modes of the Fastrac chamber plus cavities near the frequency of the chamber first tangential mode. The mode shapes illustrate the complexity of fluid oscillations in a three dimensional chamber and acoustic cavity. In addition, a first tangential forcing function was applied to the chamber with three different acoustic cavity fluid temperatures. It was observed that the acoustic cavity fluid temperature has a significant effect on the response of the chamber to first tangential mode oscillations.
Christensen, Eric↗
Quantification of Numerical Uncertainty via Nonlinear Dynamical Approach
Motivations (Ensure a Higher Level of Confidence in the Predictability & Reliability of Numerical Simulation for Multiscale Complex Nonlinear Fluid Problems) - The last two decades have been an era when computation is ahead of analysis & when very large scale practical computations are increasingly used in poorly understood multiscale complex nonlinear physical problems & non-traditional fields (Especially when computations offer the ONLY way of generating this type of data limited simulations). - At present some of the numerical uncertainties can be explained and minimized by traditional numerical analysis and standard CFD practices. However, such practices, usually based on linearized analysis, MIGHT NOT be sufficient for strongly nonlinear and/or stiff problems. - We need a good understanding of the nonlinear behavior of numerical schemes being used as an integral part of code verification, validation and certification.
HEC↗
Flowfield-Dependent Mixed Explicit-Implicit (FDMEL) Algorithm for Computational Fluid Dynamics
Despite significant achievements in computational fluid dynamics, there still remain many fluid flow phenomena not well understood. For example, the prediction of temperature distributions is inaccurate when temperature gradients are high, particularly in shock wave turbulent boundary layer interactions close to the wall. Complexities of fluid flow phenomena include transition to turbulence, relaminarization separated flows, transition between viscous and inviscid incompressible and compressible flows, among others, in all speed regimes. The purpose of this paper is to introduce a new approach, called the Flowfield-Dependent Mixed Explicit-Implicit (FDMEI) method, in an attempt to resolve these difficult issues in Computational Fluid Dynamics (CFD). In this process, a total of six implicitness parameters characteristic of the current flowfield are introduced. They are calculated from the current flowfield or changes of Mach numbers, Reynolds numbers, Peclet numbers, and Damkoehler numbers (if reacting) at each nodal point and time step. This implies that every nodal point or element is provided with different or unique numerical scheme according to their current flowfield situations, whether compressible, incompressible, viscous, inviscid, laminar, turbulent, reacting, or nonreacting. In this procedure, discontinuities or fluctuations of an variables between adjacent nodal points are determined accurately. If these implicitness parameters are fixed to certain numbers instead of being calculated from the flowfield information, then practically all currently available schemes of finite differences or finite elements arise as special cases. Some benchmark problems to be presented in this paper will show the validity, accuracy, and efficiency of the proposed methodology.
Garcia, S. M.↗
Near-critical point phenomena in fluids (19-IML-1)
Understanding the effects of gravity is essential if the behavior of fluids is to be predicted in spacecraft and orbital stations, and, more generally, to give a better understanding of the hydrodynamics in these systems. An understanding is sought of the behavior of fluids in space. What should emerge from the International Microgravity Lab (IML-1) mission is a better understanding of the kinetics of growth in off-critical conditions, in both liquid mixtures and pure fluids. This complex phenomenon is the object of intensive study in physics and materials sciences area. It is also expected that the IML-1 flight will procure key results to provide a better understanding of how a pure fluid can be homogenized without gravity induced convections, and to what extent the 'Piston Effect' is effective in thermalizing the compressible fluids.
Beysens, D.↗