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DOE OSTI2025

REBOUND: Reverse Engineering Bidirectional Outflow Under Non-Equilibrium Diffusion

Rare-earth elements (REEs) are essential for electronics, renewable energy, and defense technologies. However, the current supply of REEs relies on mining concentrated in a few countries and energy-intensive separations. DOE’s Basic Energy Sciences (BES) program has launched a grand challenge which aims to ensure a sustainable supply of critical REEs by developing innovative and environmentally friendly separation methods. As an alternative to costly and harmful traditional methods, the Non-Equilibrium Transport Driven Separations (NETS) initiative has created a microfluidic Y-channel co-flow method that applies external fields to exploit magneto- and electrohydrodynamic effects for separating dilute REE ions from complex feedstocks. Computational fluid dynamics (CFD) studies have identified a few operating conditions with promising ion selectivity and separation efficiency. However, challenges remain regarding Y-channel versatility across feedstocks and accurate incorporation of physical phenomena into CFD models. In this work, we develop a multi-fidelity modelling approach which integrates experimental results with CFD simulation to build a surrogate model for the dependence of separation efficiency to variation of design parameters. The surrogate model enables a reinforcement learning (RL) method to adaptively launch CFD and experimental runs, improving model fidelity around optimal Y-channel parameters.

36 MATERIALS SCIENCE↗

NASA NTRS2011

CFD-CAA Coupled Calculations of a Tandem Cylinder Configuration to Assess Facility Installation Effects

This paper presents a numerical assessment of acoustic installation effects in the tandem cylinder (TC) experiments conducted in the NASA Langley Quiet Flow Facility (QFF), an open-jet, anechoic wind tunnel. Calculations that couple the Computational Fluid Dynamics (CFD) and Computational Aeroacoustics (CAA) of the TC configuration within the QFF are conducted using the CFD simulation results previously obtained at NASA LaRC. The coupled simulations enable the assessment of installation effects associated with several specific features in the QFF facility that may have impacted the measured acoustic signature during the experiment. The CFD-CAA coupling is based on CFD data along a suitably chosen surface, and employs a technique that was recently improved to account for installed configurations involving acoustic backscatter into the CFD domain. First, a CFD-CAA calculation is conducted for an isolated TC configuration to assess the coupling approach, as well as to generate a reference solution for subsequent assessments of QFF installation effects. Direct comparisons between the CFD-CAA calculations associated with the various installed configurations allow the assessment of the effects of each component (nozzle, collector, etc.) or feature (confined vs. free jet flow, etc.) characterizing the NASA LaRC QFF facility.

Redonnet, Stephane↗

DOE OSTI2020

Effects of Different Types of Entrances on Natural Ventilation in a Subway Station

In this study, the natural ventilation of a horizontal entrance of a typical subway station is investigated based on numerical simulations and experiments. In addition, a renormalization group k-e model (RNG k-e model) is applied to compute both the internal and external airflow patterns. Computational fluid dynamics (CFD) simulations are validated based on the experimental results. Furthermore, a multiple variable regression model is employed to study how the different parameters affect the internal airflow rates of the subway station statistically, according to the experimental results. For this typical model, the parameter importance can be ranked as follows: (1) outdoor wind speed; (2) flow resistance of the subway station; (3) height of the wind catcher; and (4) length of the wind catcher. To understand the detailed pressure distribution of the horizontal entrance of the subway station with and without the wind catcher, 3D numerical simulations are conducted for different scenarios. We attempt to alter the size of the wind catcher (including the length and height) to study the characteristics of the pressure on the horizontal entrance of the subway station under outdoor wind-driven conditions. The pressure distributions for the entrance for different scenarios are compared and analyzed. Finally, the interactions between the internal and external flows are investigated by changing the resistance of the subway station. When the internal flow resistance is changed, the pressure coefficient (Cp) of the entrance is different as well. Hence, the Cp is not only affected by the outdoor environment, but is also influenced by the internal airflows.

CFD↗

DOE OSTI2026

A New 1D Model for Thermal Mixing and Stratification in Advanced Reactor Transients

Thermal mixing and stratification in large pools and enclosures play a critical role in the safety and performance of pool-type nuclear reactors, particularly during transient scenarios involving significant temperature differences between incoming and bulk coolant. Accurate modeling of these phenomena is essential for predicting system behavior and supporting passive safety features such as natural circulation. Here, this paper presents a new 1D model for thermal mixing and stratification, developed and implemented in the SAM code. The model represents a large pool as 1D coolant jet channels and zero-dimensional bulk pool volumes, enabling the simulation of a wide range of flow configurations, including hot and cold jet interactions, stratified layers, and the influence of complex geometries such as ceilings, free surfaces, and internal obstacles. Heat exchange between jet and pool regions is governed by closure relations calibrated against 3D computational fluid dynamics (CFD) simulations. The model improves upon earlier approaches by incorporating time-dependent jet characteristics and capturing the associated delay effects more accurately. Code-to-code comparisons and validation against experimental data from the Thermal Stratification Test Facility demonstrate the model’s accuracy and flexibility. This work offers two key contributions: (1) an efficient and robust method for simulating thermal mixing and stratification at the system level, eliminating the need for external coupling between system analysis codes and CFD, and (2) a significant enhancement of SAM’s capabilities to analyze thermal stratification phenomena in advanced reactor systems.

SAM↗

NASA NTRS2003

Large-Eddy Simulation Code Developed for Propulsion Applications

A large-eddy simulation (LES) code was developed at the NASA Glenn Research Center to provide more accurate and detailed computational analyses of propulsion flow fields. The accuracy of current computational fluid dynamics (CFD) methods is limited primarily by their inability to properly account for the turbulent motion present in virtually all propulsion flows. Because the efficiency and performance of a propulsion system are highly dependent on the details of this turbulent motion, it is critical for CFD to accurately model it. The LES code promises to give new CFD simulations an advantage over older methods by directly computing the large turbulent eddies, to correctly predict their effect on a propulsion system. Turbulent motion is a random, unsteady process whose behavior is difficult to predict through computer simulations. Current methods are based on Reynolds-Averaged Navier- Stokes (RANS) analyses that rely on models to represent the effect of turbulence within a flow field. The quality of the results depends on the quality of the model and its applicability to the type of flow field being studied. LES promises to be more accurate because it drastically reduces the amount of modeling necessary. It is the logical step toward improving turbulent flow predictions. In LES, the large-scale dominant turbulent motion is computed directly, leaving only the less significant small turbulent scales to be modeled. As part of the prediction, the LES method generates detailed information on the turbulence itself, providing important information for other applications, such as aeroacoustics. The LES code developed at Glenn for propulsion flow fields is being used to both analyze propulsion system components and test improved LES algorithms (subgrid-scale models, filters, and numerical schemes). The code solves the compressible Favre-filtered Navier- Stokes equations using an explicit fourth-order accurate numerical scheme, it incorporates a compressible form of Smagorinsky s model for the subgrid-scale turbulence, and it uses generalized curvilinear coordinates to allow analysis of a wide range of geometries. The code runs in parallel on shared memory multiprocessor computers and is written in Fortran 90 with dynamic memory allocation. A sample result for a Mach-1.4 round jet is presented in the figure. Instantaneous Mach number contours in several cross-planes downstream of the nozzle exit are shown, illustrating how an LES captures the large unsteady three-dimensional turbulent structures present in the jet.

DeBonis, James R.↗

DOE OSTI2023

Measurement of a radial flow profile with eddy current flow meters and deep neural networks

Eddy current flow meters (ECFMs) measure flows of conductive fluids. Recent interest in ECFMs has increased due to applications in advanced nuclear reactors. ECFMs are well suited for such applications, as they can provide non-invasive measurements of flow in fluids that are often difficult to measure. Traditionally, ECFMs are operated using an alternating current at a single frequency, limiting ECFMs to measure average fluid velocities, blockages, or voids. Here, we expand the capabilities of ECFMs by measuring the fluid radial velocity profile of liquid mercury. To accomplish this, we made several ECFM sensitivity measurements at a range of frequencies. Different frequencies vary the electromagnetic skin depth of the device. By adjusting frequencies, we probed the fluid velocity at various radial locations and constructed a flow-velocity profile. The relationship between the ECFM measurements and velocity profile is nonlinear and requires solving an inverse problem. Using electromagnetic finite-element simulations to train a deep neural network (DNN), we created a model that provides a stable general relationship between the sensitivity measurements of an ECFM and the fluid velocity profile. Using ECFM measurements of liquid mercury, our DNN model calculates a flow profile that agrees well with computational fluid dynamics (CFD) simulations. This technique has potential to improve flow monitoring for optimization, safe operation of conductive fluid loops, and/or validating complex CFD models.

47 OTHER INSTRUMENTATION↗

NASA NTRS1999

A Design Tool for Liquid Rocket Engine Injectors

A practical design tool for the analysis of flowfields near the injector face has been developed and used to analyze the Fastrac engine. The objective was to produce a computational design tool which was detailed enough to predict the interactive effects of injector element impingement angles and points and the momenta of the individual orifice flows. To obtain a model which could be used to simulate a significant number of individual orifices, a homogeneous computational fluid dynamics model was developed. To describe liquid and vapor sub- and super-critical flows, the model included thermal and caloric equations of state which were valid over a wide range of pressures and temperatures. A homogeneous model was constructed such that the local state of the flow was determined directly, i.e. the quality of the flow was calculated. Such a model does not identify drops or their distribution, but it does allow the flow along the injector face and into the acoustic cavity to be predicted. It also allows the film coolant flow to be accurately described. The initial evaluation of the injector code was made by simulating cold flow from an unlike injector element and from a like-on-like overlapping fan (LOL) injector element. The predicted mass flux distributions of these injector elements compared well to cold flow test results. These are the same cold flow tests which serve as the data base for the JANNAF performance prediction codes. The flux distributions 1 inch downstream of the injector face are very similar; the differences were somewhat larger at further distances from the faceplate. Since the cold flow testing did not achieve good mass balances when integrations across the entire fan were made, the CFD simulation appears to be reasonable alternative to future cold flow testing. To simulate the Fastrac, an RP-1/LOX combustion model must be chosen. This submodel must be relatively simple to accomplish three-dimensional, multiphase flow simulations. Single RP-1 pyrolysis and partial oxidation steps were chosen and the combustion was completed with the wet CO mechanism. Soot was also formed with a single global reaction. To validate the combustion submodel, global data from gas generator tests and from subscale motor test were used to predict qualitatively correct mean molecular weights, temperature, and soot levels. Because such tests do not provide general kinetics rates, the methodology is not necessarily appropriate for other than rocket type flows conditions. Soot predictions were made so that radiation heating to the motor walls can be made. These initial studies of the Fastrac were for a small region close to the injector face and chamber wall which included a segment of the acoustic cavity. The region analyzed includes 11 individual orifice holes to represent the LOL elements and the H2 film coolant holes. Typical results of this simulation are shown in Figure 1. At this point the only available test data to verify the predictions are temperatures measured in the acoustic cavity. These temperatures are in reasonable agreement at about 2000R (1111 K). Future work is expected to include improving the computational efficiency or the CFD model and/or using more computer capacity than the single Pentium PC with which these simulations were made.

Farmer, Richard C.↗

NASA NTRS2017

MiniWall Tool for Analyzing CFD and Wind Tunnel Large Data Sets

It is challenging to review and assimilate large data sets created by Computational Fluid Dynamics (CFD) simulations and wind tunnel tests. Over the past 10 years, NASA Ames Research Center has developed and refined a software tool dubbed the "MiniWall" to increase productivity in reviewing and understanding large CFD‐generated data sets. Under the recent NASA ERA project, the application of the tool expanded to enable rapid comparison of experimental and computational data. The MiniWall software is browser based so that it runs on any computer or device that can display a web page. It can also be used remotely and securely by using web server software such as the Apache HTTP Server. The MiniWall software has recently been rewritten and enhanced to make it even easier for analysts to review large data sets and extract knowledge and understanding from these data sets. This paper describes the MiniWall software and demonstrates how the different features are used to review and assimilate large data sets.

Data Analysis↗

NASA NTRSDate not supplied

Multiscale Mesh Adaptation for Transonic Aeroelastic Flutter Problems

This work applies multiscale mesh adaptation with refine to reduce spatial discretization error of aeroelastic computational fluid dynamics (CFD) simulations. Benchmark flutter models, such as the pitch and plunge NACA64A-010 airfoil and the benchmark supercritical wing, are studied with both a linearized frequency-domain solver and time-marching CFD coupled to a modal structural solver in FUN3D. The undeformed NASA Common Research Model (CRM), an aeroelastic jig shape variant of the CRM, is also studied with the linearized frequency-domain approach. For these cases, the adaptation process converges to comparable flutter predictions to hand-generated meshes but with smaller node counts. However the additional disciplines of the linearized frequency-domain analysis, the mesh deformation, and the unsteady finite-volume solver create robustness challenges that need to be addressed before it can be applied as a fully automated process for complex transonic aeroelastic problems. In particular, negative volumes are observed to be an issue for FUN3D’s linear elasticity mesh deformation solver when moving the adapted meshes.

Aeroelasticity↗

NASA NTRS2017

MiniWall Tool for Analyzing CFD and Wind Tunnel Large Data Sets

It is challenging to review and assimilate large data sets created by Computational Fluid Dynamics (CFD) simulations and wind tunnel tests. Over the past 10 years, NASA Ames Research Center has developed and refined a software tool dubbed the MiniWall to increase productivity in reviewing and understanding large CFD-generated data sets. Under the recent NASA ERA project, the application of the tool expanded to enable rapid comparison of experimental and computational data. The MiniWall software is browser based so that it runs on any computer or device that can display a web page. It can also be used remotely and securely by using web server software such as the Apache HTTP server. The MiniWall software has recently been rewritten and enhanced to make it even easier for analysts to review large data sets and extract knowledge and understanding from these data sets. This paper describes the MiniWall software and demonstrates how the different features are used to review and assimilate large data sets.

Computational Fluid Dyanmics↗

NASA NTRS1996

Performance Improvement Through Indexing of Turbine Airfoils: Numerical Simulation - Part 2

An experimental/analytical study has been conducted to determine the performance improvements achievable by circumferentially indexing succeeding rows of turbine stator airfoils. A series of tests was conducted to experimentally investigate stator wake clocking effects on the performance of the space shuttle main engine (SSME) alternate turbopump development (ATD) fuel turbine test article (TTA). The results from this study indicate that significant increases in stage efficiency can be attained through application of this airfoil clocking concept. Details of the experiment and its results are documented in part 1 of this paper. In order to gain insight into the mechanisms of the performance improvement, extensive computational fluid dynamics (CFD) simulations were executed. The subject of the present paper is the initial results from the CFD investigation of the configurations and conditions detailed in part 1 of the paper. To characterize the aerodynamic environments in the experimental test series, two-dimensional (2D), time accurate, multistage, viscous analyses were performed at the TTA midspan. Computational analyses for five different circumferential positions of the first stage stator have been completed. Details of the computational procedure and the results are presented. The analytical results verify the experimentally demonstrated performance improvement and are compared with data whenever possible. Predictions of time-averaged turbine efficiencies as well as gas conditions throughout the flow field are presented. An initial understanding of the turbine performance improvement mechanism based on the results from this investigation is described.

Griffin, Lisa W.↗

DOE OSTI2026

Numerical Modeling of a Two-Stage Ocean Current Turbine

The Equinox Ocean Turbines (EQOT) current energy converter has a unique design with power generation in two small-diameter turbines attached to the tips of a large-diameter passive rotor. This configuration offers some key advantages for capturing ocean currents. With no centrally placed generator, almost no reaction torque is required at the nacelle of the main large-diameter rotor, and the small-diameter tip turbine generators operate at a higher speed and lower torque. The physics that determine the performance and loads on the turbine are also unique. The interactions of the flow field between the two stages and the general architecture of the system cannot be captured with traditional mid-fidelity modeling tools. For design iterations and large sets of load cases, it is important to have mid-fidelity models that can capture the important phenomenon with enough accuracy to identify global trends. This work uses a limited set of high-fidelity computational fluid dynamics (CFD) simulations to help inform the selection of and construction of a custom mid-fidelity model. Mid-fidelity modeling approaches were verified by comparing key turbine performance quantities to those found with the CFD model. Hydrodynamic interactions of the two-stage rotor were identified through high-fidelity CFD modeling. This highlighted the impact of the main rotor tip vortex and wake on the secondary rotor apparent inflow. This results in a relative flow rotation and sharp deficit, that change the optimal secondary rotor rotation speed and adds unsteadiness to the blade loading respectively. Multiple mid-fidelity approaches were evaluated for their ability to capture these effects. A simple approximation of the combined-stage performance based on single-stage BEM provides a reasonable rough prediction, especially near the peak TSR values, with some larger discrepancy at higher TSRs. Predicting the combined-stage performance based on single-stage CFD data improves this prediction across the TSR range. Although the combined-stage modeling in OLAF was not successful in this stage of the project, it showed promise as a mid-fidelity method, assuming the parameters can be tuned to account for the significant differences in time and length scales between the main and secondary rotors. This may be addressed through code changes in future work. A significant finding from the OLAF work was the agreement between the vortex core radius values found independently via a parameter space search and via CFD. The technique of using single-stage secondary rotor BEM, with a custom inflow taken from single-stage main rotor CFD or OLAF, provides an efficient method to capture one-way coupled flow interactions. This method provided generally good predictions of the impact of the flow rotation on the secondary rotor but struggled to accurately predict the peaks of the unsteady load progression. Future work could include some superposition of a tuned main rotor trailing edge viscous wake into the custom inflow to better predict this interaction.

16 TIDAL AND WAVE POWER↗

NASA NTRS2006

Aerothermodynamic Analyses of Towed Ballutes

A ballute (balloon-parachute) is an inflatable, aerodynamic drag device for application to planetary entry vehicles. Two challenging aspects of aerothermal simulation of towed ballutes are considered. The first challenge, simulation of a complete system including inflatable tethers and a trailing toroidal ballute, is addressed using the unstructured-grid, Navier-Stokes solver FUN3D. Auxiliary simulations of a semi-infinite cylinder using the rarefied flow, Direct Simulation Monte Carlo solver, DSV2, provide additional insight into limiting behavior of the aerothermal environment around tethers directly exposed to the free stream. Simulations reveal pressures higher than stagnation and corresponding large heating rates on the tether as it emerges from the spacecraft base flow and passes through the spacecraft bow shock. The footprint of the tether shock on the toroidal ballute is also subject to heating amplification. Design options to accommodate or reduce these environments are discussed. The second challenge addresses time-accurate simulation to detect the onset of unsteady flow interactions as a function of geometry and Reynolds number. Video of unsteady interactions measured in the Langley Aerothermodynamic Laboratory 20-Inch Mach 6 Air Tunnel and CFD simulations using the structured grid, Navier-Stokes solver LAURA are compared for flow over a rigid spacecraft-sting-toroid system. The experimental data provides qualitative information on the amplitude and onset of unsteady motion which is captured in the numerical simulations. The presence of severe unsteady fluid - structure interactions is undesirable and numerical simulation must be able to predict the onset of such motion.

Gnoffo, Peter A.↗

NASA NTRSDate not supplied

Attitude Reconstruction of Free-Flight CFD Generated Trajectories Using Non-Linear Pitch Damping Coefficient Curves

Attitude history reconstruction of Free-flight CFD generated trajectories with non-linear pitch damping coefficient curves is investigated. Free-flight CFD simulations of the capsule shape used for the Genesis sample return mission and the upcoming Dragonfly mission to Titan are conducted for 1-, 2-, and 3-degree-of-freedom cases. Two different data reduction methodologies are employed to derive a pitch damping curve as a function of instantaneous angle of attack. These curves are then used to reconstruct the attitude history of the body which is compared to the raw simulation results. While both data reduction methods produce pitch damping curves that can generally reconstruct the motion seen in the Free-flight simulations, it is found that optimization of the pitch damping curve using an inverse estimation process yields superior and more generalizable results. Further refinement of this technique could allow pitch damping curves derived using CFD to serve as a capability complementary to existing techniques for dynamic stability characterization.

entry↗

NASA NTRSDate not supplied

Attitude Reconstruction of Free-Flight CFD Generated Trajectories Using Non-Linear Pitch Damping Coefficient Curves

entry↗

DOE OSTI2023

Virtual Engineering Software Framework for Integrated Biomass Conversion Modeling

This presentation covers the design and implementation of a software tool to systematically connect computational models of unit operations to simulate an integrated process of low-temperature conversion of biomass to fuel. This virtual engineering (VE) software was designed with the overarching goal of connecting unit models written in various programming languages and requiring different computational resources within a single, flexible framework. The models and features currently considered for the VE library include mechanistic models for pretreatment, enzymatic hydrolysis, and aerobic bioreaction; high-fidelity computational fluid dynamics (CFD) simulations for enzymatic hydrolysis and aerobic bioreaction; and the capability to perform techno-economic analyses (TEA) using Aspen Plus, a commercial software package. The CFD models require access to high-performance computing (HPC) resources, so in addition to handling multiple programming languages and interfaces, the VE software must also be capable of interacting with an HPC scheduler to submit, run, and post-process jobs. Using the Python programming language, a new VE software package has been developed that contains functionality to manage the input-output communication between various unit models, schedule simulations to run on NREL's HPC and analyze those results, and interface with existing TEA software workflows. A Jupyter-notebook GUI was also created to solicit user input and provide documentation. In cases where multiple models for a particular unit-operation exist, selection between models is accomplished through a simple checkbox, with the appropriate inputs and outputs being parsed and converted seamlessly in the background. Each operation makes use of a different programming language, but the flow of information from pretreatment to enzymatic hydrolysis to bioreaction is managed with an intuitive, centralized file-communication strategy. In this talk, the programming approach and implementation details of the notebook are presented for multiple possibilities of the conversion process, including a demonstration of the ability to manage HPC resources. Additionally, an example of a sensitivity study of treatment parameters governing the overall conversion outcome is shown which highlights the ease of defining new problems using the VE Notebook workflow and leads into a discussion of ongoing work to enable outer-loop optimization studies.

biofuel↗

DOE OSTI2025

Development of a Digital Twin for Hydrogen Dispersion and Safety Assessment in an Electrolyzer Based Hydrogen Production Facility

Digital twin models are virtual representations of physical systems that use real-time data to simulate and optimize performance. This study presents the development and initial implementation of a digital twin (DT) for the electrolyzer-based hydrogen production facility at NREL's Advanced Research on Integrated Energy Systems (ARIES), focused on enhancing safety and optimizing sensor placement through physics-based simulations and metadata integration. The DT incorporates detailed facility-specific information, including component layout, leak locations, and controlled release parameters, to model hydrogen dispersion under varying environmental conditions. Using steady-state computational fluid dynamics (CFD) simulations informed by real meteorological data, such as wind speed, direction, and vertical wind profiles, the DT enables visualization of hydrogen plume behavior and spatial concentration distributions. Comparative analysis between high and low wind speed scenarios illustrates the significant influence of wind dynamics on plume shape and extent, with horizontal momentum dominating dispersion at higher speeds, while buoyancy effects become more prominent under low wind conditions. These simulations generate a rich dataset embedded within the DT, allowing users to assess potential leak outcomes and identify optimal sensor locations based on concentration thresholds. The model supports scenario-based analysis to guide safety strategies and equipment deployment for open-area hydrogen infrastructure. The digital twin thus serves as a dynamic platform for virtual prototyping, providing predictive insight into hydrogen behavior and enhancing risk-informed decision-making. This initial phase establishes a validated foundation for future integration of transient, uncontrolled leak scenarios and real-time sensor feedback, positioning the DT as a critical tool for safety design, operational planning, and adaptive monitoring in hydrogen systems. Overall, the approach demonstrates the value of combining environmental data with digital simulations to inform safer and more efficient deployment of hydrogen technologies.

08 HYDROGEN↗

NASA NTRS2017

Two-Pendulum Model of Propellant Slosh in Europa Clipper PMD Tank

The objective of this fluids analysis is to model propellant slosh for the Europa Clipper mission using a two-pendulum model, such that controls engineers can predict slosh behavior during the mission. Propellant slosh causes shifts in center of mass and exerts forces and torques on the spacecraft which, if not adequately controlled, can lead to mission failure. The two-pendulum model provides a computationally simple model that can be used to predict slosh for the Europa Clipper tank geometry. The Europa Clipper tank is cylindrical with a domed top and bottom and includes a propellant management device (PMD). Due to the lack of experimental data in low gravity environments, computational fluid dynamics (CFD) simulation results were used as 'real' slosh behavior for two propellants at three fill fractions. Key pendulum parameters were derived that allow the pendulum model's center of mass, forces, and moments to closely match the CFD data. The parameter trends were examined as a function of tank fill fraction and compared with solutions to analytic equations that describe the frequency of slosh in tanks with simple geometries. The trends were monotonic as expected, and parameters resembled analytical predictions; any differences could be explained by the specific differences in the geometry of the tank. This paper summarizes the new method developed at Goddard Space Flight Center (GSFC) for deriving pendulum parameters for two-pendulum equivalent sloshing models. It presents the results of this method and discusses the validity of the results. This analysis is at a completed stage and will be applied in the immediate future to the evolving tank geometry as Europa Clipper moves past its preliminary design review (PDR) phase.

Propellant Slosh↗