Evaluation of Lunar Dust Dispersion with Computational Fluid Dynamics Discrete Phase Modeling

Under the dynamic influence of near-surface plasma, intricate dynamics of lunar dust have been observed during the Surveyors and Apollo missions in the form of Lunar horizontal glow. These dynamics are primarily driven by electrostatic forces generated by the continual bombardment of solar wind and highly energetic UV photons on the lunar surface and dust particles. This paper revisits the phenomenon of dust charging within the lunar photoelectron sheath and subsequent dynamics. The investigation has been carried out using a comprehensive model of the lunar photoelectron sheath characterized by observed solar spectra, latitude-dependent Fermionic photoelectrons, non-Maxwellian solar wind electrons, and cold ions. A test dust particle is introduced into the sheath, and equilibrium charge and static levitation conditions are derived. The result of dynamical evolution suggests the existence of a narrow parametric regime corresponding to the periodic hopping trajectory of the dust particle over the lunar surface. In other cases, the dust particles are found to re-impact the surface after a single ballistic hop. We further identify that the discrete charging of the dust could be crucial in determining the dust dynamics, particularly in the tenuous plasmas. The analysis of the discrete dust charging model reveals significant discrepancies with the continuous dust charging model and suggests a lower likelihood of static dust levitation in the lunar environment. The present study is important for unraveling the fundamental processes governing surface evolution on the Moon and other airless bodies throughout the Solar System.

The feasibility of extended exploration and human presence on the Moon and Mars depends critically on dealing with various environmental factors, and especially on the effects of dust. One of the most restricting facets of lunar surface exploration, as experienced by the prior Apollo landed missions, is the fine lunar dust, its high adherence, and its restrictive friction-like action. Moreover, the lunar dust particle size distribution extends generally into the submicron range, where it could potentially have toxic effects on exposed astronauts through their respiratory system. MoonDust is a project being performed in collaboration with the Canadian Space Agency to study the effects of lunar dust on optics and mechanical elements, and to develop innovative nano-filtration solutions to extend their operational lifetime within a lunar and/or Mars environment. To assist this work, a small lunar environment simulation vacuum chamber is being developed at MPBC, to enable the study of lunar dust effects on optics elements and rotary mechanisms, at pressures brought down below 10 -5 Torr. The developed simulator includes an injection system for lunar dust simulants, an excimer UV laser-light source for vacuum UV (VUV), and various diagnostic ports for relevant optical and electrical measurements. The MoonDust innovative dust mitigation solution exploits key characteristics of the lunar dust while incorporating nano-filtration technologies based on carbon nanotubes (CNT) materials. The aim is to minimize the required consumables while providing high capacity and high efficiencies for the more dangerous submicron particles. This paper reports on the development of the lunar environmental chamber and the associated lunar dust simulator. Some of the preliminary trial experimental results for filters based on CNTs for optical devices and rotary mechanical joint protection are also presented.

Dust accumulation in jet engines reduces engine efficiency and even affects aviation safety. A computational fluid dynamics study was carried out to evaluate the capability of a computational fluid dynamics (CFD) wherein the Ohio State University coefficient of restitution model (OSU model) was incorporated. The model was used to determine the effects of particle size and operating conditions similar to experiments in dust deposition in the cooling passage in a turbine vane. An impingement hole array was used to model the turbine vane cooling passage, so that the flow interactions between neighboring jets could be accounted for. The Discrete Phase Model in ANSYS Fluent was used to predict the particle impact locations, after convergence of the flow field simulation. Deposition results were obtained for an inlet-to-outlet pressure ratio of 1.015 with back pressure of 1 atm and three temperatures (300 K, 700 K and 1000 K). The CFD predictions of dust deposition qualitatively agree with experimental results. However, quantitative agreements between the CFD model and experiments will be pending improvements of the model, in areas such as thermophoretic deposition, resuspension simulation and coefficient of restitution model that accounts for varying surface conditions.

Liquid loading is one of the major flow assurance challenges in gas wells, causing production problems and reducing the ultimate recovery. Liquid loading is defined as the inability of a well to carry all the co-produced liquid up the tubing. This leads to liquid accumulation in the well resulting in increased bottomhole pressure and decline of gas flow rate. Although many studies have been performed on liquid loading phenomena, available models generally lack the ability to capture transient behavior of liquid loading in gas wells. We have developed a computational fluid dynamics (CFD) model using Ansys Fluent 19.1 R3 version to model the transient features of liquid loading. In this study, the CFD model is developed and validated with data from 42 meter long vertical pipe lab at Texas A&M University. The Eulerian multiphase approach combined with volume of fluid approach (VOF) - Multi-fluid VOF model with realizable k-Є turbulence closure is used to study the flow behavior. In addition, hexahedral mesh is utilized and compared to tetrahedron mesh to test accuracy and computational time. The developed CFD model has unique parameters combinations that shows an acceptable agreement with the experimental work. Model accuracy and computational time is improved by using hexahedral mesh. Liquid film flow reversal mechanism is expected to be the root cause of liquid loading in gas wells rather than droplet fall back mechanism. The CFD model captures the transition from one phase to another that is crucial for determining well end life. Model novelty is based on the ability to be a reliable predictive tool that can help in the remediation of liquid loading and give a precise representation of liquid loading transient behavior in gas wells.

Electrostatic particle collection in vacuum

Development and experimental validation of a CFD model for PCM in a vertical triplex tube heat exchanger

Computational fluid dynamics (CFD) models are powerful computational tools to simulate urban-landscape scale atmospheric dispersion events. They are proven to be very useful for security management and emergency response. Essential inputs to CFD models include landscape characteristics, which are often captured by various GIS data layers. While it is logical to couple GIS and CFD models to take advantage of available GIS data and the visualization and cartographic rendering capabilities of GIS, the integration of the two tools have been minimal. In this paper, we took the first step to evaluate the use of GIS data in CFD modeling. Specifically, we explore how efficient is to use GIS data in CFD models and how sensitive the CFD results are to different GIS data formats. Using campus topography and building data, and the FEFLO-URBAN CFD model, we performed atmospheric release simulations using topographic data in contour and raster formats. We found that using raster format was quite efficient and contour data required significant effort. Though the simulation outputs from the two data formats were not identical, their overall outcomes were similar and did not post alarming discrepancies. We concluded that using GIS data have tremendous potential for CFD modeling.

In order to reduce the blasting dust concentration in the tunnel during the drilling and blasting, accelerate the tunnel excavation process, and improve the working environment for the construction workers, a three-dimensional geometric model of dust transport was established based on the gas-solid two-phase flow model using the DesginModeler software, and the discrete phase model (DPM) in the FLUENT software was used to simulate the variation of dust concentration and the distribution of dust particle size at different locations along the tunnel route within 1200 s after tunnel blasting. The results showed that the concentration of blasting dust gradually decreased over time, with the fastest decrease in the range of 2 s to 120 s, and after 900 s, the dust concentration stabilized. The overall spatial distribution of the dust concentration showed a trend of decreasing from the palm face to the tunnel entrance and from the bottom plate to the upper part. The distribution pattern of dust with different particle sizes was not the same along the length of the tunnel. The large particles settled in the area of 25 m from the palm face under the action of gravity. With the increases of distance, the mass flow rate decreased, and the dust particle size became smaller, but the proportion of small particles gradually increased, while the R-R distribution index increased. The results in this study were confirmed to be reliable by comparing the measured data to provide guidance for the dust reduction technology in tunnel blasting, so as to quickly remove the dust generated during the blasting process and improve the engineering construction efficiency.

Wind tunnel and CFD study of dust dispersion from pesticide-treated maize seed

This study addresses a critical challenge faced by the oil and gas industry: erosion of sand control screens used in well production operations. The objective is to evaluate sand screen erosion rates through experimental testing and computational modeling, with the goal of establishing practical solutions for improving sand screen performance and creating production plans that increase longevity. By examining erosion behavior under realistic conditions, this study aims to enhance the industry's ability to predict and manage sand screen erosion-related failures in harsh environments. Erosion testing was conducted on wire-wrap sand screen coupon samples with sand slurry approach velocities between 1.2 ft/s and 2.0 ft/s to simulate aggressive production conditions. Three measurement techniques, optical microscopy, maximum particle passed (MPP), and filter cut point (FCP), were used to assess sand screen gap changes before and after erosion. Additionally, computational fluid dynamics (CFD) simulations, incorporating the Discrete Phase Model (DPM), were performed to replicate the experimental conditions, capturing fluid flow dynamics, particle tracking, and erosion mechanisms. The CFD model was calibrated against experimental data to improve accuracy and refine erosion predictions. This combined approach enhances the assessment of erosion behavior and enables more reliable predictions of sand screen performance in harsh well environments that cannot be economically replicated in a laboratory. Experimental results showed predictable differences in erosion rates and screen gap expansion across different measurement methods. Optical microscopy and MPP exhibited agreement, while comparatively, FCP underestimated erosion, though all methods were found to have valuable insights. CFD simulations successfully captured the erosion trends observed in testing. The results indicate that experimental testing remains critical for accurate erosion assessment, while CFD provides valuable insights into erosion patterns and influencing factors. Trends suggest that screen erosion is influenced by factors such as particle concentration, flow velocity, and base pipe hole configurations, highlighting the importance of choosing an optimized screen design for each well application. This study provides a unique combination of experimental testing and CFD analysis to evaluate erosion in sand control screens, offering a more comprehensive understanding of erosion mechanisms. The findings contribute to the industry by validating a computational erosion prediction model that can be used while also identifying the limitations of both the model and current screen gap measurement techniques. This research enhances predictive capabilities for sand screen performance.

Temperature estimation of a receiver equipped with a 3D compound parabolic concentrator

Computational fluid dynamics (CFD) model has been widely used for prototyping data centers. Evolving it to high-fidelity {\em digital twin} is desirable for the management and operations of large-scale data centers. Manually calibrating CFD model parameters to achieve twin-class fidelity by specially trained domain expert is tedious and labor-intensive. To reduce manual efforts, existing automatic calibration approaches developed for various computational models apply heuristics to search model configurations within an empirically defined parameter bound. However, in the context of CFD, each search step requires long-lasting CFD model's iterated solving, rendering these approaches impractical with increased model complexity. This paper presents Kalibre, a knowledge-based neural surrogate approach that performs CFD model calibration by iterating four key steps of i) training a neural surrogate model based on CFD-generated data, ii) finding the optimal parameters at the moment through neural surrogate retraining based on sensor-measured data, iii) configuring the found parameters back to the CFD model, and iv) validating the CFD model using sensor-measured data as the ground truth. Thus, the parameter search is offloaded to the neural surrogate which is ultra-faster than CFD model's iterated solving. To speed up the convergence of Kalibre, we integrate prior knowledge of the twinned data center's thermophysics into the neural surrogate design to improve its learning efficiency. With about five hours computation on a 32-core processor, Kalibre achieves mean absolute errors (MAEs) of $0.81^o$C and $0.75^o$C in calibrating two CFD models for two production data halls hosting thousands of servers each while requires fewer CFD solving processes than existing baseline approaches.

A numerical investigation was performed to study the variation in axial and lateral velocity profiles occurring downstream of the inlet nozzle of a typical Westinghouse 17×17 PWR fuel assembly. A Computational Fluid Dynamic (CFD) model was developed with commercial CFD software. The model comprised the lower region of the fuel assembly, including: the Debris Filter Bottom Nozzle (DFBN), P-grid, Bottom Inconel grid, one and half grid span, as well as the lower core plate hole. The purpose of the study was to obtain insight into the flow redistribution resulting from the interaction of the jet arising from the lower core plate hole and the fuel assembly structure. In particular the axial and lateral velocities before and after the nozzle were studied. The results, axial and lateral velocity contours, streamlines and maximum axial and lateral velocity distributions at various elevations are presented and discussed in relation to the potential risk of high turbulent excitation over the rod and the resulting rod-to-grid fretting-wear damage. The CFD model results indicated that the large jet flows from the lower core plate are effectively dissipated by DFBN nozzle and the grids components of the fuel assembly. The breakup of the large jets in the DFBN and the lower grids helps to reduce the steep velocity gradients and thus the rod vibration and fretting-wear risk in the lower part of the fuel assembly. The presented CFD model is one step towards developing advanced tools that can be used to confirm and evaluate the effect of complex PWR structures on flow distribution. In the future the presented model could be integrated in a larger CFD model involving several fuel assemblies for evaluating the lateral velocities generated due to the non-uniform inlet conditions into the various fuel assemblies.

In this study, we present a new quantification method for surface concentrations of lunar dust and lunar simulant. This technique demonstrates the use of portable X-ray fluorescence spectroscopy (pXRF) to quantify surface lunar dust loading on surfaces using an adaption of existing pXRF techniques and is the first demonstration of a high accuracy and precision tool designed to quantify lunar dust loading in-situ on large surfaces within seconds. This study shows the background in current methodologies for quantification of lunar dust in tests as well as current and potential future techniques for lunar surface missions, as well as current applications of commercial off-the-shelf (COTS) pXRF technology. The methodology for adapting current pXRF techniques is presented, followed by a demonstration of this new method on a variety of materials and test campaigns related to spaceflight or lunar surface missions. This technique shows high fidelity for immediate utilization as well as a demonstration of high potential for future surface missions. Potential current uses can include development and qualification testing, as well as requirement verification and validation. Included future work outlines calibration adjustments to make this technique more adaptable and hardware developments for eventually using this tool during lunar missions.

This paper aims on application of computational fluid dynamic (CFD) modelling on two-phase and multiphase flows in 75 mm conventional hydrocyclone, 350 mm dense medium cyclone (DMC) and 100 mm diameter laboratory column flotation. Along with classification experiments, a dual-planar high speed electrical resistance tomography (ERT) is used to measure the internal flow dynamics in situ in 75 mm hydrocyclone and column flotation at different operating conditions. Experiments are carried out in 75 mm hydrocyclone for different operational parameters and feed solids content varying in the range of 0–30 wt%. Results are presented in terms of the air core diameter and solids volume fraction contours using Maxwell’s conductivity equation. It is confirmed by ERT that the air core occupied area and wall solids conductivity levels decreases with increasing the feed solids concentration. Similarly, ERT is used to estimate the mean gas hold-up and radial distribution in order to understand the hydrodynamics of the column flotation. The effect of air superficial velocity and liquid flow rate on gas hold-up is discussed. Algebraic slip mixture model modified with lift, drag and rheology is used to predict the air core size, the solid concentration distribution and classification performance for the hydrocyclone. Validation of air core size and mean solid volume fractions by ERT measurements with the CFD simulations is attempted. The CFD predicted air core radius and medium segregation in the DMC is validated against literature based gamma ray tomography data. Further discrete phase model (DPM) is used to track and measure the residence times of different size and density coal particles. CFD predicted gas hold-up in the column flotation is also validated against in-house measured ERT and imaging data.