Developing a CFD Model to Predict Radiological Materials Packaging Temperatures within a Generic Staging Building
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Due to the projected decline of demand for gasoline in light duty engines and the advent of ethanol as a green fuel, the use of gasoline/ethanol blend fuels in heavy duty applications are being investigated as they are projected to have lower cost and lower lifecycle green house gas (GHG) emissions. In heavy duty engines, the primary mode of combustion is mixing controlled combustion where wide range of mixture conditions (equivalence ratio) exist. Soot emissions of these fuels in richer conditions are not well understood. The goal of this research is to evaluate some commercially available soot modeling codes for the particulate matter emissions from gasoline/ethanol fuel blends, especially at fuel rich conditions. A Rapid Compression Machine (RCM) is modeled in a three-dimensional numerical simulation using CONVERGE computational software using a reduced chemical kinetic mechanism with SAGE chemistry solver and a RANS k-ϵturbulence model with a sector model including the creviced piston. The creviced piston is used in the experimental setup to reduce boundary layer effects and to maintain a homogeneous core in the reaction cylinder. Computational fluid dynamics simulations are conducted for different gasoline-ethanol fuel blends from E10 (10% ethanol v/v) to E100. The fuel blend is modeled as a surrogate mixture of toluene, iso-octane, n-heptane for gasoline content, and ethanol. The computational results were validated against experimental results using pressure measurements and laser extinction diagnostics. Different soot models are investigated to evaluate their capability of predicting the sooting tendencies of fuel blends, especially in richer conditions experienced during mixing-controlled combustion. The experimental combustion characteristics such as the ignition delay of different blends of fuel are reasonably well predicted. The Particulate Size Mimic (PSM) model accurately predicts the soot generation characteristics of the different fuels, but the Hiroyasu-NSC model falls short in this regard. For accurate prediction of soot with the PSM model, the thermodynamic conditions during combustion must be accurately modeled. While the current computational modeling tools can produce accurate results for the prediction of particulate matter emissions, there is much work to be done in improving our understanding of the underlying fundamental processes.
Through the TEAMER program, Sandia National Laboratories (SNL) collaborated with IDOM Incorporated to study their MARMOK-Oscillating Water Column (MARMOK-OWC) wave energy conversion device. The study yielded a quantitative understanding of hydrodynamic pressures on the oscillating water column (OWC) device surfaces, the mooring tensions, and the dynamic performance of the device under extreme ocean wave conditions. This project utilized a comprehensive multi-phase Navier-Stokes flow solver with an overset body-fit mesh to predict fluid velocities and hydrodynamic forces on the MARMOK-OWC device. Computational Fluid Dynamics (CFD) analysis were conducted using OpenFOAM. This data includes the OpenFOAM cases (setup and data) to run the extreme events developed during the project. This project is part of the TEAMER RFTS 4 (request for technical support) program.
Additively manufactured heat exchangers are one possible route to cost-effective sCO 2 power cycles. In this paper, experimental results are obtained for two helical pin fin tubes that were designed following parametric optimization of the fin array. Neither the numerical optimization nor the experimental testing have been previously reported in the literature. The two tube designs were, (1) the optimization inspired design, and (2) the optimization-inspired design with a fin diameter increased by a factor of 2. To characterize the print, the designs were scanned using X-ray computed tomography to measure feature sizes and heat transfer area. The optimization was conducted in a commercial, computational fluid dynamics code. The code solved the Reynolds Averaged Navier-Stokes (RANS) and energy equations with turbulence closure provided by the shear stress transport (SST) k-ω model. In the experiments, the Nusselt number augmentation was measured using the Wilson plot technique and the friction factor was determined with mass flow and pressure drop measurements. The experimental testing indicated that the optimization-inspired design had a friction factor that was four times less than the baseline tube design at equal Nusselt number. Additionally, the optimization-inspired design had a 14% improvement in Nusselt number, at equal friction factor, relative to the best performing computational fluid dynamics (CFD) trial points. Tube design (2), with the larger diameter pin fins, had similar performance, within experimental error, as the tube with the smaller diameter pin fins (1). Both tubes achieved overall fin array efficiencies near 1. A performance factor, V/V 0 , equal to the volume of the enhanced heat exchanger divided by the volume of the baseline (no-fins) heat exchanger, is recommended to quantify internal cooling performance. In conclusion, the experimental shell and tube heat exchanger, using the additively manufactured tube, is competitive with printed circuit heat exchangers in its pressure drop class and could be further improved by optimizing a shell-and-tube heat exchanger utilizing this heat transfer enhancement feature.
The Pi convection-cloud chamber can generate steady-state turbulence in both rectangular and cylindrical shapes via Rayleigh-Bénard convection (RBC) by maintaining warm bottom and cold top surfaces. Although most experiments in the Pi chamber were conducted in cylindrical shapes, all previous Pi chamber simulations were conducted in a rectangular shape due to the limitations of those models to discretize a cylindrical domain when using the finite difference method therein. Here, we use OpenFOAM, an open-source finite-volume-based Computational Fluid Dynamics (CFD) software package, to conduct Large-Eddy Simulation (LES) of dry RBC in the Pi chamber at high Rayleigh numbers (10 8 to 10 9 ). Results show that large-scale circulation (LSC) direction varies in the chamber with a constant side wall temperature. Imposing a slight temperature imbalance at the side wall ranging from 0.1 to 0.7 degrees can lock the LSC, aligning better with Pi chamber observations, particularly at higher Rayleigh numbers. In addition, we examine the impact of surface topography on LSC and heat transfer in RBC systems within cylindrical and rectangular shapes under varying conditions. Results show that roughing top/bottom surfaces by adding bars of a few tens millimeters height can strengthen thermal plumes and enhance temperature fluctuations in the chamber. Furthermore, we observe that different bar height configurations lead to notable changes in LSC orientation and thermal stratification, highlighting the complex interactions between surface features and convection patterns. This finding highlights how surface topography and chamber geometry affect Rayleigh-Bénard convection, improving understanding of turbulent heat transfer and atmospheric boundary-layer processes. Direct Numerical Simulations (DNS) are also conducted to validate LES results. In conclusion, while LES effectively captures qualitative behaviors seen in DNS, it tends to underestimate velocity variances near walls, illustrating a trade-off between computational efficiency and accuracy.
The evaluation of aerosol exposure relies on generic mathematical models that assume uniform particle deposition profiles over the human respiratory tract and do not account for subject-specific characteristics. Here we introduce a hybrid-automated computational workflow that generates personalized particle deposition profiles in 3D reconstructed human airways from computed tomography scans using Computational Fluid and Particle Dynamics simulations. This is the first large-scale study to consider realistic airways variability, where 380 lower and 40 upper human respiratory tract 3D geometries are reconstructed and parameterized. The data is clustered into nine groups using random forest regression. Computational fluid and particle dynamics simulations are conducted on these representative geometries using a realistic heavy-breathing respiratory cycle and radioactive iodine-131 as a source term. Monte Carlo radiation transport simulations are performed to obtain detailed energy deposition maps. Our findings emphasize the importance of personalized studies, as minor respiratory tract variations notably influence deposition patterns rather than global parameters of the lower airways, observing more than 30% variance in the mass deposition fraction.
The thermal energy storage (TES) system has the capability to efficiently preserve thermal energy directly derived from the energy source, minimizing any conversion losses. Especially latent heat storage offers distinct advantages, including a substantial increase in energy storage density and minimization of temperature fluctuations within the plants. However, the phase change material (PCM) employed in latent heat storage has low thermal conductivity. Consequently, various studies are being conducted to enhance heat transfer. One approach to enhance heat transfer involves utilizing metal foam to maximize the heat transfer area. However, modeling metal foam with its intricate structure is a challenging task in numerical analysis. For this reason, ongoing research focuses on simplifying the modeling of metal foam. Nevertheless, fully encompassing all the characteristics of actual metal foam proves to be a challenging task for the simplified analytical model. The objective of this paper is to interpret the simple lattice metal foam analysis model from the perspective of behavior induced by buoyancy. When comparing the analysis results of solid PCM and liquid PCM with the same thermal conductivity under changes in porosity and gravity direction, we conducted an analysis to discern the trends in effective thermal conductivity that are overestimated due to convection. In the analysis, a constant heat flux of 10 kW and a constant surface boundary condition of 350 K were applied, and a sensitivity study regarding the mesh was conducted. The results indicate that, from the perspective of gravity in the simple lattice model, the solid analysis yields an effective thermal conductivity 29-47% higher compared to the liquid analysis. Additionally, as porosity increases, there is an observed increase of 24-33% in effective thermal conductivity.
Occupational and environmental exposure to toxic nanoparticles, driven by the rapid expansion of nanotechnology, raises significant respiratory health concern. Numerous studies have explored airflow and particle dynamics in adult nasal airways, but understanding the impact of age-related anatomical changes in children and the elderly remains limited. This study systematically investigates age-related anatomical variations and associated influence on nasal airflow dynamics and ultrafine particle deposition characteristics. Using Computational Fluid-Particle Dynamics (CFPD) method, simulation was conducted under diverse inhalation conditions spanning a wide age range, including: two children (5 years old), two young adults (in their twenties), and two elderly (over 77 years old). Our results reveal distinctive variations across age groups in anatomical dimensions, which affect distribution of wall shear stress where the elderly and children display unique patterns distinct from the young adults. While total deposition efficiency differs significantly between children and adults, filtration efficiency in the subregion with most deposition, main respiratory, remains consistent. However, inter-subject differences are observed in the vestibular and olfactory regions,emphasizing nuanced impact of age-related anatomical variations. Overall and subregional empirical equations for deposition efficiency were developed by incorporating the combined diffusion parameter, Sc a Δ b , corroborating the use of geometrical characteristic parameters for each specific subject in predicting nasal deposition efficiency across age groups. Our findings contribute to predictive nanoparticle exposure analysis in nasal airways across different age groups, thereby enhancing respiratory healthcare for individuals across the life span.
Firebrand burning is a complex phenomenon that is influenced by several parameters which are difficult to fully explore experimentally. Computational fluid dynamics models capable of predicting local quantities are essential for accurate prediction of char oxidation in firebrands. This article presents a computational fluid dynamics model to estimate firebrand mass loss, diameter change, and surface temperature during char oxidation. The model was validated using previously conducted wind tunnel experiments. These experiments were conducted for firebrands of two different aspect ratios, which were arranged in three different configurations (single, horizontal array, and vertical array), and for four different wind speeds (0.5, 1, 1.5, and 2 m/s). The computational fluid dynamics results were compared with a previous 1 D model. In all the test cases, the computational fluid dynamics model predicted the physical phenomena with significantly improved accuracy compared to a 1 D model. The char oxidation model presented in this article can be coupled with other models to study firebrand generation and trajectory, biomass pyrolysis, fluidized bed reactors, and coal combustion.
Studies have been performed on the release mechanism for large pellets using high pressure gas in a shattered pellet injector. Typically, pellets are dislodged from the cryogenic surface and accelerated down a barrel using high pressure gas delivered by a fast-acting propellant valve. The pellets impact an angled surface which shatters the pellet into many small fragments before entering the plasma. This technique was initially demonstrated on DIII-D (Commaux et al 2016 Nucl. Fusion 56 046007) and is now deployed on JET, KSTAR, ASDEX-Upgrade, and other tokamaks around the world in support of ITER's disruption mitigation system design and physics basis. The large hydrogen, 28.5 mm diameter, 2 length-to-diameter ratio, pellets foreseen for ITER SPI operation have low material strength and low heat of sublimation, which cause the pellets to be fragile and highly reactive to the impact of warm propellant gas. Due to the size of the pellets, significantly more propellant gas is required to dislodge and accelerate them. This creates a potentially significant propellant gas removal issue as 2–6 bar-L of gas is expected to be required for release and speed control. The research presented in this paper is an in-depth exploration of the parameters that are keys to reliable pellet release and speed control. Computational fluid dynamics (CFD) modeling of propellant flows through various breech designs was conducted to determine the force generated on the back surface of a pellet. These simulations assumed the use of the ORNL designed flyer plate valve. CFD modeling combined with experimental measurements provide adequate insight to determine a path to an optimal valve and breech design for ITER SPI pellet release and speed control while minimizing propellant gas usage.
One key area of interest in heat pipe modeling/simulation is to analyze the startup behavior of the liquid-metal heat pipes (LMHPs) from a frozen state. This so-called ‘frozen startup’ process involves a complex set of nonlinear mass and heat transport phenomena, including phase transitions from solid to liquid and vapor, multiphase interactions, microporous wick flow, and compressible vapor dynamics. The complexity of these processes makes it challenging to simulate LMHP’s frozen startup using conventional numerical methods or commercial computational fluid dynamics (CFD) software. This paper presents a simplified conduction-based modeling approach that can provide practical insights into the entire LMHP frozen startup process, while alleviating the challenges of modeling its complex physics. The theoretical foundation and physical assumptions of the proposed model are based solely on heat-conduction equation, allowing for a more tractable simulation without sacrificing essential physical accuracy. The proposed model was implemented in a commercial CFD software, and its prediction was compared with the experimental data obtained from sodium heat-pipe startup experiments. The comparison highlights the proposed model's ability to capture the transient thermal behavior of LMHP during frozen startup. This study not only validates the conduction-based frozen startup modeling method but also shows its potential as a practical and efficient tool for understanding the startup performance of the LMHP systems.
The novel heat exchanger (HX) designs implementing geometrical and surface modification combinations are expected to perform better than traditional HX technologies. Applied enhancement techniques seek to achieve (1) higher overall heat transfer performance, (2) increased compactness, and (3) simplified or comparable manufacturability. One innovative enhancement technique is to generate swirling flow vortices induced by channel or tube twisting. The turbulence generated by the twisted cross-section greatly enhances the heat transfer rate with minimal increases in pressure drop. Plate-type HXs and Printed Circuit Heat Exchangers (PCHXs) are compact designs that achieve high heat transfer rates per unit volume by utilizing several small channels, which maximizes the heat transfer surface area between the hot and cold fluids. Currently, advanced manufacturing technologies enable the design and fabrication of compact-type units with complicated channel geometries to achieve the highest performance and meet the compactness criteria of innovative HX technology. The proposed HX design concept combines the compactness of plate-type HXs and twisted channels, which provide additional turbulence and flow swirl enhancement. The plate-type oval-twisted HX (PTOTHX) is a crossflow configuration, with 16 short channels on one side (for hot fluid) and 8 long channels on the perpendicular side (for cold fluid). The inlet plenums have flow guide vanes to redirect flow and produce uniformity across the various flow paths. The compact size and purportedly improved heat transfer performance of the PTOTHX investigated herein prove its viability in various applications. Some notable potential nuclear applications of the PTOTHX include reactor core, spent fuel cooling, and residual heat dissipation. To establish a reference case, circular channels (PTCHX) are also considered in the present study for comparison with (PTOTHX). This paper aims to outline the numerical analysis procedures for determining the viability of the PTOTHX by comparing its heat transfer performance with the PTCHX units. The computational study used STAR-CCM+, a commercial computational fluid dynamics (CFD) code. Sensitivity analysis and model selection studies are conducted to determine the appropriate mesh density and turbulence model to provide the reported results. Numerical analyses comparing the Nusselt number (Nu) of the PTOTHX design with a comparable HX unit, including a circular cross-section and no twisting (PTCHX), show an overall heat transfer performance increase of 29-55% for balanced flow and 29-59% for imbalanced flow. Oval-cross-sectional twisted channels induce swirling flow vortices, enhancing the working fluid's convective heat transfer capabilities.
The activities of verification, validation, and uncertainty quantification (VVUQ) provide a comprehensive means to assess the credibility of computational models. Within VVUQ, solution verification assesses numerical errors and evaluates whether the simulation is sufficiently accurate for its intended applications. As computational modeling gains traction in the development of complex, high-consequence systems, the need for robust solution verification intensifies, particularly because experimental data for these systems are often limited. This work examines improvements in the robustness of Richardson extrapolation (RE), a method commonly used in solution verification to study the discretization error of computational models using a power law. Nonuniform mesh refinement is discussed alongside other pollutants that affect the robustness of the power law model. Maximum likelihood estimation (MLE) is proposed as a robust strategy to address the uncertainty generated by nonuniform mesh refinement. An exploratory computational fluid dynamics (CFD) study of a 2D planar Poiseuille flow is conducted to determine if nonuniform mesh noise can be modeled with this MLE approach for more robust RE.
The Spallation Neutron Source (SNS) is a high-power accelerator-based pulsed neutron source led by Oak Ridge National Laboratory (ORNL) to achieve high fluxes of neutrons for scientific experiments. Active and passive cooling of the systems and parts forming the SNS have been considered to warrant the safe operation of the facility. The diverse cooling systems make use of conjugated heat transfer mechanisms to provide a stable operation temperature for all components in the machine. Thermal power deposited into stainless-steel piping lines due to particle radiation may reach values of up to 1.2 W/cc in the regions located closer to the center of the lower IRP. These energy deposition levels, in not actively cooled components, such as the transfer-line-outer-vacuum-layer may increase the temperature of the component beyond design requirement limitations. The evaluation of the operation temperatures for the former components relies in the assumption that a low-pressure helium atmosphere provides enough heat removal capacity based on natural convection phenomena. In this work, the evaluation of steady state temperatures in components such as the CMS transfer lines has been evaluated using computational fluid dynamics (CFD), analytical correlations and experimental measurements. The companion experiments were conducted in a closed helium system at pressures varying from 1.1 to 1.5 bar. A copper rod was affixed horizontally between viewing windows and heated at constant power, and measurements were made of both the rod temperature and ambient temperature via a system fiberoptic distributed temperature sensors and RTDs. It was found that the measured heat transfer coefficients agree well with the predictions of Churchill and Chu correlations across the range of cases considered. Additionally, the ambient helium volume above the rod was imaged via background oriented schlieren (BOS), and these data was used to determine the line-averaged density gradients in this region. These gradients were compared to simulation data to validate the predictions of natural convection simulations.
Rapid growth in artificial intelligence and data center workloads demands high-performance liquid cooling to manage increasing chip power. This study presents two metal-additive-manufactured cold plates with sinusoidal fins, constant-amplitude wavy fins and linearly variable-amplitude wavy fins and compares them against metal-additive-manufactured straight fins using experiments conducted at 1 kW heat dissipation as well as high-fidelity 3D conjugate computational fluid dynamic simulations. The cold plates were printed in AlSi10Mg material and underwent design using a Python-automated workflow prior to manufacture and testing. The experiments show that wavy fins reduce the normalized thermal resistance by 35 to 45 % at water flow rates from 1 to 4 LPM. At a fixed 20 kPa pressure drop, the variable-waviness design lowered peak surface temperature by 9 °C and thermal resistance by 51 %, while edge-channel maldistribution in the constant wavy fin design limited gains. A thermal resistance breakdown revealed that 55–63 % of the total thermal resistance in wavy designs comes from base heat conduction, 27–33 % from fin heat conduction, and 9–13 % from fin heat convection, indicating the need to address conduction bottlenecks. Parametric sweeps identify a 3 mm fin pitch as optimal, and that horizontal inlet/outlet manifolds further reduce pressure drop by 30–60 % and thermal resistance by 9–16 % relative to vertical inlet-outlet manifolds. The results yield comprehensive guidelines for fin geometry, manifold alignment, material selection and additive-manufacturing constraints to realize high-performance liquid-cooled cold plates for power-dense electronics.
The report showcases advancements in modeling heat pipes, considering both scenarios with and without non-condensable gases. To achieve this, two distinct modeling approaches are juxtaposed. Firstly, the effective conduction model, implemented in the MOOSE-based code Sockeye, is employed. Secondly, a first-of-a-kind two-phase Euler-Euler Computational Fluid Dynamics (CFD) model is developed using the STAR-CCM+ code. Both models undergo validation against experimental data, acknowledging the inherent uncertainties associated with each modeling assumption. Interestingly, the non-tuned CFD model surpasses the performance of the calibrated conduction model for heat pipes operating under both conditions: with and without non-condensable gases. It's worth noting, however, that the CFD models entail significantly longer runtimes compared to the conduction models. Nevertheless, the insights garnered from the CFD model shed invaluable light on the intricate operational dynamics of heat pipes. Future work involves broadening the validation scope of these models and continuing their development to enhance their utility as robust tools for heat pipe design and operational support.
Ionic liquids have many intriguing properties and widespread applications such as separations and energy storage. However, ionic liquids are complex fluids and predicting their behavior is difficult, particularly in confined environments. We introduce fast and computationally efficient machine learning (ML) models that can predict diffusion coefficients and ionic conductivity of bulk and nanoconfined ionic liquids over a wide temperature range (350–500 K). The ML models are trained on molecular dynamics simulation data for 29 unique ionic liquids as bulk fluids and confined in graphite slit pores. This model is based on simple physical descriptors of the cations and anions such as molecular weight and surface area. Here, we also demonstrate that accurate results can be obtained using only descriptors derived from SMILES (simplified molecular-input line-entry system) codes for the ions with minimal computational effort. This offers a fast and efficient method for estimating diffusion and conductivity of nanoconfined ionic liquids at various temperatures without the need for expensive molecular dynamics simulations.
This study investigates the expansion dynamics of femtosecond laser-induced plasmas, emphasizing the impact of plasma thermophysical properties and ambient gas composition. Through shadowgraphy experiments and multiphase computational fluid dynamics (CFD) simulations, the influence of parameters such as heat capacity, molecular weight, and thermal conductivity on plume morphology, shockwave evolution, and energy dissipation mechanisms is examined. A mixture multiphase model is implemented to capture the interaction between the plasma and the surrounding gas. Simulation results reveal that plasma expansion is strongly inertia-driven. Results show that differences in plasma properties and ambient conditions affect the shape and temperature distribution of the expanding plume. The early-stage dynamics are primarily dictated by pressure forces, whereas thermal and viscous effects play a growing role in the plume's behavior during later stages of expansion. The CFD findings show the necessity of accurate initial condition characterization, including crater geometry and plasma pressure and temperature, for reliable modeling of plasma evolution in laser ablation processes.