computational fluid dynamics (CFD) simulations are broadly used in many engineering and physics fields. CFD requires the solution of the Navier-Stokes (N-S) equations under complex flow and boundary conditions. Howeve...
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computational fluid dynamics (CFD) simulations are broadly used in many engineering and physics fields. CFD requires the solution of the Navier-Stokes (N-S) equations under complex flow and boundary conditions. However, applications of CFD simulations are computationally limited by the availability, speed, and parallelism of high-performance computing. To address this, machine learning techniques have been employed to create data-driven approximations for CFD to accelerate computational efficiency. Unfortunately, these methods predominantly depend on large labeled CFD datasets, which are costly to procure at the scale required for robust model development. In response, we introduce a weakly supervised approach that, through a multichannel input capturing boundary and geometric conditions, solves steady-state N-S equations. Our method achieves state-of-the-art results without relying on labeled simulation data, instead using a custom data-driven and physics-informed loss function and small-scale solutions to prime the model for solving the N-S equations. By training stacked models, we enhance resolution and predictability, yielding high-quality numerical solutions to N-S equations without hefty computational demands. Remarkably, our model, being highly adaptable, produces solutions on a 512 x 512 domain in a swift 7 ms, outpacing traditional CFD solvers by a factor of 1,000. This paves the way for real-time predictions on consumer hardware and Internet of Things devices, thereby boosting the scope, speed, and cost-efficiency of solving boundary-value fluid problems.
Optimizing the form and parameters of ventilation systems is crucial for enhancing the microenvironment around individuals, with a primary focus on human comfort in ventilation design. Additionally, controlling exposu...
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Optimizing the form and parameters of ventilation systems is crucial for enhancing the microenvironment around individuals, with a primary focus on human comfort in ventilation design. Additionally, controlling exposure concentrations of respiratory droplets is an essential strategy for dealing with respiratory infections. Therefore, a thorough examination of the relationship between the form and parameters of ventilation systems, human comfort, and the dispersion of droplets becomes particularly significant. This study utilizes computational fluid dynamics (CFD) to optimize ventilation systems, focusing on enhancing individual comfort and reducing droplet dispersion in indoor environments, particularly in cruise cabins where the microenvironment significantly impacts passenger well-being. It evaluates three ventilation systems: orifice plate ventilation system (OPVS), ceiling mixed ventilation system (CMVS), and sidewall mixed ventilation system (SMVS). Employing the Entropy-weighted TOPSIS method, it optimizes ventilation temperature and relative humidity across 20 combinations to achieve optimal thermal comfort and airflow uniformity. The findings indicate that OPVS offers the best thermal comfort and uniform airflow, with an ideal configuration at 21 degrees C and 60% relative humidity. It also investigates the placement of air purifiers under the optimal ventilation configuration (OPVS), revealing that positioning them near the breathing zone reduces droplet concentrations by 42.6%, while central placement achieves a reduction of 40.1%. This suggests central air purifier placement for practical applications, balancing droplet concentration reduction with minimal occupant disturbance. This work contributes to understanding ventilation strategies for managing respiratory diseases and ensuring indoor comfort.
Porous membranes separate two microfluidic channels comprising organ-on-a-chip systems, enabling interaction between cells cultured in both channels. Although it is evident that the material and structural characteris...
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Porous membranes separate two microfluidic channels comprising organ-on-a-chip systems, enabling interaction between cells cultured in both channels. Although it is evident that the material and structural characteristics of porous membranes affect the microfluidic environment in organ-on-a-chip systems, porous membranes have not been studied extensively. Here, we examine the influence of structural parameters of porous membranes on the microenvironment within an organ-on-a-chip system using computational fluid dynamics. Our findings highlight the necessity of a comprehensive consideration of pore diameter and pore density to design an optimal porous membrane that simultaneously enhances solute permeability and deformation. This research suggests the potential for a more accurate design of physiological conditions in organ-on-a-chip systems by precisely adjusting the structural parameters of porous membranes.
Hydrolysis is a key process in the biorefining of biomass into chemicals and materials necessary for a sustainable and circular economy. Currently, significant technical and economic challenges exist, limiting its com...
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Hydrolysis is a key process in the biorefining of biomass into chemicals and materials necessary for a sustainable and circular economy. Currently, significant technical and economic challenges exist, limiting its commercial viability. However, process improvement and scale-up can be costly and time-consuming due to non-Newtonian rheology and high solid loading of biomass slurries, which change over time as the hydrolysis reaction progresses, leading to complex mixing and mass/heat transfer behaviors. Computation fluiddynamics (CFD) has the potential to be a powerful tool for improving biomass hydrolysis. By utilizing experimental rheological data, a digital twin of the biomass slurry-reactor system could be simulated, thereby allowing for the impact of varying different reactor designs and operational parameters to be assessed at reduced time and costs. The number of studies utilizing CFD for biomass hydrolysis modeling has been rapidly growing in the past decade. Although many still utilize single-phase steady-state simulations, more recent studies have applied increasingly complex models, including transient and multiphase conditions, even enzyme kinetic model coupling. Elucidation of the impact from reactor design, geometry, and operational parameters on key process success factors such as mixing homogeneity, power consumption, and productivity has been greatly enhanced by CFD. Nevertheless, this area of study is still in a nascent stage, with potential for future work to improve upon feedstock variety, model complexity, studied parameters, and the use of extracted results. Further development of biomass hydrolysis CFD will enable better commercialization of future biorefining and industrial biotechnological endeavors.
Consideration has been given to the current status of research on the development of kinetic models of combustion of kerosene and its components. Surrogate models of kerosene have been analyzed that describe the physi...
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Consideration has been given to the current status of research on the development of kinetic models of combustion of kerosene and its components. Surrogate models of kerosene have been analyzed that describe the physical and chemical properties of an actual fuel and are used in developing detailed and reduced kinetic models. Experimental data have been reviewed based on which testing of the kinetic models with a varying degree of complexity is carried out. Examples of the use of kinetic models in modeling numerically processes occurring in actual power-generating units have been given.
PurposeHemodynamics play an important role in the assessment of intracranial aneurysm (IA) development and rupture risk. The purpose of this study was to examine the impact of complex vasculatures onto the intra-vesse...
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PurposeHemodynamics play an important role in the assessment of intracranial aneurysm (IA) development and rupture risk. The purpose of this study was to examine the impact of complex vasculatures onto the intra-vessel and intra-aneurysmal blood *** segmentation of a subject-specific, 60-outlet and 3-inlet circle of Willis model captured with 7T magnetic resonance imaging was performed. This model was trimmed to a 10-outlet model version. Two patient-specific IAs were added onto both models yielding two pathological versions, and image-based blood flow simulations of the four resulting cases were carried out. To capture the differences between complex and trimmed model, time-averaged and centerline velocities were compared. The assessment of intra-saccular blood flow within the IAs involved the evaluation of wall shear stresses (WSS) at the IA wall and neck inflow rates (NIR).ResultsLower flow values are observed in the majority of the complex model. However, at specific locations (left middle cerebral artery 0.5 m/s, left posterior cerebral artery 0.25 m/s), higher flow rates were visible when compared to the trimmed counterpart. Furthermore, at the centerlines the total velocity values reveal differences up to 0.15 m/s. In the IAs, the reduction in the neck inflow rate and WSS in the complex model was observed for the first IA (IA-A delta NIRmean = - 0.07ml/s, PCA.l delta WSSmean = - 0.05 Pa). The second IA featured an increase in the neck inflow rate and WSS (IA-B delta NIRmean = 0.04 ml/s, PCA.l delta WSSmean = 0.07 Pa).ConclusionBoth the magnitude and shape of the flow distribution vary depending on the model's complexity. The magnitude is primarily influenced by the global vessel model, while the shape is determined by the local structure. Furthermore, intra-aneurysmal flow strongly depends on the location in the vessel tree, emphasizing the need for complex model geometries for realistic hemodynamic assessment and rupture risk analysis.
The design of the hot end plays a critical role in additive manufacturing, especially in material extrusion. Yet the melt flow behavior within the hot end assembly has not been explicitly presented regarding the hot e...
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The design of the hot end plays a critical role in additive manufacturing, especially in material extrusion. Yet the melt flow behavior within the hot end assembly has not been explicitly presented regarding the hot end design. The present study intends to fill this knowledge gap by employing a two-phase approach to investigate the melt dynamics through three commercially available hot ends. The hot ends considered are E3D v6 Standard, v6 Gold, and Revo Six, which were chosen based on brand, design, and functionality. In Phase 1, an experimental apparatus was developed to assess the impact of feeding rate and extrusion temperature on the outlet temperature, outlet velocity, and under-extrusion percentage of extruded polymer. In Phase 2, the polymer flow through each hot end is explored utilizing a computational fluid dynamics model, which was validated using data obtained in Phase 1. It was determined that the filament feeding rate is the most influential parameter in polymer extrusion and that Revo Six's symmetrical design affects the stability of extrusion. It was also revealed that the thermal evolution of the melted filament within the hot end assembly is directly affected by the length of the heating region and the polymer's material properties. The experimental and numerical procedures developed in this investigation can be useful to 3D printing users and manufacturers in selecting a hot end assembly based on application requirements. The role of hot ends on 3-D printing performance were investigated using three commercially available hot ends through a combined numerical and experimental investigation. Hot end's heating length and polymer's properties will determine thermal evolution of the melted filament within the hot end assembly The feed rate strongly impacts the melt front location in hot ends.
The core-catcher is one of the proposed severe accident mitigation facilities designed to protect containment buildings from molten core material during a severe accident. The molten core material relocated to the cor...
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The core-catcher is one of the proposed severe accident mitigation facilities designed to protect containment buildings from molten core material during a severe accident. The molten core material relocated to the core-catcher is cooled through natural circulation of the injected coolant. Understanding the flow characteristics here, affected by the core-catcher geometry, uneven thermal loads, and two-phase flow across the cooling channel of the core-catcher, is crucial owing to potential oscillating flow patterns and localized cooling deficiency issues. In this study, the influence of core-catcher geometry, particularly various separation barrier shapes at the end of the longer side of the core-catcher, on flow patterns was investigated through numerical simulation. The results confirmed that the flow pattern in the cooling channel varied significantly depending on the geometry of the separation barrier, leading to variations in the cooling performance. , 2024 The Korean Society of Mechanical Engineers.
Background: With the rapid consumption of non-renewable energy such as coal, oil and natural gas, the growing demand for environmental protection, the re-utilization of low-grade waste heat energy has become an import...
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作者：
Wang, ZekunEdgecombe, Gregory D.Hou, Jin-boNat Hist Museum
London SW7 5BD England Yunnan Univ
MEC Int Joint Lab Palaeobiol & Palaeoenvironment 2 North Cuihu Rd Kunming 650091 Peoples R China Nanjing Univ
Sch Earth Sci & Engn State Key Lab Mineral Deposits Res Nanjing 210023 Peoples R China Nanjing Univ
Frontiers Sci Ctr Crit Earth Mat Cycling Nanjing 210023 Peoples R China
Trilobites are one of the most important invertebrate clades in the Palaeozoic, with significant disparity in morphology and behaviour, the latter including intriguing instances of queueing. Previous studies employed ...
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Trilobites are one of the most important invertebrate clades in the Palaeozoic, with significant disparity in morphology and behaviour, the latter including intriguing instances of queueing. Previous studies employed computational fluid dynamics (CFD) to investigate queuing behaviour in the Devonian trilobite Trimerocephalus chopini and found drag reduction effects. Novel calculations that define a ratio between drag force and Apparent Gravity (W), along with the Submerged Froude Number (Fr-sub), however, reveal that the obtained drag force was practically negligible in terms of the underwater mobility of trilobites. A trilobite would start to experience difficulty in forward walking only when the relative flow speed was over 42 cm/s, which is inconsistent with the interpreted palaeoenvironment or the predicted moving speed of trilobites. Nevertheless, according to the proposed cantilever model, a trilobite had the ability to sense very minute change in fluid velocity (>7.16 mu m/s). High-sensitivity mechanical sensors distributed along the body, either on the exoskeleton or limbs, empowered queuing individuals to discern the fixed self-similar pattern of the wake generated by their predecessors in the queue. In general, if a trilobite were out of the wake, the asymmetrical velocity and pressure field would aid in repositioning itself, facilitating the maintenance of migratory queues. This permitted blind trilobites to securely sense their companions, compensating for lack of long-range visual capability. This paradigm of force assessment is suitable to computationalfluid Dynamic analyses in other extinct animal-environment interactions, offering a framework to evaluate whether drags and wakes impact more on organism's mobility (W >> 0.1,Fr-sub >> 1) or their mechanical sensors, and provides a unique cross-scale insight into animals' adaptation to palaeohydrodynamic variation.
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