Typical Flow Research Articles

Sub-core permeability estimation from coreflooding experiments: Numerical analysis for evaluating accuracy and improving methods

Coreflooding experiments are one of the primary methods for reservoir rock characterization and have been developing in recent years, providing increasing detail. An advanced analysis of coreflooding experiments consists of constructing three dimensional permeability (k) maps of the core sample with sub-core resolution. Such detailed characterizations provide important information on the core heterogeneity and enable the construction of accurate numerical flow models that can reproduce experimental results. This work presents a method for estimating k, combining data from multiple coreflooding experiments, and studies the estimation accuracy considering a large number of test cases consisting of synthetic data obtained by numerical experiments. Cases include varying parameters, such as: fluid injection flow rates and types, relative permeability curves, capillary pressure functions and core heterogeneity. The new method is shown to significantly improve the estimation accuracy in comparison to methods that incorporate data only from a single experiment. Furthermore, a method for improving k estimations in regions where water is trapped is presented and its implementation is shown to increase the overall accuracy of k estimation. An additional method is considered, that requires only single-phase flow solutions, thus increasing the computational efficiency. However, it is shown to be applicable only for a small subset of cases.

Botnet Attack Identification and Mitigation condition Software-Defined Networks Utilizing CNN Algorithm

One new design that makes managing and communicating across large-scale networks easier and more flexible is software-defined networking, or SDN. It allows for the smooth and dynamic execution of complicated network choices via programmable and centralized interfaces. But SDN opens doors for people and companies to tailor network apps to their needs, allowing them to enhance services. On the other hand, it began to encounter a host of new privacy and security issues and brought the dangers of one point of failure all at once. In most cases, hackers use OpenFlow switches to conduct botnets or distributed Denial of Service (DDoS) assaults against the controller. Popular security apps that use deep learning (DL) to quickly identify and counteract attacks are on the rise. Here, we examine botnet-based DDoS attack detection using DL approaches in an SDN-supported context and demonstrate their performance. For the assessment, we utilize a dataset that we just created ourselves. In order to choose the most useful subset of characteristics, we used weighting of features and tuning techniques. Using both a synthetic dataset and actual testbed conditions, we validate the measurements or simulation results. The primary objective of this research is to identify botnet-based DDoS assaults using easily-obtained characteristics and data using a lightweight DL approach with baseline hyper-parameters. We found that the DL technique's performance is affected by the optimal subset of features, and that the accuracy of predictions of the same approach may be varied with a different collection of features. Lastly, our empirical findings show that the CNN approach works better than both the dataset and the actual testbed environments. With CNN, the detection rate for typical flows is 99% and for malicious flows it drops to 97%.

Platoon control and external human–machine interfaces: innovations in pedestrian–autonomous vehicle interactions

At uncontrolled mid-block crosswalks, autonomous vehicles (AVs) are legally and safely obligated to yield to pedestrians, potentially exacerbating traffic congestion. This study explores integrating AV platoon control with eHMIs to examine its long-term potential for enhancing traffic flow safety and efficiency. A novel agent-based pedestrian-vehicle interaction framework is developed to evaluate the proposed strategy, accurately reproducing the heterogeneous behaviors of pedestrians and vehicles, such as pedestrians' risk tolerance, their responses to eHMIs, and vehicles' yielding mechanisms. Additionally, a platoon formation module is proposed to achieve the desired speed and inter-vehicular spacings from arbitrary initial condition. Simulation results indicate that implementing the proposed strategy reduced the conflict rate by 10%, increased the yielding rate by 11%, and decreased aggregate delay by 34.6% in typical flow conditions. The sensitivity analysis reveals that the effectiveness of the proposed strategy in improving traffic safety and efficiency increases with higher pedestrian and vehicle flow rates.

Study on the influence of typical turbulent flow field on the metering performance of cross four channel ultrasonic flowmeter

Abstract In this paper, influence of typical turbulent flow field on a multi-channel ultrasonic flowmeter was studied. Experimental sample of the cross four-channel ultrasonic flowmeter were designed and processed, and CFD simulation models of flowmeter and right-handed spoiler, gate valve and velocity profile spoiler were established. Through simulation, the turbulent flow field behind typical spoilers such as right-handed spoiler, gate valve and velocity profile spoiler, and the influence of turbulent flow field on the metering performance of the cross four-channel ultrasonic flowmeter were studied. On this basis, the CFD simulation results and the real flow experiment results were compared and analyzed, and the reliability of the CFD simulation analysis results was verified, which provides the research basis for improving flowmeter performance.

Hysteresis in strongly magnetized N2 discharges

A semi-empirical global model for a nitrogen discharge in a strong magnetic field is developed. The model is based upon experimental data from high-resolution Doppler and extreme-ultraviolet vacuum spectroscopy, which establish the plasma composition, discharge parameters, and, most importantly, electronic transitions. This allows the number of required molecular systems and atomic/ionic states to be reduced, thereby retaining only the essential plasma chemistry reactions. The set of 35 stiff non-linear ordinary differential equations is numerically integrated using an unconditionally stable adaptive method. Simulations show the existence of two solution branches with low and high electron temperature, respectively. A distinct hysteresis is exhibited by the discharge and illustrated for three typical N2 mass flow rates. The dependencies of the plasma parameters on the applied power are presented and discussed in detail, including in the vicinity of the bifurcation points. The efficiency of operation in the opposing limits of N2 discharge behavior as either a source of plasma or light emission is examined, with special emphasis on electric propulsion capabilities.

Validation of MOOSE’s subchannel module using the AREVA FCTF heated bundle benchmark

The SubChannel Module, referred to as SCM henceforward in this document, is a subchannel code within the Multiphysics Object-Oriented Simulation Environment (MOOSE) developed at the Idaho National Laboratory (INL). SCM, is able to model flow through liquid-metal cooled, wire-wrapped fuel pin sub-assemblies, ordered in a triangular lattice. This work extends the existing validation done for these flow types and geometries and introduces validation for the newly implemented capability to model flows within a deformed duct. The subchannel duct deformation modeling approach consisted of reproducing the deformed duct effect on the geometric parameters of the boundary subchannels, i.e., modifying surface area, wetted perimeter and pin to duct gap. Then, the model was validated using experimental data taken from Areva’s fuel cooling test facility (FCTF).

Uncertainties in measurements of bubbly flows using phase-detection probes

The analysis of bubbly two-phase flows is challenging due to their turbulent nature and the need for intrusive phase-detection probes. However, accurately characterizing these flows is crucial for safely designing critical infrastructure such as dams and their appurtenant structures. The combination of dual-tip intrusive phase-detection probes with advanced signal processing algorithms enables the assessment of pseudo-instantaneous 1-D velocity time series; for which the limitations are not fully fathomed. In this investigation, we theoretically define four major sources of error, which we quantify using synthetically generated turbulent time series, coupled with the simulated response of a phase-detection probe. Based on the analysis of 1010 simulated bubble trajectories, our findings show that typical high-velocity flows in hydraulic structures hold up to 15% error in the mean velocity estimations and up to 35% error in the turbulence intensity estimations for the most critical conditions, typically occurring in the proximity of the wall. Based on thousands of simulations, our study provides a novel data-driven tool for the estimation of these baseline errors (bias and uncertainties) in real-word phase-detection probe measurements of bubbly flows (air concentrations c<40%).

Enhancement of effluent degradation by zinc oxide, carbon nitride, and carbon xerogel trifecta on brass monoliths.

In recent years, heterogeneous photocatalysis has emerged as a promising alternative for the treatment of organic pollutants. This technique offers several advantages, such as low cost and ease of operation. However, finding a semiconductor material that is both operationally viable and highly active under solar irradiation remains a challenge, often requiring materials of nanometric size. Furthermore, in many processes, photocatalysts are suspended in the solution, requiring additional steps to remove them. This can render the technique economically unviable, especially for nanosized catalysts. This work demonstrated the feasibility of using a structured photocatalyst (ZnO, g-C3N4, and carbon xerogel) optimized for this photodegradation process. The synthesized materials were characterized by nitrogen adsorption and desorption, X-ray diffraction (XRD), and diffuse reflectance spectroscopy (DRS). Adhesion testing demonstrated the efficiency of the deposition technique, with film adhesion exceeding 90%. The photocatalytic evaluation was performed using a mixture of three textile dyes in a recycle photoreactor, varying pH (4.7 and 10), recycle flow rate (2, 4, and 6 L h-1), immobilized mass (1, 2, and 3mgcm-2), monolith height (1.5, 3.0, and 4.5cm), and type of radiation (solar and visible artificials; and natural solar). The structured photocatalyst degraded over 99% of the dye mixture under artificial radiation. The solar energy results are highly promising, achieving a degradation efficiency of approximately 74%. Furthermore, it was possible to regenerate the structured photocatalyst up to seven consecutive times using exclusively natural solar light and maintain a degradation rate of around 70%. These results reinforce the feasibility and potential application of this system in photocatalytic reactions, highlighting its effectiveness and sustainability.

Transition of the flow type in the supersonic cavity controlled by the wall temperature

The wall temperature of the high-speed aircraft increases quickly under hypersonic/supersonic incoming flow, which will cause a significant change in the flow structure. To study the transition of the flow type in the supersonic cavity controlled by the wall temperature, numerical simulations are conducted. The cavity length-to-depth ratio (L/D) is varied from 10 to 15, and the wall temperature ranges from 300 K to 1300 K. The results indicate that the type of cavity flow with an L/D ratio of 13 transforms from a closed cavity flow to a transitional cavity flow, when the temperature reaches approximately 775 K. And the transitional temperature rises with the elevated total temperature of the incoming flow. Furthermore, the mechanism of the cavity flow change with wall temperature could be the competition between the recirculation zone and the shear layer in the cavity. The rising pressure with higher wall temperature in the recirculation zone weakens the downward development of the cavity shear layer, preventing it from hitting the cavity floor. As a result, the mass exchange of cavity lip surface, pressure distribution, total pressure recovery coefficient, and heat transfer distribution in the supersonic cavity change dramatically. The critical wall temperature also affected by the sidewall effects and the inflow Mach number.

Exploring the conflict risk characteristics of air weaving sections in Metroplex terminal areas with flight trajectory data and adaptive graph spatial-temporal transformer

Metroplex terminal areas is involved with numerous air weaving sections, where various types of arrival and departure traffic flows intersect or converge, leading to high-risk aircraft conflicts and inefficient Metroplex operation. The primary objective of this study is to explore the conflict risk characteristics of operational interactions between airports in Metroplex terminal areas with large-scale trajectory data, including risk evaluation, risk propagation and risk prediction. One complete month of ADS-B trajectory data is collected from a representative multi-airport system in Central and South China to illustrate the procedure. Specifically, flight trajectories are firstly clustered within Metroplex terminal areas, and a trajectory-tube model is then built to characterize the airport flows within the same cluster. Then, a clustering-based collision probability calculation method is proposed to evaluate the risk of air weaving sections. The spatial patterns of risks in air weaving sections reveal that operational interactions among Metroplex airports are quite different under various runway configurations. Furthermore, an adaptive graph spatial-temporal transformer (ASTT) network is developed to predict the future risk of each air weaving section in Metroplex terminal areas. The results indicate that the developed ASTT network can collaboratively encode the spatiotemporal characteristics in the air weaving section risk data, which achieves more accurate and robust prediction performance than other compared models during multiple look-ahead time steps. Moreover, the adaptive spatial graph technique designed in the ASTT can also reveal the hidden risk propagation effects among air weaving sections. The results of this study could provide insightful suggestions to air traffic authorities for developing effective coordination and conflict mitigation strategies, such as redesigning flight procedures, reallocating routes, and optimizing aircraft sequences to enhance the efficiency and safety of Metroplex operations.

Kinetic model implementation in raceway pond reactors with hydrodynamic and radiation fields

Vertical mixing plays a critical role in solar-driven processes using raceway pond reactors (RPRs). However, incorporating the time history of radiation for each fluid element is still an open issue. This work aims to develop an effective methodology using Computational Fluid Dynamics (CFD) tools that couples hydrodynamics and radiation fields into kinetic models of biomass growth or cell lysis enhanced from radiation. First, three methodologies to assess vertical mixing were investigated. It was found that, under typical RPR flow conditions, the velocity in the direction of solar light incidence can maintain particles in constant motion and a near-homogenous particle distribution. In addition, two RPR applications were studied regarding radiation influence analysis: the production of microalgae and an innovative approach for waste activated sludge (WAS) pre-treatment, fostering biogas production. Regarding microalgae production, coupling the biokinetic models with CFD data enables the development of a cost-effective computational methodology to describe the growth of microalgae cultures accounting for hydrodynamics and radiation fields. This work was successful in introducing hydrodynamics and radiation conditions in models to design and optimise RPRs. Reduced geometries based in 2D and Periodic Boundary Conditions were used for CFD simulations to make it feasible for RPRs design purposes.

Prediction of the flow behaviour of AISI 321 austenitic stainless steel during dynamic recovery using sine hyperbolic constitutive equation and artificial neural network

ABSTRACT In the present investigation, AISI 321 austenitic stainless steel was subjected to hot compression deformation at temperatures of 800, 850, and 900°C and strain rates in the range of 0.001-1 s-1. Results showed that in all the predefined conditions, the microstructure of the samples consisted of elongated austenite grains which indicates the occurrence of dynamic recovery. Furthermore, the hot flow curves obtained at this temperature range showed a trend similar to the dynamic recovery flow type behavior. In these curves, the flow stress increased with increasing applied strain and then tended to a constant value. The saturation stress at 800˚C increases from about 200 to 280 MPa with increasing strain rate from 0.001 to 1 s-1. For the same strain rate changes, the saturation stress increases from 150 to 240 MPa, and 90 to 200 MPa, at deformation temperature of 850 and 900˚C, respectively. The flow curves obtained from the hot compression tests were modelled using the sine hyperbolic constitutive equation and alternatively an artificial neural network. The results showed that the artificial neural network better predicts the flow behavior of AISI 321 austenitic stainless steel during dynamic recovery compared to the sine hyperbolic constitutive equation.

Comparative study of multidirectional pedestrian flows: Insights and dynamics

This study investigates multidirectional pedestrian flow by examining walking characteristics and behavioral factors impacting pedestrian dynamics. Parameters such as mean walking velocities, distance covered, and time taken by pedestrians were analyzed. Contrary to the expected inverse relationship between velocity and density, our findings revealed an increase in mean velocities in certain scenarios, attributed to conditions where the pedestrian density had not reached its maximum possible level and unpredicted pedestrian behaviors. Comparative analysis revealed that both Pakistani and Chinese pedestrians walk at nearly similar speeds. For instance, Pakistani pedestrians maintain a mean velocity of 1.36 ± 0.42 m/s at a density of 0.48 ped/m², while Chinese pedestrians maintain 1.27 ± 0.23 m/s at a density of 0.41 ped/m². Behavioral characteristics such as aggressive behavior, crowd avoidance, and waiting behavior were identified, with aggressive pedestrians exhibiting higher velocities than those avoiding crowds. A space-time diagram was utilized to categorize pedestrian flow types and behaviors, demonstrating increased stopping times with higher pedestrian numbers. Cultural factors, including side preferences, were analyzed using a binomial test, which returned a p-value of 0.968, indicating no significant preference for right-hand movement among Pakistani participants. These insights enhance the understanding of pedestrian dynamics and the influence of cultural norms on movement efficiency.

Mannosylated PAMAM G2 dendrimers mediated rate programmed delivery of efavirenz target HIV viral latency at reservoirs

In this current research, we conceptualized a novel nanotechnology-enabled synthesis approach of targeting HIV-harboring tissues via second-generation (G2) polyamidoamine (PAMAM) mannosylated (MPG2) dendrimers for programmed delivery of anti-HIV drugs efavirenz (EFV) and ritonavir (RTV). Briefly, here mannose served purpose of ligand in this EFV and RTV-loaded PAMAM G2 dendrimers, synthesized by divergent techniques, denoted as MPG2ER. The developed nanocarriers were characterized by different analytical tools FTIR, NMR, zeta potential, particle size, and surface morphology. The results of confocal microscopy showed substantial alterations in the morphology of H9 cells, favored by relatively higher drug uptake through the MPG2ER. Interestingly, the drug uptake study and cytotoxicity assay of MPG2ER demonstrated that it showed no significant toxicity up to 12.5 µM. A typical flow cytometry histogram also revealed that MPG2ER efficiently internalized both drugs, with an increase in drug uptake of up to 81.2 %. It also enhanced the plasma pharmacokinetics of EFV, with Cmax7.68 μg/ml, AUC of 149.19 (μg/ml) * hr, and MRT of 26.87 hrs. Subsequently, tissue pharmacokinetics further evidence that MPG2ER accumulated more in distant Human immunodeficiency virus (HIV) reservoir tissues, such as the lymph nodes and spleen, but without exhibiting significant toxicity. Abovementioned compelling evidences strongly favored translational roles of MPG2 as a potential therapeutic strategy in the clinical eradication of HIV from viral reservoir tissue.

Identification of organic constituents on atmospheric particulate matter in the East Asian background air of free troposphere by GC×GC-TOFMS

The presence of organic compounds on the particulate matter (PM) or aerosols can arise from the condensation of gaseous organic compounds on the existing aerosols, or from organic precursors to form secondary organic aerosols (SOA) through photochemistry. The objective of this study is to characterize organic constituents on aerosols relevant to their emission sources and the key compounds revealing the evolution of aerosols with the use of a novel analytical technique. A time-of-flight mass spectrometry (TOFMS) coupled with comprehensive two-dimensional gas chromatography (GC×GC) was developed using a flow type of modulator instead of a thermal type as a prelude to field applications without the need for cryogen. The methodology of GC×GC-TOFMS is discussed in this study in detail.Since the coarse PM (PM10-2.5) may exhibit with a relatively high OC content compared to PM2.5, the GC×GC results have been obtained by analyzing PM10 samples collected in parallel with OC/EC analysis of PM2.5 samples at the Lulin Atmospheric Background Station (LABS, 23.47°N, 120.87°E, 2862 m ASL) as the high-mountain background site in East Asia. We found that the organic analytes were in a majority in the range of 12–30 carbon numbers falling in the category of semi-volatile organic compounds (SVOCs) with 43 compounds of alcohol, aldehyde, ketone, and ester varieties if excluding alkanes. Intriguingly, trace amounts of plasticizers and phosphorus flame retardants such as phthalates (PAEs) and triphenyl phosphate (TPP) were also found, likely originating from regions involved in open burning of household solid waste in Southeast Asia or e-waste recycling in southern China and along the long-range transport route. Compounds such as these are unique to the specific sources, demonstrating the wide spread of these hazardous compounds in the environment.

Syn and post-glacial volcanic activity in the western retroarc area of the andean southern volcanic zone: Overo volcano

Located in a poorly studied zone of the rear arc in the Transitional Southern Volcanic Zone, the Overo volcano presents a complete record of syn-glacial, inter-glacial, and post-glacial activity, marked by significant changes in eruptive mechanisms over time. Following pre-glacial units, an effusive syn-glacial basaltic phase was succeeded by an extensive inter-glacial diking that fed andesitic monogenetic fields. Subsequently, an eruptive pulse, possibly coupled with the destabilization of the main edifice, resulted in a block and ash deposit channeled into a glacial valley towards the southwest, later covered by extensive basaltic lava flows. Then, different types of pyroclastic flows and glacial deposits covered these earlier units. Finally, these younger glacial deposits were overlain by a localized postglacial pyroclastic deposit and widespread lava flows, which ultimately reconstructed the deeply eroded glacial morphology of the Overo volcano. This volcanic record reveals the young and complex activity of this poorly known western rear-arc volcanic center in the Transitional Southern Volcanic Zone of the Andes, whose evolution is more akin to the arc front volcanoes to the west than to their eastern within-plate counterparts. We propose that this magmatic evolution was influenced by the Pleistocene-Holocene Last Glacial Maximum activity (LGM), beginning with an initial phase of volcanic activity encapsulated within glacial conditions. Glacial retreat then triggered isostatic uplift and crustal relaxation, resulting in dike formation, flank instability, and syn-eruptive collapse of the volcanic edifice. Subsequently, a lesser glacial pulse partially eroded the volcano morphology and produced the currently preserved glacial deposits. Finally, a latest and limited post-glacial pyroclastic eruption occurred simultaneously with the formation of an extensive monogenetic basaltic field, shaping the final morphology of the volcano.

Load-balanced Routing Heuristics for Bandwidth Allocation of AVB Flow in TSN

Time-Sensitive Networking (TSN) is a new technology developed from Ethernet that guarantees deterministic transmission of various types of flows, such as Time-triggered (TT) flows and Audio-video-bridging (AVB) flows, in the same network. Currently, Time-aware Shaping (TAS) and Credit-based Shaping (CBS) are widely used for scheduling hybrid flows, where the credit value in CBS is directly linked to the logical bandwidth value idleSlope , which affects the real-time performance of AVB flows. However, as the network scale increases, existing bandwidth allocation methods result in higher computation times and lower allocation success rates. In this paper, the aforementioned problem is addressed by two-step: first, we design a load-balanced routing heuristic (LBRH) to improve the allocation success rate; second, we accelerate the CBS bandwidth allocation by using unified bandwidth allocation scheme, which integrates LBRH and further improves the allocation success rate. Performance evaluation in multiple test cases shows that LBRH can improve the success rate of bandwidth allocation, and the unified bandwidth allocation scheme integrating LBRH significantly reduces the overall execution time while improving the success rate of bandwidth allocation, which is more suitable for large-scale TSN networks with complex routing.

Co-wetting behavior of molten slag and iron on carbon materials in blast furnace

The interaction between molten slag, liquid iron, and carbon is one of the most typical and complex multiphase flow behaviors in the high-temperature zone of blast furnace. The wetting behavior among these phases is the most fundamental characteristic that determines their interactions. This research focuses on the co-wetting behavior of molten slag and iron on graphite, using high-temperature experiments and atomistic simulations. The results revealed that the multiphase cooperative reaction wetting process is influenced by multiple factors. The wettability of molten iron is mainly affected by its initial carbon content, while the wettability of slag is influenced by both the initial carbon content of the molten iron and its own compositional changes. The initial carbon content in molten iron affects the carburizing reaction, which in turn influences the wetting mechanism between molten iron and graphite. Additionally, it alters the reaction of FeO in the slag, thereby modifying the properties of the slag-carbon interface and affecting the overall co-wetting process. Meta-dynamic calculations showed that the reduction of molten iron oxide by dissolved carbon is significantly more effective than that by solid graphite carbon, demonstrating that the behavior of carbon between iron and slag is a key factor in the multiphase cooperative reaction process.

A Robust Quantitative Method to Distinguish Runoff‐Generated Debris Flows From Floods

AbstractDebris flows and floods generated by rainfall runoff occur in rocky mountainous landscapes and burned steeplands. Flow type is commonly identified post‐event through interpretation of depositional structures, but these may be poorly preserved or misinterpreted. Prior research indicates that discharge magnitude is commonly amplified in debris flows relative to floods due to volumetric bulking and increased frictional resistance. Here, we use this flow amplification to develop a metric (Q*) to separate debris flows from floods based on the ratio of observed peak discharge to the theoretical maximum water discharge from rainfall runoff. We compile 642 observations of floods and debris flows and demonstrate that Q* distinguishes flow type to ∼92% accuracy. Q* allows for accurate identification of debris flows through simple channel cross‐section surveys rather than through qualitative interpretation of deposits, and therefore should increase the performance of models and engineered structures that require accurate flow‐type observations.

Non-monotonic behavior of jam probability and stretched exponential distribution in pedestrian counterflow

Abstract We adopt a floor field cellular automata model to study the statistical properties of bidirectional pedestrian flow moving in a straight corridor. We introduce a game-theoretic framework to deal with the conflict of multiple pedestrians trying to move to the same target location. By means of computer simulations, we show that the complementary cumulative distribution of the time interval between two consecutive pedestrians leaving the corridor can be fitted by a stretched exponential distribution, and surprisingly, the statistical properties of the two types of pedestrian flows are affected differently by the flow ratio, i.e., the ratio of the pedestrians walking toward different directions. We also find that the jam probability exhibits a non-monotonic behavior with the flow ratio, where the worst performance arises at an intermediate flow ratio of around 0.2. Our simulation results are consistent with some empirical observations, which suggest that the peculiar characteristics of the pedestrians may attributed to the anticipation mechanism of collision avoidance.