Multiphase Analysis Research Articles

Research on the impact of overflow well shut-in on wellbore integrity and safety

If an overflow occurs, the well must be closed immediately. To ensure the safety of the drilling wellbore in ultra-deep wells, it is critical to analyze the transient flow process and pressure fluctuations of the fluid in the annular space of the overflow well shut-in. This paper investigates the pressure fluctuation model of multi-phase fluid in the annular space after overflow occurs during gas well drilling, analyzes the influence factors of multi-phase fluid's pressure wave velocity, and simulates and analyses pressure fluctuation changes in the annular space in light of the impact of overflow well shut-in on wellbore safety. The model's correctness is verified by comparing it to experimental data published in the literature. The model is developed and examined using the example of a genuine gas well in western China. According to the study, as soon as the BOP closes, pressure rapidly increases to a high of 6.09 MPa at 5.89 s before falling to a valley of 4.68 MPa at 35.36 s. When the mild shut-in time lasts 20 s, the wellhead annular pressure reaches a maximum of 5.8 MPa. If the wellhead equipment can withstand the annular space's first pressure wave, a hard shut-in is recommended. To optimize the overflow well shut-in system and ensure wellbore safety, the change in pressure in the wellhead annular space as a result of varied shut-in timings and drilling fluid displacement is studied.

Cooling and Multiphase Analysis of Heated Environmentally Friendly R152A (C2H4F2) Fluid Coming from the Production Process According to Nist Indicators

Cooling and Multiphase Analysis of Heated Environmentally Friendly R152A (C2H4F2) Fluid Coming from the Production Process According to Nist Indicators

On nonlinear effects in multiphase WKB analysis for the nonlinear Schrödinger equation *

We consider the Schrödinger equation with an external potential and a cubic nonlinearity, in the semiclassical limit. The initial data are sums of WKB states, with smooth phases and smooth, compactly supported initial amplitudes, with disjoint supports. We show that like in the linear case, a superposition principle holds on some time interval independent of the semiclassical parameter, in several régimes in term of the size of initial data with respect to the semiclassical parameter. When nonlinear effects are strong in terms of the semiclassical parameter, we invoke properties of compressible Euler equations. For weaker nonlinear effects, we show that there may be no nonlinear interferences on some time interval independent of the semiclassical parameter, and interferences for later time, thanks to explicit computations available for particular phases.

Ferromagnetic ordering in Fe: TiO2 solid solutions: A visual electron density mapping by maximum entropy method using powder X-ray data

Magnetic semiconducting FeTiO2 solid solutions with Fe compositions of 6 %, 9 %, and 12 % were analyzed using multi-phase Rietveld refinement analysis for average structure and maximum entropy for electronic structure. VSM analysis showed that the 9 % and 12 % Fe doped TiO2 compositions had a maximum magnetization of 0.3128 emu/g and coercivity of 574 Oe and 568 Oe, respectively. This confirms ferromagnetic tuning with Fe doping at or above 9 %. The MEM electron density at the bond critical points (BCP) of the apical and equatorial (Ti/Fe)–O bonds in 12 % Fe-doped TiO2 is 1.088 e/Å3 and 0.8652 e/Å3, indicating polar covalent bond. This work primarily examines a new empirical correlation between MEM electron density and magnetic parameters. Fe: TiO2 solid solutions have high magnetization and coercivity due to strong and identical (Ti/Fe) – O apical and equatorial polar covalent bonding, with low interstitial charge buildup at non-regular tetrahedral rutile lattice sites.

Thermal dynamics assessment for multi-phase flow analysis with motile cilia and electric double layer effects: Application of Levenberg–Marquardt backpropagation NNs

Ciliary movement holds substantial importance in the realm of biomedical research. Disorders arising from impaired ciliary motion, such as primary ciliary dyskinesia and specific respiratory ailments, underscore the critical need to investigate both the normal functioning and dysfunction of cilia. Such research is fundamental to the development of effective treatments and therapies. This work explores the application of Levenberg–Marquardt backpropagation neural networks (LMBP-NNs) for simulating the flow of a non-Newtonian Jeffery fluid in peristaltic motion. Inspired by synchronous ciliary movement, microfluidic systems mimicking cilia functionality have been developed. These artificial cilia can generate controlled fluid flow patterns, enabling various applications such as drug delivery, mixing, and particle sorting in lab-on-a-chip devices. The present study focuses on measuring thermal and mass transfer in beating cilia during multiphase peristaltic pumping of Jeffery fluid in two- and three-dimensional channels using transverse magnetohydrodynamics in a porous medium. The governing equations for the non-Newtonian Jeffery fluid in both the fluid and dusty phases are formulated, and exact solutions are calculated for fluid phase velocity, particulate phase velocity, temperature, concentration, and pressure gradient. The physical behavior is investigated by graphing dimensionless parameters for velocity, temperature, and concentration profiles in both solid and liquid phases. The trapping phenomena is depicted by showing streamlines of various dimensionless characteristics such as porosity velocity and volume percentage. The LMBP-NNs approach is then used to train, test, and verify the neural network models using the reference datasets. The accuracy of the LMBP-NN is assessed using statistical data such as mean square error, curve fitting graphs, regression plots, and error histograms. The study also investigates flow model limits for momentum, temperature, and concentration profiles using visual representations. This study illustrates the computational capability of LMBP-NNs in modeling the peristaltic flow of Jeffery fluid and gives useful insights into fluid flow behavior in microfluidic devices containing artificial cilia. The findings help to better understand and optimize these systems for a variety of fluid manipulation and transportation applications.

Endogenous Nitric Oxide Can Enhance Oxidative Stress Caused by Air Pollutants and Explain Higher Susceptibility of Individuals with Inflammatory Disorders.

Air pollution causes morbidity and excess mortality. In the epithelial lining fluid of the respiratory tract, air pollutants trigger a chemical reaction sequence that causes the formation of noxious hydroxyl radicals that drive oxidative stress. For hitherto unknown reasons, individuals with pre-existing inflammatory disorders are particularly susceptible to air pollution. Through detailed multiphase chemical kinetic analysis, we show that the commonly elevated concentrations of endogenous nitric oxide in diseased individuals can increase the production of hydroxyl radicals via peroxynitrite formation. Our findings offer a molecular rationale of how adverse health effects and oxidative stress caused by air pollutants may be exacerbated by inflammatory disorders.

Multi-phase failure modes and effects analysis for low dose bilateral whole lung irradiation of COVID-19 positive patients requiring respiratory ventilation.

To identify high-priority risks in a clinical trial investigating the use of radiation to alleviate COVID-19 pneumonia using a multi-phase failure modes and effects analysis (FMEA). A comprehensive FMEA survey of 133 possible causes of failure was developed for the clinical trial workflow (Phase I). The occurrence, severity, and detection risk of each possible cause of failure was scored by three medical physicists. High-risk potential failure modes were identified using the risk priority number (RPN) and severity scores, which were re-scored by 13 participants in radiation oncology (Phase II). Phase II survey scores were evaluated to identify steps requiring possible intervention and examine risk perception patterns. The Phase II participants provided consensus scores as a group. Thirty high-priority failure modes were selected for the Phase II survey. Strong internal consistency was shown in both surveys using Cronbach's alpha (αc≥0.85). The 10 failures with the largest median RPN values concerned SARS-CoV-2 transmission (N=6), wrong treatment (N=3), and patient injury (N=1). The median RPN was larger for COVID-related failures than other failure types, primarily due to the perceived difficulty of failure detection. Group re-scoring retained 8/10 of the highest-priority risk steps that were identified in the Phase II process, and discussion revealed interpretation differences of process steps and risk evaluation. Participants who were directly involved with the trial working group had stronger agreement on severity scores than those who were not. The high ranking of failures concerning SARS-CoV-2 transmission suggest that these steps may require additional quality management intervention when treating critically ill COVID-19+ patients. The results also suggest that a multi-phase FMEA survey led by a facilitator may be a useful tool for assessing risks in radiation oncology procedures, supporting future efforts to adapt FMEA to clinical procedures.

NUMERICAL ANALYSIS OF A TURBULENT PLUNGING WATER JET

In the present study, we employed multiphase computational fluid dynamics analysis to investigate the mechanisms of air entrainment by plunging liquid jets. The ANSY-CFX commercial software program, which is based on finite-element analysis, was used in the numerical simulations. The effects of the exit velocity of the jet on the velocity distribution in the pool, bubble depth, and volumetric fraction of air were the extracted results of the simulations. In this article, we conducted verification analyses to compare the results obtained from our numerical runs to the results of a previously published experimental study. Good agreement was achieved between the numerical simulations and the experimental study.

Temperature prediction model in multiphase flow considering phase transition in the drilling operations

The study considers gas compression properties, gas slippage, back pressure (BP), phase transition (PT), well depth, and differences in gas-liquid physical properties. A new temperature model for multiphase flow is proposed by considering phase transition in the drilling process. The mathematical model of multiphase flow is solved using the finite difference method with annulus mesh division for grid nodes, and a module for multiphase flow calculation and analysis is developed. Numerical results indicate that the temperature varies along the annulus with the variation of gas influx at the bottom of the well. During the process of controlled pressure drilling, as gas slips along the annulus to the wellhead, its volume continuously expands, leading to an increase in the gas content within the annulus, and consequently, an increase in the pressure drop caused by gas slippage. The temperature increases with the increase in BP and decreases in gas influx rate and wellbore diameter. During gas influx, the thermal conductivity coefficient for the gas-drilling mud two phases is significantly weakened, resulting in a considerable change in temperature along the annulus. In the context of MPD, the method of slightly changing the temperature along the annulus by controlling the back pressure is feasible.

Coated Paper-Based Packaging Waste: Investigation on Sensorial Properties Affecting the Material Class Perception

Packaging waste correct sorting hugely impacts fiber-based packaging circularity. Currently, this is more crucial than ever, also due to the increased market share of fiber-based packaging. This study evaluated the relationship between the aesthetic properties and user material sorting actions of lightweight dispersion-coated and uncoated paper substrates. Unlike previous literature, no labeling or graphics were involved in this study, focusing on the physical and aesthetic properties of both coatings and substrates. Untrained panelists participated in a multi-phase (descriptive and hedonic) analysis involving a questionnaire and antonym scales about samples’ visual and tactile properties, which were also characterized. The results highlight a remarkable panelist’s ability to assess the relative gloss and roughness. Perceived roughness and mattness statistically significantly correlated to cellulosic material identification. Moreover, material sorting into the paper recycling stream was statistically significantly regulated by sample mattness, followed by sample roughness. This work suggests that, without any graphic or textual information, the combination of substrate characteristics and coating formulation strongly impacts the packaging aesthetics, hence packaging perception as paper-based material. Consequently, the correct material identification and sorting can be encouraged by proper packaging materials selection and coating development.

Study on low-temperature performance of bitumen, mastic, and asphalt mixture

This research aimed to evaluate the effect of hot mix asphalt components on its low-temperature performance using multiphase analysis. Twelve mixtures, along with corresponding bitumens and mastics were tested with a Bending Beam Rheometer (BBR) at temperatures of −16, −22, and −28°C. A new shift factor, based on creep stiffness master curves, was defined to investigate the relationship between bitumen, mastic, and mixture performance at the reference temperatures of −16°C and −22°C. Results showed that the type of aggregate, bitumen, F/B ratios, and mastic affect the low-temperatures performance of the mixture. The constructed master curves indicated a consistent trend between the low-temperature crack resistance of mastic and the corresponding mixture, although it was observed that a mixture with lower creep stiffness did not necessarily have mastic with lower creep stiffness. A correlation was established between mastic properties and mixture creep stiffness, achieving a 0.9 correlation coefficient for validation data.

Geometry of the LMC based on multiphase analysis of multiwavelength Cepheid light curves using OGLE-IV and Gaia DR3 data

ABSTRACT The period–luminosity (PL) relation of Cepheids in the Large Magellanic Cloud (LMC) plays a pivotal role in extragalactic distance measurement and the determination of the Hubble constant (H0). In this work, we probe the geometry of the LMC through a detailed study of multiphase PL relations of these Cepheids, leveraging data from the OGLE-IV and Gaia DR3 data bases. We analyse the light curves of a combined sample of ∼3300 fundamental (FU) and first overtone (FO) mode classical Cepheids. We obtain multiphase data with 50 phase points over a complete pulsation cycle from the OGLE (V, I) and Gaia (G, GBP, GRP) photometric bands. We determine the distance modulus and reddening values of individual Cepheids by fitting a simultaneous reddening law to the apparent distance modulus values. We calculate the LMC viewing angle parameters: the inclination angle (i) and position angle of line of nodes (θlon) by fitting a plane of the form z = f(x, y) to the three-dimensional distribution of Cepheids in Cartesian coordinates $(x, y, z)$. The values of LMC viewing angles from multiphase PL relations are found to be: i = 22.°87 ± 0.°43 (stat.) ± 0.°53 (syst.), θlon = 154.°76 ± 1.°16 (stat.) ± 1.°01 (syst.), respectively. The use of multiphase PL relations in multiple bands results in lower uncertainties for the LMC viewing angle parameters as compared to those derived from the mean-light PL relations. This shows that the use of multiphase PL relations with multiwavelength photometry significantly improves the precision of these measurements, allowing better constraints on the morphology and the structure of the LMC.

Understanding Midwestern US Teacher Socialization during the COVID-19 Pandemic

The COVID-19 pandemic has had both short- and long-term impacts on the institution of schooling, as well as on teachers and students who experienced it. While much has been learned about the impact of the pandemic, including in physical education, less is known about how physical education teachers navigated the sociopolitical realities of their work as they were socialized through the pandemic. Adopting occupational socialization theory, the purpose of this study was to examine the experiences of Midwestern US physical educators during the COVID-19 pandemic and the lasting implications for their careers. Participants were 30 in-service physical education teachers (20 female and 10 male) from one state in the US Midwest who each participated in a semi-structured interview. Semi-structured interviews were audio-recorded and analyzed using a multiphase collaborative qualitative analysis method grounded in analytic induction and deduction and focused on thematic development. Data analysis resulted in four themes: (a) changing instructional modalities was challenging but prompted creativity and growth; (b) resources were scarce, and marginalization was intensified through the pandemic; (c) recognizing and responding to changes in teacher and student health; and (d) stressors associated with COVID-19 may influence teachers’ career trajectories. This study not only adds to the literature related to COVID-19 but also is important for understanding how the schools’ culture changes through times of crisis. It is likely that other local, regional, national, or international events will cause disruptions in teachers’ work and the nature of student learning in the future.

Multiphase Conjugate Heat Transfer Analyses on the Assembly Situation of Rotary Shaft Seals

Rotary shaft seals prevent the exchange of fluid at shaft passages. Their function and service life depend decisively on the temperature in the contact area between the sealing edge and the shaft. Since the temperature depends on both the generation of frictional heat in the contact area and the heat transfer to the surrounding sealing system, the design of the sealing system is crucial. Within the scope of this work, multiphase conjugate heat-transfer analyses were performed considering different assembly situations. The computed results were presented and contrasted to experimental data. This resulted in a valid model for predicting the temperature in the sealing system, which provided insight into the influence of the sealing surroundings on the contact temperature.

Gamification in Health Care Management: Systematic Review of the Literature and Research Agenda

This research aims to advance the understanding of gamification in health care management using a systematic review of the literature through a multiphase analysis. To do so, first, we extract the relevant bibliographic data for our research according to a methodology of data generation structured in six stages and a descriptive analysis oriented to the technical characterization of the data. Then, we codify all the information, identify the main attributes with the collaboration of two independent experts and check their validity using the evaluation of two focus groups of professionals in gamification and health care management. We found seven attributes: (1) health care users, (2) psychology, (3) behavior, (4) activities, (5) health field, (6) technology, and (7) gamification elements. Within each of these seven attributes, there are a series of main elements that are detailed in the following for each of them. (1) Health care users: their age and the role they play in the health system. (2) Psychology: cognition, positive and negative emotions. (3) Behavior: healthy behavior encouragement, such as compliance, collaboration and responsibility. (4) Activities: physical activity and food. (5) Health field: preventive medicine and chronic diseases. (6) Technology: cell phones. (7) Gamification elements: different elements, but the number of articles in which these elements and their interactions are studied in depth is limited. Our results point toward a promising present and future research agenda that is in parallel with the development of relevant fields for the sector, such as chronic diseases, health education and preventive medicine.

Artificial intelligence-assisted optimization and multiphase analysis of polygon PEM fuel cells

ABSTRACT This study introduces innovative, optimized hexagonal and pentagonal PEM fuel cell models. The inlet pressure and temperature serve as input parameters, while power consumption and output power are objective parameters. The results of Computational Fluid Dynamics (CFD) analysis are then trained with deep neural networks and modeled using polynomial regression. Target functions are derived using the Response Surface Method (RSM) and optimized with the NSGA-II genetic algorithm. Compared to the base model, our optimized pentagonal and hexagonal PEM fuel cells significantly boost the output current density by 21.8% and 39.9%, respectively. Additionally, power consumption is lower: the pentagonal model uses 0.198%, and the hexagonal model uses 6.21% of the production power on average. Our proposed designs enhance PEM fuel cell performance by significantly boosting power production while minimizing power consumption.

Gas Additives for Silicon Anode Lithium-Ion Batteries

While many organic liquid and electrolyte salt formulations have been explored to improve the stability of lithium-ion batteries, less research has been done to determine the role of evolved gasses in the performance of commercial Li-ion battery chemistries, let alone novel combinations of gas additives that may affect the solid-electrolyte interphase (SEI) formation and evolution.[1,2] Many gases are generated during Li-ion battery cycling, any of which could have possible beneficial or harmful effects on performance. Currently, only the effect of carbon dioxide (CO2) gas addition to Li-ion batteries with Si anodes has been studied.[3-4] In addition to CO2, ethylene gas (C2H4) is a promising additive for Si anode systems because it is a precursor in polyethylene polymerization reactions, nCH2=CH2 --> [-CH2-CH2-]n. In addition, polyethylene oxide (PEO) has been observed in the Si-anode SEI and contributes to its passivation while maintaining flexibility.[5] Therefore, creating polyethylene and increasing PEO concentration in situ via ethylene gas doping may yield an improved SEI and more-stable battery.This work investigates the potential of gas-phase additives, including CO2 and C2H4, to improve the performance of Si anodes for Li-ion batteries. The pressure decay of the gasses at different starting pressures dissolving in GenF3 electrolyte (1.2 M LiPF6 in 3:7 wt:wt ethylene carbonate to ethyl methyl carbonate + 3 wt% fluoroethylene carbonate) was monitored to determine the saturation concentration of dissolved gas. The experimental pressure decay curve was fit to a model and extrapolated to predict the final pressure at equilibrium.[6] The relationship between partial pressure and concentration of dissolved gas in GenF3 at equilibrium was plotted and a curve was drawn to determine the Henry’s law constant. Varying volumes of gas were injected into battery pouch cells containing Si nanoparticle anodes and LiFePO4 (LFP) cathodes to pressurize them to different pressures. Electrochemical cycling and subsequent multi-phase analyses, including vibrational spectroscopy and X-ray characterization of the SEI surface layer and GC-MS/FID were conducted to determine the impact of gas doping on the capacity, SEI, and gas phase reaction products.

Numerical Investigation of Sulfate Diffusion Characteristics in Recycled Aggregate Concrete Based on Mesoscale Multiphase Analysis

Sulfate-induced deterioration can reduce the service life of recycled aggregate concrete (RAC). To demonstrate the transport behavior of sulfate ions in RAC, a two-dimensional, six-phase numerical model of RAC is proposed in this study. Sulfate ion diffusion coefficients were defined for different phases [attached mortar, new mortar, interfacial transition zone (ITZ) between attached mortar and original aggregate, ITZ between the new mortar and original aggregate, and ITZ between the new mortar and attached mortar] of RAC. The effects of ITZ width and porosity on ion transport behavior in RAC were analyzed. The results show that the numerical model agrees with the experimental data. Numerical results indicate that the six-phase model of RAC provides more-accurate simulation results because tortuosity is reflected in the model. The width and porosity of ITZs both affect the diffusion of sulfate ions in concrete. However, due to the low volume fraction of ITZ in concrete, just improving ITZ performance has no significant effect on ion attack resistance of concrete. The ITZ is a crucial zone where damage may originate and develop.

Percolation characteristics of pore fluid during hydrate depressurization dissociation from multi-phase multi-field coupling analysis

The recovery of gas from hydrate-bearing reservoirs is essentially controlled by pore fluid flow. Four numerical models with different multi-phase multi-field were established in this work based on the thermo-hydro-chemical model, considering ice phase, fluidized sand phase, depositing sand phase, and ice, fluidized sand and depositing sand phases, respectively. These above models were used to simulate the dissociation of hydrate-bearing cores by depressurization and to investigate the effects of freezing and melting behavior, sand production behavior, and their combined behavior on pore fluid migration. By comparing the simulations with and without the ice phase, it can be found that the permeability decreases sharply due to ice generation resulting in a decrease of 89.16% in pore-water velocity and of 99.95% in pore-gas velocity. This indicates an inhibition of pore fluid migration by freezing behavior. Meanwhile, it can be found that the ice melting behavior can temporarily promote pore-water migration but has no obvious promotion for pore-gas migration. It is difficult for the pore fluid to percolate in the regions prone to ice generation during hydrate dissociation. In addition, the permeability at 300 min with sand detachment is 16% higher than that without sand detachment. But at the same time, the pore water velocity is 28.44% smaller since sand detachment behavior does not directly power pore fluid migration. By comparing the simulations with and without the combined behavior, it can be concluded that the freezing behavior and the sand production behavior can jointly weaken the pore fluid mobility. Significantly, the former has a stronger negative effect on the pore fluid mobility than the latter during the depressurization dissociation of the hydrate-bearing sediment.

β-catenin/CBP activation of mTORC1 signaling promotes partial epithelial-mesenchymal states in head and neck cancer

Head and neck cancers, which include oral squamous cell carcinoma (OSCC) as a major subsite, exhibit cellular plasticity that includes features of an epithelial-mesenchymal transition (EMT), referred to as partial-EMT (p-EMT). To identify molecular mechanisms contributing to OSCC plasticity, we performed a multiphase analysis of single cell RNA sequencing (scRNAseq) data from human OSCC. This included a multiresolution characterization of cancer cell subgroups to identify pathways and cell states that are heterogeneously represented, followed by casual inference analysis to elucidate activating and inhibitory relationships between these pathways and cell states. This approach revealed signaling networks associated with hierarchical cell state transitions, which notably included an association between β-catenin-driven CREB-binding protein (CBP) activity and mTORC1 signaling. This network was associated with subpopulations of cancer cells that were enriched for markers of the p-EMT state and poor patient survival. Functional analyses revealed that β-catenin/CBP induced mTORC1 activity in part through the transcriptional regulation of a raptor-interacting protein, chaperonin containing TCP1 subunit 5 (CCT5). Inhibition of β-catenin-CBP activity through the use of the orally active small molecule, E7386, reduced the expression of CCT5 and mTORC1 activity in vitro, and inhibited p-EMT-associated markers and tumor development in a murine model of OSCC. Our study highlights the use of multiresolution network analyses of scRNAseq data to identify targetable signals for therapeutic benefit, thus defining an underappreciated association between β-catenin/CBP and mTORC1 signaling in head and neck cancer plasticity.