Volumetric Percentage Research Articles

The FEDRA Longitudinal Study: Repeated Volumetric Breast Density Measures and Breast Cancer Risk

Mammographic breast density (MBD) is a strong independent risk factor for breast cancer (BC). We investigated the association between volumetric MBD measures, their changes over time, and BC risk in a cohort of women participating in the FEDRA (Florence-EPIC Digital mammographic density and breast cancer Risk Assessment) study. The study was carried out among 6148 women with repeated MBD measures from full-field digital mammograms and repeated information on lifestyle habits, reproductive history, and anthropometry. The association between MBD measures (modeled as time-dependent covariates), their relative annual changes, and BC risk were evaluated by adjusted Cox models. During an average of 7.8 years of follow-up, 262 BC cases were identified. BC risk was directly associated with standard deviation increments of volumetric percent density (VPD, HR 1.37, 95%CI 1.22-1.54) and dense volume (DV, HR 1.29, 95%CI 1.18-1.41). An inverse association emerged with non-dense volume (NDV, HR 0.82, 95%CI 0.69-0.98). No significant associations emerged between annual changes in VPD, DV, NDV, and BC risk. Higher values of MBD measures, modeled as time-dependent covariates, were positively associated with increased BC risk, while an inverse association was evident for increasing NDV. No effect of annual changes in MBD emerged.

Continuous Wave of Condensation Improves the Filling of Curved Canals: a Micro-CT Study

The aim of this study was to compare the filling capacity in curved root canal using a new continuous wave of condensation technique (Termo Pack II, Easy Dental Equipments, Brazil) or lateral compaction. The percentage of voids in the filling of mesial root canals of mandibular molars was assessed by micro-computed tomography (micro-CT). Mesial root canals (n=24) of mandibular molars with a degree of curvature between 20° and 40° were prepared using rotary system (ProDesign Logic, Easy, Brazil) up to #35, .05 taper. The root canals were filled by using the continuous wave of condensation system or lateral compaction and AH Plus sealer (n=12). Scanning at 9 µm was performed after preparation and after filling by using micro-CT SkyScan 1176. The volumetric percentage of filling material and voids (total length and in each root canal third) were calculated. Data were analyzed using ANOVA/Tukey and Student’s t tests (α=0.05). Before the filling techniques, the root canals volume after preparation was similar (p>0.05). The root canals filled by the continuous wave of condensation technique presented the lowest percentage of voids, and the greatest percentage of filling material in total length and thirds (cervical, middle and apical) (p<0.05). Both techniques were not able of completely filling the root canals. The continuous wave of condensation technique Termo Pack II promoted better root canal filling in curved root canals, when compared with lateral compaction.

Enhancement of conventional concrete mix designs for sensible thermal energy storage applications

The study examines twenty-nine different concrete mix designs with varying constituents to improve thermal performance for energy storage at elevated temperatures up to 420 °C. Effects of variables including the type and volumetric percentage of coarse and fine aggregates, the type and replacement content of supplemental cementitious materials, water-to-cement ratio, the type and quantity of steel fiber reinforcement, and the inclusion of iron oxide powder are experimentally investigated by measuring the mechanical and thermal properties of each mix, with the overall goal of enhancing thermal performance and mitigating mechanical degradation for thermal energy storage (TES) applications. It is found that the use of siliceous aggregate with a high volumetric percentage produces the highest improvement (23 %–37 % at elevated temperatures) of concrete thermal conductivity, while silica fume replacement of Type I cement provides the highest improvement (4 %–8 % at elevated temperatures) of concrete specific heat. To simulate the operation of a TES system, thermal cycling was conducted to examine the change in concrete properties as a function of repetitive heating (during and after 50 total cycles to 420 °C). Based on the results of testing, concrete mix designs with high aggregate percentages (up to 72 % by volume), siliceous coarse aggregate, silica fume replacement of Type I cement (15 % by weight), and steel fiber reinforcement (up to 2 % by volume) facilitate enhanced TES performance by providing consistent thermal conductivity of ~2.2 W/m·K and specific heat of ~3.2 MJ/m3·K under cyclic high temperature exposure.

Crystalline texture of cobalt nanowire arrays probed by the switching field distribution and FORC diagrams

The crystalline texture of arrays of low diameter Co nanowires (NWs) synthesized by electrodeposition using electrolytes with different acidities (pH in the range 2.0–6.6) was studied by the switching field distribution (SFD) and first order reversal curve (FORC) diagrams. Particularly, the SFD determined as the derivative of the descending part of the major hysteresis loop has proven to be a reliable and powerful method for the identification of different crystalline textures in the NWs and the quantification of their corresponding texture percentages. The presence of the face centered cubic-like texture at low pH values and hexagonal close packed textures with the c-axis perpendicular and parallel to the NWs axis at higher pH values have been identified by performing multiple Gaussian fits to the SFD by virtue of their different magnetic behavior observed during reversal of the magnetization. The field position and size of each curve in the multiple Gaussian fit provide information about the corresponding magnetic contribution and volumetric texture percentage of each crystalline texture in the NWs, respectively. The analysis of the SFD has been complemented and validated with FORC diagram measurements, showing that the width of the coercive field distribution is in good agreement with the width of the SFD. Also, it has been found that the different branches observed in the FORC diagrams along the interaction axis provide further insight on the interaction between magnetocrystalline fields. This work provides a novel methodology for the use of magnetometry as a reliable technique for the study of the interplay between the microstructure and magnetic behavior of arrays of NWs.

The use of artificial intelligence and time characteristics in the optimization of the structure of the volumetric percentage detection system independent of the scale value inside the pipe

ABSTRACT When scale builds up in a transmission pipeline, it narrows the pipe’s interior and causes losses in both power and efficiency. A noninvasive instrument based on gamma-ray attenuation is one of the most reliable diagnostic procedures for determining volumetric percentages in a variety of circumstances. A system with a NaI detector and dual-energy gamma generator simulations (241Am and 133 Ba radioisotopes) is recommended for simulating a volume percentage detection system utilizing Monte Carlo N particle (MCNP). Three-phase flow consisting of oil, water, and gas moves through a scaled pipe of variable wall thicknesses in a stratified flow regime with changing volume percentages. After gamma rays are emitted from one end of the pipe, a detector take in the photons coming from the other end. Four temporal features, including kurtosis and mean value of the square root (MSR), skewness, and waveform length (WL) picked up by the detector, were thus obtained. By training two GMDH neural networks with the aforementioned inputs, it is possible to forecast volumetric percentages with an RMSE of less than 0.90 and independently of scale thickness. The low error value, simplicity of the system, and reduction of design costs ensures the effectiveness of the suggested method and the advantages of employing this approach in the petroleum and petrochemical industries.

Increasing the Corrosion Resistance in the UNS S32750 Super Duplex Steel Welded Joints through Hybrid GTAW-Laser Welding and Nitrogen.

The development of techniques to improve the welding of super duplex steels is necessary in order to ensure that the phase balance and properties of the material are not affected during this process. Hybrid arc-laser welding is a perfect combination of the advantages of both processes, producing deeper weld beads with more balanced phases than the pulsed laser process. Here, the objective was to improve the corrosion resistance of UNS S32750 weld beads by increasing the volumetric austenite percentage in the fusion zone (FZ) with a hybrid process of GTAW (gas tungsten arc welding) and pulsed laser Nd-YAG (neodymium-doped yttrium aluminum garnet). Welds were performed in bead on plate conditions with fixed laser parameters and a varying heat input introduced through the GTAW process. Additionally, welds within a nitrogen atmosphere were performed. After base metal characterization, an analysis of the FZ and heat affected zone were performed with optical microscopy, scanning electron microscopy and critical pitting tests (CPT). The synergy between the thermal input provided by the hybrid process and austenite-promoting characteristic of nitrogen led to a balanced volumetric austenite/ferrite fraction. Consequently, the results obtained in CPT tests were better than conventional welding processes, such as laser or GTAW solely.

Finite element analysis on the formation, size and pattern of distribution of TiB2 in MMC

A 6 volumetric percentage of TiB2 reinforcement with A356 aluminium matrix is fabricated through in-situ process. The three pouring temperatures of 750 °C, 780 °C & 810 °C with ten min, twenty min and thirty min holding times. Six identical locations are selected from 24 locations based on pouring height of the ingot. Also, the direction of pouring the melt considered for fluidity and temperature distribution. This assessment is performed by using Procast software to permit for aluminium titanium di-boride metal matrix component, through in-situ formed with the favoured distribution of debris and with preferred length of reinforcement, at numerous positions of the solid issue. A finite element tool is used for analyse the formation of MMC and the pattern of distribution through the thermal analysis in various locations of the ingot. From the total curve graph of the heat transfer and distribution of the melt based on the turbulence and pouring height, the 810 °C shown good results. Also, the results is best suitable for aeronautical applications to replace the magnesium.

Influence of volumetric percentage of high entropy alloys on mechanical behaviour of 6061 T6 Al alloy surface composite processed by friction stir processing

ABSTRACT The purpose of this study is to find the influence of volumetric percentage of High Entropy Alloys (HEA) on Mechanical Behaviour of 6061 T6 Al alloy surface composite processed by Friction Stir Processing (FSP). Al-6061-T6 alloy was considered as the base material and Al-Fe-Cu-Ni-Zn as HEA with relevant weight proportion. HEA were reinforced on plate by making a slot on them using shaper and varying the volumetric percentage of slot. Friction stir processing was carried out on the samples with optimal working parameters. Study of the properties such as microstructure of joint and strength will directly affect the parameters such as corrosion of joint which will decide the service and life of the joint in different environments. Radiography was carried out for the samples after FSP to check for any defects or cracks. The microstructures for all the samples are studied based on grain size refinement and uniform Distribution of HEA around the travel pattern of tool. It is observed that micro hardness of samples increased with increase in percentage of HEA which is more than the hardness value of base material (Al alloy). It is evident that 4% sample exhibits better tensile properties than other.

The efficacy of three passive ultrasonic irrigation systems on intracanal medicament removal in a novel standardised three-dimensionally printed model.

This study compared the efficacy of several passive ultrasonic irrigation (PUI) systems in removing intracanal medicament using 3-dimensionally printed root canal model assembled with dentin specimen. After the placement of the model in the agar container (37°C), the intracanal medicament was removed using three different PUI instruments including CK file, Irrisafe and Endosonic Blue. Then, the area coated by the medicament and the volumetric percentage of the remaining medicament was measured. Irrisafe and Endosonic Blue showed higher removal efficacy than CK and the control regarding both the coated area and remaining volume (p < 0.05). CK showed the lowest efficacy among the tested PUI systems (p > 0.05). Notably, Endosonic Blue group showed the smallest coated area among the tested groups (p < 0.05). Conclusively, PUI systems made of nickel-titanium alloy with small dimensions, such as Endosonic Blue, have advantages for the removal of intracanal medicaments from curved root canals.

External root resorption (ERR) and rapid maxillary expansion (RME) at post-retention stage: a comparison between tooth-borne and bone-borne RME

BackgroundThe study aimed to compare external root resorption (ERR) three-dimensionally in subjects treated with tooth-borne (TB) versus bone-borne (BB) rapid maxillary expansion (RME). Forty subjects who received tooth-borne RME (TB group, average age 13.3 years ± 1.10 years) or bone-borne RME (BB group, average age 14.7 ± 1.15 years) were assessed using CBCT imaging before treatment (T0) and after a 6-month retention period (T1). 3D reconstructions of the radicular anatomy of maxillary first molars (M1), first and second premolars (P1 and P2) were generated to calculate volumetric (mean and percentage values) and shape changes (deviation analysis of the radicular models) obtained at each time point. 2D assessment of radicular length changes was also performed for each tooth. Data were statistically analyzed to perform intra-group (different teeth) and inter-group comparisons.ResultsIn both groups, all the investigated teeth showed a significant reduction in radicular volume and length (p < 0.05), with the first molars being the teeth most affected by the resorption process (volume and palatal root length). When volumetric radicular changes were calculated as a percentage of the pre-treatment volumes, no differences were found among the investigated teeth (p > 0.05). Based on the deviation analysis from radicular models superimposition, the areas most affected by shape change were the apex and bucco-medial root surface. Overall, the amount of ERR was significantly greater in the TB group (mm3: M1 = 17.03, P1 = 6.42, P2 = 5.26) compared to the BB group (mm3: M1 = 3.11, P1 = 1.04, P2 = 1.24).ConclusionsDespite the statistical significance, the difference in the amount of ERR of the posterior maxillary dentition between TB-RME and BB-RME remains clinically questionable.

Enhancing Dark Fermentative Hydrogen Production from Problematic Substrates via the Co-Fermentation Strategy

The aim of the present paper is the improvement of dark fermentative hydrogen production from problematic substrates. In detail, the study is aimed at (i) investigating the inhibiting effect of two problematic biomasses (i.e., of olive mill wastewater, containing recalcitrant/toxic compounds and cheese whey, lacking pH buffering capacity) on the dark fermentation process, (ii) as well as verifying the possibility to apply a co-fermentation strategy to enhance the process. To investigate the inhibiting effect of the substrates, two experimental sets were conducted using olive mill wastewater and cheese whey alone, under different food-to-microorganism ratios (i.e., 1, 2.5, and 5). Further experiments were conducted to verify the possibility of improving hydrogen production via the co-fermentation strategy. Such experiments included two tests conducted using different volumetric percentages of olive mill wastewater and cheese whey (90% olive mill wastewater + 10% cheese whey and 80% olive mill wastewater + 20% cheese whey). Results show that using olive mill wastewater alone, the inhibiting effect increased at a higher food-to-microorganism ratio. Moreover, because of the occurrence of a metabolic shift, hydrogen was not produced using 100% cheese whey. Interestingly, compared to the 100% olive mill wastewater condition, the use of 20% cheese whey allowed to double the hydrogen yield, reaching the high cumulative hydrogen production of 2.08 LL−1. Obtained results confirm that the two investigated substrates exert inhibiting effects on microorganisms. Nevertheless, co-fermentation is an effective strategy to improve the dark fermentation process of problematic biomass.

Sustainable ferrocement mortar with different waste materials and curing methods

In this study, the essential aim is to produce an environment-friendly ferrocement mortar using different waste internal curing materials and external curing methods. Wastes of broken bricks and porcelanite were used with different volumetric replacement percentages (5, 10 and 15%) of fine aggregate. Moreover, pozzolanic materials (silica fume and fly ash) were used. Besides to the water-cured reference mixture, four different curing methods (air, flan coat emulsified asphalt, wax sealing paint and carbon dioxide (CO2) gas) were used. The compressive and flexural strengths and densities of mortars of different ages (7, 14 and 28 days) were investigated. The outcomes demonstrate that the compressive strength of carbon dioxide cured ferrocement improved by 33.3 and 28% when 5 and 10% broken bricks were used and by 25.3 and 29% when 5 and 10% porcelanite were used, respectively, relative to that of the reference. The flexural strength was slightly improved when 10% porcelanite was used. The results demonstrate that the resulting ferrocement mortar improved despite using different waste materials in production.

Pulmonary nodule volumetric accuracy of a deep learning-based reconstruction algorithm in low-dose computed tomography: A phantom study

PurposeTo compare the image properties and pulmonary nodule volumetric accuracies among deep learning-based reconstruction (DLR), filtered back projection (FBP), and hybrid iterative reconstruction (hybrid IR) in low-dose computed tomography (LDCT). MethodsA multipurpose chest phantom containing artificial spherical pulmonary nodules with 5-, 8-, 10-, and 12-mm diameters and Hounsfield units (HUs) of −630 and +100 HU was scanned 20 times at a standard dose, based on a low-dose screening CT trial, and at 1/2, 1/6, and 1/12 of the standard dose. To assess noise reduction performance and volumetric accuracy, the standard deviations (SDs) of the pixel values and volumetric percentage errors (PEs) were compared among FBP, hybrid IR, and DLR. The noise non-stationarity index (NNSI) was calculated from 20 image replicates and compared among FBP, hybrid IR, and DLR to evaluate noise stationarity. ResultsThe SD reduction rates for FBP in hybrid IR and DLR were 62 %–85 % and 79 %–90 %, respectively. For the four nodules with +100 HU, the PE of all reconstruction methods was <±25 % (not clinically relevant). For the four nodules with −630 HU, the PEs were equivalent or lower for hybrid IR and DLR than for FBP, and the PE difference between hybrid IR and DLR ranged from 0 % to 7%. The NNSI was significantly higher for DLR than for FBP and hybrid IR (p < 0.01). ConclusionsGreater noise suppression was achieved with DLR than with hybrid IR without compromising nodule volumetric accuracy in LDCT despite the representative noise non-stationarity.

Stratified Flames in Dual Annular Counter-Rotating Swirl Burner for Wider Operability Gas Turbines

Abstract This study investigates numerically the effects of equivalence ratio (Φ) on flow/flame interactions and emissions of stratified oxy-methane (CH4/O2/CO2) flames in a dual annular counter-rotating swirl (DACRS) burner for wider operability and environmental-friendly gas turbines. The flow mixture entering the combustor is split into two coaxial streams of different equivalence ratios. The central stream is characterized by higher Φ to continuously ignite the flame for enhanced flame stability, whereas the annular stream is a highly lean mixture to sustain the environmental performance of the combustor. The partially premixed combustion model is adopted in the ansys-fluent 2021-r1 software to model the reaction kinetics of the generated stratified flames in the two-dimensional axisymmetric domain. Nine cases of the same inlet velocity ratio (primary stream to secondary stream) of 3.0 are examined at a fixed oxygen fraction (OF: volumetric percentage of oxygen in the O2/CO2 mixture) of both streams of 30%. Flame stratification is achieved by varying the equivalence ratios of the primary (Φp = 0.9, 0.8, and 0.7) and secondary (Φs = 0.7, 0.55, and 0.4) streams. The results indicate effective flame/flow interactions, complete combustion, and reduced emissions for the DACRS stratified flames.

Nonlinear buoyancy driven flow of hybrid nanoliquid past a spinning cylinder with quadratic thermal radiation

The buoyancy driven flow on a vertical cylinder finds relevance in many engineering applications as in geophysics, chemical engineering, metallurgy, oceanography etc. The flow of water transporting hybrid nanoparticles (25 nm Ag and 40 nm MgO) around a spinning cylinder surface subjected to quadratic radiative heat transfer is explored using nonlinear buoyancy-induced (quadratic convection). The Esfe models for thermal conductivity and dynamic viscosity as a function of a volumetric percentage of nanoparticle are amalgamated. The partial differential equations (PDEs) for buoyancy driven boundary layer flow are used to construct the dimensionless nonlinear form of governing PDEs, which are then solved by discretization method i.e., 2D Galerkin Finite Element Method (GFEM). Heat transport is found to be greater for quadratic radiation/convection than for linear thermal radiation/convection. Using response surface methodology, the maximum average heat transport (5.78391) is achieved for maximum parametric value of buoyancy parameter, rotating parameter and radiation parameter. Residual and sensitivity analyses are conducted for quadratic fitting. In addition, sensitivity of average Nusselt number towards radiation parameter is always positive.

Geometrical Optimization of Printed Interdigitated Electrode Sensors to Improve Soil Moisture Sensitivity

Printing electronics allows us to fabricate low-cost, simple sensor networks. Distributed soil moisture sensors in agriculture industry will result in better water management practices; however, price and reliability do not allow for ubiquitous availability. Here, we demonstrate the fabrication of low-cost, flexible, interdigitated electrode (IDE) soil moisture sensors with the electrode widths of 537, 877, 1055, 1204, and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$1916~\mu \text{m}$ </tex-math></inline-formula> on polyimide (PI) substrates using a silver nanoparticle (Ag NP) ink. The sensors were tested in sandy textured soil with a volumetric water content ranging from 0.05 to 0.25 m3/m3. Analytically, the sensitivities of all the sensors are expected to be equal, as the proposed mechanisms dictate that the capacitance should depend linearly on the dielectric constant of the moist soil. However, we found the sensitivity for the widest IDE, which measured <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$1916~\mu \text{m}$ </tex-math></inline-formula> to be 442 pF/H2O volumetric percentage, whereas the sensitivity for the sensor with 537- <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mu \text{m}$ </tex-math></inline-formula> -wide electrodes to be only 221 pF/H2O volumetric percentage. We hypothesized that the increase in sensitivity can be directly related to the increase in the capacitive fringing field height, which results in increased sensing volume for the widest IDE. The increased sensing volume leads to increased water molecule polarization, increasing the overall capacitance change with respect to changing water content. To validate the hypothesis, we conducted electric fringing field experiments to observe the trend between the maximum fringing field height and the electrode width of an IDE. Results confirmed that increased sensing volume was caused by the increased fringing field height of the electrode in an IDE.

Application of Artificial Intelligence for Determining the Volume Percentages of a Stratified Regime’s Three-Phase Flow, Independent of the Oil Pipeline’s Scale Thickness

As time passes, scale builds up inside the pipelines that deliver the oil or gas product from the source to processing plants or storage tanks, reducing the inside diameter and ultimately wasting energy and reducing efficiency. A non-invasive system based on gamma-ray attenuation is one of the most accurate diagnostic methods to detect volumetric percentages in different conditions. A system including two NaI detectors and dual-energy gamma sources (241Am and 133Ba radioisotopes) is the recommended requirement for modeling a volume-percentage detection system using Monte Carlo N particle (MCNP) simulations. Oil, water, and gas form a three-phase flow in a stratified-flow regime in different volume percentages, which flows inside a scaled pipe with different thicknesses. Gamma rays are emitted from one side, and photons are absorbed from the other side of the pipe by two scintillator detectors, and finally, three features with the names of the count under Photopeaks 241Am and 133Ba of the first detector and the total count of the second detector were obtained. By designing two MLP neural networks with said inputs, the volumetric percentages can be predicted with an RMSE of less than 1.48 independent of scale thickness. This low error value guarantees the effectiveness of the intended method and the usefulness of using this approach in the petroleum and petrochemical industries.

Prediction of breast cancer risk by automated volumetric breast density measurement.

Dense breast (DB) is recognized as a breast cancer (BC) risk factor. Although DB is common in Japanese women, the incidence of BC is lower than in Caucasians. We evaluated whether DB is a risk factor or whether there are other risk factors for BC in Japanese women. We retrospectively analyzed 635 BC patients and 999 controls who received a mammography at our hospital between February 2019 and March 2021. Volumetric breast density percentage (VBD%), breast volume (BV), and fibroglandular volume (FGV) were measured using Volpara™, an automated, three-dimensional image analysis program. A VBD% of 7.5% or higher was classified as DB. The association between the VBD%, BV, and FGV, and BC risk were assessed using logistic regression. Of the BC group and the control group, 77% and 79% had DB. The stratified FGV was positively associated with BC risk (odds ratio: 2.84; 95% confidence interval 1.58-5.12; P < 0.001). No significant association was found between either the VBD% or BV and BC risk. The proportion of Japanese women with DB was high, suggesting that DB might not be significantly associated with BC risk. However, our results also suggested that the FGV may be related to BC risk in Japanese women.

Thermal performance enhancement of a new dual-PCM heat sink using two-objective optimization

Phase change materials (PCMs) can effectively improve the performance of electronic heat sinks especially when subjected to intermittent heat loads. PCMs however brings some shortcomings such as increased size of component, and slowed heat rejection during the discharging, which urged the inevitability in development of optimized design. This study presents the results of the two-objective shape optimization of a new dual-PCM heat sink. The cooling phenomenon is analysed with thorough and realistic consideration of heat loss through the fin tips to the ambient, as well as heat transfer between the PCM and the air above it. Natural convection of liquid PCM and its volume variation during phase change transition are taken into account. Two-objective optimizations are performed to maximize the heat sink operational time in the charging process and minimize the discharging time, for three critical temperatures of 50 °C, 65°C, and 80 °C. Response Surface Methodology (RSM) is utilized to attain this goal. The fin thickness, the fin height, the width of ducts and the base thickness are selected as design parameters. The optimum volumetric percentages of PCM are found to be 80.50%, 76.94% and 74.81% for set point temperatures (SPTs) of 50 °C, 65 °C, and 80 °C, respectively. The optimized designs for three SPTs deliver charging periods up to 7% longer and discharging periods up to 4.2% shorter than the reference geometry. Furthermore, total volume of the heat sink is decreased up to 23% due to current optimizations, signifying a favourable compact design.

Accurate Flow Regime Classification and Void Fraction Measurement in Two-Phase Flowmeters Using Frequency-Domain Feature Extraction and Neural Networks

Two-phase flow is very important in many areas of science, engineering, and industry. Two-phase flow comprising gas and liquid phases is a common occurrence in oil and gas related industries. This study considers three flow regimes, including homogeneous, annular, and stratified regimes ranging from 5–90% of void fractions simulated via the Mont Carlo N-Particle (MCNP) Code. In the proposed model, two NaI detectors were used for recording the emitted photons of a cesium 137 source that pass through the pipe. Following that, fast Fourier transform (FFT), which aims to transfer recorded signals to frequency domain, was adopted. By analyzing signals in the frequency domain, it is possible to extract some hidden features that are not visible in the time domain analysis. Four distinctive features of registered signals, including average value, the amplitude of dominant frequency, standard deviation (STD), and skewness were extracted. These features were compared to each other to determine the best feature that can offer the best separation. Furthermore, artificial neural network (ANN) was utilized to increase the efficiency of two-phase flowmeters. Additionally, two multi-layer perceptron (MLP) neural networks were adopted for classifying the considered regimes and estimating the volumetric percentages. Applying the proposed model, the outlined flow regimes were accurately classified, resulting in volumetric percentages with a low root mean square error (RMSE) of 1.1%.