Average Percentage Deviation Research Articles

Performance model evaluation of turbine flow meter in vertical gas-liquid two-phase flows

Aiming at the need for flow measurement of gas-liquid flows in domestic gas well production, this paper proposes a measurement method based on the combination of the turbine flow meter (TFM) and a rotating electric field conductance sensor (REFCS). In experiments, the REFCS is used for the measurement of the gas holdup. To verify the applicability of the TFM models investigated in the previous study, for the modeling part, the mass, momentum and torque models are evaluated in vertical upward gas-liquid two-phase flows. In our model test, the meter factor model of TFM considers the effects of the slip ratio between the gas and liquid phases and flow patterns. In particular, the gas holdup involved in calculating the slip ratio in the model evaluation is obtained from the REFCS measurements. Model test results show the torque model has better volumetric flow rate prediction accuracy than the mass and momentum models. In the present study, the ranges of the liquid and gas phases are Qw = 2–30 m3/d and Qg = 1–16 m3/d, it was found that the average absolute deviation (AAD) in the predicted volume flow rate is equal to 1.23 m3/d and the average absolute percentage deviation (AAPD) is equal to 7.69%. The evaluated results presented in this paper will allow better estimates of the volumetric flow rates of gas-liquid flows based on the combined TMF and REFCS measurements during the monitoring of gas well production.

Densities, Viscosities, and Derived Properties for Binary Mixtures of Long-Chain Alcohols of 1-Hexanol + 1-Pentanol, + 2-Pentanol, + 2-Methyl-1-butanol, + 1-Heptanol, and + 1-Octanol from 288.15 to 338.15 K

Densities and viscosities for binary mixtures of long-chain alcohols are important to design transfer heat and mass equipment and to interpret the kind of interactions that occur in the studied blends. Current investigation indicated the measurements of densities and viscosities for liquid mixtures of 1-hexanol + 1-pentanol, + 2-pentanol, + 2-methyl-1-butanol, + 1-heptanol, and + 1-octanol from 288.15 to 338.15 K at atmospheric pressure and over the whole range of mole fractions. A vibrating tube densimeter and a glass capillary viscometer were used to measure the density and viscosity of the alcohol binary mixtures, respectively. Experimental measurements of the pure alcohols have been compared with the data reported in the literature using average absolute percentage deviation (AAPD) as a criterion. The obtained results demonstrated for density an AAPD of 0.023% and for viscosity an AAPD of 0.597%, which is a good agreement between the experimental findings and literature data. Excess molar volume and viscosity deviation present negative deviations for all the alcohol mixtures at the conditions considered in this research. These results indicate that the mixture suffers a volume contraction, which is caused by intermolecular forces of attraction between different alcohol molecules. The Redlich–Kister equation is used to fit the excess molar volume and viscosity deviation. Kinematic viscosities of the binary blends have been calculated through the Nava-Ríos et al. and McAllister equations.

Modeling Viscoelastic Solid Earth Deformation Due To Ice Age and Contemporary Glacial Mass Changes in ASPECT

AbstractThe redistribution of past and present ice and ocean loading on Earth's surface causes solid Earth deformation and geoid changes, known as glacial isostatic adjustment. The deformation is controlled by elastic and viscous material parameters, which are inhomogeneous in the Earth. We present a new viscoelastic solid Earth deformation model in ASPECT (Advanced Solver for Problems in Earth's ConvecTion): a modern, massively parallel, open‐source finite element code originally designed to simulate convection in the Earth's mantle. We show the performance of solid Earth deformation in ASPECT and compare solutions to TABOO, a semianalytical code, and Abaqus, a commercial finite element code. The maximum deformation and deformation rates using ASPECT agree within 2.6% for the average percentage difference with TABOO and Abaqus on glacial cycle (∼100 kyr) and contemporary ice melt (∼100 years) timescales. This gives confidence in the performance of our new solid Earth deformation model. We also demonstrate the computational efficiency of using adaptively refined meshes, which is a great advantage for solid Earth deformation modeling. Furthermore, we demonstrate the model performance in the presence of lateral viscosity variations in the upper mantle and report on parallel scalability of the code. This benchmarked code can now be used to investigate regional solid Earth deformation rates from ice age and contemporary ice melt. This is especially interesting for low‐viscosity regions in the upper mantle beneath Antarctica and Greenland, where it is not fully understood how ice age and contemporary ice melting contribute to geodetic measurements of solid Earth deformation.

THE ASSESSMENT OF NATIONAL ROAD SURFACE CONDITIONS ANALYSIS BASED ON THE INTERNATIONAL ROUGHNESS INDEX (IRI) METHOD USING ROADROID APPLICATION

Road infrastructure is built as an infrastructure to meet needs and facilitate accessibility and mobility of socio-economic activities in the community. With the benefits that are so important, therefore the road construction and maintenance sector become a priority to be researched and developed in planning, implementing, and maintaining it. At the location of Jalan Khatulistiwa section, most of the road surface conditions are in moderate condition so the recommendation for improving road surface conditions is periodic maintenance on 56 segments and the other 13 segments are carried out routine maintenance. In the IRI measurement using the Roadroid application, there is a tendency to produce an IRI value that is greater than the IRI measurement using a laser profilometer, but the IRI value obtained by Roadroid tends to approach the IRI value as measured by a laser profilometer with an average percentage difference per segment of 2.91% with 2 segments that have different conditions. Based on the provisions of Pd-01-2021-BM, the IRI value test of the Roadroid has met the requirements as a class III measure of unevenness (IRI).

Protoype Sistem Penyiram Lahan Perkebunan Kangkung Otomatis Berbasis Internet of Things dengan Logika Fuzzy Sugeno

Watering is one of the jobs that are routinely carried out in plant maintenance which usually causes various problems. One of them is the absence of the same measure of water quantity when watering will result in the plants being treated can experience excess or lack of water, causing the plants to dry out or rot and die. So we need a tool that can help in terms of watering plants. The internet of things-based automatic watering machine for water spinach plantations is expected to be a system to assist farmers in watering especially kale that can detect moisture in the soil and temperature around the land and has scheduling options, automatic fuzzy and manual that can be controlled via the android application. which has been designed and can work based on the selected option. This tool is made using the Sugeno fuzzy logic method because this method is suitable for use in making decisions to find the values ​​of humidity and temperature that fluctuate and are less certain. Based on the results of the study, the average percentage difference in the humidity sensor is 0.016 % and the accuracy (accuracy) on the humidity sensor circuit is 99.98%, while the percentage difference in the temperature sensor is 0.02% and the accuracy (accuracy) on the LM35 temperature sensor circuit is 99.99%.

Thermal and atomic properties of hydrogen atom and diatomic molecules in Wilson-Racah Quantum System

In this study, a conventional quantum mechanics in which the potential function is not specified but replaced by specifying four parameters Wilson-Racah orthogonal polynomials in the energy and physical parameter space was presented. The wave function is written as a bounded sum of elements of a complete basis with these polynomials as expansion coefficients. By finding the asymptotic of these Wilson – Racah polynomials, the physical properties of the corresponding system (wave function, bound state energy spectrum and/or scattering phase shift) was obtained. Wilson – Racah quantum system was applied to determine the thermodynamics and atomic properties of Hydrogen atom and diatomic molecules. All properties of associated physical systems are obtained directly and simply from the asymptotic of the associated orthogonal polynomials. This new model, gives good an approximate prediction of the Hydrogen atom energy with an estimated average error of 0.125%. The proposed procedure merely relies on experimental values of five molecular constants. The average relative percentage deviations of the thermodynamic properties’ functions Q, U, C, S and F which are 2.42, 0.45, 0.30, 1.23 and 1.50% satisfied the experimental finding as ascertained. These represent satisfactory compromise between accuracy and rapid computations.

Modeling and optimization of photo-fermentation biohydrogen production from co-substrates basing on response surface methodology and artificial neural network integrated genetic algorithm

The main aim of the present study was to establish a relationship model between bio-hydrogen yield and the key operating parameters affecting photo-fermentation hydrogen production (PFHP) from co-substrates. Central composite design-response surface methodology (CCD-RSM) and artificial neural network-genetic algorithm (ANN-GA) models were used to optimize the hydrogen production performance from co-substrates. Compared to CCD-RSM, the ANN-GA had higher determination coefficient (R2 = 0.9785) and lower mean square error (MSE = 9.87), average percentage deviation (APD = 2.72) and error (4.3%), indicating the ANN-GA was more suitable, reliable and accurate in predicting biohydrogen yield from co-substrates by PFHP. The highest biohydrogen yield (99.09 mL/g) predicted by the ANN-GA model at substrate concentration 35.62 g/L, temperature 30.94 °C, initial pH 7.49 and inoculation ratio 32.98 %(v/v), which was 4.20 % higher than the CCD-RSM model (95.10 mL/g).

A real-time fire evacuation system based on the integration of Building Information Modeling and Augmented Reality

In the past decade, the drawings in construction projects' standard fire evacuation routes are usually guided in two-dimensional (2-D) views to explain hazardous areas and evacuation routes. Common users cannot interpret the drawings quickly, understand their exact position within the building, and select appropriate evacuation routes. Thus, when fires occur, the construction project's fire can cause damages, and the number of dead or injured workers involved can be high. Nowadays, Building Information Modeling (BIM) and Augmented Reality (AR) are used in construction projects to create construction in a three-dimensional (3-D) visualization. This study aims to create a prototype application that combines Building Information Modeling (BIM) and Augmented Reality (AR) to improve the fire evacuation system and provide real-time access to information for evacuating from hazardous locations. A marker-based location system was implemented, using a marker as a spatial index to link the physical location and virtual information. The system was tested for accuracy using the proposed system and the MATALL Laser Distance Meter on the 4th floor of the Department of Civil Engineering Building at Chulalongkorn University. The results showed that the average percentage difference from the current location to the exit measured by the proposed system was lower than that measured by the MATALL Laser Distance meter, with an average percentage difference of less than 2.2%. Therefore, the proposed system effectively provides real-time access to information such as the current location, exit, distance of the shortest route from the current location to the destination, and virtual green line, voice, and arrow direction for evacuation guidance. It is convenient for decision-making and helps users find destinations quickly and efficiently.

Solubility of Cortisone and Hydrocortisone in Supercritical Carbon Dioxide and Ethanol

Cortisone and hydrocortisone are poorly water-soluble corticosteroids widely used to treat many inflammatory and immune diseases. In the prospect of employing them in pharmaceutical applications or analytical techniques involving cosolvent-modified supercritical fluids, their solubility has been determined, for the first time, in a mixture of supercritical CO2 and 2, 3, or 4 mol % of ethanol, at 318.15, 328.15, 348.15, and 373.15 K, and in the pressure range of 13–27 MPa. Tests were conducted in a semi-flow laboratory apparatus, and results were fitted with the most popular density-based correlations reported in the literature for ternary systems. Even though the two drugs exhibit similar molecular structures, the solubility of cortisone in the ethanol-scCO2 mixtures is on average 3.5 times higher than that of hydrocortisone. This is congruent with the fact that the solubility of cortisone in pure ethanol is higher. The seven-parameter Reddy–Madras model (adjusted absolute average percent deviation (AARD%) = 8.8%) proved to be the best correlating one for cortisone while the six-parameter Garlapati–Madras approach (AARD% = 11.6%) provided the best fitting for hydrocortisone. The reliability of the experimental results was also confirmed by the positive response to the Méndez-Santiago–Teja self-consistency test.

Radiance consistency and deviation characteristics in the regions of overlap between three new-generation GEO meteorological satellites

ABSTRACT The combination of multi-source Geostationary Earth Orbit (GEO) satellites can realize simultaneous global observation with high frequency, which is significant to fine weather forecast and global climate change research. Here the radiance consistency and deviation characterization in the overlapping regions are analysed for three new generation GEO satellites, including the Advanced Himawari Imager (AHI) onboard the Himawari-8 satellite, the Advanced Baseline Imager (ABI) onboard the Geostationary Operational Environmental Satellite-17 (GOES-17) and the Advanced Geostationary Radiation Imager (AGRI) onboard FengYun satellite-4A (FY-4A). The result shows that the radiance has higher consistency for visible and near-infrared (VNIR) channels with correlation coefficient r > 0.98 than infrared (IR) channels with r > 0.90 in the overlapping regions of different GEO satellites. For FY-4A & Himawari-8, the average percentage deviation (APD) of VNIR channels is 5.54%–9.03%. The brightness temperature (BT) bias of IR channels is 1.16 K-2.50 K. For GOES-17 & Himawari-8, the APD of VNIR channels is 4.48%–6.71%, and the BT bias of IR channels is 0.96 K −2.76 K. Solar-viewing geometries significantly influence the radiance deviation in the over regions. The future work is to design a radiance fusion method and achieve cloud detection in ample space with high frequency by combining multi-source GEO satellites.

Toward Single-Time-Point Image-Based Dosimetry of 177Lu-PSMA-617 Therapy.

Radiopharmaceutical therapies (RPTs) with 177Lu-prostate-specific membrane antigen (PSMA) ligands have demonstrated promising results for the treatment of metastatic castration-resistant prostate cancer. The lack of absorbed-dose-effect relationships currently prevents patient-specific activity personalization. To ease the implementation of dosimetry in the routine clinical workflow for RPT, simplified methods such as single-time-point (STP) instead of multiple-time-point (MTP) imaging protocols are required. This work aimed at assessing differences in the time-integrated activity (TIA) of STP versus MTP image-based dosimetry for 177Lu-PSMA-617 therapy. Methods: Twenty metastatic castration-resistant prostate cancer patients with MTP quantitative 177Lu-SPECT imaging data (∼24, 48, and 72 h post injection (p.i.)) available on first and second 177Lu-PSMA-617 therapy cycles were included in this study. Time-activity curves were fitted for kidneys and lesions to derive effective half-lives and yield a reference TIA. STP approaches involved the formula by Hänscheid (STPH) and a prior-information method (STPprior) that uses the effective half-lives from the first therapy cycle. All time points were considered for the STP approaches. Percentage differences (PDs) in TIA between STP and MTP were compared for the second therapy cycle. Results: Using STPH at 48 h p.i. for kidneys showed a -1.3% ± 5.6% PD from MTP, whereas STPprior showed a PD of 4.6% ± 6.2%. The smallest average PDs for the 56 investigated individual lesions were found using STPprior at 48 h p.i., at only 0.4% ± 14.9%, whereas STPH at 72 h p.i. had a smallest PD of -1.9% ± 14.8%. Conclusion: STP dosimetry for 177Lu-PSMA-617 therapy using a single SPECT/CT scan at 48 or 72 h p.i. is feasible, with a PD of less than ±20% compared with MTP. The validity of both STPH and STPprior has been demonstrated. We believe this finding can increase the adoption of dosimetry and facilitate implementation in routine clinical RPT workflows. Doing so will ultimately enable the finding of dose-effect relationships based on fixed therapy activities that may, in future, allow for absorbed-dose-based RPT activity personalization.

Increasing solubility of phenytoin and raloxifene drugs: Application of supercritical CO2 technology

In the present investigation, the solubility of two drugs i.e., phenytoin and raloxifene, was obtained in supercritical CO2 at various temperatures and pressures. The obtained results were shown that the solubility of phenytoin and raloxifene, based on mole fraction, was between 0.68 × 10−6 to 15.70 × 10−6 and 0.79 × 10−5 to 8.09 × 10−5, respectively. The experimental solubilities data shown the direct influence of pressure on them; nevertheless, the extraction temperature had a different effect. Besides, two mathematical approaches based on thermodynamic models were used to model the phenytoin and raloxifene experimental results. Indeed, solubilities data were predicted using Peng-Robinson equations of state (PR EoS) in conjunction with three famous mixing rules i.e., Kwak-Mansoori (KM) and van der Waals (vdW) type I and II. The obtained results demonstrated the Peng-Robinson equations of state with the Kwak-Mansoori mixing rule predicted the solubilities of phenytoin and raloxifene drugs with more accuracy, especially at higher pressures (in order with an average percent deviation equal to 6.2282 and 5.5715, respectively). Moreover, three density-based correlations, as semi-empirical models, i.e., Garlapati and Madras, Bartle et al. and Mendez-Santiago Teja correlations, were used to model the phenytoin and raloxifene solubilities data. For both drugs, Bartle et al. model showed better performance.

Publicly available framework for simulating and experimentally validating clinical PET systems.

Monte Carlo (MC) simulations are a powerful tool to model medical imaging systems. However, before simulations can be considered the ground truth, they have to be validated with experiments. To provide a pipeline that models a clinical positron emission tomography (PET)/CT system using MC simulations after extensively validating the results against experimental measurements. A clinical four-ring PET imaging system was modeled using Geant4 application for tomographic emission (v. 9.0). To validate the simulations, PET images were acquired of a cylindrical phantom, point source, and image quality phantom with the modeled system and the simulations of the experimental procedures. For the purpose of validating the quantification capabilities and image quality provided by the simulation pipeline, the simulations were compared against the measurements in terms of their count rates and sensitivity as well as their image uniformity, resolution, recovery coefficients (RCs), coefficients of variation, contrast, and background variability. When compared to the measured data, the number of true detections in the MC simulations was within 5%. The scatter fraction was found to be 30.0%±2.2% and 28.8%±1.7% in the measured and simulated scans, respectively. Analyzing the measured and simulated sinograms, the sensitivities were found to be 8.2 and 7.8cps/kBq, respectively. The fraction of random coincidences were 19% in the measured data and 25% in the simulation. When calculating the image uniformity within the axial slices, the measured image exhibited a uniformity of 0.015±0.005, whereas the simulated image had a uniformity of 0.029±0.011. In the axial direction, the uniformity was measured to be 0.024±0.006 and 0.040±0.015 for the measured and simulated data, respectively. Comparing the image resolution, an average percentage difference of 2.9% was found between the measurements and simulations. The RCs calculated in both the measured and simulated images were found to be within the EARL ranges, except for that of the simulation of the smallest sphere. The coefficients of variation for the measured and simulated images were found to be 12% and 13%, respectively. Lastly, the background variability was consistent between the measurements and simulations, whereas the average percentage difference in the sphere contrasts was found to be 8.8%. The clinical PET/CT system was modeled and validated to provide a simulation pipeline for the community. The pipeline and the validation procedures have been made available (https://github.com/teaghan/PET_MonteCarlo).

Camera-based radiotherapy dosimetry using dual-material 3D printed scintillator arrays.

To describe a methodology for the dual-material fused deposition modeling (FDM) 3D printing of plastic scintillator arrays, to characterize their light output under irradiation using an sCMOS camera, and to establish a methodology for the dosimetric calibration of planar array geometries. We have published an investigation into the fabrication and characterization of single element FDM printed scintillators intending to produce customizable dosimeters for radiation therapy applications. 1 This work builds on previous investigations by extending the concept to the production of a high-resolution (scintillating element size 3×3×3mm3 ) planar scintillator array. The array was fabricated using a BCN3D Epsilon W27 3D printer and composed of polylactic acid (PLA) filament and BCF-10 plastic scintillator. The array's response was initially characterized using a 20×20cm2 6 MV photon field with a source-to-surface (SSD) distance of 100cm and the beam incident on the top of the array. The light signals emitted under irradiation were imaged using 200ms exposures from a sCMOS camera positioned at the foot of the treatment couch (210cm from the array). The collected images were then processed using a purpose-built software to correct known optical artefacts and determine the light output for each scintillating element. The light output was then corrected for element sensitivity and calibrated to dose using Monte Carlo simulations of the array and irradiation geometry based on the array's digital 3D print model. To assess the accuracy of the array calibration both a 3D beam and a clinical VMAT plan were delivered. Dose measurements using the calibrated array were then compared to EBT3 GAFChromic film and OSLD measurements, as well as Monte Carlo simulations and TPS calculations. Our results establish the feasibility of dual-material 3D printing for the fabrication of custom plastic scintillator arrays. Assessment of the 3D printed scintillators response across each row of the array demonstrated a nonuniform response with an average percentage deviation from the mean of 2.1%±2.8%. This remains consistent with our previous work on individual 3D printed scintillators which showed an average difference of 2.3% and a maximum of 4.0% between identically printed scintillators.1 Array dose measurements performed following calibration indicate difficulty in differentiating the scintillator response from ambient background light contamination at low doses (<20-25cGy) and dose rates (≤100 MU/min). However, when analysis was restricted to exclude dose values less than 10% of the Monte Carlo simulated max dose the average absolute percentage dose difference between Monte Carlo simulation and array measurement was 5.3%±4.8% for the fixed beam delivery and 5.4%±5.2% for the VMAT delivery CONCLUSION: In this study, we developed and characterized a 3D printed array of plastic scintillators and demonstrated a methodology for the dosimetric calibration of a simple array geometry.

The predictive ability of a QCT-FE model of the proximal femoral stiffness under multiple load cases is strongly influenced by experimental uncertainties

Despite significant improvements in terms of the predictive ability of Quantitative Computed Tomography based Finite Element (QCT-FE) models in estimating femoral strength (fracture load and stiffness), no substantial clinical adoption of this method has taken place to date. Narrowing the wide variability of FE results by standardizing the methodology and validation protocols, as well as reducing the uncertainties in the FEA process have been proposed as routes towards improved reliability. The aim of this study was to: First, validate a QCT-FE model of proximal femoral stiffness in multiple stance load cases, and second, using a parametric approach, determine the influence of select experimental and modeling parameters on the predictive ability of our model. Ten fresh frozen human femoral samples were tested in neutral stance, 15° adducted and 15° abducted load cases. Voxel-based linear-elastic QCT-FE models of the samples were generated to predict the models’ stiffness values in all load cases. The base FE models were validated against the experimental results using linear regression. Thirty six deviated models were created using the minimum and maximum values of experiment-based “plausible range” for 18 parameters in 4 categories of embedding, loading, material, and segmentation. The predictive ability of the models were compared in terms of the coefficient of determination (R2) of the linear regression between the measured and predicted stiffness values in all load cases. Our model was capable of capturing 90% of the variation in the experimental stiffness of the samples in neutral stance position (R2 = 0.9, concordance correlation coefficient (CCC) = 0.93, percent root mean squared error (RMSE%) = 8.4%, slope and intercept not significantly different from unity and zero, respectively). Embedding and loading categories strongly affected the predictive ability of the models with an average percent difference in R2 of 4.36% ± 2.77 and 2.96% ± 1.69 for the stance-neutral load case, respectively. The performance of the models were significantly different in adducted and abducted load cases with their R2 dropping to 71% and 70%, respectively. Similarly, off-axes load cases were affected by the parameters differently compared to the neutral load case, with the loading parameter category imposing more than 10% difference on their R2, larger than all other categories. We also showed that automatically selecting the best performing plausible value for each parameter and each sample would result in a perfectly linear correlation (R2> 0.99) between the “tuned” model’s predicted stiffness and experimental results. Based on our results, high sensitivity of the model performance to experimental parameters requires extra diligence in modeling the embedding geometry and the loading angles since these sources of uncertainty could dwarf the effects of material modeling and image processing parameters. The results of this study could help in improving the robustness of the QCT-FE models of proximal femur by limiting the uncertainties in the experimental and modeling steps.

A comparison of transient elastography with acoustic radiation force impulse elastography for the assessment of liver health in patients with chronic hepatitis C: Baseline results from the TRACER study.

Liver stiffness measurements can be used to assess liver fibrosis and can be acquired by transient elastography using FibroScan® and with Acoustic Radiation Force Impulse imaging. The study aimed to establish liver stiffness measurement scores using FibroScan® and Acoustic Radiation Force Impulse in a chronic hepatitis C cohort and to explore the correlation and agreement between the scores and the factors influencing agreement. Patients had liver stiffness measurements acquired with FibroScan® (right lobe of liver) and Acoustic Radiation Force Impulse (right and left lobe of liver). We used Spearman's correlation to explore the relationship between FibroScan® and Acoustic Radiation Force Impulse scores. A Bland-Altman plot was used to evaluate bias between the mean percentage differences of FibroScan® and Acoustic Radiation Force Impulse scores. Univariable and multivariable analyses were used to assess how factors such as body mass index, age and gender influenced the agreement between liver stiffness measurements. Bland-Altman showed the average (95% CI) percentage difference between FibroScan® and Acoustic Radiation Force Impulse scores was 27.5% (17.8, 37.2), p < 0.001. There was a negative correlation between the average and percentage difference of the FibroScan® and Acoustic Radiation Force Impulse scores ( r (95% CI) = -0.41 (-0.57, -0.21), p < 0.001), thus showing that percentage difference gets smaller for greater FibroScan® and Acoustic Radiation Force Impulse scores. Body mass index was the biggest influencing factor on differences between FibroScan® and Acoustic Radiation Force Impulse (r = 0.12 (0.01, 0.23), p = 0.05). Acoustic Radiation Force Impulse scores at segment 5/8 and the left lobe showed good correlation (r (95% CI) = 0.83 (0.75, 0.89), p < 0.001). FibroScan® and Acoustic Radiation Force Impulse had similar predictive values for the assessment of liver stiffness in patients with chronic hepatitis C infection; however, the level of agreement varied across lower and higher scores.

Computational fluid dynamics approach to study methane hydrate formation in stirred reactor

Hydrate formation management in oil and gas industries needs a detailed understanding of hydrate formation phenomena in terms of dynamics and kinetics aspects. Stirred reactors are one of the popular experimental systems to study hydrate formation/dissociation in terms of kinetics and thermodynamics mechanisms. Various processes/systems such as gas hydrate formation and decomposition phenomena in oil and gas facilities are simulated using computational fluid dynamics (CFD). This research examines the hydrate formation in a stirred reactor for a water-methane system using the Eulerian multiphase flow model by employing CFD software (STAR CCM +). The developed numerical model incorporates the conservation equations of momentum, mass, and energy, where the hydrate equations, including mass transfer, hydrate kinetics, and heat of hydrate formation, are included in the governing equations. In this paper, the methane hydrate formation in the stirred reactor for the stirring rate of 300 RPM and volume fraction of 0.04 with a pressure of 5,500 kPa is simulated. Then, the simulation results are validated using the experimental data collected from the literature, resulting in an overall absolute average deviation percentage (AAD%) of 15.6 %. The influences of stirring rate (300 to 500 RPM), methane volume fraction (0.04 to 0.4), pressure (3,500 to 7,500 kPa), and subcooling (1.96 to 9.23 °C) are studied on the hydrate formation in the agitated reactor. The results reveal that the developed CFD model can predict the methane hydrate formation in the stirred reactor with acceptable precision. According to the simulation runs, methane hydrate is formed mainly near the walls and around the stirrer blades. In addition, an increase in subcooling, gas volume fraction, pressure, and stirring rate leads to more hydrate formation in the reactor with a constant temperature of 274.3 K. The maximum mass fraction of hydrate is observed for the case when the gas volume fraction and stirring rates are 0.4 and 900 RPM, respectively. However, the minimum value of methane hydrate is 0.092 g, where the volume fraction and impeller speed are 0.04 and 300 RPM.The findings of this study can help to further understand hydrate formation phenomena in oil and gas facilities. This model can provide oil and gas engineering sectors with effective strategies to control and manage gas hydrates. In addition, the proposed CFD model can be helpful for engineers and researchers in the petroleum industry to simulate hydrate formation in other complicated geometries in petroleum facilities.

An Improved Farmland Fertility Algorithm with Hyper-Heuristic Approach for Solving Travelling Salesman Problem

Travelling Salesman Problem (TSP) is a discrete hybrid optimization problem considered NP-hard. TSP aims to discover the shortest Hamilton route that visits each city precisely once and then returns to the starting point, making it the shortest route feasible. This paper employed a Farmland Fertility Algorithm (FFA) inspired by agricultural land fertility and a hyper-heuristic technique based on the Modified Choice Function (MCF). The neighborhood search operator can use this strategy to automatically select the best heuristic method for making the best decision. Lin-Kernighan (LK) local search has been incorporated to increase the efficiency and performance of this suggested approach. 71 TSPLIB datasets have been compared with different algorithms to prove the proposed algorithm’s performance and efficiency. Simulation results indicated that the proposed algorithm outperforms comparable methods of average mean computation time, average percentage deviation (PDav), and tour length.

NUCLEAR REACTION CROSS-SECTION EVALUATION OF NEUTRON-INDUCED REACTIONS IN SOME COMMON REACTOR FUEL ISOTOPES OF SOME ELEMENTS AT ENERGY RANGE OF 13.6-15.2 MeV

As part of the effort to enrich the nuclear data library and combat the challenge of the scarcity of data, EXIFON 2.0 code has been used to evaluate the (n, p) of 54,56Fe, 55Mn, 58,60Ni, 27Al, 50Cr, and 239Pu. Results of the evaluated excitation functions obtained with the EXIFON code were compared with the ENDF data retrieved from IAEA Nuclear Data section of the ENDF data library. Some of the evaluated excitation functions agreed well with the ENDF data, while some show some degree of variance. The good agreement was obtained for nuclides with EVEN-EVEN nuclei. The overall percentage deviation of total cross section from ENDF values obtained is less than 1% for, 50Cr, 56,54Fe, 55Mn, 60Ni, 27Al and 239Pu except for 58Ni which is 4% while this work records an overall average percentage deviation of 0.5% . However, the results show good agreement with available retrieved data and hence can be used where data is scarce or grossly inadequate.

Measurement of Liquid–Liquid Flows Using Turbine Flowmeter and Conductance Sensor With Multiheight Electrodes in Vertical Pipes

Liquid–liquid two-phase flows are common industrial processes in chemical, petroleum, and other related fields. It is a great challenge for the flow measurement using the turbine flowmeter (TFM) in low-velocity liquid–liquid flows due to the serious slippage effect between the oil and water phases. The complex physical discrepancies between the two phases make the response of TFM vastly different from that in single-phase flow. This study proposes a system combining TFM and conductance sensors with multiheight electrodes (CSMHEs) to determine liquid–liquid two-phase flows. This study investigates the effects of phase distribution and slippage on the wheel hub drag torque. The model of wheel hub drag torque in different flow patterns is established, and a new variable meter factor model of TFM in liquid–liquid flows is constructed. Experiments in 20-mm simulated well reveal that the TFM can make accurate predictions of total flow rate and enable online measurements of individual phase superficial velocities. The absolute average percentage deviations (AAPDs) of superficial water and oil velocities are 2.01% and 7.24%, respectively.