Flow Technique Research Articles

Solubility of tris(2-methylbutyl) phosphate in supercritical carbon dioxide and its application for the recovery of uranium from U-Zr and U-Th aqueous solutions

The employment of supercritical fluid extraction (SFE) within the nuclear industry may reduce the environmental burden by reduction in solvent waste generation. In this perspective, a SFE based method was developed for selective extraction of uranium from U-Zr and U-Th solutions using tris-(2-methylbutyl) phosphate (T2MBP) as a ligand in supercritical carbon dioxide (SCCO2). Prior to SFE studies, the utilisation of T2MBP in SCCO2 was examined by carrying out solubility measurements using dynamic flow technique at (313−333) K and (10−20) MPa. T2MBP has sufficient solubility in SCCO2 and ranges from 2.55 × 10-2 mol·mol-1 to 8.95 × 10-2 mol·mol-1. The solubility increases with pressure and decreases with temperature, resulting in retrograde solubility behaviour. The experimental solubility data was successfully correlated using different density based semi-empirical equations. Based on the solubility data, selective recovery of uranium from U-Zr and U-Th solutions was demonstrated using SCCO2+T2MBP.

Hybrid Laminar Flow Control Optimizations for Infinite Swept Wings

Maintaining the laminar flow on surfaces through active control is a significantly promising technique for reducing fuel burn and alleviating environmental concerns in commercial aviation. However, there is a lack of systematic parameter studies for the hybrid laminar flow control (HLFC) together with natural laminar flow (NLF). To address this need, we optimize the infinite swept wings with different sweep angles and at various conditions, including different Mach numbers, Reynolds numbers, and lift coefficients. The Reynolds-averaged Navier-Stokes (RANS) solver coupled with the linear stability theory is applied for the laminar-turbulent transition prediction, and the traditional optimization method based on evolutionary algorithms is applied for laminar flow wing optimization. The optimization results found that HLFC is required when the NLF fails at a larger sweep angle (35°) and Reynolds number ( 20 × 10 6 ). The lower pressure peak with boundary-layer suction is found to delay the transition of the regional aviation condition. Besides, the pressure distribution of HLFC is similar to NLF results at the lower Reynolds number ( 10 × 10 6 ) or sweep angle (25°), i.e., a gentle negative pressure gradient near the leading edge and a small favorable pressure gradient behind it. Clarifying the characteristics of laminar flow wings will advance the application of the laminar flow technique within its field.

Turning waste into profit: Circular economic optimization of quartz sand from tin mining and processing

This paper analyzes whether the mining industry can apply circular economy principles in its investment, using two business scenarios of the circular economy. Scenario A utilizes quartz sand from tin mining residues and then processes it into concrete sand. Meanwhile, Scenario B is similar to Scenario A in the first stage, but the residue produced from the first stage is reprocessed to produce concrete sand. To compare the economic feasibility of both scenarios, this study applies a discounted cash flow technique and an incremental analysis. Material flow analysis investigates the circularity and productivity from resource utilization in every design. The two business scenarios are economically viable, but Scenario B is better than Scenario A. NPV of Scenarios A and B are US$ 513 thousand and US$ 322 thousand, respectively. The NPVB-A is US$ 147, whereas the IRR of Scenario A is 26.24 % and Scenario B is 34.05 %. The circularity of Scenarios A is 0.86 with a productivity of US$1.62/m3, and the circularity of Scenario B is 0.94 with a productivity of US$1.80/m3. Therefore, Scenario B is more efficient than that of Scenario A. Eventually, implementations of the circular economy principles in the mining industry are possible. These results can become a consideration for investors to innovate through circular economy approaches in their mining business for sustainable production and consumption purposes.

A fluorescent PIV technique for turbomachinery flows

This paper presents the development and applications of a fluorescent Particle Image Velocimetry (PIV) technique as a countermeasure for undesired light reflections on surfaces of channel walls or obstacles. The employment of the fluorescent dye-doped tracer particle with a wavelength-specific optical filter enables a separation of the stokes-shifted particle light emission from reflections on the surfaces. Aiming at applying the technique to engine-like turbomachinery flows, the fluorescent tracer particles were made out of pyrromethene 567 and Di-Ethyl-Hexyl-Sebacat considering multiple aspects of characteristics. The developed particles were firstly tested in a low-speed wind tunnel with a metal turbine blade placed in the flow path and a laser sheet oriented to impinge the blade surface. With the installation of an adequate optical filter, the undesired light reflections were successfully removed, and reasonable vector calculations were enabled in proximity to the reflective blade surfaces. Secondly, the fluorescent PIV was performed on a high-pressure turbine stage hosted in a high-speed short-duration rotating turbine rig to demonstrate the feasibility of the technique in engine-representative turbomachinery flows.

Visualization of recirculation zones over a perforated plate: An optical flow technique for characterization of fluid dynamics in structured packing

In the context of increasing the performance of structured packing used in distillation columns, we develop a state-of-the-art flow diagnostic method to investigate the intricate fluid dynamics of a falling film interacting with a perforation. Perforations are one of the several key microstructure elements in industrial structured packing whose role in mass transfer enhancement and liquid redistribution is yet not well understood. We focus the present investigation on the liquid curtain, or "twin film", blanketing the perforation. Twin films are prone to strong capillary waves and recirculation zones, and experiments of fundamental nature are required to assess the fluid dynamics in the curtain formation in the perforations and ultimately uncover mechanisms that intensify interfacial mass transfer. Here, a three-dimensional two-component (3D-2C PTV) optical-flow-based technique using the concept of defocus is implemented on a test bench designed to study the effect of perforations on falling liquid films. This method provides an opportunity to evaluate the hydrodynamics of the liquid curtain through streamline patterns and dynamic modes and to describe key features that could promote mass transfer intensification in structured packing.

From Batch to the Semi-Continuous Flow Hydrogenation of pNB, pNZ-Protected Meropenem.

Meropenem is currently the most common carbapenem in clinical applications. Industrially, the final synthetic step is characterized by a heterogeneous catalytic hydrogenation in batch mode with hydrogen and Pd/C. The required high-quality standard is very difficult to meet and specific conditions are required to remove both protecting groups [i.e., p-nitrobenzyl (pNB) and p-nitrobenzyloxycarbonyl (pNZ)] simultaneously. The three-phase gas-liquid-solid system makes this step difficult and unsafe. The introduction of new technologies for small-molecule synthesis in recent years has opened up new landscapes in process chemistry. In this context, we have investigated meropenem hydrogenolysis using microwave (MW)-assisted flow chemistry for use as a new technology with industrial prospects. The reaction parameters (catalyst amount, T, P, residence time, flow rate) in the move from the batch process to semi-continuous flow were investigated under mild conditions to determine their influence on the reaction rate. The optimization of the residence time (840 s) and the number of cycles (4) allowed us to develop a novel protocol that halves the reaction time compared to batch production (14 min vs. 30 min) while maintaining the same product quality. The increase in productivity using this semi-continuous flow technique compensates for the slightly lower yield (70% vs. 74%) obtained in batch mode.

Lowering risk intolerance to unlock private investments in renewable energy-based rural electrification

As public resources are scarce, investments from the private sector are essential to scale up rural electrification and thus to achieve universal access to electricity by 2030. However, the lack of clear public policies, together with a high perceived risk, have been a deterrent to investors' participation in off-grid electrification projects. In this paper, we focus on identifying the main drivers of risk, namely the set of uncertainties and perceived risks that prevent private companies from investing in off-grid electrification projects. We use a stochastic discount cash flow technique — net present value (NPV) combined with Monte Carlo simulation — to incorporate these uncertainties and quantify the business and investment risks associated with an off-grid solar PV project. The technique is applied to the case of Colombia, wherein major contributors to risk are the variability in revenues and the annual revenue growth rate. For this case, we estimate the probability of project failure and investigate how private companies could mitigate risks by keeping operating costs to <50 % of revenues. In this regard, the role of the government proves to be essential in providing a better investment environment for private investors. We suggest that government interventions could take the form of financial de-risking instruments, including better-designed end-user subsidies and the implementation of concession agreements through long-term contracts. These results are of interest to private investors who need to account for risk analysis when deciding whether to invest or not in off-grid projects. Also, our findings guide policymakers seeking to understand the private sector perspective while designing efficient policy mechanisms to increase access to electricity in developing countries.

A review on insects flight aerodynamics, noise sources, and flow control mechanisms

Wildlife always acts as an inspiration source for humans to help them study and mimic flight methods. Insects are one of the most important sources of biological systems’ inspiration to control flow and reduce aerodynamic noise. Insects are classified into different kinds, and most can fly by fluttering their wings. In general, insects’ flight muscles are divided into direct and indirect types that act synchronously and asynchronously with nerve impulses, respectively. These muscles help insects use a mixture of rotating, flapping, and pitching movements to achieve specific wing kinematics. Insects use various mechanisms for generating aerodynamic forces, including the Weis-Fogh or clap and fling mechanism, delayed stall due to unsteady motion (Wagner effect), wing rotation (Kramer effect), wake capture or wing–wake interaction, added mass, and absence of stall. On the other hand, the insect noises are divided into aerodynamic and structural. Insects’ aerodynamic noise is created by fluctuating forces, flow–solid interaction, shed vortex, and turbulence inflow. Meanwhile, insects’ structural noise is made by frictional and tymbal mechanisms. Their flow control methods are classified into two categories: wing shape and sub-structures. Wing shape features such as planform, chord length and location, twist, sweep, wingtip, and aspect ratio influence the flow around the insects. The sub-structures such as leading edge, trailing edge, swallowtail, and surface textures affect the flow too. A thorough understanding of insects’ fly, aerodynamic noise, and their control flow techniques will significantly help engineers to produce competitive products with better aerodynamic performance and aeroacoustic signature.

Model Predictive Control Based Energy Management System Literature Assessment for RES Integration

Over the past few decades, the electric power industry evolved in response to growing concerns about climate change and the rising price of fossil fuels. The usage of renewable energy sources (RES) rose as a remedy for these problems. The increased penetration of RES in the existing generation system increased the need for an intelligent energy management system (EMS) so that the system can operate in any possible circumstances. Many sectors of society, including the education sector, are working to realize the importance of this sustainable energy system. This paper reviews the process of selecting an efficient control technique for continuous power flow from different RES to meet the load demand requirement using an enhanced model predictive control (MPC)-based EMS framework. This EMS is a software platform to provide fundamental support services and applications to deliver the functionality needed for the effective operation of electrical generation and transmission facilities to ensure adequate security of energy supply at minimum cost. The centralized EMS with technical objectives focusing on power quality and seamless power flow can be achieved through dynamically enhanced MPC.

Combined experimental and theoretical study on the elastic electron scattering cross sections of ethanol

Combined theoretical and experimental studies on the elastic scattering of electrons on ethanol were performed in the energy range of 30–800 eV. The differential elastic electron scattering cross sections (DCS) of ethanol were measured for scattering angles of 30° to 150° using the relative flow technique and nitrogen (N2) as the reference gas. From these experimental DCS, integral elastic and momentum transfer cross sections were estimated. The comparison of the experimental results from the present work to those of other groups showed good agreement within the experimental uncertainty. In addition to the experimental determination, the DCS of ethanol were calculated by applying the independent atomic model with screening-corrected additivity rule and the modified independent atomic model. These theoretical calculations reproduced the experimental data well within the experimental uncertainty, with agreement better at high electron energies as was expected.Graphical abstract

Peningkatan Produktivitas Tanaman Hidroponik Menggunakan Tenaga Surya

Electricity is highly essential in hydroponic agriculture. To enhance the productivity of hydroponic plants, LED grow lights are used to provide illumination during the nighttime. This electrical energy is utilized for the circulation pump of the plant's nutrients and to power the LED grow lights. To address this, the approach taken is to harness solar energy and convert it into electrical energy. This conversion of solar energy into electrical energy is known as photovoltaic, which involves the use of solar cells as the device. The hydroponic system employed in this research is the Deep Flow Technique (DFT) hydroponic system. The circulation pump operates every hour for 10 minutes, while the LED grow lights are turned on from 20:00 to 24:00. On average, the plants grow approximately 0.8 to 1.5 cm per day, and the leaves grow around 1 to 2 strands per day. The total daily electricity requirement for the circulation pump amounts to 36.4 watt-hours.

Scalable conditional deep inverse Rosenblatt transports using tensor trains and gradient-based dimension reduction

We present a novel offline-online method to mitigate the computational burden of the characterization of posterior random variables in statistical learning. In the offline phase, the proposed method learns the joint law of the parameter random variables and the observable random variables in the tensor-train (TT) format. In the online phase, the resulting order-preserving conditional transport can characterize the posterior random variables given newly observed data in real time. Compared with the state-of-the-art normalizing flow techniques, the proposed method relies on function approximation and is equipped with a thorough performance analysis. The function approximation perspective also allows us to further extend the capability of transport maps in challenging problems with high-dimensional observations and high-dimensional parameters. On the one hand, we present novel heuristics to reorder and/or reparametrize the variables to enhance the approximation power of TT. On the other hand, we integrate the TT-based transport maps and the parameter reordering/reparametrization into layered compositions to further improve the performance of the resulting transport maps. We demonstrate the efficiency of the proposed method on various statistical learning tasks in ordinary differential equations (ODEs) and partial differential equations (PDEs).

Integrated intelligent neuro computing technique for mixed convective flow and heat transfer in heterogeneous permeability media

This article examines the flow and heat transfer characteristics of variable permeability such as linear, exponential and quadratic permeability functions with Brinkmann–Forchheimer extended Darcy model by utilizing the intelligent computing paradigm via artificial Levenberg–Marquardt back propagated neural networks (ALM – BPNNs). The vertical porous channel walls are considered as electrically conducting and non-conducting. The variable permeability and induced magnetic field effects are significant on flow and heat transfer. To solve the obtained governing equations, finite element method is adopted. It is observed that for the three cases of permeability functions, increase in Hartmann number drops the velocity profile and is accompanied with an increase in the fluid thermal state level. The significance of the Brinkmann number on the fluid temperature in all the cases of permeability indicates a rise in temperature due to increased heat generation. But, the reverse effect is observed when the mixed convection parameter rises, and the boundary layer thickness reduces due to which temperature drops for distinct cases of permeability under consideration. The heat transfer characteristics are analyzed through an artificial neural network and multiple linear regression models. The present work finds its applications in studying packed bed heat exchangers and fixed-bed catalytic reactors.

Ultrasensitive Hybridization Chain Reaction-Assisted Multisite Exonuclease III Amplification Strategy Combined with a Direct Quantitative Fluorescence Lateral Flow Technique for Multiple Bacterial 16S rRNA Detection.

Accurate and in-time detection of bacteria conduces to preventing their rapid spread around the environment, while a nucleic acid test (NAT) is a powerful tool for early diagnosis of pathogens. Herein, we propose a hybridization chain reaction (HCR)-mediated multisite exonuclease III (Exo-III) amplification strategy (HCR/Exo-III amplifier) to achieve the one-pot and ultrasensitive isothermal amplification of bacterial 16S rRNA and a portable fluorescence detection device (PFD) to directly read signals in a lateral flow assay (LFA). In detail, the target-initiated HCR products present multiple binding sites for triggering the Exo-III amplifier that produces numerous target amplicons. Following that, the target amplicons travel up on the strip and bridge between the DNA-CdTe/CdS probes and the capture DNA to form a positive fluorescence line. After that, the strip is inserted into the PFD to accomplish the fluorescence signal reading. The constructed HCR/Exo-III amplifier-based PFD-LFA implemented the simultaneous and specific detection of three bacteria with a detection limit of a few tenths of fM for synthetic 16S rRNA fragments and dozens of CFU/mL for Staphylococcus aureus, Listeria monocytogenes, and Salmonella typhimurium in pure cultures. The sensing platform features isothermal amplification, convenient operation, and good economy, displaying great potential for on-site testing toward multiple nucleic acid analytes.

Nonlinear solver based on trust region approximation for [formula omitted] utilization and storage in subsurface reservoir

Simulation of CO2 utilization and storage (CCUS) in subsurface reservoirs with complex heterogeneous structures requires a model that captures multiphase compositional flow and transport. Accurate simulation of these processes necessitates the use of stable numerical methods that are based on an implicit treatment of the flux term in the conservation equation. Due to the complicated thermodynamic phase behavior, including the appearance and disappearance of multiple phases, the discrete approximation of the governing equations is highly nonlinear. Consequently, robust and efficient techniques are needed to solve the resulting nonlinear system of algebraic equations. In this study, we present a powerful nonlinear solver based on a generalization of the trust-region technique for compositional multiphase flows. The approach is designed to embed a newly introduced Operator-Based Linearization technique and is grounded on the analysis of multi-dimensional tables related to parameterized convection operators. We split the parameter space of the nonlinear problem into a set of trust regions where the convection operators preserve the second-order behavior (i.e., they remain positive or negative definite). We approximate these trust regions in the solution process by detecting the boundary of convex regions via analysis of the directional derivative. This analysis is performed adaptively while tracking the nonlinear update trajectory in the parameter space. The proposed nonlinear solver locally constrains the update of the overall compositions across the boundaries of convex regions. We tested the performance of the proposed nonlinear solver for various scenarios. In many cases, our approach yields an improved behavior of the nonlinear solution in comparison to state-of-the-art solvers.

A Review of State-of-the-Art Techniques for Power Flow Analysis

This paper presents a review of the State-of-the-Art Techniques for Power Flow Analysis (PFA) that are newly proposed. However, some of the existing classical methods for the Power Flow Analysis such as Newton-Raphson method, Gauss-Siedel method, and Fast Decoupled Power Flow Technique were also discussed so as to give a background and a wider view of the improvements recorded so far. From the findings, the State-of-the-Art Techniques such as Particle Swamp Optimization Algorithm for optimal Power Flow Incorporating Wind Farms, Hybrid Firefly and Particle Swamp Optimization Algorithm, Mann Iteration Process Technique for III-Conditioned System, and A New Approach Newton-Raphson Load Flow Analysis in Power System Networks with STATCOM have shown superiority over and above the existing classical methods in terms of accuracy, speed of convergence and overall efficiency. Particularly, there are two newly proposed methods for dc grids: Direct Matrix–Current application (DM-CA) and Direct Matrix-Impedance Approximation (DM-IA) methods that stand out with respect to accuracy, convergence and computational effort which means they can be used for planning, optimization and analysis purposes of practical dc grids.

Oscillator strengths and cross sections of the valence-shell excitations of CH[formula omitted]I studied by fast electron scattering

Oscillator strengths and cross sections of the valence-shell excitations in CH3I are important for studying molecular photodissociation and monitoring the destruction of ozone in the Earth’s atmosphere. Based on the relative flow technique, absolute generalized oscillator strengths of the valence-shell excitations in CH3I have been determined by using an angle-resolved electron energy loss spectrometer. The measurement was carried out at an incident electron energy of 1.5 keV and an energy resolution of 80 meV. Optical oscillator strengths for the dipole-allowed transitions have been obtained at the zero limit of the squared momentum transfer, providing an independent cross check with the previous experimental results. The integral cross sections from the excitation threshold to 5000 eV have also been obtained by means of the BE-scaling method. The present experimental oscillator strengths and cross sections can supplement the fundamental spectroscopic data of CH3I and will play an important role in the studies of molecular photodissociation dynamics.

Visualization of Gas-Liquid Interfacial Behavior in a Narrow Channel Using High-Speed Neutron Imaging

Gas-liquid two-phase flow is a very complicated flow phenomenon that involves the interaction between gas and liquid phases. Recently, an accurate simulation technique of two-phase flow has been developed. However, the validation of the simulated results is insufficient due to less experimental data. It is especially difficult to measure interfacial behavior with significant spatio-temporal fluctuation. To understand such phenomena, measurement methods with high spatial and temporal resolutions are required. Neutron imaging is a powerful tool for two-phase flow visualization. It can be applied to flow measurement in an opaque channel and has applicability to the heated condition. In this study, two-phase flow in the narrow rectangular channel was visualized by high-speed neutron imaging. The dynamics of the interfacial structure of air-water flow were investigated from the neutron transmission images, and the liquid film behavior was observed qualitatively.

Fabrication of Rapid Electrical Pulse-Based Biosensor Consisting of Truncated DNA Aptamer for Zika Virus Envelope Protein Detection in Clinical Samples

Zika virus (ZV) infection causes fatal hemorrhagic fever. Most patients are unaware of their symptoms; therefore, a rapid diagnostic tool is required to detect ZV infection. To solve this problem, we developed a rapid electrical biosensor composed of a truncated DNA aptamer immobilized on an interdigitated gold micro-gap electrode and alternating current electrothermal flow (ACEF) technique. The truncated ZV aptamer (T-ZV apt) was prepared to reduce the manufacturing cost for biosensor fabrication, and it showed binding affinity similar to that of the original ZV aptamer. This pulse-voltammetry-based biosensor was composed of a T-ZV apt immobilized on an interdigitated micro-gap electrode. Atomic force microscopy was used to confirm the biosensor fabrication. In addition, the optimal biosensor performance conditions were investigated using pulse voltammetry. ACEF promoted aptamer-target binding, and the target virus envelope protein was detected in the diluted serum within 10 min. The biosensor waveform increased linearly as the concentration of the Zika envelope in the serum increased, and the detection limit was 90.1 pM. Our results suggest that the fabricated biosensor is a significant milestone for rapid virus detection.

Microlayer dynamics of hydrodynamically interacting vapour bubbles in flow boiling

Nucleate boiling, a ubiquitous heat transfer mode, involves multiple vapour bubble nucleations on the heater surface and offers high heat transfer coefficients. The bubble growth process on a heating substrate involves the formation of microlayer, a thin liquid film trapped between the growing bubble and the heating substrate, and contributes to the bubble growth phenomenon through evaporation. Microlayer dynamics for a single bubble have been widely investigated in the pool and flow boiling conditions. However, the literature on multiple bubbles interactions and their associated microlayer information is scarce. Notably, in the case of flow boiling, where the microlayer dynamics are not symmetric due to the bubble's movement, the bubbles’ interaction and its influence on associated microlayer dynamics have never been reported. Therefore, microlayer and bubble dynamics in multiple interactions have been investigated experimentally using simultaneous application of thin-film interferometry and high-speed videography techniques in flow boiling with water as the working fluid. Our experimental investigation revealed that the secondary nucleation could cause a reduction in lift-off time and may assist or hinder the movement of the first bubble. The experimental results also demonstrated that the secondary nucleation could deplete the microlayer of the first bubble hydrodynamically even when the bubbles are far apart. Furthermore, it has been found that the microlayer depletion rate depends on the growth rate and the location of the secondary nucleation. Hence, this experimental study emphasises the need to consider the interaction of bubbles while modelling boiling flows to avoid overestimating the contribution of microlayer evaporation.