Flux Distribution Research Articles

Tailoring Zn2+ Flux by an Ion Acceleration Layer Modified Separator for High-Rate Long-Lasting Zn Metal Anodes.

A large concentration gradient originating from sluggish ion transport on the surface of Zn metal anodes will result in uneven Zn2+ flux, giving rise to severe dendrite growth, especially at high current density. Herein, an ion acceleration layer is introduced by a facile separator engineering strategy to realize modulated Zn2+ flux and dendrite-free deposition. Zinc hexacyanoferrate as the modifying agent featuring strong zincophilicity and rapid diffusion tunnel can enable fast trap for Zn2+ near the electrode surface and immediate transport onto deposition sites, respectively. The ion acceleration effect is substantiated by improved ion conductivity, decreased activated energy, and promoted Zn2+ transference number, which can moderate concentration gradient to guide homogenous Zn2+ flux distribution. As a result, the separator engineering guarantees Zn||Zn symmetrical cells with long-term stability of 2700 h at 2 mA cm-2, and 1770 h at a large current density of 10 mA cm-2. Moreover, cycling stability and rate capability for full cells with different cathodes can be substantially promoted by the modified separator, validating its superior practical feasibility. This study supplies a new scalable approach to tailoring ion flux near the electrode surface to enable robust Zn metal anodes at a high current density.

Static and Dynamic Regulation of Precursor Supply Pathways to Enhance Raspberry Ketone Synthesis from Glucose in Escherichia coli.

Raspberry ketone (RK), a natural product derived from raspberry fruit, is commonly utilized as a flavoring agent in foods and as an active component for weight loss. Metabolic engineering has enabled microorganisms to produce RK more efficiently and cost-effectively. However, the biosynthesis of RK is hindered by an unbalanced synthetic pathway and a deficiency of precursors, including tyrosine and malonyl-CoA. In this study, we constructed and optimized the RK synthetic pathway in Escherichia coli using a static metabolic engineering strategy to enhance the biosynthesis of tyrosine from glucose, thereby achieving the de novo production of RK. Additionally, the synthetic and consumption pathways of malonyl-CoA were dynamically regulated by p-coumaric acid-responsive biosensor to balance the metabolic flux distribution between cell growth and RK biosynthesis. Following pathway optimization, the medium components and fermentation conditions were further refined, resulting in a significant increase in the RK titer to 415.56 mg/L. The optimized strain demonstrated a 32.4-fold increase in the RK titer while maintaining a comparable final OD600 to the initial strain. Overall, the implemented static and dynamic regulatory strategies provide a novel approach for the efficient production of RK, taking into account cell viability and growth.

Self‐Assembling Design Method of Stator Slots for AC Rotating Machines

To maximize the performance of rotating machines, it is essential to establish a design method with minimal arbitrariness. This paper proposes a self‐assembling method to design stator slots for alternating current (AC) rotating machines. First, we develop a line‐current approximation model of the stator winding using pulse‐width modulation technique and realize an ideal spatial magnetic flux density distribution. Subsequently, we design the realistic stator with an acceptable current density of the winding by forming unique slot shapes in a self‐assembling manner under two synthetic conditions using the developed line‐current approximation model as the starting model. The designed stator realizes a rotating magnetic field similar to the conventional design results. Additionally, we perform an analysis of motor rotation characteristics by combining the self‐assembled stator with a surface‐mounted permanent magnet rotor to determine the possibility of a higher output compared to that when using a conventional stator. The self‐assembled motor without relying on empirical rules shows a possibility of further improving the torque characteristics, thereby contributing to designing the AC rotating machines. © 2024 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.

A boundary-type algorithm based on the discrete ordinates for neutron transport equation

The spatial distribution of neutron flux in the core of a nuclear reactor plays a crucial role in ensuring nuclear safety. It can be determined by solving the neutron transport equation, where computational resource consumption is gradually receiving more attention, especially in problems with multiple reflective boundary conditions. It is common practice to assume initial boundary values in one angular direction to obtain a global solution, and then use reflective boundary conditions to solve for the other directions, iterating until convergence. However, this approach has the drawback of requiring the global solution, and each iteration necessitates storing the neutron flux values, consuming time and storage space. In order to address this issue, this paper proposes a precise and efficient boundary-type method, the Half Boundary Method (HBM). This method establishes relationships between adjacent node values through integration and mathematical deduction, ultimately obtaining the relationship among any node and the boundary values in any direction. As a result, iteration is only required for boundary values, reducing the iteration amount and thus saving time and storage space. Using the discrete ordinate (SN) method for angular discretization and HBM for spatial discretization, this paper solved the steady-state neutron transport equation for two-dimensional systems modeled with Cartesian geometry. The method is validated using several benchmark problems, including the 2D ISSA benchmark, the 2D mono-group k-eigenvalue problem and BWR rod bundle test problem. All of these problems demonstrate good results and effectively reduced computational time.

Numerical modelling and experimental investigations to predict the tool wear of copper electrodes during µ-EDM process

The micro electrical discharge machining (µ-EDM) process is one of the most widely used techniques to produce miniaturized components in micro-electro mechanical system (MEMS) applications due to its inherent advantages. This work investigates the wear phenomena and the morphology of the copper electrodes during the micro-die sinking process. A numerical model of a single spark is developed assuming the Gaussian distribution of heat flux to estimate the crater dimensions formed in the copper tool electrode (tool wear) used as a result of electric discharge. The crater dimension attained from the ABAQUS finite element model is validated with experimental results using a single spark test setup. Moreover, the effect of input parameters namely capacitance and voltage on the electrode wear rate and surface roughness is also studied. The crater dimensions from the single discharge study are used to formulate the wear model for different possibilities of crater distribution, such as non-overlapping craters, craters with less than 30 % overlap, and 50 % overlap. The electrode wear rate (EWR) also displayed a decline from 20.4 % to 11.6 % and further to 8 % when the overlap was permitted up to 30 % and up to 50 % for the wear model respectively. The developed model results are further compared with experimental results in terms of the electrode wear rate and depth of erosion and the deviations are found to be 20.33 % and 20.55 % respectively

Numerical study on heat transfer of two-phase fluid in helical coil pipe under ocean condition

The thermal hydraulic characteristics and heat transfer of two-phase fluid in helical coil once-through steam generator under ocean conditions like rolling and heaving motions are studied numerically. A CFD model is established to analyze the effects of motion parameters like amplitude, period and rolling radius and the heat flux distribution are discussed. The analysis shows that the overall heat transfer decreases under ocean conditions, but the overall deterioration is limited, indicting the helical coil pipe has the stability for ocean conditions. The additional forces like Coriolis, centrifugal and inertial forces introduced by rolling motion are analyzed theoretically and the result shows it detorts the original two main vortexes responsible for high heat transfer due to its spiral geometry, making heat transfer fluctuates up and down periodically near the steady state value. As rolling height increases, the heat transfer is nonlinear due to the competition between Coriolis force and centrifugal and inertial forces. As rolling amplitude increases, the heat transfer variation increases and the local heat transfer deterioration is severely aggravated, indicating high rolling amplitude should be avoided as possible. Increasing rolling period makes heat transfer behavior more approximate to static case as gravity and centrifugal force due to spiral geometry is dominate. Under heaving motion, the overall heat transfer decreases, and increasing heaving amplitude and decreasing period make the fluctuation more severe.

Dynamic analysis for ultra-supercritical boiler water wall considering uneven heat flux distribution and combustion instability

The dynamic characteristics of water-cooled wall are of great significance to the evaluation of the safety and flexibility for the boiler during peak shaving process. However, few dynamic studies considered the uneven heat flux distribution on the water-cooled wall, let alone the variable heat load caused by the combustion instability. In this paper, a segmented dynamic model is developed for the water-cooled wall of a 660 MW ultra supercritical boiler. The model is validated under steady and dynamic working conditions, respectively. Then, the step responses of the steam temperature in different flow loops under different load conditions are comparatively studied under the disturbances of single-parameter changes. In the cases of 10 % step decrease of either the feedwater temperature, the heat load or the feedwater mass flowrate, the outlet steam temperature is influenced greatly by the step decreased feedwater temperature under 100 % BMCR condition, while it is impacted most by the step decreased feedwater mass flow under 50 % THA condition. Under these disturbances, the outlet steam temperature of the tube with higher heat loads has larger variation and longer response time. In addition, the simulated combustion instability by the sinusoidal fluctuating heat load on the water wall is employed to explore the influences of the flame fluctuation amplitude and frequency to the water wall. The maximum steam temperature rises with the increase in amplitude but drops with the frequency of flame fluctuation. The thresholds for the flame fluctuation amplitude and frequency are obtained under different load conditions.

Spatiotemporal distribution of pCO2 and CO2 flux and the regulatory factors: From the perspective of a subtropical canyon-shaped reservoir, southwest China

Reservoir carbon cycling is a critical component of the global carbon cycle, particularly in subtropical canyon-shaped reservoirs where unique geomorphological features and hydrological regulation under monsoon climate provide a distinct perspective for carbon cycle research. This study takes the Zipingpu Reservoir (ZPPR) in southwestern China as an example and reveals significant seasonal variations in partial pressure of carbon dioxide (pCO2) and carbon dioxide flux at the water-air interface (FCO2) through annual monitoring. The average pCO2 in ZPPR is 486 μatm, and the average FCO2 is 0.093 g C m-2d-1, with approximately 42.4 % of FCO2 measurements being negative, indicating the reservoir's role can act as a carbon sink. The study also estimated the gas transfer coefficient (K), with an average value of 1.888 md-1. Peak FCO2 during spring and summer is three times higher than in other seasons, consistent with the main influencing factors of inflow dynamics, metabolic processes, and reservoir operation strategies. Inflow and operational activities, particularly during spring and summer, drive CO2 emissions in the downstream reach and upstream tributary, while biological activity facilitates CO2 uptake in the lacustrine area and forebay tributary, with enhanced absorption occurring in the autumn. Concurrently, high-intensity FCO2 emissions from the upstream river section during summer underscore the importance of carbon emission monitoring and management during critical periods. The findings not only enhance the understanding of FCO2 assessment accuracy but also provide a framework for evaluating and optimizing carbon dynamics management strategies in canyon-shaped reservoirs, contributing valuable insights to global carbon cycle research.

Comparison of Heat Transfer Performance of Lattice-Structured Heat Sinks

This paper presents a comparative study of the heat transfer performance of lattice-structured heat sinks. Twenty different unit cells are chosen, and heat sinks are modeled in nTop with constant unit cell size. Al 6061 alloy is chosen as the material for analysis due to its good thermal conductivity, low weight, low cost, and high strength. Steady-state thermal analysis is performed using ANSYS with constant input parameters for all samples. Heat flux and temperature distribution within the heat sinks are analyzed. From the simulation, it was found that TPMS and plate-based heat sinks outperform other types with better heat transfer.

A multiscale hybrid modelling methodology for cell cultures enabled by enzyme-constrained dynamic metabolic flux analysis under uncertainty

Mammalian cell cultures make a significant contribution to the pharmaceutical industry. They produce many of the biopharmaceuticals obtaining FDA-approval each year. Motivated by quality-by-design principles, various modelling methodologies are frequently trialled to gain insight into these bioprocesses. However, these systems are highly complex and uncertain, involving dynamics at different scales, both in time and space, making them challenging to model in a comprehensive and fully mechanistic manner. This study develops a machine-learning-supported multiscale modelling framework of cell cultures, linking the macroscale bioprocess dynamics to the microscale metabolic flux distribution. As a relevant biopharmaceutical case study, we consider the production of Trastuzumab by Chinese Hamster Ovary (CHO) cells in batch. A macroscale hybrid model is constructed by integrating macro-kinetic and machine-learning approaches. Enzyme-constrained Dynamic Metabolic Flux Analysis (ecDMFA) is adopted to calculate flux distributions based on the dynamic predictions of the hybrid model. Uncertainty estimation of the multiscale model is conducted through bootstrapping. Judging from experimental data, our hybrid model can reduce the modelling error of the macroscale dynamics to 8.0%; a 70% reduction from the purely mechanistic model. In addition, the predicted dynamic flux distribution aligns with observations seen in literature, highlighting important metabolic changes throughout the process. Model uncertainty is maintained at a low level, demonstrating the trustworthiness of the predictions. Overall, our comprehensive modelling framework has the potential to facilitate the development of digital twins in the biopharmaceutical industry.

Genome-Scale Metabolic Modeling of Halomonas elongata 153B Explains Polyhydroxyalkanoate and Ectoine Biosynthesis in Hypersaline Environments.

Halomonas elongata thrives in hypersaline environments producing polyhydroxyalkanoates (PHAs) and osmoprotectants such as ectoine. Despite its biotechnological importance, several aspects of the dynamics of its metabolism remain elusive. Here, we construct and validate a genome-scale metabolic network model for H. elongata 153B. Then, we investigate the flux distribution dynamics during optimal growth, ectoine, and PHA biosynthesis using statistical methods, and a pipeline based on shadow prices. Lastly, we use optimization algorithms to uncover novel engineering targets to increase PHA production. The resulting model (iEB1239) includes 1534 metabolites, 2314 reactions, and 1239 genes. iEB1239 can reproduce growth on several carbon sources and predict growth on previously unreported ones. It also reproduces biochemical phenotypes related to Oad and Ppc gene functions in ectoine biosynthesis. A flux distribution analysis during optimal ectoine and PHA biosynthesis shows decreased energy production through oxidative phosphorylation. Furthermore, our analysis unveils a diverse spectrum of metabolic alterations that extend beyond mere flux changes to encompass heightened precursor production for ectoine and PHA synthesis. Crucially, these findings capture other metabolic changes linked to adaptation in hypersaline environments. Bottlenecks in the glycolysis and fatty acid metabolism pathways are identified, in addition to PhaC, which has been shown to increase PHA production when overexpressed. Overall, our pipeline demonstrates the potential of genome-scale metabolic models in combination with statistical approaches to obtain insights into the metabolism of H. elongata. Our platform can be exploited for researching environmental adaptation, and for designing and optimizing metabolic engineering strategies for bioproduct synthesis.

Hemispheric Asymmetry of Ionospheric Poynting Flux During Geomagnetically Quiet Periods

AbstractUsing a large database containing DMSP F13 observations under geomagnetically quiet conditions from 1998 to 2009, the hemispheric asymmetries of the distribution of the Poynting flux were investigated. Significant hemispheric asymmetries were observed in both altitude‐adjusted corrected geomagnetic (AACGM) and geographic coordinates, and the maximum average flux in the northern hemisphere was greater than that in the southern hemisphere by a factor of three in both coordinates. The distribution of downward Poynting flux hot‐spot (DPFH) between the two hemispheres had longitudinal difference of ∼180°. The Poynting flux's hemispheric asymmetry in AACGM and geographical coordinates at different seasons were investigated. The observed seasonal variations in the Southern Hemisphere (SH) are not as significant as those in the Northern Hemisphere (NH). In addition, the downward net Poynting flux observed during the solstice period is greater than that observed for the equinox period above 60°S.

Core Loss Analysis of Axial Modular Flux Switching Permanent Magnet Machine Considering the Impact of No‐Magnetic Ring

This paper investigates the relationship between the distributions of the core loss and the flux density harmonic amplitude along the axial direction in an axial‐modular flux‐switching permanent‐magnet (AM‐FSPM) machine. The flux leakage in the no‐magnetic ring leads to an uneven distribution of flux density in the core due to the modular cooperation structure. Subsequently, variations in the fundamental flux density amplitudes in the PM field and the armature reaction field are obtained with changes in the thickness of the no‐magnetic ring. In addition, the impact of no‐magnetic ring thickness on machine torque and core loss is analyzed to determine the optimal thickness for the no‐magnetic ring. Finally, the validity of the theoretical analysis is confirmed by experimental validation. © 2024 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.

An experimental study of the CHF in a square channel with non-uniformly heated rod under low pressure and low flow conditions

Experimental research on critical heat flux (CHF) was carried out in a vertical square channel with non-uniformly heated rod at low pressure and low flow conditions. The influence of inlet subcooling on CHF was also investigated. The results showed that the CHF position of the non-uniformly heat flux distribution mainly appeared in the middle and lower part of the heater rod. More significantly, it was found that CHF was enhanced with the rise of the inlet subcooling. The CHF data measured in this experiment were also assessed with the commonly used CHF empirical correlations suitable for low pressure and low flow. The results indicated that the general correlations predicting for CHF of uniform heat flux distribution were not applicable for prediction CHF of non-uniform heat flux distribution and these correlations usually overestimated the experimental values. In addition, The F-factor approach proposed by Tong was used to predict the experimental data and the error predicted by F-factor were mostly between 30 % and 50 %. Finally, F-factor was modified based on experimental data and the error between the predicted value and experimental results was between 0 and 30 %, and most of the data was between 0 and 20 %.

The Galaxy Activity, Torus, and Outflow Survey (GATOS). IV. Exploring Ionized Gas Outflows in Central Kiloparsec Regions of GATOS Seyferts

Utilizing JWST MIRI/Medium Resolution Spectrograph integral field unit observations of the kiloparsec-scale central regions, we showcase the diversity of ionized gas distributions and kinematics in six nearby Seyfert galaxies included in the GATOS survey. Specifically, we present spatially resolved flux distribution and velocity field maps of six ionized emission lines covering a large range of ionization potentials (15.8–97.1 eV). Based on these maps, we showcase the evidence of ionized gas outflows in the six targets, and find some highly disturbed regions in NGC 5728, NGC 5506, and ESO137-G034. We propose active galactic nucleus (AGN)-driven radio jets plausibly play an important role in triggering these highly disturbed regions. With the outflow rates estimated based on [Ne V] emission, we find the six targets tend to have ionized outflow rates converged to a narrower range than the previous finding. These results have an important implication for the outflow properties in AGN of comparable luminosity.

Development of diesel combustion with low cooling loss and high dispersion spray using two-dimensional optical measurements

In this study, a novel, high-efficiency, and clean combustion concept utilizing low cooling loss and high dispersion spray is proposed. The research aims to validate the objectives of this concept through spatiotemporal analysis of phenomena when key variables such as combustion chamber shape, spray parameters, and swirl are modified. This new combustion approach focuses on achieving low heat loss by using smaller nozzle diameters, multi-hole nozzles, and reduced swirl compared to conventional combustion. The combustion chamber is designed with an increased cavity diameter and an expanded taper diameter to enhance upward spray dispersion, thereby reducing fuel spray penetration into the cavity and decreasing cooling loss. This configuration reduces the fuel spray penetration in cavity, achieving a reduction in cooling heat loss. Furthermore, to increase the volume in the lower part of the combustion chamber, a corner-bottom shape is employed. Additionally, by causing spray impingement through the corner bottom shape, the strategy aimed to prevent the return of the mail injections to the central part of the combustion chamber. These parameters were evaluated using two-dimensional optical measurements, which calculated thermal flux, temperature, velocity, and KL value distributions. The impact of cavity diameter on internal cooling loss is significant, and preventing flame stagnation from a smoke perspective is crucial. An increase in taper diameter reduces squish velocity, achieving heat losses reduction, while necessitating spray dispersion into the squish area. The influence of swirl ratio on heat losses is more pronounced in the squish and taper areas than inside the cavity, necessitating consideration of flame temperature reduction within the cavity when reducing swirl ratios. The implementation of double after injection influences low heat losses and avoids flame stagnation, enabling soot reduction. The corner bottom shape combustion chamber proved effective in reducing heat losses and particulate matter (PM) at medium and high loads.

PreMevE‐MEO: Predicting Ultra‐Relativistic Electrons Using Observations From GPS Satellites

AbstractUltra‐relativistic electrons with energies greater than or equal to two megaelectron‐volt (MeV) pose a major radiation threat to spaceborne electronics, and thus specifying those highly energetic electrons has a significant meaning to space weather communities. Here we report the latest progress in developing our predictive model for MeV electrons in the outer radiation belt. The new version, primarily driven by electron measurements made along medium‐Earth‐orbits (MEO), is called PREdictive MEV Electron (PreMevE)‐MEO model that nowcasts ultra‐relativistic electron flux distributions across the whole outer belt. Model inputs include >2 MeV electron fluxes observed in MEOs by a fleet of GPS satellites as well as electrons measured by one Los Alamos satellite in the geosynchronous orbit. We developed an innovative Sparse Multi‐Inputs Latent Ensemble NETwork (SmileNet) which combines convolutional neural networks with transformers, and we used long‐term in situ electron data from NASA's Van Allen Probes mission to train, validate, optimize, and test the model. It is shown that PreMevE‐MEO can provide hourly nowcasts with high model performance efficiency and high correlation with observations. This prototype PreMevE‐MEO model demonstrates the feasibility of making high‐fidelity predictions driven by observations from longstanding space infrastructure in MEO, thus has great potential of growing into an invaluable space weather operational warning tool.

Asymmetrical distribution of buoyancy flux and its effect on smoke propagation velocity and backlayering length in inclined tunnel fires

Inclined tunnels are commonly seen in modern society. Compared with horizontal tunnel fires, smoke movement in inclined tunnel fires exhibits noticeable asymmetry. In this study, a series of numerical simulations are conducted to investigate the asymmetrical distribution of source buoyancy flux and its impact on smoke movement in inclined tunnel fires. Because of buoyancy and the stack effect, the proportion of the buoyancy flux of the smoke advancing towards the upper portal, η, varies with time. When the fire plume impinges the tunnel ceiling, there is an initial distribution of buoyancy flux and the value of η is determined by tunnel inclination angle α. Subsequently, η gradually increases until the steady state is achieved. The growth trajectory of η with time is also controlled by α, but the steady-state value is dependent on both α and the fire location. Models are established to calculate η in different stages. The value of η influences smoke flow characteristics. Smoke propagation velocity scales with the cubic root of buoyancy flux per unit width, which can be derived based on η. Additionally, the backlayering length increases with the steady-state value of η. The findings contribute to a better understanding of the mechanisms governing the smoke flow in inclined tunnel fires.

Research on the high-performance computing method for the neutron diffusion spatiotemporal kinetics equation based on the convolutional neural network

Due to the uncertainty of computational results and the lack of interpretability of models in solving physical field equations in current deep learning, this paper designs a convolutional neural network that can be used to solve the neutron diffusion spatiotemporal kinetics equation in polar and cylindrical coordinate systems. This algorithm directly utilizes the macroscopic cross-section of the material without using the lattice homogenization method, replaces the finite volume method with the extended matrices, and solves the extended matrices using the convolutional kernels instead of the iterative algorithms. Taking the simplified Tsinghua High Flux Reactor (THFR) as an example, the feasibility of the algorithm is verified on the PyTorch platform and compared with the calculation results of the source iteration method running on the GPU. The calculation results show that when the number of grids in the radial and axial sections of the simplified THFR model is 804,600 and 3,576,000, respectively, and the algorithm is iterated 3000 times, the normalized power of the convolutional neural network and the source iteration method converges to 10−10, and the maximum point by point error of the neutron flux density of the above two algorithms converges to 10−5. The computational time consumed by the convolutional neural network is approximately 880.64 s and 3729.62 s, which reduces the computational time by 4.66% and 5.05% compared to the GPU parallel accelerated source iteration method, and the former consumes 43.75% less memory compared to the latter. The convolutional neural network is mainly used as the virtual physics engine for the THFR digital twin system, in addition to solving the neutron diffusion spatiotemporal kinetics equation and further improving computational speed. The algorithm directly utilizes the neutron macroscopic cross-section of the material to calculate the neutron flux density distribution without using the lattice homogenization, providing theoretical guidance and algorithm support for developing the high-precision multi-physical field coupling model.

Active flux based adaptive and non-adaptive observer for sensorless interior permanent magnet synchronous machine drive

The use of the interior permanent magnet synchronous machine (IPMSM) drive has profoundly increased in a large number of applications due to numerous advantages. Owing to the disadvantages of mechanical sensors, sensorless control techniques are employed to enhance the performance of the IPMSM drive by removing the effect of noise and gain drift due to the sensor, increasing reliability, cost saving, and reducing overall size. This article presents the comparative analysis between the adaptive observer and non-adaptive extended electromotive force (EEMF) observer based on the active flux concept in a stationary reference frame (α–β). Moreover, the effect of slot harmonics and non-sinusoidal distribution of rotor flux is present in the three-phase IPMSM, this problem is considered as the control system disturbances in this article. Due to the non-sinusoidal distribution of flux and slot harmonics, the observer structure in the rotating reference frame (d–q) fails to estimate at the low-speed operation range. Comparative analysis between adaptive and non-adaptive observer structures is provided for a wide speed range. The effectiveness of the observer structures is examined using the classical field-oriented control scheme. In the end, simulation and experimental results are demonstrated to validate the performance of the sensorless control scheme using the adaptive and non-adaptive observer structures for the three-phase IPMSM drive setup.