Conductivity Distribution Research Articles

Changes in Thermal Conductivity of the Rocks of the West Siberian Basin Lithosphere in the Vicinity of the Tumenskaya SG-6 Well

Numerical reconstructions of the thermal regime of the lithosphere of the West Siberian basin in the Koltogor-Urengoi graben in the vicinity of the Tyumenskaya SG-6 superdeep well are used to analyze the depth distribution of thermal conductivity of basin rocks. Five depth intervals which differ in the character of changes in thermal conductivity of rocks are distinguished: the permafrost zone, the sedimentary section below this zone, the zone of anomalous rock weakening, the consolidated crust, and the mantle. The algorithms for calculating the thermal conductivity are considered and the main factors affecting its change with depth are determined for each of the five intervals. A sharp decrease in the thermal conductivity of rocks in the bottom part of the sedimentary cover and in the basement top in the vicinity of the SG-6 well is associated with rock weakening due to tectonic fracturing and hydrothermal erosion. The analysis suggests that the stationarity conditions of the process are not observed in optical scanning thermal conductivity measurements and, therefore, this method may overestimate the true thermal conductivity of rocks.

Revealing the interlayer orientations for bilayer graphene grown on hexagonal boron nitride by c-AFM measurement

Owing to its excellent properties in optical and electronic applications, twisted bilayer graphene (TBG) has attracted extensive research attention. As an encapsulation layer, hexagonal boron nitride (h-BN) is indispensable for fabricating TBG devices. Because h-BN and graphene exhibit similar lattice structures, TBG on h-BN exhibits periodic moiré patterns, which enable interlayer orientations to be revealed for bilayer graphene on h-BN. Herein, we used two-step chemical vapor deposition to synthesize TBG exhibiting multiple twist angles on h-BN. Conductive atomic force microscopy measurements revealed that the conductivity distribution was different for the graphene/h-BN and TBG moiré patterns. Using the characteristics of the moiré patterns formed by these layers, h-BN and graphene interlayer orientations were precisely determined. This provides a feasible method for investigating the turbostratic arrangement of few-layer van der Waals heterostructures.

A Database of Snow on Sea Ice in the Central Arctic Collected during the MOSAiC expedition

Snow plays an essential role in the Arctic as the interface between the sea ice and the atmosphere. Optical properties, thermal conductivity and mass distribution are critical to understanding the complex Arctic sea ice system’s energy balance and mass distribution. By conducting measurements from October 2019 to September 2020 on the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition, we have produced a dataset capturing the year-long evolution of the physical properties of the snow and surface scattering layer, a highly porous surface layer on Arctic sea ice that evolves due to preferential melt at the ice grain boundaries. The dataset includes measurements of snow during MOSAiC. Measurements included profiles of depth, density, temperature, snow water equivalent, penetration resistance, stable water isotope, salinity and microcomputer tomography samples. Most snowpit sites were visited and measured weekly to capture the temporal evolution of the physical properties of snow. The compiled dataset includes 576 snowpits and describes snow conditions during the MOSAiC expedition.

Electrical conductivity and species distribution of aluminum chloride and 1‐butyl‐3‐methylimidazolium chloride ionic liquid electrolytes

AbstractElectrical conductivity (σ) of aluminum chloride (AlCl3) and 1‐butyl‐3‐methylimidazolium chloride (BMIC) ionic liquid (IL) was investigated as a function of temperature and AlCl3 mole fraction ( ). Electrochemical impedance spectroscopy was used to measure the electrical conductivity. Composition of AlCl3:BMIC ionic liquid was varied by changing the from 0 to 0.67. The temperature was changed from 70°C to 110°C at 10°C intervals. It was found that the electrical conductivity increases with an increase in temperature. Electrical conductivity increases with from 0 to 0.5 and then starts to decrease after = 0.5. A species concentration profile was developed based on thermodynamic model at room temperature for the IL containing , , , , , , and at different . The only anion species presents between 0 and 0.5 are and . Anions like , , , and are found at higher . A good agreement between the model and the experimental data was obtained. The variations in anion concentration, molecular structure, and cation–anion interactions are to be the causes of the changes in electrical conductivity of AlCl3:BMIC system.

Effect of Mulching on Soil Quality in an Agroforestry System Irrigated with Reused Water

In this study, a special rice-energy willow/poplar agroforestry system was used to analyze the effects of reused water irrigation and mulching on soil salinity, earthworm biomass and abundance, soil organic matter (SOM) content and weed coverage in treerow-dependent habitats. After three-year-irrigation, we investigated the woody line (WL), the buffer zone (BZ) and the crop line habitats (CL). Between 2019 and 2021, we collected data on the distribution of soil-specific electrical conductivity (EC), ammonium-lactate soluble sodium (AL-Na) and exchangeable cations (Na+, K+, Ca2+, Mg2+) and soil NO2− + NO3−-N contents from CL habitats irrigated with effluent water from an intensive catfish farm. Based on our results, significantly greater earthworm abundance (274 pc m−2) and earthworm biomass (54.0 g m−2) values were measured in WL than in BZ or CL habitats. There was no significant difference in weed coverage between the CL (0.61%) and BZ (1.91%), but weeds were significantly denser on the WL (12.3%). In the third year, the EC, AL-Na and ESP values were lower, but the SOM was higher in mulched soil (183.1 mS cm−1, 253.1 mg kg−1, 4.4 ESP% and 4.597%, respectively) than in un-mulched soil.

Concentrations and health risk appraisal of heavy metals and volatile organic compounds in soils of automobile mechanic villages in Ogun State, Nigeria.

This report presents the findings of the concentrations, distributions and health risks assessment of heavy metals (HMs) and volatile organic compounds (VOCs) in topsoils of two typical automobile mechanic villages (MVs) situated within Ogun State, Nigeria. One of the MVs is located in basement complex terrain (Abeokuta), while the second is in the sedimentary formation (Sagamu). Ten composite samples were collected at depth of 0-30cm with the aid of soil auger from spent oil-contaminated spots within the two MVs. The chemical parameters of interest were Pb, Cd, benzene, ethylbenzene, toluene, total petroleum hydrocarbon (TPH) as well as oil and grease (O&G). In addition, soil pH, cation exchange capacity (CEC), electrical conductivity (EC) and particle size distribution were also evaluated in order to find out their impacts on assessed soil pollutants. Results revealed that the soils in both MVs are of sandy loam texture, slight acidic to neutral pH, mean CEC < 15 cmol/kg and mean EC > 100 μS/cm. The mean concentration of each of analyzed HMs and VOCs in soils from the two MVs was < 5mg/kg, while the mean values of TPH and O&G content were > 50mg/kg. The mean Cd values in soils of both MVs were higher than the national soil screening level of 0.8mg/kg, but lower than the Canadian and Italian guidelines. There is no significant correlation between each of HMs/VOCs and any of assessed soil physicochemical variables. The non-cancer risk expressed in terms of hazard index (HI) was > 1 via oral ingestion route for adults and children at the two MVs, indicating adverse non-carcinogenic health risk. The HI > 1 value was obtained for adults only through the dermal absorption pathway in Abeokuta MV. However, HI values for the two age groups at the two MVs via inhalation route were < 1, indicating no likelihood of any non-carcinogenic effects via the breathing exposure. The potential of non-cancer risk via oral ingestion route in both MVs was derived from the contributive ratios of HMs and VOCs in the order: Cd > benzene > Pb > toluene. The carcinogenic risk (CR) values due to ingested Cd, benzene and Pb for both age groups at the two MVs exceed the safe limit range of 10-6 to 10-4. Cadmium, benzene and lead made considerable contributions to the estimation of CR through dermal exposure for adults only in Abeokuta MV. The CR values via inhalation pathway for adults and children in both MVs were within the threshold range. Artisans and children should circumvent accidental ingestion of contaminated soils in addition to wearing of protective clothes during routine vehicle maintenance activities.

Innovative hydrogeophysical approach for detecting the spatial distribution of hydraulic conductivity in Bahri city, Sudan: A comparative study of Csókás and Heigold methods

Hydraulic conductivity is one of the crucial parameters used to identify the potentiality and productivity of groundwater aquifers. This research employs an integrated approach using geophysical well logging, exploratory factor analysis and surface electrical resistivity methods to detect the vertical and horizontal variation of hydraulic conductivity in Bahri city, Sudan. Based on the geophysical well logs of Spontaneous potential (SP), natural gamma ray (GR), and electrical resistivity (RS), Csókás method is used to determine the continuous variation of hydraulic conductivity along the aquifer. Csókás method is an experimentally modified version of the Kozeny–Carman equation and is based on the formation factor of the groundwater aquifer and the effective grain size. This approach is performed in three groundwater boreholes, and the obtained hydraulic conductivities showed a close agreement with that of the pumping test analysis. Furthermore, the hydraulic conductivity is measured using multivariate statistical factor analysis. This statistical approach relies on the correlation between the extracted factors and petrophysical and hydrogeological parameters. In this research, a strong negative linear correlation between the first factor and hydraulic conductivity is indicated. Consequently, a site-specific equation is suggested for continuous estimation of hydraulic conductivity along the aquifer. In the last stage, the results obtained from the Csókás method are interpolated with vertical electrical sounding (VES) measurements using to detect the horizontal variation of hydraulic conductivity throughout the studied area. This was achieved by combining the hydraulic conductivities of geophysical well logging and vertical electrical soundings to obtain a consistent estimation. As a result, the variation of hydraulic conductivity is obtained, and the average was 1.9 m/day which shows a close agreement with the average of the previous investigations (1.5 m/day). This approach is highly recommended since it can enhance data coverage, cutting down the expense of hydrogeological investigations and lowering the uncertainty of the hydrogeological models.

Conductance distributions in correlated disordered metals

Conductance is a vital ingredient for understanding electronic transport in disordered systems. In this paper, we report numerical computations of the logarithmic conductance distribution based on the Landauer technique of a one-dimensional noninteracting power-law correlated Anderson model. In particular, we investigate the role of disorder correlations in diagonal potential on the conductance distribution function at the center of the band. The distribution reveals a clear signature of the delocalization phase transition, triggered by the internal correlations in the disordered distribution in the correlated disordered model. For localized states, the probability distribution function is Gaussian, while for extended states, it is lognormal. Furthermore, the system exhibits universal logarithmic conductance fluctuations in the insulating regime and tends to diverge at the delocalization transition in the thermodynamic limit.

Estimation of the Soil Water Content Using the Early Time Signal of Ground-Penetrating Radar in Heterogeneous Soil

Ground-penetrating radar (GPR) is an important tool for measuring soil water content (SWC) at the field scale. The amplitude analysis of the early time signal (ETS) of GPR may provide a rapid way to estimate SWC. By assuming a homogeneous medium, various studies have been conducted on the relationship between the amplitude of ETS and the topsoil layer’s electromagnetic parameters (dielectric permittivity and conductivity) through numerical simulations, laboratory experiments, and field experiments. Soil is a typical inhomogeneous medium, and soil cultivation is a factor affecting its heterogeneity. In this context, we discuss the ability of the amplitude of ETS to estimate the water content of heterogeneous soil. First, we establish a multi-scale stochastic medium model with the inhomogeneous distribution of dielectric permittivity and conductivity and simulate the GPR response by the finite-difference time-domain (FDTD) method to observe the influence of medium heterogeneity on the GPR response. The heterogeneity of the soil models is evaluated by a geostatistical analysis described by two parameters, correlation length and variability. Then, we analyze the relationship between variability and the average envelope amplitude (AEA) of ETS. A strong soil heterogeneity increases the error of the AEA method in estimating SWC. Finally, the AEA method is used to estimate the SWC of two adjacent fields with different heterogeneities, which were caused by different cultivation methods. The results of the numerical simulation and field experiment indicate that the soil heterogeneity can have an impact on the estimation of SWC using EST, with an error lower than 3% within a depth range of 1/2 λ to λ (wavelength). This suggests that the EST of GPR can be applied to soil layers with relatively large lateral changes in water content.

3D hydrostratigraphic and hydraulic conductivity modelling using supervised machine learning

Accurately modeling highly heterogenous aquifers is one of the big challenges in hydrogeology. There is a pressing need to develop new methods that transform high-resolution data into hydrogeological parameters representative of such aquifers. We use random forest-based machine learning to predict the distribution of hydrostratigraphic units and hydraulic conductivity (K) at a regional scale. We used lithologic logs from >2000 boreholes and resistivity-depth models from 2717 km of Airborne Electromagnetics (AEM). Eighty unique lithologic categories are lumped into 5 hydrostratigraphic units. K data is derived from descriptions of grain size and texture. The input data are resampled into a 200 × 200 × 1m grid and split into 70% training and 30% validation. K prediction had a training F1 score of 95% and 87% testing accuracy. After hyperparameter tuning these scores improved to 99.6% and 92%, respectively. Hydrostratigraphic unit prediction showed a training F1 score of 97% and 91% testing accuracy, improving to 100% and 95% after hyperparameter tuning. This method produces a high-resolution 3D model of K and hydrostratigraphic units that fills gaps between widely spaced boreholes. It is applicable in any setting where boreholes and AEM are available and can be used to build robust groundwater models for heterogeneous aquifers.

Nanoscale Intertwined Biphase Nanofiber as Active and Durable Air Electrode for Solid Oxide Electrochemical Cells

The poor temperature activity and durability due to surface Sr segregation are two main challenges restricting the practicability of state-of-the-art La1–xSrxCo1–yFeyO3 (LSCF) air electrodes for solid oxide electrochemical cells (SOCs). This article reports the recent discovery to unleash the constraints of performance and stability by constructing a novel nanofiber air electrode consisting of a LSCF host and GDC guest in nanoscale intertwined moiety (LSCF/GDC NF). The electrical conductivity relaxation and distribution of relaxation time results collectively disclosed the boosted surface oxygen exchange rate by two orders of magnitude at moderate SOC operation conditions (600 °C), as compared to commercial LSCF (1.01 × 10–3 cm s–1 vs 4.1 × 10–5 cm s–1). As a result, the electrochemical performance was synchronically promoted by over 5-fold (0.12 Ω·cm2 vs 0.64 Ω·cm2). Moreover, the interval stability test over 200 h in switching atmospheres (air/H2O/CO2) buttresses the superb robustness of LSCF/GDC NF with an extremely slow deactivation rate of 1.79 × 10–6 Ω·cm2 h–1 and nondetectable top-surface Sr segregation, collectively affirmed by X-ray photoelectron spectroscopy and low-energy ion scattering spectra. At atomic scale, the operando X-ray diffraction results preliminarily unravel that the formation of intertwined moiety employs the compressive strain on LSCF, which maintains the length of Sr–O against thermoinduced elongation. In addition, systemically, XPS and density functional theory simulation results prove the thermodynamically favored formation of oxygen vacancies at the biphase boundary in LSCF/GDC NF and raised the energy barrier for the formation of an intrinsic vacant Sr site. This study provides a practical and facile strategy to engineer the air electrode with enhanced performance and durability.

Estimation method of layered ground thermal conductivity for U-tube BHE based on the quasi-3D model

The distribution of ground thermal conductivity (λs) is a significant consideration for the design of ground source heat pump systems. This paper proposed a new method to estimate the layered λs for U-tube borehole heat exchanger (BHE) using particle swarm optimization (PSO) and distributed thermal response test (DTRT) data. Firstly, a quasi-3D heat transfer model considering geothermal gradient for U-tube BHE had been built to simulate fluid temperature profiles. And the experiment in DTRT was performed using a 45 m sandbox. Then, the layered λs were estimated through PSO and DTRT data based on the established model. The results showed that the convergent λs distribution could be reliably obtained by short-term DTRT. Furthermore, the estimation results are independent of the number of layers and data points. The mean difference in λs distribution between 9 layers and 45 layers is 0.007 W/(m∙K) and the layered λs also could be obtained when the number of layers is more than the number of temperature data points, and the root mean square error between 30 and 220 points is less than 0.3 W/(m∙K).

Sodium concentration imaging in dermis layer by square-wave open electrical impedance tomography (SW-oEIT) with spatial voltage thresholding (SVT)

In this study, sodium concentration in the dermis layer is imaged by the square wave open electrical impedance tomography (SW-oEIT) with spatial voltage thresholding (SVT). The SW-oEIT with SVT consists of three steps which are (1) voltage measurement, (2) spatial voltage thresholding, and (3) sodium concentration imaging. In the 1st step, the root mean square voltage is calculated based on the measured voltage under the square wave current through the planar electrodes on the skin domain Ω. In the 2nd step, the m-th measured voltage is converted to a compensated voltage v * based on the voltage electrodes distance and threshold distance in order to highlight the region of interest of the dermis layer In the 3rd step, sodium concentration is imaged by the Gauss-Newton reconstruction method. The SW-oEIT with SVT was applied to multi-layer skin simulation and ex-vivo experiments under various dermis sodium concentrations c in the range of 5–50 mM. As an image evaluation result, the spatial mean conductivity distribution in is successfully determined as increasing c on both simulations and experiments. The relationship between and c was evaluated by the determination coefficient R 2 and the normalized sensitivity The optimized with the highest evaluation values of 0.84 and 0.83 is under the condition of = 2 mm. Based on the signal evaluation, the SW-oEIT with SVT has a 15.32% higher correlation coefficient CC compared to the conventional oEIT based on sinewave injection.

Natural convection due to lateral uniform heat flux in a slender porous cavity saturated with nanofluid: Departure from LTE state

The present article deals with the influence of the local thermal nonequilibrium (LTNE) state on natural convection in an enclosure filled with nanofluid-saturated porous medium. The flow is induced due to the maintenance of constant heat flux on the vertical walls and insulation of horizontal walls. The Darcy model has been adopted to describe the flow governing equations. These equations are solved numerically by using the alternate direction implicit method and analytically by applying parallel flow assumptions valid for large aspect ratios. Boundary layer analysis is performed to report the boundary layer thickness ( δ x ∼ 2 1 / 2 ( k nf / k f ) 1 / 10 ( R a T ) − 1 / 5 ) as well as the heat transfer rate of nanofluid ( N u nf ∼ ( k nf / k f ) − 1 / 5 R a T 2 / 5 ) . The combined effect of LTNE state parameters (interface heat transfer coefficient (H), porosity scaled thermal conductivity ratio (γ)) and volume fraction of nanoparticle ( ϕ ) is addressed on the flow dynamics and heat transfer mechanism. Rigorous analysis, indicates that the average heat transfer rate of nanofluid and solid porous matrix are increasing function of H and γ, however, the role of γ is accelerated for a relatively high value of H. For increasing the value of γ from 1 to 10, the enhancement in the heat transfer rate of nanofluid is reported to be up to 27% at 10% volume fraction of nanoparticles. The average Nusselt number of nanofluid, as well as solid phase, are reduced when the value of ϕ is increased under the LTNE circumstances. Furthermore, the flow structure is controlled by unicellular structure with rotating anticlockwise direction in the entire study. For the very small value of H the temperature distribution in the solid porous matrix is mainly by conduction mode and distribution is linear, however, for a relatively high value of H the distribution in the same is controlled by both conduction as well as convection, and it will be more pronounced for the higher value of γ.

Simultaneous inversion for source field and mantle electrical conductivity using the variable projection approach

Time-varying electromagnetic field observed on the ground or at a spacecraft consists of contributions from (i) electric source currents, such as those in the ionosphere and magnetosphere, and (ii) corresponding fields induced by source currents within the conductive Earth’s interior by virtue of electromagnetic induction. Knowledge about the spatio-temporal structure of inducing currents is a key component in ionospheric and magnetospheric studies, and is also needed in space weather hazard evaluation, whereas the induced currents depend on the Earth’s subsurface electrical conductivity distribution and allow us to probe this physical property. In this study, we present an approach that reconstructs the inducing source and subsurface conductivity structures simultaneously, preserving consistency between the two models by exploiting the inherent physical link. To achieve this, we formulate the underlying inverse problem as a separable nonlinear least-squares (SNLS) problem, where inducing current and subsurface conductivity parameters enter as linear and nonlinear model unknowns, respectively. We solve the SNLS problem using the variable projection method and compare it with other conventional approaches. We study the properties of the method and demonstrate its feasibility by simultaneously reconstructing the ionospheric and magnetospheric currents along with a 1-D average mantle conductivity distribution from the ground magnetic observatory data.Graphical

Cover crop and biofuel crop effects on hydraulic properties for claypan soils

AbstractPerennial biofuel and cover crops systems are important for enhancing soil health and can provide numerous soil, agricultural, and environmental benefits. The study objective was to investigate the effects of cover crops and biofuel crops on soil hydraulic properties relative to traditional management for claypan soils. The study site included selected management practices: cover crop (CC) and no cover crop (NC) with corn/soybean rotation, switchgrass (SW), and miscanthus (MI). The CC mixture consisted of cereal rye, hairy vetch, and Austrian winter pea. The research site was located at Bradford Research Center in Missouri, USA, and was implemented on a Mexico silt loam. Intact soil cores (76‐mm diam. by 76‐mm long) were taken from the 0–10, 10–20, 20–30, and 30–40 cm depths with three plot replicates and two sub‐samples per plot replicate per depth. Soil hydraulic properties evaluated for each sample included: saturated hydraulic conductivity (Ksat), water retention, bulk density, and pore size distributions. Results showed with the test of Duncan's least significant differences that treatments of MI (1.18 Mg m−3) and SW (1.21 Mg m−3) had lower values of bulk density averaging across soil depth than CC (1.27 Mg m−3) and NC (1.31 Mg m−3). Management systems significantly increased Ksat with the biofuel treatments at 0–10 cm compared to NC system. The MI management showed a significant increase in macroporosity and fine mesoporosity as compared to other management systems. Slight changes have occurred in the measured soil physical properties for CC system compared to NC plots. Overall, increasing soil organic matter from more plant roots from long‐term biofuel cropping systems can improve soil water storage and crop productivity.

Power and efficiency optimizations of a simple irreversible supercritical organic Rankine cycle

Based on finite time thermodynamics, a simple irreversible supercritical organic Rankine cycle (SORC) model is set up. Subjected to the total heat conductance constraint of heat exchangers, the power output (PO) and thermal efficiency (TE) of the SORC are maximized firstly by varying the heat conductance distributions of heat exchangers and mass flow rate of organic working fluid. The results reveal that in the discussed variation ranges of the optimization variables, the PO and TE of the SORC after triple optimizations are augmented by 39.45% and 7.13%, respectively, and the optimization effects of the triple optimizations are remarkable. Moreover, the optimization results gained by the triple maximizations of the PO and TE, respectively, are evidently different. In the discussed working fluids, the order of the triple maximum POs of the SORCs is R143a > R218 > R125 > R41 > R245fa, thus the recommended working fluid corresponding to the largest PO is R143a. The multi-optimization of the PO and TE are secondly performed by using NSGA-II, the optimal parameters of the SORCs with R125 and R143a acquired by TOPSIS and Shannon Entropy decision-making methods are taken for the optimal design schemes, respectively. The gained results in this paper offer useful design guidelines for the practical SORCs.

Improved Magneto-Acousto-Electrical Computed Tomography (MAE-CT) With Multi-Angle Plane Wave Excitation.

As a tissue conductivity imaging method, magneto-acousto-electric tomography (MAET) has the advantage of high axial spatial resolution compared with traditional electrical impedance imaging methods. However, it has the problems of difficulty in imaging targets with irregular conductivity distribution and poor lateral spatial resolution. Although the rotation-based MAET method can partly solve the irregular target problem, there is still a poor imaging signal-to-noise ratio (SNR) problem. Our previous study established a framework of an innovative MAET method, which has a very similar imaging theory and reconstruction algorithm to those of computed tomography (CT). Therefore, we name the method magneto-acoustic-electric computed tomography (MAE-CT). This paper proposes an improved implementation of MAE-CT based on multi-angle plane wave excitation. This method combines the electronic steering of the linear array transducer with the mechanical rotation to increase the number of projection angles while keeping the imaging complexity. In this study, we first established a finite element simulation model to verify the method's feasibility. Then phantom experiments were conducted to systematically investigate the performance of the proposed method. Finally, in vitro liver tissue experiment was conducted to further explore the feasibility of the method. The experimental results show that our method improves both the SNR and spatial resolution of the reconstructed image. For the phantom results, this method can detect conductivity of 0.67 S/m in an area with a size of 2 mm. To the best of our knowledge, this is the best result of spatial resolution available for MAET.

Multi-objective optimization of recompression S-CO2 cycle for gas turbine waste heat recovery

Recompression supercritical carbon dioxide Brayton cycle (RCSCBC) has important application prospects in the fields of gas turbine waste heat recovery. A RCSCBC model considering finite temperature difference heat transfer between heat reservoir and working fluid, irreversible compression, irreversible expansion and other irreversibility losses is established. Then the mass flow rate of the working fluid, cycle pressure ratio and the heat conductance distribution ratios of four heat exchangers are taken as optimization variables, the multi-objective coordinated optimization with net power output, exergy efficiency, thermal efficiency and ecological function as the goals is carried out, and an artificial neural network model is constructed to solve the problem of long optimization time. The results show that the decision-making result by Shannon Entropy method for the four-objective optimization has the lowest deviation index, and is the optimal. Compared with the initial design point, the thermal efficiency of the cycle for the optimization results by the Shannon Entropy method can reach 40.69%, which is increased by 29.8%. The net power output can reach 10.972 MW, which is increased by 9.5%. The ecological function can reach 7.265 MW, which is increased by 114.75%. The exergy efficiency can reach 74.72%, which is increased by 24.22%.

Towards understanding uniformity of megasonic-assisted through-mask electrochemical micromachining based on bubble dynamics

In through-mask electrochemical micromachining (TMEMM), bubbles on the anode surface can lead to ohmic voltage drop and non-uniform conductivity distribution, resulting in lower etching accuracy. With the advantages of low cavitation effect, strong acoustic streaming and high acoustic intensity, megasonic facilitates the reduction of bubble accumulation on the anode surface, thus improving etching accuracy. In this paper, a multiphysics field simulation model is developed to predict the two-phase flow evolution and etching profile at the anode interface. The simulation results show that the gas content at the anode interface in the megasonic field is low, and the gas distribution is relatively uniform. The etching depth and etching uniformity of TMEMM are improved. Experiments demonstrate the accuracy of the proposed simulation model. In addition, micro pits array with CVdiameter and CVdepth of 2.28 % and 5.70 %, respectively, were prepared using the MA-TMEMM method. Visualization experiments systematically study the machining mechanism of MA-TMEMM. The underlying dynamic force balance on the gas bubble is analyzed to illustrate the mechanism and experimental observations. Finally, the advantage of megasonic in removing bubbles from the anode surface to improve etching uniformity was demonstrated by counting the detached bubble diameter and effective coverage.