Target Power Research Articles

Highly active and stable nanocomposite anode for solid oxide fuel cells on non-conductive substrate

Thin film solid oxide fuel cells (TF−SOFCs) with mixed ionic electronic conducting (MIEC) Ni−GDC anode comprise a practical solution to alleviate the poor ionic conductivity and sluggish reaction kinetics of low-temperature SOFCs (< 600 °C). In the present study, we fabricate TF−SOFCs using a magnetron sputtering system. To finely adjust the composition ratio of the nickel cermet anode, we deposit NiO−GDC via a reactive co-sputtering process, which reduces the sputtering yield of nickel. We fabricate NiO−GDC anodes with various composition ratios by changing the sputtering power for the nickel target (50–100 W), while maintaining the sputtering power for the GDC target (50 W). The electrochemical performance of the NiO−GDC anode-based TF−SOFCs is successfully optimized by controlling the composition, crystallinity, and surface morphology of the anodes. Structural analysis reveals that the optimized composition ratio of NiO (64.46 vol% Ni) in cermet is higher than that of conventional sintered nickel-based cermet anode (40–50 vol% Ni), which is attributed to the sensitive characteristics of the nano-sized grain structure to thermal agglomeration in a reducing environment. Consequently, we obtain the most stable structure and the highest performance (439.5 mW/cm2 at 500 °C) with the optimal NiO−GDC composition (NiO 75 W / GDC 50 W).

3-Port beam splitter of arbitrary power ratio enabled by deep learning on a multimode waveguide

A 3-port beam splitter with arbitrary power ratio is developed on a multimode waveguide by effectively manipulating the multimode interference through 4 locally placed microheaters. For matched interference, different light powers are coupled to the three output waveguides but the sum does not undergo extra loss, whereas the splitter integrates also the variable attenuation function, from zero to maximum, to any of the outputs. Different from the conventional design approach using extensive simulations, an equivalent neural network is established to represent such a multimode waveguide system based on experimental data only. From this neural network, an optimization program is developed to inverse the output and input. For a target power splitting ratio, the required heater currents can be readily calculated on a computer and then loaded onto the waveguide chip. The experimental results match well with the targets. This work demonstrates that the nonlinear activation is inherently integrated in the thermally controlled multimode waveguide though the optical material itself is linear. This feature can be used to construct complex deep learning networks. It may lead to the development of advanced integrated optical switches and computing networks.

Sample size planning for multiple contrast tests.

Sample size calculations for two (independent) samples are well established and applied in (pre-)clinical research. When planning several samples, which is common in, for example, preclinical studies, sample size planning tools based on analysis of variance methods are available. Since the underlying effect sizes of these methods are often hard to interpret and to provide for the sample size planning, we employ multiple contrast test procedures for sample size computations in both parametric (under normality assumption) and nonparametric designs using Steel-type tests. Since the exact distributions of the test statistics are unknown under the alternative and variance heterogeneity, we use approximate solutions. Furthermore, since no closed formula for the sample size is available, we use numerical approximations for their computation. Extensive simulation studies are finally conducted to assess the quality of the approximations. It turns out that the methods are accurate in the sense that the multiple contrast test procedures reach the target power to detect the alternative of interest with the sample size computed. The developed procedures are a valuable tool to plan (pre-)clinical trials with several samples and are easily accessible in publicly availablesoftware.

Thermal Performance of Perovskite‐Based Photovoltaics for Operation in Low Earth Orbit

Perovskite‐based photovoltaics are attractive for applications in space. The space environment is harsh with ionizing radiation, atomic oxygen, UV radiation, extreme temperatures, and thermal cycling. Herein, the thermal performance of perovskite active layer and perovskite photovoltaic devices in low earth orbit is analyzed. A 1 μm silicon oxide layer coupled with 500 nm zirconia thin film aid in cell thermal management is determined. The residual stresses between various layers in a device are modeled and it is proved that thermally induced mechanical failure of the perovskite (time years) is unlikely during operating lifetime of any mission. Target power conversion efficiencies are also shared to manage maximum operating temperature of a perovskite‐based device.

Influence of carbon target power on the tribological and electrochemical properties of NbMoSiC composite films in seawater

Because the wear and corrosion of marine engineering equipment will cause huge economic losses to enterprises every year, thus it is necessary to develop advanced protective films to ensure the normal operation of marine equipment. Here NbMoSiC composite films are deposited using DC magnetron sputtering in an argon atmosphere through varying the carbon target sputtering power, and their microstructure and mechanical properties are investigated using scanning electron microscopy (SEM), X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS)，Raman spectroscopy and dynamic ultra-micro hardness tester, respectively. The tribological properties of the films in air and artificial seawater are determined by a reciprocating ball-on-disc tester, while the electrochemical properties of the films in seawater were evaluated by an electrochemical workstation. The results demonstrate that the presence of Nb2C, MoSi2, free silicon, and amorphous carbon (a-C) in the NbMoSiC composite films. Particularly, Sample C250, featuring a carbon content of 35.02 at.%, exhibits higher hardness, elastic modulus, excellent wear resistance, and superior corrosion resistance. However, a further increase in carbon target sputtering power leads to escalated surface roughness and microchannels, ultimately resulting in reduced wear and corrosion performance. Electrochemical analysis reveal that the strong synergistic effect of amorphous carbon as well as the metal oxide phase formed on the surface significantly enhanced the corrosion resistance of the film in artificial seawater with a corrosion current density as low as 1.8 × 10−8 A/cm2.

Effect of Target Power on Microstructure, Tribological Performance and Biocompatibility of Magnetron Sputtered Amorphous Carbon Coatings.

The tribological properties and preosteoblast behavior of an RF magnetron-sputtered amorphous carbon coating on a Si (100) substrate were evaluated. The graphite target power was varied from 200 to 500 W to obtain various coating structures. The amorphous nature of the coatings was confirmed via Raman analysis. The contact angle also increased from 58º to 103º, which confirmed the transformation of the a-C surface from a hydrophilic to hydrophobic nature with an increasing graphite target power. A minimum wear rate of about 4.73 × 10-8 mm3/N*mm was obtained for an a-C coating deposited at a 300 W target power. The 300 W and 400 W target power coatings possessed good tribological properties, and the 500 W coating possessed better cell viability and adhesion on the substrate. The results suggest that the microstructure, wettability, tribological behavior and biocompatibility of the a-C coating were highly dependent on the target power of the graphite. A Finite Element Analysis (FEA) showed a considerable increase in the Von Mises stress as the mesh size decreased. Considering both the cell viability and tribological properties, the 400 W target power coating was identified to have the best tribological property as well as biocompatibility.

A Novel Autonomous Landing Method for Flying–Walking Power Line Inspection Robots Based on Prior Structure Data

Hybrid inspection robots have been attracting increasing interest in recent years, and are suitable for inspecting long-distance overhead power transmission lines (OPTLs), combining the advantages of flying robots (e.g., UAVs) and climbing robots (e.g., multiple-arm robots). Due to the complex work conditions (e.g., power line slopes, complex backgrounds, wind interference), landing on OPTL is one of the most difficult challenges faced by hybrid inspection robots. To address this problem, this study proposes a novel autonomous landing method for a developed flying–walking power line inspection robot (FPLIR) based on prior structure data. The proposed method includes three main steps: (1) A color image of the target power line is segmented using a real-time semantic segmentation network, fusing the depth image to estimate the position of the power line. (2) The safe landing area (SLA) is determined using prior structure data, applying the trajectory planning method with geometric constraints to generate the dynamic landing trajectory. (3) The landing trajectory is tracked using real-time model predictive control (MPC), controlling FPLIR to land on the OPTL. The feasibility of the proposed method was verified in the ROS Gazebo environment. The RMSE values of the position along three axes were 0.1205,0.0976 and 0.0953, respectively, while the RMSE values of the velocity along these axes were 0.0426, 0.0345 and 0.0781. Additionally, experiments in a real environment using FPLIR were performed to verify the validity of the proposed method. The experimental results showed that the errors of position and velocity for the FPLIR landing on the lines were 6.18×10−2 m and 2.16×10−2 m/s. The simulation results as well as the experimental findings both satisfy the practical requirements. The proposed method provides a foundation for the intelligent inspection of OPTL in the future.

Seismic response analysis of submerged floating tunnel considering non-uniform excitation and flexible-support boundary effect

In order to ensure the safety of submerged floating tunnel(SFT) during operation, it is necessary to carry out SFT response analysis under environmental loads. Given that SFTs are often constructed in valley areas situated in seismic zones, the aseismic performance of SFT needs to be investigated. However, there are important factors of non-uniform excitation and flexible-support boundary which have not been explored thoroughly. Non-uniform excitation affects the load input characteristics while flexible-support boundary affects the dynamic characteristics of structure itself. In this paper, we built a multi-point seismic wave synthesis model which fits well with the target power spectrum and a numerical response analysis model which reflects the dynamic characteristics of SFT structure well. The results based on the proposed model show that vertical non-uniform excitation can significantly increase the peak value of SFT tether tension and tube displacement with flexible-support boundary under whether artificial or natural seismic wave series input. While flexible-support boundary can availably produce vibration control effect on peak value of tether tension and tube response of whether displacement or stress indices under non-uniform wave series input. This work can provide reference for dynamic safety assessment and vibration control design of SFT to improve the development of ocean space.

Influence of Ag Target Power on Microstructure and Properties of TiN-Si3N4-Ag Composite Coatings

Influence of Ag Target Power on Microstructure and Properties of TiN-Si3N4-Ag Composite Coatings

The influence of the non-uniform airflow on the energy and cooling performance of the simplified electric vehicle front end cooling module

Electric vehicles (EVs) are viable alternatives to reduce greenhouse gas emissions and dependence on fossil energy resources. The front end cooling module (FECM), including the heat exchanger (HX), cooling fan, grille and other components, is indispensable for EVs. As the cooling airflow demand of EVs is smaller than that of traditional vehicles, the grille becomes flat and small so as to reduce the wind drag and improve the driving range, which causes more non-uniform airflow in the FECM. However, the influence of this change on the cooling fan has not been deeply researched so far.Thus, a simplified FECM model in this paper is designed to explore the influence of non-uniform airflow caused by different grilles. This study uses the computational fluid simulation (CFD) to get the numerical results and the airflow distribution inside the FECM, aiming to minimize the negative impact of the non-uniform airflow on the cooling fan and to reduce the power consumption, which has not been discussed by researches before. The results show that the target power consumption can be reduced by 5–18% through optimizing the grille, meanwhile meeting the mass flow rate required for cooling, which provides a reference for designers to refine parameters such as the grille size, and is beneficial for the energy saving and mileage improvement of EVs.

Microstructure and electrochemical properties of Cr– Si–C–N coatings as biological dry electrode

Bio-electrode Cr–Si–C–N coatings were fabricated on glass and Si wafer substrates via unbalanced magnetron sputtering. Their microstructure and mechanical properties were characterized by X-ray diffraction (XRD), scanning electron microscopy (SEM) and nano-indentation, respectively. The Cr–Si–C–N coatings exhibited a composite structure consisting of Cr(C, N) nanocrystals embedded in an amorphous matrix of a-SiNx, a-SiCN and a-C/a-CN. The nano-hardness of the coatings decreases with an increase in graphite target current or Si target power due to the formation of more amorphous phase. CrSiCN-3A deposited under high N2 flow (25sccm) and graphite target current (3A) exhibited the lowest open-circuit voltage (OCP, 0.119V) due to its more amorphous phase. CrSiCN–800W demonstrated maximum potential drift of 7 mV, current drift of 0.01 μA and minimum noise resistance, indicating poor corrosion resistance attributed to its low silicon content (1.9 at%) and high crystallinity (70.7%). The grain size of the coatings was not significantly affected by increasing Si target power from 1000W to 1200W, but only resulted in a reduction in crystallinity. The OCP and contact resistance exhibited an initial decrease followed by an increase with increasing Si target power. Notably, CrSiCN–1000W demonstrated the lowest potential and current drift (0.19 mV, 0.0001 μA) as well as contact impedance due to its large grain size and distinct columnar microstructure.

Integrated OFDM Waveform Design for RadCom System-Based Signal-to-Clutter Noise Ratio Maximization

Integrated Radar and Communication (RadCom) Systems have become more crucial ingredients in the next generation of networks due to numerous types of characteristics, including reducing the system size, minimizing power consumption, and mitigating spectrum scarcity. In this paper, we propose an integrated Orthogonal Frequency Division Multiplexing (OFDM) waveform design strategy for RadCom system-based Signal-to-clutter Noise Ratio (SCNR) maximization. The multi-carrier OFDM waveform is exploited at the RadCom transceiver to perform the functions of the radar system and communication system concurrently. We aim to improve the radar detection performance by maximizing the SCNR and maintaining the Data Information Rate (DIR) thresholds for communication system metrics. The maximization problem is posed as a convex optimization model and solved analytically using KKT conditions to find an optimal integrated waveform design. The findings obtained via simulation verify that the proposed strategy is capable of solving the waveform design issue for RadCom systems with low complexity. In addition, the proposed strategy effectively improves radar target detection and power consumption for RadCom systems.

BAS-PSO Algorithm for Integrated Energy System Optimization of Multiple Energy Supply Facilities

Regional low carbon will play an important role in the path of achieving the “double carbon” goal, and there are still many key technologies to be broken in its planning research. In this paper, an optimal scheduling model of integrated energy system with multiple energy supply devices is established by using Beetle Antennae Search-Particle Swarm Optimization (BAS-PSO) algorithm. First, in the scheduling model, a carbon trading mechanism is introduced and a stepped carbon trading cost model is constructed to constrain the carbon emissions of the plant. Then, using drosophila algorithm, the premise of whether wind power generation and photovoltaic power generation need to be built is determined by judging the economics of wind power generation and photovoltaic power generation in the construction area, and then the target power consumption curve and new energy power supply output curve are fitted. Then use the life cycle analysis method to analyze the carbon emissions generated by electric energy storage equipment, consider the carbon trading mechanism in the system economic operation model, and solve the model by BAS-PSO algorithm to overcome the problems of local optimum and slow convergence speed. Finally, a typical park integrated energy system is simulated to analyze the economic operation conditions and energy efficiency level of the system before and after participation in demand response. The innovation of this paper lies in considering the carbon trading mechanism and solving with the optimized BAS-PSO algorithm. Considering carbon trading can effectively improve the system wind power consumption capacity, and the optimized BAS-PSO algorithm improves the defects of traditional PSO. The simulation analysis results show that the established optimal scheduling model with multiple energy supply devices can realize the optimal operation of the integrated energy system of the park in the demand response environment; the improved BAS-PSO finds the lowest energy consumption within 100 iterations in 21 out of 50 iterations; the improved BAS-PSO algorithm reduces the energy consumption by 27.1 kW on average.

Design, analysis and test of conventional and winglet propellers under highly loaded conditions

In this paper, some conventional and winglet inboard propellers are designed, analyzed and tested under highly loaded conditions. The design objective is to achieve the highest efficiency at a given propeller RPM and target power. A non-linear optimization solver is coupled with the panel method to design the conventional propellers. A robust parameterized geometry definition is given for the winglet propellers, with the flexibility to change the shapes of the winglet, including its location and direction, and its sections’ pitch and camber. The winglet propellers are designed using the SHERPA (Simultaneous Hybrid Exploration that is Robust, Progressive, and Adaptive) algorithm and the performance of each geometry in the optimization process is predicted by the steady RANS (Reynolds-Averaged Navier–Stokes) method with periodic boundary conditions. Both the conventional propellers and winglet propellers are designed under the open water condition and multiple designs are further analyzed by the unsteady RANS method, together with the hull, the rudder, the free surface and an inclined shaft angle. It is found that (i) in the conventional propeller designs, the unsteadiness in propeller-induced forces on the hull reduces with increased distance from the propeller blade tip to the bottom of the hull; (ii) the efficiency of optimized conventional propellers generally decreases with the decrease of propeller diameter; (iii) under the specified design conditions, the blade tips of the optimized winglet propellers exhibit a tendency to bend towards the pressure side of the blade; (iv) when appropriately designed, winglet propellers can attain enhanced efficiency and reduced unsteadiness in propeller-induced forces acting on the hull’s underside, in comparison to conventional propellers of the same overall diameter. Consequently, winglet propellers are good design choices for highly loaded conditions with strict constraints on diameter. Finally, one conventional propeller design and one winglet propeller design are selected to make full-scale prototypes and tested on the water, where the fuel economy of these prototypes is measured and compared with the numerical predictions. The results demonstrate that the winglet design surpasses the optimal conventional propeller design, yielding a 13.2% improvement in fuel economy under light conditions and a 9.3% improvement under heavy conditions. These findings substantiate the advantages of utilizing winglet designs for propellers operating under highly loaded conditions.

Preparation and properties of Al/Si coating with excellent formability and corrosion resistance on steel plate

In order to simultaneously improve formability of the coated steel and corrosion resistance of steel, Al/Si coating with tailored Si content, controllable composition and structure were prepared on Q235 by combining magnetron sputtering and then treated by heat treatment. The effect of Si content on the thickness, composition, structure of Al/Si coating on the surface of Q235 steel, and corrosion resistance and formability of Al/Si coated Q235 steel were systematically investigated. With 160 W of Al target power and different Si target power (0, 60, 80 and 100 W), the thickness of the coating on Q235 steel for 1.5 h is about 5 µm. Al/Si coating thickness with 80 W of Si target power is 5.33 ± 0.32 µm. The coating on Al/Si80-Q235 is uniform and dense, and mainly consists of FeAl2Si, Fe3Al, Fe2Al5, and Al2O3. Al/Si80-Q235 demonstrated excellent formability and Al/Si80 coating improved corrosion resistance of Q235 steel. When immersed in NaCl solution, the self corrosion current density of Al/Si coated Q235 was significantly lower than Al coated Q235. Especially, the self corrosion current density of Al/Si80-Q235 was only 1/51 that of Al coated Q235. The corrosion resistance of Al/Si coated steel was remarkably improved compared with Al coated steel due to the addition of Si.

Comprehensive characterization of Al-doped ZnO thin films deposited in confocal radio frequency magnetron co-sputtering

Al-doped ZnO thin films with varying Aluminium (Al) content were deposited by radio frequency magnetron co-sputtering of two ZnO and Al targets in confocal configuration. A comprehensive study of the effect of Al content variation on the structural, optical and electrical properties were studied for as-deposited films and after an annealing step under controlled argon atmosphere. Chemical composition analyses, performed by both X-ray photoelectron spectroscopy and energy dispersive X-ray spectrometry, show an Al content variation in the deposited films in the 0-14 at.% range by varying the Al target power from 0 to 30 W, while the Zn target power was kept constant at 200 W. All deposited films exhibit a wurtzite crystalline structure and a decreasing crystalline quality for Al content above 5 at.% as shown by grazing incidence X-ray diffraction patterns. Atomic Force Microscopy analysis revealed films with homogeneous and dense surface morphology with roughness in the one nm range. Carrier concentration, resistivity and photoluminescence vary significantly with Al content in the ZnO films and appear optimized for an Al content window ranging from 1.5 to 5.5 at. %. Both optical and electrical properties are improved by a post-annealing at 300°C under argon. A high figure of merit of 43.6 × 10-4 sq.Ω-1 was obtained for the ZnO film with Al content of 3.6 at.% after annealing at 300°C. Optimized properties are obtained for a higher Al content than the standard value of 2 at. % widely used in published works.

Global path planning with lifetime constraint model-based offline optimized loading strategy for vehicle fuel cell system

To promote the commercialization of fuel cell vehicles, simultaneously improving the dynamic response and durability of fuel cells under loading conditions are extremely important. Since it can seriously affect the system design and lifespan of the fuel cell system. Unfortunately, fast and reliable loading is a pair of contradictory relationships and it needs an optimal loading slope under variable loading conditions. Therefore, this paper proposes a global path planning (GPP) model by considering lifetime limitations to solve the problem. Firstly, the initial GPP model is established according to the initial power and target power, which is exploited to determine exploratory and calibration tests. Subsequently, the trade-off relationship between fast and reliable loading is addressed by the multi-objective cost function based on the dynamic weight coefficient adjustment method to construct a complete GPP model. Eventually, the optimal slopes solution is calculated by the Dijkstra algorithm. The superiority, robustness, and feasibility of the presented method are successfully verified under a 90 kW fuel cell system test bench. The verification test results show that compared with the reference solution, the utilization of optimal solution loading can significantly reduce the dynamic response time by 22.22% and improve the loading reliability by 40.93%. Moreover, the number of calibration tests determined based on the GPP model is 85.19% less than that of the traditional method. Thus, the proposed loading strategy can load quickly and reliably.

Optimization of Permanent Magnet Synchronous Generator Output Power in Wind Power Plants with ANN Back Propagation

The focus of this research is optimizing a wind power plant using a Permanent Magnet Synchronous Generator (PMSG). The backpropagation method of the artificial neural network system was chosen to optimize the output power of the wind power generator. Based on the simulation results, the backpropagation algorithm of the artificial neural network obtains the output power based on the input variable in the form of changing wind speed. The results show that the best value is learning rate = 0.5, error = 0.0001, max. epoch= 100000, neuron hidden layer = 5. The Mean Square Error (MSE) value obtained is 0.1026 reaching the goal at epoch 14845. The reverse training regretion reaches 0.99917. The optimization results are close to the specified error, which is 0.0001, while what is obtained is 0.0145. The power generated by the wind speed is 10.7 m/s before being optimized using the back propagation neural network method worth 321 watts, while the optimized power results are 409 watts. The difference in the average target power obtained is 88 watts compared to the power of the Artificial Neural Network (ANN).

Coupled KIPP-EDGE2D modeling of parallel transport in the SOL and divertor plasma for the ITER baseline scenario

The KInetic code for Plasma Periphery (KIPP) models the parallel (along magnetic field lines) propagation of charged particles in the scrape-off layer (SOL) and divertor of tokamaks. An iterative coupling between KIPP and a 2D edge fluid code, EDGE2D, which in turn is coupled to the Monte Carlo solver for neutrals, EIRENE, was used to achieve a converged KIPP-EDGE2D-EIRENE solution. In the iterative coupling algorithm, KIPP transfers kinetic parallel electron and ion heat conductivities to EDGE2D, whereas EDGE2D returns to KIPP 2D distributions of macroscopic plasma parameters across the computations grid. The initial EDGE2D-EIRENE solution simulated the SOL and divertor plasma of the ITER inter-edge localized mode (ELM) baseline scenario. This work employs the same methodology as an earlier study based on the analysis of JET high radiative H-mode conditions, with strong nitrogen injection leading to partial detachment at divertor targets (Chankin et al 2022 Plasma Phys. Control. Fusion 64 095007). The results are qualitatively similar to those of the JET study in demonstrating the strong heat flux limiting effect, together with the rise in electron and ion temperatures in the main SOL. At the same time, the kinetic effects of the parallel propagation of charged particles are not expected to drastically change the target power deposition at divertor targets calculated by EDGE2D-EIRENE alone.

Ship Detection in PolSAR Images Based on a Modified Polarimetric Notch Filter

Ship detection based on synthetic aperture radar (SAR) imagery is one of the key applications for maritime security. Compared with single-channel SAR images, polarimetric SAR (PolSAR) data contains the fully-polarized information, which better facilitates better discriminating between targets, sea clutter, and interference. Therefore, many ship detection methods based on the polarimetric scattering mechanism have been studied. To deal with the false alarms caused by the existence of ghost targets, resulting from azimuth ambiguities and interference from side lobes, a modified polarimetric notch filter (PNF) is proposed for PolSAR ship detection. In the proposed method, the third eigenvalue obtained by the eigenvalue–eigenvector decomposition of the polarimetric covariance matrix is utilized to construct a new feature vector. Then, the target power can be computed to construct the modified PNF detector. On the one hand, the detection rate of ship targets can be enhanced by target-to-clutter contrast. On the other hand, false alarms resulting from azimuth ambiguities and side lobes can be reduced to an extent. Experimental results based on three C-band AIRSAR PolSAR datasets demonstrated the capability of the proposed PNF detector to improve detection performance while reducing false alarms. To be specific, the figure of merit (FoM) of the proposed method is the highest among comparative approaches with results of 80%, 100%, and 100% for the tested datasets, respectively.