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This study discusses the effect of stress on 4H-silicon carbide (4H-SiC) power diodes using numerical simulations. Two power diodes were evaluated; namely, a 600 V PiN diode and 1.8 kV junction barrier Schottky (JBS) diode. Stress changes the carrier mobilities in the material of the PiN diode of a bipolar diode; that is, the mobility is enhanced by the piezoresistive effect, which minimizes the on-resistance or leakage current. The simulation results demonstrate that compressive stress can have a positive effect on the device operation, particularly in p$^+$-substrate power diodes. Regarding the JBS diode, the GPa-order tensile stress positively effects both forward and reverse characteristics. A cantilever structure is suitable for JBS diodes, and press-pack packaging for PiN diodes can enhance the device characteristics.

The thermal environment of the lunar surface is of crucial importance for the lander thermal design and the interpretation of scientific data. Clarifying the radiative sources and intensity on the outer surface of the lander is one of the key aspects of lander thermal design. The installation of temperature sensors on the body of the Chang'e-4 (CE-4) and Chang'e-5 (CE-5) landers has provided valuable opportunities for quantifying the influence of lunar thermal conditions on the surface temperature of the lander. In this study, we established a temperature model for the near-surface regolith and a heat transfer model based on the observations from sensors installed on the body of the lander and auxiliary pillars. By integrating factors, such as the density of the lunar regolith, the thermal conductivity of the lunar regolith, and the relative positions of the temperature measurement points to the Earth and the Sun, we conducted analyzes on the temperature measurement data for both CE-4 and CE-5, respectively. Our results indicate that during the daytime of the Moon, the temperature of the lander's surface is mainly influenced by solar radiation and the infrared thermal radiation from the lunar surface. During the nighttime of the Moon, the heat transferred outward from the inside of the lander plays a key role in the temperature of the outer surface of the lander. The lunar surface thermal environment significantly affects the temperatures of both the shaded and sunny sides of the lander, with its influence on the shaded side even surpassing that on the sunny side. The lunar surface's thermal environment directly impacts the stability and reliability of the electronic components within scientific payloads. Our results offer dependable lunar thermal environment parameters for the design of scientific instruments on future lunar landers and the deployment of instruments in their designated positions.

A decomposed dynamic dispatching and preventive maintenance (D-DDPM) framework is presented to overcome the computational challenges of solving large DDPM problems. Stochastic deterioration of machine health is explicitly considered. By efficient allocation of individual machine’s capacity under different machine health, the D-DDPM framework decomposes the global DDPM problems into single-machine DDPM problems while ensuring throughput optimality. Intelligent machine agents are then designed to solve the single-machine DDPM problems efficiently and to perform real-time decisions for individual machines. After the decomposition, the overall computational complexity grows only linearly with the number of machines and the proposed framework could be adopted in large systems. In the numerical study, the D-DDPM framework is near-optimal in small systems that have optimal DDPM solutions. In which, the computation time is reduced by 90.72% and the average cycle time is within 6% of optimal. For large systems without optimal DDPM solutions, numerical results show that the D-DDPM maintains throughput optimality and reduces average cycle time by up to 90% against other control policies. [ABSTRACT FROM AUTHOR]

Based on deep neural network, elliptic partial differential equations in complex regions are solved. Accurate and effective strategies and numerical methods for elliptic partial differential equations are proposed by implementing deep feedforward artificial neural network, appropriate loss function solving strategy are constructed. The solution of an elliptic partial differential equation is obtained by iteratively learning the parameters of a neural network. Constructing a composite multi-layer radial basis function neural network can improve the real function approximation performance and operational accuracy of the constructed multi-layer radial basis function neural network. Use this high-precision composite multi-layer radial basis function neural network to solve partial differential equations. By providing specific examples of solving partial differential equations, the effectiveness of this method is tested. An improved partial differential equation solving method based on deep neural networks (Taylor PINN) has been proposed. This method utilizes the universal approximation theorem of deep neural networks and the function fitting ability of Taylor’s formula to achieve a meshless numerical solution process. The numerical experimental results on Helmholtz, Klein Gordon, and Navier Stokes equations show that Taylor PINN can well fit the mapping relationship between the coordinates of spatiotemporal points in the computational domain and the value of the desired function, which can provide accurate numerical prediction results. Compared with commonly used physical information based neural network methods, Taylor PINN improves prediction accuracy by 3–20 times for different numerical problems.

REBa2Cu3O7-x (REBCO) coated conductor has emerged as a promising material for the development of ultra-high-field (UHF) magnets. However, the presence of screening-current induced strain within this tape-shaped conductor impacts the operational stability of REBCO coils. We focused on the design of an all-superconducting 36 T / 40 mm UHF magnet, which included a 16 T insert magnet consisting of two nested REBCO coils. In this study, the screening-current induced strain in the 16 T magnet was numerically studied using the coupled electromagnetic-mechanical model, which considered the tilting angle of REBCO tapes and the strain dependency of the critical current. We calculated the screening-current induced strain of each pancake individually and compared these results with those calculated by the sequential model. According to the coupled model, the maximum hoop strain was 0.52%, relatively lower than that calculated by sequential model. The most dangerous pancake was estimated to be the outermost pancake of each coils. Additionally, we varied the critical current value of the REBCO tapes and studied the relationship between the critical current value and screening-current induced strain. This work provides a feasible way to calculate the screening-current effect in large-scale HTS magnets.

We present a general-purpose, fast and computationally efficient numerical method to predict the performance of filters based on electric-LC (ELC) resonators or split-ring resonators (SRR) in a very large frequency range (i.e., 8–40 GHz). In particular, we tackle the problem arising from the design of arrays of ELC/SRR-based resonators developed in a multi-layer dielectric stack under a coplanar waveguide excitation. The intrinsic complexity of the analyzed structure (open, multi-layer, and with resonators) makes it unpractical to rely exclusively on full-wave electromagnetic simulations. Furthermore, the presence of multiple modes in propagation can lead to a quite difficult assessment of the optimal simulation conditions. For all these reasons, we propose a method based on the cascade of scattering matrices for all the sub-modules of the considered filters. We demonstrate the efficacy of the proposed numerical technique for a good prediction of the high-frequency performance of the filters. The fabrication on silicon substrate of structures integrating electric-LC resonators (for X band applications) or split-ring resonators (for Ka band applications) serves the purpose of validating the presented method, with a very good agreement between simulations and measurements.

The technology of wireless power transfer, which wirelessly transmits power to any device, has been widely studied. Wireless power transfer using magnetic field resonance involves the use of coils and a material called ferrite, which improves the transmission characteristics. Until now, electromagnetic field analysis has been used to design ferrite cored coils, but electromagnetic field analysis requires a long analysis time and a computer with a large amount of memory. In this study, the ferrite shield and coil are represented as a image coil under the condition that the positional relationship between the ferrite shield and the coil does not change. This enabled the derivation of mutual inductance only by numerical analysis, which had been difficult up to now. In addition, experiments have shown that when the coil size does not change, mutual inductance can be derived only by numerical analysis using arbitrary coil parameters, regardless of the number of turns and pitch. The average error in deriving the design value was 5.2%. This facilitated the design of ferrite cored coils at 85 kHz and contributed greatly to the design of the system.

Specialized arithmetic units allow fast and efficient computation of lesser used mathematical functions. The overall impact of those units would be negligible in a general purpose processor, as added circuitry makes chips more complex despite most software would seldom make use of it. On the opposite side, custom computing machines are built for a specific task, and they can always benefit from specialized units if they are available. In this work, floating point architectures are proposed for computing the cube on Intel and Xilinx FPGAs. Those implementations reduce the cost and latency compared to using simple floating point multiplications and squarers. [ABSTRACT FROM AUTHOR]

This article aims to understand the effect of firms’ application development activities when introducing new technologies from universities or public institutes on the success of commercialization and corporate growth. Technology itself does not guarantee corporate growth; instead, it is commercialization that contributes more to achieving a sustainable competitive edge, as it offers economic value. We collected samples on the commercialization performance of start-ups that adopted the technology of universities or public research institutes and measured the intensity of the firms’ application development activities as the gap between the technology readiness levels (TRLs) at the time of technology acquisition and the firms’ current TRL. Our findings show that the process of transferring technology to firms is mediated by the firms’ application development performance. Most notably, we first observed that firms’ investments in commercialization have no significant direct effect on commercialization success; instead, we found that this relationship is mediated by the TRL gap. This article suggests that it is necessary to consider the entire process—from the technology transfer to firms to successful commercialization—to form a mechanism under which universities and research institutes can create substantial additional value and allow their research to realize their full potential. [ABSTRACT FROM AUTHOR]

A triple-mode dc-dc converter with wide ranges of input and load for energy harvesting in Internet-of-Things edge nodes is reported. The proposed energy harvester is designed and fabricated in a 0.18- $\mu \text{m}$ CMOS process. It demonstrates MPPT, automatic buck-boost operation, stable operation in proper energy-distribution path based on the changes of load and input source, and efficient energy conversion control with peak efficiency up to 88.7%, with load transient response time of $ < 450~\mu \text{s}$ , a wide input range of 1.2 – 4 V and an output range of 1 – 4 V, as well as a maximum load up to 50 mA. [ABSTRACT FROM AUTHOR]

The paper provides a novel framework to study the accuracy and stability of numerical integration schemes when employed for the time domain simulation of power systems. A matrix pencil-based approach is adopted to evaluate the error between the dynamic modes of the power system and the modes of the approximated discrete-time system arising from the application of the numerical method. The proposed approach can provide meaningful insights on how different methods compare to each other when applied to a power system, while being general enough to be systematically utilized for, in principle, any numerical method. The framework is illustrated for a handful of well-known explicit and implicit methods, while simulation results are presented based on the WSCC 9-bus system, as well as on a 1,479-bus dynamic model of the All-Island Irish Transmission System. [ABSTRACT FROM AUTHOR]

For massive dosimetry analysis of finite composite materials (CMs), an effective approach is proposed based on the artificial intelligence (AI) computational algorithm. Machine learning (ML) method is used to analyze systematic energy characteristics of finite CM for dosimetry exposure. To prove the validity of our algorithm, we analyzed a finite CM in a specific scenario and calculated its exposure dosimetry. The dataset for algorithm training is obtained through numerical analysis. In order to verify the efficiency of the proposed method, the accuracy of this algorithm and its time consumption are calculated. Five ML methods are subsequently used to compare the average absorption of the energy resonance exposure in the finite CM. The time consumption and error distribution in test sets prove the high efficiency of AI computational algorithm to analyze the energy exposure of finite CM. The proposed AI algorithm is useful for the massive numerical analysis in the research of electromagnetic (EM) exposure. [ABSTRACT FROM AUTHOR]

In this article, a hybrid capacitor voltage balancing control based on selective harmonic elimination pulsewidth modulation (SHE-PWM) is proposed for four-level hybrid-clamped (4L-HC) converters that operates at very low switching frequency. In low and medium modulation index (ma) range, a novel SHE formulation is introduced, where the objective function for natural capacitor balancing is added into the nonlinear SHE equations. With the optimal SHE patterns and switching angles obtained from this formulation, all capacitors can be balanced naturally without additional switching actions for swapping the redundant states to regulate the capacitor voltages, which greatly reduces the switching frequency compared with other active capacitor voltage balancing methods and modulations. In high ma range, SHE model predictive control (SHE-MPC) is adopted, where the output voltages follow SHE-PWM patterns but with MPC used for capacitor balancing and switching frequency regulations. Simulation and experimental results, as well as detailed numerical analysis and comparisons with other PWM and capacitor voltage balancing methods for 4L-HC converters are provided to demonstrate the good voltage regulation performance and superiorities of the proposed method. [ABSTRACT FROM AUTHOR]

With the loss of a large number of space vectors under switch open-circuit faults, the neutral point potential (NPP) control of T-type three-level converters is faced with a huge challenge. It becomes harsh to balance the NPP and maintain the symmetry of line voltages under switch open-circuit faults simultaneously. In order to improve the NPP control performance and stable operation of T-type three-level converters, this article presents a hybrid modulation strategy that can enhance the NPP control ability even under switch open-circuit faults. Through a carrier-based analysis tool, two candidate modulation strategies are first evaluated from the perspective of the adjustment range of the neutral point current. The first one maintains the conventional three-level modulation in two nonfault phase arms. The second one degrades the mode of modulation from three-level modulation to two-level modulation in two nonfault phase arms. By making full use of the NPP oscillation characteristics of the two candidate methods, a hybrid modulation strategy based on transition duty-cycle and enabled bridge-arm adjustment is put forward to achieve a comprehensive optimal control performance. Numerical analysis and experiments are carried on to prove the correctness and feasibility of the proposed method. [ABSTRACT FROM AUTHOR]

Consensus reaching process (CRP) is important and present in a wide range of application areas. In practical CRP, the managers (e.g., enterprise) often hire some informed individuals (e.g., persuaders) to promote the efficiency of consensus reaching. This article proposes a CRP with minimum cost of informed individuals and time constraint in large-scale group decision-making (LSGDM) with bounded confidence effects. The consensus model with bounded confidence effects (CBC model) is formulated. Then, desirable properties of the CBC model are discussed to facilitate its resolution. Next, an extended particle swarm optimization algorithm is designed to solve the CBC model. Finally, a numerical analysis, a comparison analysis, and a simulation analysis are provided to illustrate the feasibility and effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]

The aim of this article is to perform a rapid electromagnetic (EM) analysis of large perfectly electric conducting (PEC) platforms with local variations. Such problems often require many-query simulations to navigate complex parameter spaces and thus quickly become computationally expensive. The proposed work starts with a stationary-variable domain decomposition, where the computational domain is decomposed into large fixed parts and small portions with local variations. Subsequently, we introduce a separable and compressible platform Green’s function at the outer surface of those variable subdomains in an upfront offline calculation. Once obtained, the online computational complexity does not depend on the size of the in situ platform. With the validation of numerical results, we conclude that the proposed work has the potential to greatly speed up the online evaluation of local designs and optimizations compared to the brute-force computation. [ABSTRACT FROM AUTHOR]

The late-time evaluation of electromagnetic (EM) field quantities yielded by convolution integrals that combine Green’s functions available at discrete time samples and strictly causal excitations is critically revisited. A typical situation is used for tracing the causes of the divergent late-time behavior that is often experienced. A framework combining a suitable integral partitioning with a polynomial approximation is shown to effectively guarantee the integrals’ convergence. The formulation is validated via numerical experiments evidencing its accuracy and computational efficacy. The method is amenable to be used in a wide range of problems requiring the late-time evaluation of convolution integrals of the indicated type. [ABSTRACT FROM AUTHOR]

When analyzing multiconductor transmission lines with the edge coupling by the method of moments, the matrices of per-unit-length parameters may be inaccurate, which leads to an unacceptable noncausal response at the end of the transmission line. The article proposes a simple technique of a nonuniform segmentation of multiconductor transmission lines with edge coupling boundaries to eliminate the inaccurate calculation of the capacitance matrix. This technique allows obtaining accurate capacitance matrices with the lowest computational costs on single-variant and multivariate analyses, as well as optimization or stability analysis. [ABSTRACT FROM AUTHOR]

We present a hybrid numerical method that combines full-wave analysis with ray-tracing to efficiently model propagation in reconfigurable intelligent surface (RIS)-enabled communication channels. Full-wave simulation is used to obtain the radiation pattern of the transmitter and the complex radar cross section (RCS) of the RIS. Then, the RIS is imported into a ray-tracer as a secondary transmitter. That enables the modeling of the interaction of the RIS with complex environments. We present the formulation of the proposed technique and its validation against full-wave (finite element) results in representative scenarios of indoor propagation in the presence of an RIS. [ABSTRACT FROM AUTHOR]

The high in-bore magnetic field generated by synchronous induction coil launcher (SICL) was analyzed and measured. According to the current filament method, the magnetic induction intensity generated by the drive coils and each armature filament were calculated. The magnetic field distribution law of the synchronous induction coil launcher was obtained through magnetic field superposition principle. Based on the Biot-Savart law, the equation for calculating magnetic induction intensity of synchronous induction coil launcher was deduced, and the numerical calculation model of magnetic field distribution of synchronous induction coil launcher was established. The magnetic field distribution and numerical calculation model when the drive coils discharge with or without armature were carried out, and the numerical calculation results of the magnetic induction intensity when the drive coils discharge were compared with the finite element simulation results. Finally, the accuracy of the numerical calculation model was verified by comparing the one-dimensional hall probe arranged on the single-stage test platform with the simulation results.

Part of electrical engineering is circuit theory, which includes methods for calculating steady and transient currents in a series RL circuit. Power systems are typically inductive and can be modeled with RL circuits. An RL circuit is formed by a real voltage source, inductors and resistors. The inductance and resistance of the circuit elements do not depend on time. The ideal voltage source, which is part of the real source, has voltage depending on time. Current in a series RL circuit is the solution to an ordinary differential equation, which is a mathematical expression of Kirchhoff’s voltage law. The goal is the maximum possible reduction of mathematical manipulations in solving the equation for current calculation. Methods for solving the equation in a series RL circuit was proposed. In contrast to the literature, neither the phasor technique, the Fourier circuit analysis, the Laplace transform nor the convolution integral technique is used in the calculation of current. A mathematically correct solution to the equation is supplemented with solutions of illustrative examples. This solution is confronted with solution methods in electrical engineering and physics textbooks. The importance of the initial condition of current whose first derivative occurs in the equation is emphasized. An original definition of steady current and transient current is proposed.

This article investigates the noise performance of a two-element phased array and interferometer containing a recently introduced self-interference canceler, which in the context of this work acts as a mutual-coupling canceler. To this end, a general framework is proposed to permit noise analysis of this network and a large variety of other networks. The framework-based numerical analysis for a two-element-phased array shows that the addition of the canceler significantly increases the beam-equivalent noise temperature. For a two-element interferometer used in cosmology, this increase in noise temperature is still acceptable as the sky noise temperature in the 20-to-200 MHz band is high. When used in an interferometer, the canceler provides the ability to null mutual coherence at the interferometer output. The ability to provide matching to reduce the sensitivity of the null in mutual coherence to the phase of the $\boldsymbol {90^{\circ }}$ hybrids in the canceler is discussed. [ABSTRACT FROM AUTHOR]

Non-uniform constellations (NUCs) successfully utilize geometrical shaping to approach the Shannon capacity, but increase demapping complexity. In this paper, enhanced non-uniform constellations for low-complexity and high-capacity communications are investigated and addressed in two steps: low-complexity demappers for fixed constellations and the constrained design of enhanced NUCs. First, simplified demappers for NUCs are studied, and modified virtual point searching (VPS)-based demappers are proposed. Theoretical analysis and numerical results show that the proposed modified VPS-based demappers reduce demapping complexity with negligible performance degradation. Secondly, two shaping constraint schemes are proposed to NUC design for the purpose of low complexity and high capacity. NUCs optimized under the proposed constraints outperform the uniform constellations, and the proposed demappers have good applicability to the optimized NUCs. The proposed NUC design constraint schemes and simplified demappers enable solutions to achieve low-complexity high-capacity communication. [ABSTRACT FROM AUTHOR]

An advanced eddy current (EC) sensor incorporating with direct current (dc) magnetizing unit is presented, and its sensor signals are evaluated numerically considering hysteresis behavior. In this article, we propose an efficient method to calculate sensor signals while considering both a moving magnetizer and a high-frequency alternating current (ac) excitation. The calculation process is divided into two sequential analyses. The first step is a time-domain simulation to calculate a gradual change of dc magnetic field from the moving magnetizer. Then, its solution of the magnetic flux density is stored and used to make a subsequent magnetization curve based on the fitting equation-based hysteresis model. The obtained sub-magnetization curve is used for a time-harmonic simulation, and the sensor signal can be finally obtained. We applied the calculation method to a prototype sensor, and it enables to evaluate sensor signals quantitatively at the different magnetizing field and defect size. [ABSTRACT FROM AUTHOR]

The present work addresses the ongoing development of a mesh-based magnetic equivalent circuit (MEC) to estimate the magnetic flux distribution in a superconducting hybrid rotating synchronous machine, superconducting (SC) rotor, and conventional stator. The MEC is to be integrated in an existing thermoelectric lumped-parameter machine model for the transient simulation of High Temperature Superconductor (HTS) field coil synchronous generator (SG) in the dq0 frame of reference. It will allow the inclusion of the magnetic flux density inside the definition of the non-linear resistance of the superconductor in addition to the already-present temperature and current. The objective is to gain further accuracy on the coupled thermal and electromagnetic behavior of superconducting hybrid machines during partial or total loss of the superconducting state. In the present work, the MEC is benchmarked against a Finite Element Model (FEM). It is shown that the MEC can provide proper magnitude of the magnetic flux density over the HTS winding achieving a good estimation of the magnetic response of the field winding by taking into account the penetration of current within the superconductor. The case study is a 100-MVA hydroelectric HTS field coil SG considering a field current ramp. [ABSTRACT FROM AUTHOR]

A method for estimating the stability criterion in the space-time finite integration (FI) method using the subgrid technique was developed. Numerical- and analytical-dependent domains were compared to estimate the stability limit. Space-time subgrids locally refined with two, three, and four divisions were examined. The stability limit based on the proposed method almost agrees with that of the numerical experiment. [ABSTRACT FROM AUTHOR]

The quasi-static approximation that considers inductive–capacitive–resistive effects is referred to as the Darwin model of Maxwell’s equation. However, numerical analysis of the Darwin model is computationally expensive on account of large ill-conditioned equations. In this article, we proposed a new model order reduction technique for the Darwin model of Maxwell’s equations to drastically reduce the computational cost. In this method, four symmetric non-gauged equations were solved to obtain the basis vectors and avoid solving the non-symmetric equations. The reduced-order model (ROM) was obtained through congruent transformation, and time-domain analysis was performed using the time-difference method. We observed that the symmetric ROM was superior to the asymmetric ROM, in terms of accuracy and stability of the time-domain analysis. [ABSTRACT FROM AUTHOR]

Deep learning has achieved remarkable success in diverse applications; however, its use in solving partial differential equations (PDEs) has emerged only recently. Here, we present a feasibility study of applying physics-informed deep learning methods for solving PDEs related to the physical laws of electromagnetics. The methodology uses automatic differentiation, and the loss function is formulated based on the underlying PDE and boundary conditions. The feasibility of the method is shown using three electromagnetic problems of varying complexity and the results show close agreement with the ground truth from a finite-element analysis solver. The application of transfer learning is also explored and results in faster training. Furthermore, a hybrid approach involving physics-based governing equations and labeled data is also introduced to improve the accuracy of the results. [ABSTRACT FROM AUTHOR]

Most existing studies on autonomous intersection management (AIM) often focus on algorithms to accommodate conflicts among vehicles by assuming that the entrance lane and the exit lane of vehicles are exogenous inputs. This paper shows that allowing entrance lanes and exit lanes to be optimized can significantly improve traffic efficiency. In particular, this paper proposes “all-direction” lanes, where left-turn, through, and right-turn traffic is all allowed at the same lane. We develop two methods for optimizing entering time (i.e., when to enter the intersection) and route choice decisions (i.e., entrance lane and exit lane), including the sliding-time-window-based global optimum (GO-STW) and the first-come-first-served method with optimal route choices (FCFS-R). The developed lane-based methods can be formulated as mixed integer linear programming (MILP) problems, which can be solved using the CPLEX solver. A heuristic is further adopted to solve the MILP model in a timely manner, which illustrates the potential real-time applicability of the proposed method. Numerical analysis is conducted to examine performance and effectiveness of the proposed methods and heuristic. We found that the optimization of lane/route choices is often more critical than entering time. [ABSTRACT FROM AUTHOR]

In this work, we experimentally investigate the dynamics of pairs of opto-thermally driven, mechanically coupled, doubly clamped, silicon micromechanical oscillators, and numerically investigate the dynamics of the corresponding lumped-parameter model. Coupled limit cycle oscillators exhibit striking nonlinear dynamics and bifurcations in response to variations in system parameters. We show that the input laser power influences the frequency detuning between two non-identical oscillators. As the laser power is varied, different regimes of oscillations such as the synchronized state, the drift state, and the quasi-periodic state are mapped at minimal and high coupling strengths. For non-identical oscillators, coexistence of two states, the synchronized state and the quasi-periodic state, is demonstrated at high coupling and high laser power. Experimentally, this bistability manifests as irregular oscillations as the system rapidly switches between the two states due to the system’s sensitive dependence on initial conditions in the presence of noise. We provide a qualitative comparison of the experimental and numerical results to elucidate the behavior of the system. [2022-0005] [ABSTRACT FROM AUTHOR]

We present a design of reflector impulse radiating antenna (IRA) with six feeding arms and a printed tapered balun that also provides broadband matching to a $50 ~\Omega $ system. The design is obtained by thorough numerical analysis and optimization. Six feeding arms provide a lower input impedance while maintaining the same boresight gain in comparison to an IRA with four arms. By placing the balun in the antisymmetry plane of the antenna, boresight gain is practically intact and the resulting antenna construction is rigid. In order to increase the power handling for continuous-wave excitations, the resistors between the arms and the reflector are omitted yielding an antenna that can handle at least hundreds of watts. The compromises that arise when omitting the resistors are discussed. The results are verified by comparing the measurements of the fabricated prototype to the results obtained by the numerical analysis. [ABSTRACT FROM AUTHOR]

5G systems are becoming a reality and the evolution toward beyond 5G and 6G systems is already being defined, also to cope with the ever increasing capacity demanded by on-ground users. This will pose challenging requirements on the feeder link of future satellite systems, which risks to become a bottleneck for the overall system performance. In this article, we propose a novel architecture of linear precoding for the feeder link of a broadcast satellite system operating with full frequency reuse to significantly enhance the achievable capacity. The architecture has been simulated and tested in a challenging multifrequency scenario, where Ku, Ka, Q/V, and W bands have been considered for transmission. The numerical performance analysis and the open issues related to the practical realization of the proposed architecture are also thoroughly discussed. [ABSTRACT FROM AUTHOR]

Thermal management using nanofluids has gained popularity in recent times owing to their superior thermophysical properties enabling higher heat dissipation levels in electronic components. Boiling process or latent heat component greatly enhances the heat transfer and considering the complexity of boiling phenomenon and the high cost of nanofluids, there is an excellent scope for numerical studies in this area. In the present study, an Eulerian multiphase model is developed to ascertain the pool boiling characteristics of Alumina nanofluid at atmospheric pressure using a flat plate heater. The previous experimental study conducted by the authors is used as a reference and for validation of the numerical model. The pool boiling curves for 0.5%, 1%, and 2% Alumina nanofluids with water as base fluid are obtained through numerical simulations employing the heat flux partitioning (HFP) model. A significant enhancement in the pool boiling heat flux is reported and compared with the available literature on alumina nanofluids. The theoretical correlations for nucleate pool boiling, namely, the Rohsenow correlation and the Kandlikar correlation, were found to under-predict heat flux compared to numerical results. The significance of critical heat flux (CHF), or the onset of boiling crisis in pool boiling, is detailed and a methodology for numerically determining the same is developed. The CHF enhancement of up to 120% over the base fluid reported in the present study is found to be consistent with the experimental results. [ABSTRACT FROM AUTHOR]

In this article, a two-dimensional hybrid finite-element formulation is proposed to further reduce the computational time required for the time simulation of superconducting (SC) bulks. Low computational time formulations are important for the design stage of electrical machines with superconductors, where optimization tools are typically used. The proposed hybrid formulation is based on the partitioned E-H electromagnetic scheme (EHS) formulation and the magnetic vector potential formulation (A-formulation). The EHS formulation is used to solve the domains with highly nonlinear electric materials, while the A-formulation is used to solve the nonelectric domains. The main characteristics of the EHS are its partitioned formulation, where the matrix form of Ampère's and Faraday's laws is separated and computed a priori, and the electric resistivity is defined at each node. The EHS formulation is first compared with the H-formulation for a single SC domain and then integrated with an A-formulation and compared with the H and H-φ formulations to simulate a bulk surrounded by air. Results verify the excellent accuracy of the EHS and A-EHS formulations, and a promising reduction of computational time is observed, with more emphasis on low levels of magnetization of the SC sample. When compared with the H-φ formulation, a time reduction between 48% (6 T) and 90% (1 T) is obtained. [ABSTRACT FROM AUTHOR]

Carbon-fiber-reinforced-polymer (CFRP) materials have been widely used in military and civilian fields to replace metals as load-bearing structural components. Nevertheless, due to the complex and anisotropic internal structures, its electromagnetic (EM) protection capability is different from metal materials. Aiming at studying the EM properties of CFRP materials, an efficient analysis method based on the anisotropic finite-difference time-domain (FDTD) algorithm was proposed. First, the equivalent EM parameter tensors of a single-layer CFRP lamina were calculated by using the $S$ -parameter retrieval method. Then, a multilayer equivalent EM parameter model was established, and the execution equations of the anisotropic FDTD algorithm were derived. Finally, the influence of layer number, fiber orientation pattern, carbon fiber conductivity, and doping ratio on EM properties were studied by using the obtained method. The numerical analysis results indicated that the proposed method could improve the computational efficiency significantly while keeping the accuracy. The conclusions can provide certain engineering guidance for the electrical application of CFRP materials. [ABSTRACT FROM AUTHOR]

Modeling the geomagnetic induction in pipeline networks is essential for the risk assessment and management of geomagnetic disturbances. The induced geoelectric field (GEF) is usually spatially nonuniform, depending on the distribution of the geomagnetic variation and the earth conductivity. However, few studies have been conducted on the induction in complex pipeline networks with nonuniform GEF. In this article, a calculation model for induction in pipeline networks with nonuniform GEF is proposed by utilizing the modified equivalent-pi circuits. Then, the proposed model is used to investigate the distribution of pipe-to-soil potentials and geomagnetically induced currents in the pipeline network under several typical nonuniform GEF scenarios due to geomagnetic source fields, including local enhancement and spatially gradual variation. Furthermore, taking the coast effect as a typical case, the influence of the lateral variation of earth conductivity on the induction is analyzed. The results show that the nonuniform GEF may greatly affect the induction results in the local parts of the pipeline network. [ABSTRACT FROM AUTHOR]

This article addresses the efficient numerical analysis of sparsely distributed small modifications in a large structure, that is, the sparsely distributed partial modification problem (SDPMP). A hierarchical matrix (H-matrix)-based fast direct solver is adopted to solve the SDPMP in a very short time for each new set of modifications. The main idea of this method is to reuse the parts of the compressed inverse matrix operator that do not change and only recompute the modified parts. In contrast with already existing algorithms designed to tackle a single localized modification, this new approach is still very fast for sparsely distributed small modifications, so it becomes a very attractive option to solve optimization problems efficiently, due to the very cheap analysis of the modified structure at each iteration of the optimization procedure. The efficiency of the solution of SDPMP is demonstrated for several cases involving passive and active metasurfaces and a reconfigurable antenna. As a practical example, a programmable metasurface reflector is optimized with particle swarm optimization to obtain a prescribed reflection pattern. [ABSTRACT FROM AUTHOR]

Magnetic fluid seals are widely used. However, during the filling process of the magnetic fluid, a large part of the magnetic fluid is attracted to the magnet, causing the loss of the magnetic fluid, and the magnetic fluid sealing device can easily cause damage to the pole teeth due to the problem of disassembly and installation. To solve the above problems, this article designs a pole piece integrated magnetic-fluid sealing structure and a new type of disassembly and installation method. The finite element method is used to calculate the magnetic field distribution of the pole piece integrated magnetic fluid seal structure, and the theoretical withstand pressure value is obtained according to the withstand pressure calculation formula. Three kinds of magnetic fluids were used to conduct comparative experiments on the magnetic fluid sealing device at different temperatures and different filling amounts. The results showed that the pressure resistance of the magnetic fluid sealing increased with the increase of the filling amount, and the increase of the saturation magnetization, consistent with theory. It is also found that the thickness of the pole piece is very thin. During the processing, Compared with the ordinary pole piece, the integrated pole piece has the advantage of large length, the coaxial is easily ensured, and the processing difficulty is reduced; second, during the filling process, all the magnetic fluid is sucked to the pole teeth, there is no loss of the magnetic fluid, and the pole teeth are intact after more than a hundred times of disassembly and installation, which further improves the life of the magnetic fluid sealing device. [ABSTRACT FROM AUTHOR]

Many complex nonlinear optimization or control issues can be transformed into the solving of time-varying nonlinear equations (TVNEs), playing a fundamental role in the control and management of complex systems. As a result, a robust and high-precision online solution method is significant for TVNE. However, there are three main challenges for handling TVNE via the existing methods: First, short-time invariance assumption frequently leveraged in the existing methods leads to lagging errors that are difficult to eliminate. Second, it is difficult in dealing with unknown noise disturbance during the solution process, which causes low solution accuracy or solution failure. Third, existing continuous-time methods are hard to be implemented on digital equipments. In this article, an anti-noise discrete-time neural dynamics (DTND) is designed and studied to overcome the above issues systematically. The theoretical analysis and numerical simulations demonstrate that the proposed model effectively eliminates the lagging errors and achieves the accurate solution of the TVNE in a noisy environment. Moreover, to verify the superior numerical computational property of the DTND model, the intention recognition of lower limbs is explored from the artificial systems, computational experiments, and parallel execution (ACP) framework. Specifically, a nonlinear artificial dynamic system (NADS) concerning the human surface electromyogram (sEMG) signals and joint information is established, which performs in parallel with the actual human lower limb physical experiments. Simulation results illustrate that, within the acceptable range of the digital computer, the controller designed by the DTND model can well guide the NADS to accurately recognize the motion intention of the human lower limb. [ABSTRACT FROM AUTHOR]

In this article, an optimized tracking control scheme is studied for the quadrotor unmanned aerial vehicle (QUAV) system by combining both reinforcement learning (RL) and the backstepping technique. The RL aims to overcome the difficulty coming from solving the Hamilton–Jacobi–Bellman (HJB) equation, and it is performed via iterating both critic and actor each other, where the critic is for improving the control performance and the actor is for executing the control behavior. In mathematics, a QUAV system is composed of two connected subsystems that are, respectively, modeled by the translational and rotational dynamic equations, which are coupled via a rotation matrix; hence, the optimized tracking scheme is composed of two interconnected individual controls corresponding to the position and attitude, respectively. To achieve the two optimized position and attitude controls, the RL is constructed on the basis of the neural network (NN) approximation of the HJB equation’s solution by utilizing NN’s outstanding function approximation ability. Particularly, the position control is accomplished by introducing an intermediate control because the translational dynamic is an underactuated system. Since the proposed RL algorithm is significantly simple in comparison with the published methods, the optimized QUAV control can be easily executed in practical applications. Finally, the results are demonstrated by a Lyapunov stability analysis and a numerical simulation. [ABSTRACT FROM AUTHOR]

An effective method for identifying inertia characteristics of cone-shaped space target based on deep learning is proposed. The inertia ratio is determined by the time-varying scattering fields from the cone-shaped targets. The multistatic method is introduced to reduce the evaluation time of time-varying scattering fields. The micro-Doppler spectrogram (MDS) dataset is constructed by the time–frequency analysis with numerical simulation method, point scattering model, and experimental tests. The compressed dataset is further achieved by truncated singular value decomposition (SVD). Finally, the micromotion parameter identification model is constructed to identify the inertia ratio for the cone-shaped space target. The interaction loss function and the feedforward denoising convolutional neural networks (DnCNNs) are employed to improve the identification accuracy. Parameters identification of the precession frequency, precession angle, spin frequency, and inertia ratio with both simulation and experiment datasets demonstrate the validity of the proposed method. [ABSTRACT FROM AUTHOR]

Advanced applications of the finite-element method use hybrid meshes of differently shaped elements that need transition cells between quadrilateral- and triangular-faced elements. The greatest ease of construction is obtained when, in addition to triangular prisms, one uses also pyramids with a quadrilateral base, as these are the transition elements with the fewest possible faces and edges. A distinctive geometric feature of the pyramid is that its vertex is the point in common with four of its faces, while the other canonical elements have vertices in common with three edges and three faces, and that is why pyramids’ vector bases have hitherto been obtained with complex procedures. Here, we present a much simpler and more straightforward procedure by shifting to a new paradigm that requires mapping the pyramidal cell into a cube and then directly enforcing the conformity of the vector bases with those used on adjacent differently shaped cells (tetrahedra, hexahedra, and triangular prisms). The hierarchical curl-conforming vector bases derived here have simple and easy to implement mathematical expressions, including those of their curls. Base completeness is demonstrated for the first time, and results confirming the avoidance of spurious modes and faster convergence are also reported. [ABSTRACT FROM AUTHOR]

The growing number of elderly people (EP) has become one of the most important problems in recent years. This part of the population is often dependent and does not tolerate environmental changes well, so long-term care (LTC) structure assignments should be well prepared. This article proposes a stochastic optimization approach to solve the LTC structure assignment problem for a population of EP while taking into account health state changes and uncertain future demand. The objective of this approach is to make the best assignment decision among several structures or to wait for a better solution if no suitable structure is available. The model is validated and calibrated on the basis of stakeholder objectives and territorial special features through simulation. We propose a numerical analysis based on both quantitative and qualitative analyses to compare our model with simple assignment policies. Note to Practitioners—The increase in the elderly and dependent population and the lack of a long-term structure to address this aging population make it difficult to assign EP to the appropriate LTC. This decision often determines the quality of the end of life. Several parameters must be taken into account to choose the best solution: the health situation, geographic location, and financial resources. If the elderly person stays too long in a situation not suited to his/her condition, then his/her risk of a decline in health is significant. The dilemma is whether to choose: 1) to wait to have the structure most adapted to the health of the state or 2) to assign the elderly person to the most suitable structure available. We propose a stochastic optimization approach to help stakeholders assign EP to an LTC structure in a given territory. The model uses projections of the health state of the population over a time horizon to make decisions and considers elderly care requirements and characteristics, such as geographic compatibility and financial resources. The model performs better than a greedy algorithm (based on the first-in-first-out approach) and an optimization model without time projections. [ABSTRACT FROM AUTHOR]

The virtual track train (VTT) is a new type of urban transit system with all-wheel active steering technology utilized to make the long combination vehicle run along the planned route (virtual track) like railway vehicles along physical track. This paper proposed a scalable cascade modular path following control strategy for the newly designed gantry virtual track train (G-VTT) based on preview & tracking controller, focusing on the lateral control for low-speed turning manoeuvre. The mathematical characteristics of the 2-norm was utilized to establish a local tracking objective function (LTOF) to find the optimal lateral acceleration (OLA) of the tracking point in the preview window and calculate the optimal wheel steering angle (WSA) to achieve the optimal local trajectory. Considering the lag time Td, the yaw stability and path following ability of the vehicle are contradictory in some cases, so the damping adjustment factor λ was proposed to optimize the damping characteristics and the time-delay stability factor ξ was proposed to evaluate the time-delay stability. The influence of the key parameters, preview time Tp, Td, ξ and λ, on the stability and following ability were analyzed by frequency domain analysis method, and the optimal region of ξ and λ was obtained to instruct the configuration of λ and Tp. Finally, steady-state and dynamic forward predictive models were proposed to compensate for the oscillation caused by the lag time. The effectiveness of the proposed control strategy, forward predictive models and the configuration method of λ and Tp were verified by theoretical analysis and numerical simulation. [ABSTRACT FROM AUTHOR]

To exploit users’ heterogeneous data demands, several mobile network operators worldwide have launched the mobile data trading markets, where users can trade mobile data quota with each other. In this paper, we aim to understand the importance of data trading market (DTM) by studying the users’ operator selection and trading decisions, and analyzing the operator’s profit maximizing strategy. We model the interactions between the mobile operator and the users as a three-stage Stackelberg game. In Stage I, the operator chooses the operation fee imposed on sellers to maximize its profit. In Stage II, each user chooses his operator. In Stage III, each DTM user chooses his trading decisions. We derive the closed-form expression of the unique Nash equilibrium (NE) in Stages II and III, where every user proposes the same price such that the total demand matches with the total supply. We further show that the Stage I’s problem is convex and compute the optimal operation fee. Our analysis and numerical results show that an operator with a small initial market share can increase its profit by proposing a DTM, which is in line with the real-world situation in Hong Kong. [ABSTRACT FROM AUTHOR]

In recent robotic applications, a critical need is to simultaneously detect communication (emission state) and estimate its trajectory. Whilst wireless sensor observations are useful, they are often uncertain due to the stochastic communication bursts and robot mobility. Over-sampling the information environment can incur excessive radio interference and energy usage. Therefore, one challenge is how to improve the efficiency of sensing under sparse and dynamic information, and make accurate inference on the robot's location. Here, we design a novel mixed detection and estimation (MDE) scheme to enhance both the accuracy and the efficiency by exploiting the mobility pattern correlations. Relying on a Markov state-space model, dynamic behaviors of robot's communication state and movement are formulated. A two-stage sequential Bayesian scheme, premised on random finite set (RFS), is developed to detect and estimate the involved unknown states. Specifically, in order to counteract the probability likelihood disappearance (caused by no information emission) and improve robustness to ambient noise, a sequential pre-filtering technique is designed, which can refine local observations and thereby significantly improve the accuracy of the system. We validate the proposed MDE scheme via both theoretical analysis and numerical simulations, demonstrating it would improve both the detection and estimation accuracy and efficiency. [ABSTRACT FROM AUTHOR]

A detailed analysis of theexcited state absorption (ESA) transition 4I13/2→4I9/2 which occurs in erbium (Er) doped ZBLAN fiber lasers is performed through numerical modeling. It is found that the ESA plays a significant role in enhancing the 2.8 μm lasing of Er3+ ions. The ESA promotes the ions residing in 4I13/2 (the lower state of the 2.8 μm laser) to 4I9/2, where the ions subsequently decay to 4I11/2 (the upper state of the 2.8 μm laser) rapidly. An energy recycling is consequently realized via the ESA. The ESA can be activated in cascaded 2.8 μm/1.6 μm Er-doped ZBLAN fiber lasers by absorbing the 1.6 μm signal. Through numerical simulation it is found that in cascaded lasers the slope efficiency of the 2.8 μm laser can be elevated to ∼48% with the assistance of the ESA, a value that surpasses the Stokes limit (∼35%) substantially and agrees well with the experimental results previously reported. It is also found that the ESA-induced energy recycling is exothermic, an effect that is non-ignorable in the high-power circumstance. Moreover, the injection of an additional 1.6 μm pump for directly exploiting the 4I13/2→4I9/2 ESA is simulated using the model. It is found that as the second pump is introduced, the 2.8 μm lasing almost entirely relies on the ESA-induced energy recycling, and hence, the laser is capable of operating under very low 976 nm pump power. The simulation results indicate that the 2.8 μm lasing in Er-doped ZBLAN fiber lasers can even be realized using a single 1.6 μm pump, via a combination of the 4I15/2→4I13/2 and 4I13/2→4I9/2 transition. The outcomes of this work can inspire the development of novel, high-performance 2.8 μm Er-doped ZBLAN fiber lasers. [ABSTRACT FROM AUTHOR]

A promising 2-mm-long highly coherent air-clad suspended core planar Si-rich SiN tapered waveguide is proposed for supercontinuum generation in the midinfrared. Supercontinuum evolution is investigated by tuning the waveguide for both of the transverse-electric (TE) and transverse-magnetic (TM) polarizations employing pump at 1.55 m with a pulse duration of 50-fs and peak power of 50 W. Optimum waveguide dimensional parameters including width and thickness are obtained between 1.5-3 $\mu$ m and 250 nm for TE excitation and 270–330 and 1.5 $\mu$ for TM excitation, respectively, keeping slab thickness constant at 100 nm for both the designs. Initially, SC coverages are investigated for two uniform sections situated at the terminal points of the waveguide. Spectral coverages are also studied for two types of tapered approaches: increasing order tapering (IOT) and decreasing order tapering (DOT). In the case of uniform waveguide, simulation results of either excitation show that SC coverage can be predicted beyond 5 $\mu$ in the midinfrared. On the other hand, width varying IOT approach for TE and DOT approach for TM excitation make better impacts both in spectral extension and spectral flatness owing to simultaneous variations of dispersion and nonlinearity along the pulse propagation direction. Thus, the midinfrared supercontinuum extension up to 6 $\mu$ by TE and 6.3 $\mu$ by TM with better spectral flatness can be predicted by the proposed taper compared to the traditional waveguide design. Finally, the coherence of the generated SC is also studied for the various tapering coefficients at the proposed waveguide output. [ABSTRACT FROM AUTHOR]

A novel multi-instant gain-scheduling scheme is proposed in order to further improve the state estimation performance of discrete-time Takagi–Sugeno fuzzy systems in this article. Different from those existing methods, the enabled working pattern at each sampling instant can be determined in cycle according to utilization of the updated information of adjacent normalized fuzzy weighting functions in depth, and then the featured time-varying free matrices are introduced for each working pattern, which can remove those existing constraints on traditional free matrices. Consequently, the conservatism can be reduced significantly and it does broaden the range of application for observer-based fuzzy state estimation. Despite the fact that the quantity of the free matrices becomes much bigger than before, it needs to be pointed out that the actual computational complexity only increases by a small amount through depressing the number of cycles. Given that the developed designing process belongs to an offline computation, it is an acceptable tradeoff between the increasement of computational burdens and the reduction of conservatism. In the end, the effectiveness of the developed method is illustrated through the detailed analysis of numerical simulations. [ABSTRACT FROM AUTHOR]

In this paper, we address the problem of joint direction-of-arrival (DoA) and range estimation using frequency diverse coprime array (FDCA). By incorporating the coprime array structure and coprime frequency offsets, a two-dimensional space-frequency virtual difference coarray corresponding to uniform array and uniform frequency offset is considered to increase the number of degrees-of-freedom (DoFs). However, the reconstruction of the doubly-Toeplitz covariance matrix is computationally prohibitive. To solve this problem, we propose an interpolation algorithm based on decoupled atomic norm minimization (DANM), which converts the coarray signal to a simple matrix form. On this basis, a relaxation-based optimization problem is formulated to achieve joint DoA-range estimation with enhanced DoFs. The reconstructed coarray signal enables application of existing subspace-based spectral estimation methods. The proposed DANM problem is further reformulated as an equivalent rank-minimization problem which is solved by cyclic rank minimization. This approach avoids the approximation errors introduced in nuclear norm-based approach, thereby achieving superior root-mean-square error which is closer to the Cramér-Rao bound. The effectiveness of the proposed method is confirmed by theoretical analyses and numerical simulations. [ABSTRACT FROM AUTHOR]