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Positioning accuracy and power consumption are essential performance indicators of integrated navigation and positioning chips. This paper proposes a single-frequency GNSS/MEMS-IMU/odometer real-time high-precision integrated navigation algorithm with dynamic power adaptive adjustment capability in complex environments. It is implemented in a multi-sensor fusion navigation SiP (system in package) chip. The simplified INS algorithm and the simplified Kalman filter algorithm are adopted to reduce the computation load, and the strategy of adaptively adjusting the data rate and selecting the observation information for measurement update in different scenes and motion modes is combined to realize high-precision positioning and low power consumption in complex scenes. The performance of the algorithm is verified by real-time vehicle experiments in a variety of complex urban environments. The results show that the RMS statistical value of the overall positioning error in the entire road section is 0.312 m, and the overall average power consumption is 141 mW, which meets the requirements of real-time integrated navigation for high-precision positioning and low power consumption. It supports single-frequency GNSS/MEMS-IMU/odometer integrated navigation SiP chip in real-time, high-precision, low-power, and small-volume applications.

Medium-deep borehole heat exchanger (BHE) systems represent an emerging form of ground source heat pump technology. Their heat transfer process is significantly influenced by geothermal gradient and soil stratification, typically simulated using segmented finite line source (SFLS) models. However, this approach involves computationally intensive procedures that hinder practical engineering implementation. Building upon an SFLS model adapted for complex geological conditions, this study proposes a comprehensive simplified algorithm: (1) For soil stratification: A geothermally-weighted thermal conductivity method converts layered heterogeneous media into an equivalent homogeneous medium; (2) For geothermal gradient: A temperature correction method establishes fluid temperatures under geothermal gradient by superimposing correction terms onto uniform-temperature model results (g-function model). Validated through two engineering case studies, this integrated algorithm provides a straightforward technical tool for heat transfer calculations in BHE systems.

Aiming at the problem of serious shutdowns of conveyors caused by abnormal coal flow of scraper conveyors, a coal flow monitoring method based on speckle structured light is proposed. The point cloud data of the coal body on the scraper conveyor is collected through the speckle structured light acquisition system. Then, the proposed PDS-Algorithm (Planar Density Simplification Algorithm) is used to complete the simplification and differentiation of the collected point cloud data, which provides a basis for constructing geometric characteristics of coal flow lineament. This paper uses the processed point cloud data to calculate the volume of the coal mass and monitor the coal flow of the scraper conveyor. Finally, this method is used in the detection of abnormal coal flow of a coal mine scraper conveyor, and the results show that the proposed abnormal flow monitoring method can meet the accuracy and real-time requirements of coal mine abnormal alarms.

Adaptive façades represent a viable and effective technological solution to reduce the building energy demand for cooling while achieving interesting aesthetic effects on the building envelope to screen solar radiation. During the last decade, many different design solutions, including those based on shape memory alloys, have been experimented to obtain appropriate responses without being dependent on electro-mechanically actuated systems. Several recent and ongoing studies have been published in the scientific literature regarding the different actuator typologies, as well as the different properties of the materials used, which usually determine the adaptive solution characteristics after a series of complex and time-consuming simulations using specialised dynamic modelling software. Due to the time and resources required, this kind of evaluation is usually delivered during the last and more advanced design stage as a form of assessment of already-taken architectural and technological choices. The study reported in the paper aims to offer a quick, time-saving simplified algorithm to calculate the response of an adaptive façade, according to the ISO 13790 standards, to be adopted during the early design stage to evaluate the possible effects of design decisions. The study includes three main steps: (a) the conceptualisation of the adaptive solution considering the context conditions; (b) the definition of the calculation algorithm; (c) the application of the method to a test room in a case study building located in Bologna for supporting the discussion of the related outcomes.

For the time scale of the applied pulses is orders of magnitude smaller than the time scale on which the workpiece is machined, simulation of the temperature evolution and the changes of the workpiece shape in pulse electrochemical machining (PECM) process would be a computationally very expensive procedure. A multi-physics model and the quasi steady state shortcut (QSSSC) approach are presented for modeling the temperature evolution in PECM process. By defining a critical upper limit, a simplified algorithm is introduced to simulate the changes of workpiece shape in PECM process. The assumption is made that geometry structure is fixed before the system reaches the quasi steady state (QSS) and the material removal is calculated by current density when the QSS is reached. Simulation results indicate that the simplified algorithm is convenient for the calculation of the shape change of the electrodes. The validity of the simplified algorithm is verified by the comparison of workpiece profiles obtained by simulation prediction and experiments.

Abstract Network systems are commonly used in various fields, such as power grids, Internet of Things, and gas networks. The reliability redundancy allocation problem is a well-known reliability design tool that needs to be developed when the system is extended from a series-parallel structure to a more general network structure. Therefore, this study proposes a novel reliability redundancy allocation problem, referred to as the general reliability redundancy allocation problem, to be applied in network systems. Because the general reliability redundancy allocation problem is NP-hard, a new algorithm referred to as binary-addition simplified swarm optimization is proposed in this study. Binary-addition simplified swarm optimization combines the accuracy of the binary addition tree algorithm with the efficiency of simplified swarm optimization, which can effectively reduce the solution space and speed up the time required to find high-quality solutions. The experimental results show that binary-addition simplified swarm optimization outperforms three well-known algorithms: the genetic algorithm, particle swarm optimization, and simplified swarm optimization in high-quality solutions and high stability on six network benchmarks. Graphical Abstract Graphical Abstract

This study proposes a simplified super-twisting algorithm (SSTA) control strategy for improving the power quality of grid-connected photovoltaic (PV) power systems. Some quality issues are considered in this study including the power factor, reducing the total harmonic distortion (THD) of current, compensating the reactive power, and injecting at the same time the energy supplied by the PV system into the grid considering non-linear load. This improvement is achieved by two topologies; controlling both the boost DC–DC converter and the DC–AC inverter that links the PV system to the grid. The DC–DC converter is controlled using proportional-integral (PI) and SSTA to maximize the power generated from the PV panel regardless of its normal and abnormal conditions, while the DC–AC inverter is employed to direct power control strategy with modified space vector modulation using the phase-locked loop (PLL) technique of a three-level neutral-point-clamped (NPC) inverter based on the proposed strategies (PI and SSTA). In addition, a shunt active power filter (SAPF) is used to connect the PV system to the AC grid and feed a non-linear load. To validate the simulation results presented in this paper using Matlab software, a comparative study between the PI controller and the SSTA is presented. The results show the effectiveness and moderation of the suggested SSTA technique in terms of feasibility, tracking performance, less power ripple, dynamic response, THD value, overshoot, steady-state error, and robustness under varying irradiation, temperature, and non-linear conditions.

To address the challenges of global warming and the greenhouse effect, extensive research has been dedicated to microgrids (MGs) powered by renewable energy sources (RESs). This paper presents an innovative control mechanism, the synergetic simplified super-twisting algorithm (SSSTA), designed specifically for a DC-MG incorporating a battery energy storage system (BESS), a solar photovoltaic (PV) unit, and DC loads. The PV system connects to a shared DC bus via a unidirectional DC–DC boost converter, optimized for maximum power point tracking from the PV generator. At the same time, the BESS is linked using a bidirectional DC–DC buck-boost converter to the same bus, aimed at maintaining supply–demand balance within the DC-MG through charging and discharging. The SSSTA is designed to regulate each power control unit in the MG. It ensures the desired voltage level at the common DC bus while tailoring energy allocation to meet load requirements. The study shows that SSSTA improves the performance and stability of DC-MG systems incorporating solar PV and batteries. By implementing SSSTA, the stability of the MG system is sustained even under varying load conditions, thereby minimizing the impact of disturbances such as fluctuations in load demand and solar irradiation. As a result, implementing this control strategy enhances the reliability and efficiency of MGs integrated with RESs, promoting broader adoption. Furthermore, to offer a clearer understanding of the proposed control approach, the results of the proportional-integral control are also presented. Simulation experiments in MATLAB confirm the effectiveness of the designed control mechanism.

The aquila optimization algorithm (AO) is an efficient swarm intelligence algorithm proposed recently. However, considering that AO has better performance and slower late convergence speed in the optimization process. For solving this effect of AO and improving its performance, this paper proposes an enhanced aquila optimization algorithm with a velocity-aided global search mechanism and adaptive opposition-based learning (VAIAO) which is based on AO and simplified Aquila optimization algorithm (IAO). In VAIAO, the velocity and acceleration terms are set and included in the update formula. Furthermore, an adaptive opposition-based learning strategy is introduced to improve local optima. To verify the performance of the proposed VAIAO, 27 classical benchmark functions, the Wilcoxon statistical sign-rank experiment, the Friedman test and five engineering optimization problems are tested. The results of the experiment show that the proposed VAIAO has better performance than AO, IAO and other comparison algorithms. This also means the introduction of these two strategies enhances the global exploration ability and convergence speed of the algorithm.

By increasing the demand for radio frequency (RF) and access of hackers and spoofers to low price hardware and software defined radios (SDR), radio frequency interference (RFI) became a more frequent and serious problem. In order to increase the security of satellite communication (Satcom) and guarantee the quality of service (QoS) of end users, it is crucial to detect the RFI in the desired bandwidth and protect the receiver with a proper mitigation mechanism. Digital narrowband signals are so sensitive into the interference and because of their special power spectrum shape, it is hard to detect and eliminate the RFI from their bandwidth. Thus, a proper detector requires a high precision and smooth estimation of input signal power spectral density (PSD). By utilizing the presented power spectrum by the simplified Welch method, this article proposes a solid and effective algorithm that can find all necessary interference parameters in the frequency domain while targeting practical implantation for the embedded system with minimum complexity. The proposed detector can detect several multi narrowband interferences and estimate their center frequency, bandwidth, power, start, and end of each interference individually. To remove multiple interferences, a chain of several infinite impulse response (IIR) notch filters with multiplexers is proposed. To minimize damage to the original signal, the bandwidth of each notch is adjusted in a way that maximizes the received signal to noise ratio (SNR) by the receiver. Multiple carrier wave interferences (MCWI) is utilized as a jamming attack to the Digital Video Broadcasting-Satellite-Second Generation (DVB-S2) receiver and performance of a new detector and mitigation system is investigated and validated in both simulation and practical tests. Based on the obtained results, the proposed detector can detect a weak power interference down to −25 dB and track a hopping frequency interference with center frequency variation speed up to 3 kHz. Bit error ratio (BER) performance shows 3 dB improvement by utilizing new adaptive mitigation scenario compared to non-adaptive one. Finally, the protected DVB-S2 can receive the data with SNR close to the normal situation while it is under the attack of the MCWI jammer.