Search Results (27,904)

Most of the previous SOC equalization methods for microgrid energy storage target DC microgrids and use centralized control structures, while in recent years many researchers have begun to focus on a decentralized, communication-based implementation of distributed control structures. In this paper, based on the existing research, we use the multi-agent system (MAS) structure and dynamic consistency algorithm (DCA) to realize the estimation of the SOC mean value of microgrid energy storage obtained by each agent in the system. For the problems of the iterative convergence that exists in the distributed control, such as being too slow, too frequent communication, stability, etc., we optimally select the parameters of the consistency iterative summation to improve convergence. In addition, we use the event-driven method to further reduce the unnecessary communication frequency. Finally, a numerical simulation model of the AC microgrid is established by Matlab to verify the effectiveness of the method, which reduces the communication volume by about 50% while maintaining the effect of the control strategy. Full article

As China’s “Dual Carbon” strategy is implemented and the new urbanization advances, balancing economic development, emission reduction, and carbon sequestration has become an important issue during the growth of emerging metropolitan areas, and it is also important for achieving high-quality urban development. Therefore, this study had three major objective functions: economic growth, carbon emission reduction, and increased carbon storage. The multi-objective land use quantity structure was solved using the Non-dominated Sorting Genetic Algorithm II (NSGA-II), and the best solution in the solution set was introduced using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) for evaluation. Finally, combined with the Future Land Use Simulation (FLUS) model, the low-carbon evolution of the metropolitan area was predicted on a spatial scale. The trade-off plan results show that by 2035, the economic benefits will reach CNY 7.65 trillion, carbon emissions will be kept under 99.24 million tons, and carbon storage will steadily increase by 15.2 million tons. Therefore, optimizing land use from the perspective of balancing carbon emissions, carbon sequestration, and economic development can provide valuable references for planning low-carbon development and the rational use of spatial resources in future metropolitan areas. Full article

In the past two decades, there has been a noticeable decoupling of machines and operating systems. In this context, WebAssembly has emerged as a promising alternative to traditional virtual machines. Originally designed for execution in web browsers, it has expanded to executing code in restricted and secure environments, and it stands out for its rapid startup, small footprint, and portability. However, WebAssembly presents significant challenges in data transfer and the management of interactions with the module. Its specification requires each module to have its own memory, resulting in a “share-nothing” architecture. This restriction, combined with the limitations of importing and exporting functions that only handle numerical values, and the absence of an application binary interface (ABI) for sharing more complex data structures, leads to efficiency problems; these are exacerbated by the variety of programming languages that can be compiled and executed in the same environment. To address this inefficiency, the Karmem was designed and developed. It includes a new interface description language (IDL) aimed at facilitating the definition of data, functions, and relationships between modules. Additionally, a proprietary protocol—an optimized ABI for efficient data reading and minimal decoding cost—was created. A code generator capable of producing code for various programming languages was also conceived, ensuring harmonious interaction with the ABI and the foreign function interface. Finally, the compact runtime of Karmem, built atop a WebAssembly runtime, enables communication between modules and shared memory. Results of the experiments conducted show that Karmem represents an innovation in data communication for WASM in multiple environments and demonstrates the ability to overcome challenges of efficiency and interoperability. Full article

Changes in crop types and long-term monoculture substantially impact soil microbial communities. Exploring these changes and their influencing factors is of great significance for addressing the challenges posed by continuous cropping. Soil surface layer samples from greenhouse tomatoes fields cultivated for 5 (Y5), 9 (Y9), 13 years (Y13), and a surrounding corn field (CK) as a control were analyzed. The Y13 sample showed a significant increase in the relative abundance of Pseudomonadota (43.1%) and a decrease in Actinobacteria (50.3%) compared to the CK sample. Soil bacterial alpha diversity generally declined from the CK to Y13 (0.1–22.2%) sample, with a small peak in Y9 for Chao1 and Observed_species. Significant differences in Chao1 and Observed_ species were observed between the CK and Y13 samples. Beta diversity analysis revealed a pronounced variation in soil bacterial community structure across planting years, with the divergence from the CK sample intensifying over time. In comparison to the Y5 vs. CK samples, Y9 and Y13 exhibited marked differences from the CK across the same and broader metabolic pathways, suggesting a potential convergence of microbial activities over time. The Y9 and Y13 samples showed significantly higher biosynthesis abundance (7.50% and 6.36%, respectively) than the CK. In terms of soil physicochemical indices, the carbon–nitrogen ratio was the primary factor influencing soil bacterial composition. In conclusion, we found that crop alteration and continued planting changed the soil’s bacterial composition and increasing planting years suppressed the soil’s bacterial diversity, leading to a stable bacterial ecology after nine years. Implementing appropriate measures during this critical period is vital for optimal soil utilization. Full article

In this study, a model-free  PIφ-sliding mode control ( PIφ-SMC) methodology is proposed to synchronize a specific class of chaotic fractional-order memristive neural network systems (FOMNNSs) with delays and input saturation. The fractional-order Lyapunov stability theory is used to design a two-level  PIφ-SMC which can effectively manage the inherent chaotic behavior of delayed FOMNNSs and achieve finite-time synchronization. At the outset, an initial sliding surface is introduced. Subsequently, a robust  PIφ-sliding surface is designed as a second sliding surface, based on proportional–integral (PI) rules. The finite-time asymptotic stability of both surfaces is demonstrated. The final step involves the design of a dynamic-free control law that is robust against system uncertainties, input saturations, and delays. The independence of control rules from the functions of the system is accomplished through the application of the norm-boundedness property inherent in chaotic system states. The soft actor-critic (SAC) algorithm based deep Q-Learning is utilized to optimally adjust the coefficients embedded in the two-level  PIφ-SMC controller’s structure. By maximizing a reward signal, the optimal policy is found by the deep neural network of the SAC agent. This approach ensures that the sliding motion meets the reachability condition within a finite time. The validity of the proposed protocol is subsequently demonstrated through extensive simulation results and two numerical examples. Full article

Thermosetting resins have good temperature resistance and high strength and have been widely used as plugging agents in oil fields. However, the current resin materials have high costs, and unmodified thermosetting resins are brittle or have deteriorated properties such as flame retardancy after curing to form a crosslinked network structure. In this study, the resin was modified via physical blending. The curing strength and temperature resistance were used as the main indicators. The resin matrix, curing agent, rheology modifier, and filling materials were modified and formulated optimally to form a high-strength resin gel plugging system. The resin gel system exhibited good fluidity and pumpability. When the shear rate was 200 s⁻¹ at 25 °C, the initial viscosity was 300–400 mPa·s. The viscosity gradually decreased with increasing shear rate, and the apparent viscosity had good long-term stability at room temperature. A contamination test of different types of drilling fluids on the resin gel system showed that this system had good anti-contamination capability and could maintain a high curing strength even after being contaminated. At the same time, the system exhibited good plugging capability. A wedge-shaped fracture with an inlet size of 7 mm and an outlet size of 5 mm was plugged at 12.84 MPa for 10 min without leakage. A sand-filling pipe (with a diameter of 3.8 cm and pipe length of 30 cm) connected to the pipeline with a 6 mm outlet was subjected to a constant pressure of 11.29 MPa and plugged for 8 min before breaking through. Therefore, it exhibited good capability for plugging fissures and cavities. The resin gel leakage-plugging system has significant potential to realize effective plugging of the deep large-fracture leakage layer. Full article

The prevailing approach to the wind resistance design of transmission towers is rooted in the quasi-static method. However, this methodology faces criticism for neglecting tower-line coupling dynamics. Despite efforts to boost structural wind resilience, the research on tower failure mechanisms, especially under extreme winds considering tower-line coupling, is limited. To address this gap, the wind-induced dynamic failure modes of the transmission tower-line system are investigated in this paper. The consistent discrete random flow generation method is employed to simulate the fluctuating wind field for transmission lines. Incorporating the compressive buckling mode of angle steel, the plastic hinge model of the frame element is employed to simulate mechanical nonlinearity. A typical transmission tower-line system is concerned, with a finite element model established for a three-tower, four-line coupled configuration. The findings reveal that the wind-induced collapse of the transmission tower is directly triggered by the buckling failure of the compressed main members, with the vulnerable section located beneath the lower cross-arm. The transmission tower experiences bidirectional bending and compression instability under an unfavorable wind direction. In contrast, the traditional pushover collapse modes of the transmission tower cannot fully capture the characteristics of the collapse failure, mainly due to the ignorance of the transverse wind force action induced by the coupling effect. This research underscores the importance of incorporating lateral dynamic considerations into transmission tower designs and advocates for optimizing strategies to mitigate wind-induced collapse modes. Full article

The pursuit of climate neutrality requires global systemic actions involving the use of solutions aimed at reducing emissions. Changes must be introduced in all sectors affecting climate change, namely power engineering and district heating, construction, transport, and industry, as well as agriculture and forestry. Analyzing the structure of final energy consumption in the EU by sector, it can be stated that households account for 27% of the total energy consumption. Comprehensive actions are needed to increase the energy efficiency of buildings. The aim of this paper was to indicate aspects of improving energy efficiency in buildings and their equipment, taking into account the striving for climate neutrality. Analyzed possibilities and conditions of using various solutions of energy-efficient systems aimed at increasing energy resilience and security and preventing environmental degradation. Particular attention was paid to construction and material solutions, as well as installation solutions, which increased the accumulation and energy efficiency of the building. These activities are closely related to the conditions and dynamics of the heat exchange process in the applied solutions and are also related to the factors influencing thermal comfort and energy consumption in buildings. Due to the growing popularity of modern information technologies and artificial intelligence in energy management in recent years, this article reviews the latest research in this area. One of the directions of future research indicated by scientists is autonomous building control in real time, adapting to the momentary needs of users. The analysis of the possibilities of using modern energy efficiency solutions in buildings conducted in this work may be useful for optimizing heat and energy management models and models of society’s consumption as an element of energy transformation towards climate neutrality and counteracting the deepening of energy poverty. Full article

The moment of inertia of the primary flywheel and the secondary flywheel in a dual mass flywheel (DMF) directly affects the vibration damping performance in an automotive driveline. To enable better minimization of vibration and noise by changing the moment of inertia of the DMF to adjust the frequency characteristics of the automotive driveline, a new variable inertia DMF structure is proposed by introducing electromagnetic devices. The finite element simulation model of the electromagnetic field of an electromagnetic device is established, the electromagnetic field characteristics in the structure are analyzed, and the variation in the electromagnetic force under different air gaps and current conditions is obtained. The electromagnetic force test system of the electromagnetic device is constructed, and the validity of the finite element simulation analysis of the electromagnetic field of the electromagnetic device is verified. A mechanical model of the electromagnetic device is established to analyze the characteristics of the displacement of the moving mass in the structure as well as the variation in the moment of inertia of the DMF at different rotational speeds and currents. The maximum adjustable proportion of its moment of inertia can reach 15.07%. A torsional model of the automotive driveline is established to analyze the effect of variable inertia DMF on the resonance frequency of the system under different currents. The results show that the electromagnetic device introduced in the DMF can realize the active adjustment of the moment of inertia and enable the resonance frequency to decrease with increasing rotational speed, which expands the idea of optimizing the vibration damping performance of the DMF and provides a reference for better control of the torsional vibration of the automobile or other mechanical transmission systems. Full article

Peeling wheat yields higher-quality flour. During processing in a flaking machine, wheat kernels undergo continuous compression within the machine’s chamber. As this compression persists, damage to the kernels intensifies and accumulates, eventually leading to kernel breakage. To study the damage characteristics of wheat kernels during peeling, this study established a continuous damage model based on Hertzian contact theory and continuous damage theory. The model’s accuracy was validated through experiments, culminating in the calculation of critical parameters for wheat peeling. This study focused on different wheat varieties (Ningmai 22 and Jichun 1) and kernel sizes (the thicknesses of the small, medium, and large kernels were standardized as follows: Ningmai 22—2.67 ± 0.07 mm, 2.81 ± 0.07 mm, and 2.95 ± 0.07 mm; Jichun 1—2.98 ± 0.11 mm, 3.20 ± 0.11 mm, and 3.42 ± 0.11 mm). Continuous compression tests were conducted using a mass spectrometer, and critical damage parameters were analyzed and calculated by integrating the theoretical model with experimental data. The test results showed that the average maximum crushing force (F_c) for small, medium, and large-sized kernels of Ningmai 22 was 96.71 ± 2.27 N, 110.17 ± 2.68 N, and 128.41 ± 2.85 N, respectively. The average maximum crushing deformation (α_c) was 0.65 ± 0.08 mm, 0.68 ± 0.13 mm, and 0.77 ± 0.17 mm, respectively. The average elastic–plastic critical pressure (F_s) was 50.21 N, 60.13 N, and 59.08 N, respectively, and the average critical values of elastic–plastic deformation (α_s) were 0.37 mm, 0.38 mm, and 0.39 mm, respectively. For Jichun 1, the average maximum crushing force (F_c) for small-, medium-, and large-sized kernels was 113.34 ± 3.15 N, 125.28 ± 3.64 N, and 136.15 ± 3.29 N, respectively. The average maximum crushing deformation (α_c) was 0.75 ± 0.11 mm, 0.83 ± 0.15 mm, and 0.88 ± 0.18 mm, respectively. The average elastic–plastic critical pressure (F_s) was 58.11 N, 64.17 N, and 85.05 N, respectively, and the average critical values of elastic–plastic deformation (α_s) were 0.45 mm, 0.47 mm, and 0.52 mm, respectively. The test results indicated that during mechanical compression, if the deformation is less than α_s, the continued application of the compression load will not result in kernel crushing. However, if the deformation exceeds α_s, continued compression will lead to kernel crushing, with the required number of compressions decreasing as the deformation increases. If the deformation surpasses α_c, a single compression load is sufficient to cause kernel crushing. Since smaller wheat kernels are more susceptible to breakage during processing, the peeling pressure (F) within the chamber should be controlled to remain below the average elastic–plastic critical pressure (F_s) of small-sized wheat kernels. Additionally, the kernel deformation (α) induced by the flow rate and loading in the chamber should be kept below the average elastic–plastic critical deformation (α_s) of small-sized wheat kernels. This paper provides a theoretical foundation for the structural design and optimization of processing parameters for wheat peeling machines. Full article

The Industrial Internet of Things (IIoT) enhances and optimizes operations and product quality by reducing expenses and preserving critical factory components. The IIoT can also be integrated into the processes of small and medium-sized enterprises (SMEs). However, several factors and risks have discouraged SMEs from adopting the IIoT. This study aims to identify the factors influencing IIoT adoption and address the challenges by conducting semi-structured interviews with experienced stakeholders in SME factories. Group quotations and thematic analysis indicate essential themes from these interviews, suggesting two primary categories, human- and machine-related factors, that affect implementation. The main human-related factor is the decision making of high-level management and owners to implement the IIoT in their plants, which requires skilled individuals to achieve IIoT solutions. Machine-related factors present several challenges, including device compatibility-, device management-, and data storage-associated issues. Comprehending and addressing these factors when deploying the IIoT can ensure successful implementation in SMEs, maximizing the potential benefits of this technology. Full article

In the knowledge era, intellectual capital has been considered a key factor in creating value within organisations. This study examines the relationships and interactions between the components of intellectual capital and the profitability of Panamanian banking and financial institutions listed on the Latin American Stock Exchange (LATINEX) from 2014 to 2020. A theoretical framework based on agency theories, signalling theory, and stakeholder theory was employed to support the results. The Valued-Added Intellectual Coefficient (VAIC)™ model, which evaluates the intellectual capital of organisations based on information from financial statements, was also utilised. In this study, stepwise regression was applied to select the optimal number of predictors to be included in each multiple regression model to examine the relationship between the return on equity (ROE) and the components of the VAIC™ in addition to control variables such as size and indebtedness. The findings confirm this study’s hypothesis, demonstrating that the structural capital efficiency (SCE) and company size (SIZE) variables explain 57% of the variance in the ROE for the analysed institutions. The results suggest that the intellectual capital (IC) of financial sector institutions listed on LATINEX is significantly influenced by the SCE coefficient, which shows a negative relationship, suggesting that investment in structural capital does not enhance profitability. On the other hand, larger institutions exhibited higher profitability during the study period. This study was limited to the analysis of two sectors: banking and finance in companies listed on LATINEX. However, its rigorous theoretical and empirical foundation opens the way for future research in which other sectors can be considered, and cross-country comparisons can be made, strengthening the research in this field for Latin America. At the same time, this study offers market regulators a scientific methodology to oversee the activities of issuing companies. Full article

This study aimed to optimize modified starch from Mangifera indica (mango) fruit using acid hydrolysis and pre-gelatinization via computer-assisted techniques as a substituent for pharmaceutical tableting excipients. The hydrolysis and microwave-assisted pre-gelatinization time and temperature were optimized using a three-level factorial design. The modified starches were characterized for flowability, compressibility, and swelling properties. It was found that all parameters fit a quadratic model, which can be used to predict the properties of the modified starch. The optimized hydrolysis reaction was 3.8 h at 56.4 °C, while the pre-gelatinization reaction was 3 min at 150 °C. Structural changes were found, ascertaining that starch modification was successful. The optimized hydrolyzed starch showed superior properties in relative to unmodified M. indica fruit starch and comparable characteristics to conventional excipients. The optimized pre-gelatinized starch presented an excellent enhancement in the flow and compression properties, with %swelling greatly augmented 3.95-fold and 1.24-fold compared to unmodified starch and SSG, respectively. Additionally, the pre-gelatinized starch presented comparable binding effect, while the hydrolyzed powder had reduced binding capacity due to shorter chains. The findings revealed that the use of software-assisted design of experiment facilitated a data-driven approach to optimize the modifications. The optimized modified mango starch demonstrated potential as a multifunctional excipient, capable of functioning as binder, disintegrant, and diluent. Full article

In response to the challenges of low fertilizer utilization rates, excessive application amounts, and difficulties in precise targeted fertilization during the middle tillage and top-dressing period for corn, a targeted deep fertilization device is designed, integrating mechanical structure design and automatic control technology. The device mainly includes a strong discharge fertilization device and a targeted fertilization control system. The fertilization device has been designed, and the main factors affecting the performance of the fertilization wheel have been identified. Based on the structure, a strong discharge fertilization plate mechanism has been added, and a mechanical model for the fertilization wheel during the refilling and discharging processes has been constructed. A targeted fertilization control system for corn has been developed that utilizes a photoelectric sensor to detect the position of the corn plants. A microcontroller combines the plant position information and the device moving speed to adjust the intermittent rotation of the stepper motor in real time, achieving targeted deep fertilization for corn. Coupled simulation analysis was conducted using discrete element software EDEM and dynamic software Adams. Through single-factor and multi-factor experiments, the main factors affecting fertilization performance were analyzed, and the optimal structural parameters for the fertilization wheel were determined. Bench validation tests were conducted, and the results demonstrated that under forward speeds of 0.4 to 1.2 m/s, the coefficient of variation of the fertilizer application rate per hole of the discharge device ranged from 2.02% to 4.46%, the error in fertilizer application rate per hole ranged from 7.12% to 12.18%, the average length of fertilizer application holes ranged from 72.5 mm to 130.2 mm, and the coefficient of variation of hole length stability ranged from 1.94% to 3.54%. These parameters were consistent with the results from the simulation tests, and the operational performance met the requirements. Finally, field tests validated the overall operational performance of the device. When the device’s speed ranged from 0.4 m/s to 1.2 m/s, the coefficient of variation of the fertilizer application rate per hole, the error in fertilizer application rate per hole, the average length of fertilizer application holes, the coefficient of variation of hole length stability, and the qualification rate of fertilization position were 3.63%, 10.46%, 108.8 mm, 2.96%, and 87.16%, respectively. The overall performance of the device is stable and meets the requirements for targeted deep fertilization in corn cultivation. Full article

Complex and nonlinear optimization challenges pose significant difficulties for traditional optimizers, which often struggle to consistently locate the global optimum within intricate problem spaces. To address these challenges, the development of hybrid methodologies is essential for solving complex, real-world, and engineering design problems. This paper introduces FVIMDE, a novel hybrid optimization algorithm that synergizes the Four Vector Intelligent Metaheuristic (FVIM) with Differential Evolution (DE). The FVIMDE algorithm is rigorously tested and evaluated across two well-known benchmark suites (i.e., CEC2017, CEC2022) and an additional set of 50 challenging benchmark functions. Comprehensive statistical analyses, including mean, standard deviation, and the Wilcoxon rank-sum test, are conducted to assess its performance. Moreover, FVIMDE is benchmarked against state-of-the-art optimizers, revealing its superior adaptability and robustness. The algorithm is also applied to solve five structural engineering challenges. The results highlight FVIMDE’s ability to outperform existing techniques across a diverse range of optimization problems, confirming its potential as a powerful tool for complex optimization tasks. Full article