Search Results (45)

During the homogenization process of lithium battery slurry, the slurry shearing process causes the surface of the homogenization equipment to wear and generate metal containing debris, which poses a risk of inducing battery self-discharge and even explosion. Therefore, inhibiting wear of homogenizing equipment is imperative, and systematic investigation into the wear behavior and underlying mechanisms of SUS304 stainless steel during homogenization is urgently required. In this study, lithium iron phosphate (LFP) and lithium nickel cobalt manganese oxide (NCM) cathode slurries were used as research objects. Changes in surface parameters, microstructure, and elemental composition of the wear region on SUS304 stainless steel under different working conditions were characterized. The results indicate that in the SUS304-lithium-ion battery slurry system, the potential wear mechanism of SUS304 gradually evolves with changes in load and rotational speed, following the order: adhesive wear (low speed, low load) → abrasive wear (medium speed, high load) → fatigue wear (high speed). Under high-load and high-rotational-speed conditions, oxidative corrosion wear on the ball–disc contact surface is particularly pronounced. Additionally, wear of SUS304 is more severe in the LFP slurry system compared to the NCM system. Macroscopic experiments also revealed that the speed effect is a core factor influencing the wear of SUS304, and the increase in its wear rate is more than twice that caused by the load effect. This study helps to clarify the wear behavior and wear mechanism evolution of homogenization equipment during the lithium battery homogenization process, providing data support and optimization direction for subsequent material screening and surface strengthening treatment of homogenization equipment components. Full article

Background: Flywheel resistance training has gained popularity due to its ability to induce eccentric overload and improve strength and power. This study examined the acute effects of low- (0.025 kg·m²) versus high-inertia (0.10 kg·m²) flywheel deadlifts, matched for force impulse, on the countermovement jump (CMJ) performance, reactive strength index (RSI) during drop jumps (DJs), and rating of perceived exertion (RPE). Methods: Sixteen trained participants (twelve men, and four women) performed three conditions in a randomized, counterbalanced order: low-inertia (LOW), high-inertia (HIGH), and control (CTRL). In the LOW and HIGH conditions, we used force plates to measure and equalize the force impulse in the two conditions (HIGH: 20182 ± 2275 N∙s vs. LOW: 20076 ± 2526 N∙s; p > 0.05), by calculating the number of deadlift repetitions required to achieve it (HIGH: 5 repetitions and LOW: 9.8 ± 0.4 repetitions). The RSI and CMJ performance were measured pre-exercise, immediately post-exercise, and at 3, 6, 9, and 12 min post-exercise. Results: Both the RSI and CMJ performance improved equally after LOW and HIGH flywheel deadlifts compared to baseline and CTRL (p < 0.01). Specifically, the RSI increased from baseline at 3 to 12 min in both conditions (LOW: 12.8 ± 14.9% to 15.4 ± 14.8%, HIGH: 12.1 ± 17.0% to 12.2 ± 11.7%, p < 0.01), while the CMJ increased from 3 to 9 min in LOW (4.3 ± 3.2% to 4.6 ± 4.7%, p < 0.01) and from 6 to 9 min in HIGH (3.8 ± 4.2% to 4.2 ± 4.9%, p < 0.05). No significant differences were observed between LOW and HIGH conditions (p > 0.05), suggesting similar effectiveness of both inertial loads for enhancing performance. The RPE increased similarly after both conditions from baseline to immediately post-conditioning (LOW: from 2.2 ± 1.2 to 5.8 ± 1.4, HIGH: from 1.5 ± 1.0 to 6.1 ± 1.5, p < 0.01) and decreased by the end of the session, although values remained higher than baseline (LOW: 4.1 ± 1.4, p < 0.01, HIGH: 4.5 ± 2.0, p < 0.01). Conclusions: These findings highlight the potential of flywheel deadlift exercise as an effective method to potentiate explosive performance of the lower limbs, regardless of inertia, provided that the total force impulse is equal. Full article

In order to analyze the effect of temperature changes on the shock initiation performance of HMX–based booster explosive, which consists of 95% HMX and 5% FPM₂₆₀₂ by weight, a temperature calibration test of acceptor was designed. The temperature changes in the booster at low and elevated temperatures under the constraint of steel sleeve were obtained. Based on the temperature calibration results, polymethyl methacrylate (PMMA) was selected as gap material to conduct a small scale gap test (SSGT) of HMX–based booster under different temperature conditions. The corresponding critical gap thickness was tested. Based on SSGT results at different temperatures, the shock initiation processes were simulated by adjusting parameters of ignition and growth reactive rate model. The critical gap thickness and critical initiation pressure of HMX–based booster at different temperatures were numerically predicted. By combining SSGT experimental data and simulation results, the attenuation law and fitting prediction formula of the critical initiation pressure of HMX–based booster were proposed. The mechanism of temperature effect on the shock sensitivity of HMX–based booster explosive was analyzed. The research results indicate that the critical gap thickness of HMX–based booster gradually increases with the rise in temperature, and the critical initiation pressure gradually decreases during the shock initiation process under the heating temperature conditions. In addition, the simulation results show that the heated HMX–based booster under steel constraints becomes more sensitive at high temperatures (>120 °C), while the cooled booster is more insensitive, but its critical initial pressure does not change significantly between 88 °C and 120 °C. The experimental and numerical prediction results are important for the shock initiation safety and design of an insensitive booster explosive. Full article

Bitter melon vine (an agricultural waste product with high fiber content) is difficult to treat and has caused problems in the environment. This research aims to produce biochar through low-temperature pyrolysis assisted by non-polluting steam explosion. The physical and chemical properties of the biochar were characterized using scanning electron microscopy (SEM) images, specific surface area measurements (BET), X-ray diffraction patters (XRD), elemental analysis (EA), and Fourier transform infrared spectroscopy (FTIR). Next, the adsorption mechanism of methylene blue (MB) on the steam-exploded bitter melon vine biochar pyrolyzed at 200 °C (qBC₂₀₀) and the effects of adsorption time, pH, initial concentration, adsorption temperature, and adsorbent dosage on the adsorption effect were investigated. Steam explosion destroyed the dense structure of the plant, increased the number of oxygen-containing surface functional groups, and improved the adsorption performance of the material. Therefore, qBC₂₀₀ more effectively adsorbed MB than untreated biochar, reaching a saturated adsorption capacity of 267.72 mg/g. The MB adsorption kinetics and isothermal adsorption process of qBC₂₀₀ align with the pseudo-second-order kinetic model and Langmuir isothermal equation (monolayer adsorption), respectively. The thermodynamic results show that MB adsorbs via a spontaneous, entropy-increasing exothermic reaction. The adsorption mechanism involves electrostatic attraction, hydrogen bonding, and π–π interactions. The prepared biomass with high fiber content is a promising new material for wastewater treatment. Full article

The capacity to update firmware is a vital component in the lifecycle of Internet of Things (IoT) devices, even those with restricted hardware resources. This paper explores the best way to wirelessly (Over The Air, OTA) update low-end IoT nodes with difficult access, combining the use of unicast and broadcast communications. The devices under consideration correspond to a recent industrial IoT project that focuses on the installation of intelligent lighting systems within ATEX (potentially explosive atmospheres) zones, connected via LoRa to a gateway. As energy consumption is not limited in this use case, the main figure of merit is the total time required for updating a project. Therefore, the objective is to deliver all the fragments of the firmware to each and all the nodes in a safe way, in the least amount of time. Three different methods, combining unicast and broadcast transmissions in different ways, are explored analytically, with the aim of obtaining the expected update time. The methods are also tested via extensive simulations, modifying different parameters such as the size of the scenario, the number of bytes of each firmware chunk, the number of nodes, and the number of initial broadcast rounds. The simulations show that the update time of a project can be significant, considering the limitations posed by regulations, in terms of the percentage of airtime consumption. However, significant time reductions can be achieved by using the proper method: in some cases, when the number of nodes is high, the update time can be reduced by two orders of magnitude if the correct method is chosen. Moreover, one of the proposed methods is implemented using actual hardware. This real implementation is used to perform firmware update experiments in a lab environment. Overall, the article illustrates the advantage of broadcast approaches in this kind of technology, in which the transmission rate is constant despite the distance between the gateway and the node. However, the advantage of these broadcast methods with respect to the unicast one could be mitigated if the nodes do not run exactly the same firmware version, since the control of the broadcast update would be more difficult and the total update time would increase. Full article

With the rapid development of the web service market, the number of web services shows explosive growth. QoS is an important factor in the recommendation scene; how to accurately recommend a high-quality service for users among the massive number of web services has become a tough problem. Previous methods usually acquired feature interaction information by network structures like DNN to improve the QoS prediction accuracy, but this generates unnecessary computations. Aiming at addressing the above problem, inspired by the multigrained scanning mechanism in a deep forest, we propose a location-aware deep interaction forest approach for web service QoS prediction (LDIF). This approach offers the following innovations: The model fuses the location similarity of users and services as a latent feature representation of them. In addition, we designed a scanning interaction structure (SIS), which obtains multiple local feature combinations from the interaction between user and service features, uses interactive computing to extract feature interaction information, and concatenates the feature interaction information with original features, which aims to enhance the dimension of the features. Equipped with these, we compose a layer-by-layer cascade by using SIS to fuse low- and high-order feature interaction information, and the early-stop mechanism controls the cascade depth to avoid unnecessary computation. The experiments demonstrate that our model outperforms eight other state-of-the-art methods on MAE and RMSE common metrics on real public datasets. Full article

To address the problems of a low tracking accuracy and slow error convergence in high-order single-input, single-output electro-optical tracking systems, a backstepping control method based on a Softsign linear–nonlinear tracking differentiator is proposed. First, a linear–nonlinear tracking differentiator is designed in conjunction with the Softsign excitation function, using its output as an approximate replacement for the conventional differentiation process. Then, this is combined with backstepping control to eliminate the “explosion of complexity” problem in conventional backstepping procedures due to repeated derivation of virtual control quantities. This reduces the workload of parameter tuning, takes into account the rapidity and stability of signal convergence, and improves the trajectory tracking performance. This method can ensure the boundedness of the system signal. The effectiveness and superiority of this control method are verified through simulations and experiments. Full article

Intense burning phenomena (fire disasters) need to be prevented in the combustible gas utilization and transportation processes to ensure industrial safety. Nonmetallic spherical spacers (NSSs) have been investigated and applied in lots of explosive atmospheres to prevent explosion execution in a confined space. In this work, a novel fuzzy-based analytic hierarchy process (FAHP) is developed to take into account the uncertainty in decision-making and effectively solve the problem of factor weight allocation in multi-objective optimization. Optimal Latin Hypercube Design (Opt LHD), Chebyshev Orthogonal Polynomials (COP), and Adaptive Simulated Annealing (ASA) were combined. A multi-objective optimization method is proposed for the structural parameter optimization problem on NSSs in order to achieve conflicting multiple-objective optimization of low displacement rate and minimal deformation. That is to say, the small volume (low displacement rate) and high explosion-suppression performance (minimal deformation) of NSSs were optimized simultaneously. The results show that, compared with the original NSS model’s deformation (2.85 mm) and displacement rate (3.63%), the optimized NSSs with weight allocation had optimized the deformation by 12.98% and displacement rate by 6.1%. Compared with the optimized design model of NSSs without weight allocation with a deformation of 2.75 mm and a displacement rate of 3.48%, the deformation has been optimized by 9.82%, and the displacement rate has been optimized by 2.0%. It was verified that the proposed method is effective. At the same time, it was verified that the suppression effect of NSSs can be enhanced by changing the shape of the NSS spacer reasonably by experimental verification. Full article

The solution of compressible flow equations is of interest with many aerospace engineering applications. Past literature has focused primarily on the solution of Computational Fluid Dynamics (CFD) problems with low-order finite element and finite volume methods. High-order methods are more the norm nowadays, in both a finite element and a finite volume setting. In this paper, inviscid compressible flow of an ideal gas is solved with high-order spectral/$hp$ stabilized formulations using uniform high-order spectral element methods. The Euler equations are solved with high-order spectral element methods. Traditional definitions of stabilization parameters used in conjunction with traditional low-order bilinear Lagrange-based polynomials provide diffused results when applied to the high-order context. Thus, a revision of the definitions of the stabilization parameters was needed in a high-order spectral/$hp$ framework. We introduce revised stabilization parameters, ${\tau }_{supg}$, with low-order finite element solutions. We also reexamine two standard definitions of the shock-capturing parameter, $\delta$: the first is described with entropy variables, and the other is the $YZ\beta$ parameter. We focus on applications with the above introduced stabilization parameters and analyze an array of problems in the high-speed flow regime. We demonstrate spectral convergence for the Kovasznay flow problem in both $L^1$ and $L^2$ norms. We numerically validate the revised definitions of the stabilization parameter with Sod’s shock and the oblique shock problems and compare the solutions with the exact solutions available in the literature. The high-order formulation is further extended to solve shock reflection and two-dimensional explosion problems. Following, we solve flow past a two-dimensional step at a Mach number of $3.0$ and numerically validate the shock standoff distance with results obtained from NASA Overflow $2.2$ code. Compressible flow computations with high-order spectral methods are found to perform satisfactorily for this supersonic inflow problem configuration. We extend the formulation to solve the implosion problem. Furthermore, we test the stabilization parameters on a complex flow configuration of AS-202 capsule analyzing the flight envelope. The proposed stabilization parameters have shown robustness, providing excellent results for both simple and complex geometries. Full article

Electrostatic accumulation is associated with almost all powder-conveying processes which could bring about electrostatic discharges. In most cases of industrial accidents, electrostatic discharge is proven to be the primary source of ignition and explosion. Herein, a surface modification process of polyaniline (PANI) is proposed to construct highly exothermic special powders, namely, HMX@PANI energetic composites, with low charge accumulation for improving powder electrostatic safety. Pure HMX are encapsulated within the PANI-conductive polymer layer through simple hydrogen bonding. Simulation results demonstrate that the forming process of HMX/aniline structure is a spontaneously thermodynamical process. The resultant inclusion complex exhibits excellent thermal stability, remarkable compatibility and intensive heat release. Importantly, PANI possesses superior electrostatic mobility characteristics because of the π-conjugated ligand, which can significantly reduce the accumulated charges on the surface of energetic powders. Moreover, the modified explosive has a narrower energy gap, which will improve the electron transition by reducing the energy barrier. The electrostatic accumulation test demonstrates that HMX@PANI composites possess a trace electrostatic accumulation of 34 nC/kg, which is two orders of magnitude lower than that of pure HMX (−6600 nC/kg) and might indicate a higher electrostatic safety. In conclusion, this surface modification process shows great promise for potential applications and could be extensively used in the establishment of high electrostatic safety for special powders. Full article

Water is a weakly compressible fluid medium. Due to its low compressibility, it is usually assumed that water is an incompressible fluid. However, if there are high-pressure pulse waves in water, the compressibility of the water medium needs to be considered. Typical engineering applications include water hammer protection and pulse fracturing, both of which involve the problem of discontinuous pulse waves. Traditional calculation and simulation often use first-order or second-order precision finite difference methods, such as the MacCormark method. However, these methods have serious numerical dissipation or numerical dispersion, which hinders the accurate evaluation of the pulse peak pressure. In view of this, starting from the weakly compressible Navier–Stokes (N-S) equation, this paper establishes the control equations in the form of flux, derives the expressions of eigenvalues, eigenvectors, and flux vectors, and gives a new flux vector splitting (FVS) formula by considering the water equation of state. On this basis, the above flux vector formula is solved using the fifth-order weighted essentially non-oscillatory (WENO) method. Finally, the proposed FVS formula is verified by combining the typical engineering examples of water hammer and pulse fracturing. Compared with the traditional methods, it is proved that the FVS formula proposed in this paper is reliable and robust. As far as we know, the original work in this paper extends the flux vector splitting method commonly used in aerodynamics to hydrodynamics, and the developed model equation and method are expected to play a positive role in the simulation field of water hammer protection, pulse fracturing, and underwater explosion. Full article

In order to improve the utilization rate of coal generation and reduce carbon emissions from coal-fired boilers, the operation parameters of power plant boilers should be matched with the actual burning coal. Due to the complex and high-risk blending process of multiple coal types, the actual application of coal types inconsistent with expectations may lead to low combustion efficiency of boilers, cause disturbances to the normal operation of thermal power units, increased energy waste and carbon emissions, and even lead to serious explosion accidents. Therefore, the online identification of coal types for thermal power units is of great significance. To obtain the precise type of coal online, in the present work, a data-driven coal identification method is proposed based on convolutional networks that do not necessitate additional hardware detection equipment and are easy to implement. Experimental results indicate that the proposed method exhibits superior performance in comparison to traditional methods, thus ultimately improving the performance of thermal power plant. Full article

Recently, resilience studies have been emphasized in the port field, recognizing that many high-risk and unsafe factors in ports might bring serious disasters and economic losses. One major cause of significant losses is accidents from fires, explosions, and the resultant adverse impacts from dangerous goods. Whilst the occurrence of major events related to dangerous goods is relatively low in occurrence, their impact on the environment and economic and social loss, and on human casualties, can be extremely high when they do occur. In order to prevent potential risks and reduce losses, based on a literature review, a safety assessment model was developed with four criteria and 15 sub-criteria of dangerous goods in ports using a fuzzy analytic hierarchy process (FAHP) approach. This model formed the basis for a subsequent stage involving questionnaires with 25 experts. The results of these questionnaires found that the key criteria are detection capability, followed by recovery capability, rescue capability, and resistance capability. Sensitivity analysis is used to identify the criteria’s weight value changes under various scenarios. These findings concern dangerous goods operations management in ports. Critically, these findings emphasize the key role played in the initial stages of determining precisely and exactly what specific goods are in fact dangerous goods, thereby avoiding a domino effect of adverse consequences later. Suggestions are made for policymakers regarding funding and supporting processes for handling dangerous goods, as well as for future research. Full article

In order to realize the full-time denitration of a boiler, high-temperature flue gas needs to be introduced when SCR is conducted during the boiler start-up stage, and there is a fire risk due to the presence of combustible fly ash at this time. Therefore, research on reburning and the explosion risk of tail flue gas encountering high-temperature flue gas during start-up and shutdown was carried out. A small testbed was designed to record the temperature of the flue gas and the composition of the flue gas before and after the test, and the ignition characteristics of combustible fly ash in the flue gas were systematically studied. The ignition temperature of combustible fly ash in various conditions was obtained, the ignition characteristics of combustible fly ash in the airflow were analyzed, and the effects of combustible gas, high-temperature flue gas temperature, and fly ash composition on ignition were also analyzed. The results show that the flue gas temperature in the test section was about 400 °C, the low-temperature flue gas temperature increased from 650 °C to 813 °C, and the combustible fly ash did not ignite regardless of whether alcohol was added as a combustible gas component. When the volatile content of combustible fly ash was 10~26.7%, the ignition temperature was 660~760 °C. The lower the volatile content of combustible fly ash was, the higher the ignition point was. When alcohol was added as a combustible component of gas, the ignition point decreased by about 50 °C. The critical ignition temperature of combustible fly ash in this test was lower than that under actual power plant operation conditions. Full article

In order to accurately identify the state of health (SOH) and remaining useful life (RUL) of lithium-ion batteries, this paper proposes an SOH estimation algorithm for lithium-ion batteries based on stream learning and LightGBM. To address the problem of inconsistent data length, which makes it difficult to establish the state mapping relationship between degraded data and health state, the health factors in this paper are extracted from capacity degradation features, entropy features, and correlation coefficient features. Then, the landmark isometric mapping (L-ISOMAP) manifold learning algorithm is used to dimensionally reduce the input feature set and map the high-dimensional features to the low-dimensional space to solve the dimensional explosion problem. Finally, a LightGBM prediction model is developed to perform SOH prediction on different datasets, and the superiority of the multidimensional model is evaluated. The experimental results show that the goodness-of-fit is 0.98 and above, and the MSE values are below 4 × 10⁻⁴. Comparing several prediction models, the LightGBM model has the best performance and better results in several indexes, such as MSE and RMSE. Under different working conditions, the proposed model in this paper has a goodness-of-fit of more than 0.98 in dataset B, which proves that the proposed model has a strong generalization ability. Full article