Great Engineering Value Research Articles

Aliphatic-acid coating and nano chitosan nucleator synergistically regulate the performance of PMMA “bone-Locking” foam dressing used for emergency fixation of clavicle fracture

Clavicle emergency fixation can prevent fractured end from piercing heart and lung organs, which is crucial for wounded life. Clavicle with complex structure, great individual differences, and adjacent to important organs, which places high-requirements on performance of fixation materials. Developing advanced clavicle fixation material is a prominent hot-topic in the field of emergency-engineering. We prepared a Polymethyl-methacrylate (PMMA) “bone-Locking” foam dressing via novel polymer foaming process. Innovatively used aliphatic-acid and bio-polar macromolecule nanoparticles to adjust structure in non-traditional self-curing polymer melts to achieve high-performance. Stearic acid coating was prepared on the surface of foaming agent can delay nucleation period, increasing the initial Polymer-Bubble interface viscosity and effectively retard nuclei growth and escape. Nano-chitosan was compounded synchronously to induce in-situ nucleation and construct polar hydrogen bonds between chains, improve the crystallinity of PMMA matrix, reduce the relaxation ability of PMMA molecular chains and increase the interface viscosity again to inhibit nuclei growth and escape, realizing spontaneous coordination between viscosity and the bubble holes formation process. Obtained high-performance foam with uniform and regular bubble holes structure eventually. More, Dynamic Dual-Variable Field Bubble-Growth Dynamics was proposed, revealing the Bubble-Growth behavior synergistic driven by Viscosity and Temperature theoretically, providing reference for improving theory in polymer foaming field. Prepared foam dressing can be directly and softly coated on clavicle and spontaneously conform to the contour of clavicle with remarkable precision, then quickly (3.5 min) curing into a lightweight (0.57 g/cm3), high-strength (40.5 MPa), breathable (224.73 mm/s) “Armor”, showing great application value in wound emergency engineering. The developed foaming method and theory provide technical and theoretical value for polymer foaming system. The foam dressing provides a promising new scheme for fixing various wound sites and ensuring the life safety of the wounded at the emergency scene.

Temperature retrieval of near space with the combined use of O2(a1Δg) and O2(b1∑+ g) dayglow emissions under self-absorption effect correction.

Atmospheric temperature information in the near space is of great academic significance and engineering value to support the development and utilization of the near space. Based on the theory of O2 molecular dayglow spectroscopy and the mechanism of atmospheric radiative transfer, a method is proposed for the joint retrieval of temperature profiles in the near space using O2(a1Δg) and O2(b1∑+ g) bands dayglow spectroscopy signal with the self-absorption effect. First, the temperature dependence of O2(a1Δg) and O2(b1∑+ g) bands dayglow is investigated, and the influence of the self-absorption effect on the radiative transfer characteristics is analyzed in the limb-view mode. Then, with the use of the onion peeling algorithm, the dayglow emission spectra signals of the O2(a1Δg) and O2(b1∑+ g) bands measured by the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) in the limb-viewing mode were processed, and combined with optimization algorithms, the temperature profiles from 35 km to 120 km is successfully retrieved. Finally, the accuracy and reliability of the self-absorption effect correction as well as the joint temperature retrieval were verified by comparing with temperature product data from remote sensing satellites such as Sounding of the Atmosphere using Broadband Emission Radiometry (SABER), Atmospheric Chemistry Experiment Fourier-Transform Spectrometer (ACE-FTS), and Michelson Interferometer for Passive Atmospheric Sounding (MIPAS). The error analysis shows that the temperature retrieval error after correction for the self-absorption effect is about 3 K minimum and 20 K maximum.

The laminar burning velocity of propyl acetate at high pressures and temperatures

Since propyl acetate has the potential to be used as a biofuel in heat engines, it is necessary to ascertain and comprehend its combustion properties. Using equivalence ratios of 0.7–1.4, the laminar burning velocity of propyl acetate was studied in the constant volume combustion vessel at the initial pressures of 1, 2, and 4 bar and initial temperatures of 390 K, 420 K, and 450 K. The constant volume method was used to determine the burning velocity via extrapolations at the initial condition. In addition, a ten-fitted empirical correlation was formulated to calculate the burning velocity for pressures and temperatures as high as 8 bar and 534 K, respectively. The extrapolated burning velocity showed good agreement with the numerical simulation burning velocity, and the correlated burning velocity agreed well with the extrapolated burning velocity. The laminar burning flux was also investigated and was ascertained that laminar burning flux increases as the initial pressure and temperature increase. The fuel mixture density significantly influences the burning flux as the initial pressure rises, whereas the laminar burning velocity has a notable impact on the burning flux as the initial temperature rises. In summary, this study advances our knowledge of propyl acetate combustion, particularly concerning its flame propagation at higher pressures and temperatures and its potential application in combustion engines, and the data are of great engineering value for developing and understanding the combustion science of propyl acetate.

A fuzzy coefficient deep flux weakening algorithm for IPMSM without out-of-control

A fuzzy coefficient q-axis current increment flux weakening (FCCIFW) control method is proposed in interior permanent magnet synchronous motor (IPMSM) drives. The proposed FCCIFW not only simplifies the calculation of flux weakening coefficient according to the derived formula, but also avoids the saturation of current regulator. In FCCIFW, the theoretical calculation formula of conversion coefficient is derived firstly, and then the fuzzy rule base is established according to the formula. FCCIFW not only refrains the use of complex flux weakening calculation formula or fixed control parameters, but also refrains the problem of out-of-control in the process of deep flux weakening control, so as to improve the overall performance in the process of flux weakening. The results show that the proposed method has an effective and correct calculation process and results, Compared with different control methods in the operation process, it shows that the proposed method has more stable control effect, which has great application value in engineering.

Study on a model analysis method of water flow characteristics in channel entrance area

With the development of inland waterway transport in our country, the demand for inland waterway navigation is increasing day by day, and the navigation safety requirements of ships are also increasing day by day. The flow condition is very important for the safe running of the ship, it not only determines the safety of the ship entering and leaving the lock, but also determines the key factor of the navigation ability of the hub. Based on the mathematical model, this paper studies the navigable flow conditions in the entrance area of the curved branching river through the modeling technology of the curved branching river, explores the peer flow characteristics of the curved branching river, and puts forward an effective measure to improve the navigable flow conditions in the entrance area of the curved river, which is of great practical significance and engineering value.

Experimental study on the influence of radial internal clearances of the rolling bearings on dynamics of a flexible rotor system

To investigate the impact of radial internal clearance of rolling bearings on the dynamic response of a flexible rotor system in a turbo-shaft engine, a dynamic similarity model of the power turbine rotor was established. Experimental research was then conducted. Four rolling bearings supporting the rotor were examined, with dynamic response tests carried out under varying radial internal clearances. The influence of the radial internal clearance on the dynamic characteristics of the rotor system was studied using the controlled variable method. The amplitude, orbit, and asynchronous vibration were analyzed through time-domain signal comparison, waterfall diagrams, and spectral analysis. The experimental results demonstrate that: (1) Adjusting the radial internal clearance of the bearings can significantly reduce the dynamic response of the flexible rotor system, with a maximum observed displacement response reduction of 88%. (2) The efficiency of vibration reduction is closely related to the axial location of the bearing. (3) Optimal radial internal clearance is not necessarily achieved at the maximum or minimum values. (4) The "locked-up" frequency phenomenon, which increases the resonance opportunities of the rotor system, can be mitigated by adjusting the radial internal clearance of different bearings. This research is of great significance and engineering value for understanding, diagnosing, and preventing excessive vibration in flexible rotor systems.

Study on the Permanent Deformation and Dynamic Stress–Strain of Coarse-Grained Subgrade Filler under Cyclic Loading

Using coal gangue as a subgrade filler will produce good benefits, and its application prospects are very broad. It is of great engineering and scientific value to study the improvement method and dynamic characteristics of coal gangue subgrade filler under traffic load. Combining the properties of coal gangue material, fly ash and lime and soil were added to improve the bearing behavior of coal gangue subgrade filler. Then, a compaction test was carried out using the principle of orthogonal experimental design. By analyzing the compaction test results, the optimal proportion of each additive was obtained. A large-scale dynamic triaxial test was carried out with the proportion of each admixture in the maximum dry density group in the compaction test. Based on the dynamic triaxial test results, the effect of confining pressure on the permanent strain was analyzed, the analysis model of permanent deformation and cycle number of traffic loading was proposed, and the correctness of the model was verified. In addition, a modified Hardin–Drnevich model was established, which can describe the dynamic stress–dynamic strain curve of coal gangue subgrade filler under traffic load, and then, the dynamic modulus and damping ratio were analyzed.

Investigation of a novel intensifying-flux hybrid excited permanent magnet machine for electric vehicles

PurposeTo address the issues of the insufficient output torque associated with the application of intensifying-flux permanent magnet (PM) machines in electric vehicles, this paper aims to propose an intensifying-flux hybrid excitation PM machine. It is possible to adjust the air gap magnetic field by adjusting the field current in the excitation winding, thereby increasing the torque output capability and speed range of the machine.Design/methodology/approachFirst, a novel intensifying-flux hybrid excited permanent magnet synchronous machine (IF-HEPMSM) is proposed on the basis of intensifying-flux permanent magnet synchronous machine (IF-PMSM) and an equivalent magnetic circuit model is established. Second, the tooth width and yoke thickness of the machine stator are optimized to ensure the overload capacity of the machine while effectively improving the wide flux regulation range. Furthermore, the electromagnetic characteristics of the IF-HEPMSM are investigated and compared with the IF-PMSM and conventional permanent magnet synchronous machine (PMSM) by using finite element simulations.FindingsThe id of IF-HEPMSM and IF-PMSM is greater than zero low-speed magnetizing current. And the flux-weakening current of the IF-HEPMSM is 18% and 3% smaller than of the conventional PMSM and IF-PMSM.Practical implicationsAiming at the problems of IF-PMSM applied to electric vehicles, this paper proposes an IF-HEPMSM. The air gap magnetic field is adjusted by controlling the current of the excitation winding to improve the reliability of the machine. Therefore, the IF-HEPMSM combines the advantages of high-power density and high efficiency of the PMSM and the controllable magnetic field of the electro-excitation machine, which is of great engineering value when applied in the field of electric vehicles.Originality/valueThe proposed IF-HEPMSM offers better flux regulation capability with electromagnetic characteristics analysis and maps of dq-axis current as compared to IF-PMSM and conventional PMSM. Moreover, the improvement of the torque can make up for the shortcomings of the insufficient torque output capability of the IF-PMSM.

Experimental Study on Key Techniques for the Construction of High Asphalt Concrete Core Rockfill Dam under Unfavorable Geological Conditions

Asphalt concrete core dams (ACCDs) have been widely constructed in Xinjiang, yet the design of materials and structures has mainly relied on empirical knowledge without substantial theoretical grounding. In this study, we carried out a large-scale relative density test of gravel material in Bamudun dam, studied the compaction characteristics of gravel material, and determined the relative density characteristic index, in order to provide a basis for the subsequent dam material rolling test and construction quality inspection. Furthermore, in order to improve the efficiency of dam construction in narrow valleys, we optimized the connection type between asphalt concrete core wall and bedrock, and proposed a rapid construction method of paving core wall after pouring mass concrete base on bedrock. Finally, we established a three-dimensional finite element model to systematically analyze the stress and deformation patterns of the dam body, core wall, and base of the ACCD at Bamudun. The results show that the maximum compressive stress suffered by the core wall during the full storage period is 1.62 MPa, there is no tensile stress, and the risk of hydraulic splitting is small. The stress and deformation levels of each part are within the safe range. This verifies the rationality of the rapid construction method. The research findings can provide a great theoretical significance and engineering value for the safe design and construction of ACCDs.

Geopolymer composites for marine application: Structural properties and durability

In marine environments, traditional ordinary Portland cement (OPC) and reinforced concrete structures are prone to corrosion, reducing their durability and service life dramatically. Geopolymers, with exceptional corrosion resistance, have great value and application potential in marine engineering. This paper presents a comprehensive overview of the research advances on geopolymer cements and concretes in marine environments in terms of mechanical properties, durability, and structural properties. The research so far has demonstrated that geopolymers exhibit superior mechanical properties and durability due to their denser interface and lower porosity compared to OPC. However, geopolymers have significant brittleness defects, and their performance in marine environments, especially in splash and tidal zones with alternating wet and dry conditions, is severely affected. This is due to the influence of chloride ions, divalent cations, pH, and sulfate in seawater, which promote or inhibit the formation and transformation of reaction products and microstructures, thereby affecting their mechanical properties and stability. Nevertheless, the use of composite technologies such as modified precursors, fibers, and nanomaterials has a positive effect on enhancing their structural properties and durability. This provides guidance and solutions for the application of high-durability, low-carbon emission, and more sustainable building materials in maritime engineering.

Semi-supervised learning approach for construction object detection by integrating super-resolution and mean teacher network

Deep learning-based object detection methods are utilized for safety management at construction sites, which require large-scale, high-quality, and well-labeled datasets for training. The existing construction datasets are relatively small due to the high expense of labor-intensive annotation, and the varying quality of the construction images also affects the detection performance of the model. To address the limitations of datasets, this study proposes a new method for construction object detection by integrating super-resolution and semi-supervised learning. The proposed method improves the quality of construction images and achieves excellent detection performance with limited labeled data. First, the Real-ESRGAN model is introduced to improve the quality of construction images and make the construction objects visible. The proposed super-resolution method can enhance the texture details of low-resolution images, hence improving the performance of object detection models. Second, the mean-teacher network is adopted to expand the training set, thus avoiding the labor-intensive annotation work. To verify the effectiveness of the proposed method, the method is applied to the state-of-the-art Yolov5 object detection model, and construction images from the Site Object Detection Dataset (SODA) with different labeled data proportions (from 10% to 50% in 10% intervals with an extreme case of 5%) are used as the training set. By comparing with the existing supervised learning method, it is shown that the proposed method can achieve better detection performance. In particular, the method is more effective in enhancing detection performance when the proportion of the labeled data is smaller, which is of great practical value in real-world engineering. The experimental results show the potential of the proposed method in improving image quality and reducing the expense of developing construction datasets.

Predicting shear stress distribution on structural surfaces under internal solitary wave loading: A deep learning perspective

The density of the ocean varies unevenly along the vertical axis. In the presence of external disturbances, internal solitary waves (ISWs) are generated. The strong shear flow field induced by ISW seriously threatens the operational safety of marine structures. Therefore, it has become a hot spot to study the force law of marine structures in ISW. The existing studies are conducted when the ISW parameters are known. However, ISW is not visible in real situations, which leads to difficulties in obtaining ISW parameters. Therefore, it is of great engineering value to accomplish real-time force prediction of marine structures without knowing the ISW parameters in advance. To fill the gap, this study proposes a novel hydrodynamic prediction model with a sensor array as the sensing system and a deep learning algorithm as the decision-making system. The model successfully achieves accurate prediction of the shear stress on the cylinder in the ISW. In addition, a technique for optimizing sensor placement is proposed. This will help identify critical regions in the graphical representations to enhance exploration of flow field information. The results demonstrate that the prediction accuracy of the optimized sensor layout scheme surpasses that of randomly deployed sensors. As a result, this study will provide an important assurance for the safe operation of marine structures.

Deformation localization and crack propagation of sandstone containing different flaw inclination angles under different loading rates

Defects with varying geometric distribution in the rock mass play a crucial role in determining the stability of engineered rock masses. Previous studies have primarily investigated the initiation, propagation, and coalescence behaviors of flaws within rock masses. Nevertheless, there has been limited analysis of flawed rock masses under different loading rates. In this study, we present the deformation localization and cracking process of three types of inclined flawed sandstone specimens through conducting uniaxial compression and acoustic emission tests at four different levels of loading rate. The results supported the following findings: 1) Sandstone specimens with different flaw inclination angles exhibit the loading rate strengthening effect, and the strengthening effect gradually decreases with the increase of loading rate. 2) As the loading rate increases, the type of crack emergence changes from wing cracks to anti-tensile cracks, and the time of flaw initiation is shortened. 3) The cumulative acoustic emission counts were higher for the low-loading rate specimens than for the high-loading rate specimens. 4) Tensile cracks typically occur as the initial cracks. Anti-tensile cracks often coexist with wing cracks in rock specimens that have undergone tensile damage. Coplanar secondary cracks are the primary indication of shear damage formation in rock specimens. 5) The increase in loading rate promotes the transition of rock specimens from the mixed tensile-shear damage mode to the shear damage mode. These research results are of great theoretical significance and engineering value for understanding the failure mechanism of rock mass containing flaws and proposing effective measures to prevent cracking and ensure the safety of brittle solid structures.

Aluminum particle agglomeration characteristics and suppression method during the combustion of aluminum‐based solid propellants: A review

AbstractAluminum is widely used in solid rocket propellants to improve the energy performance of the propellant. However, during propellant combustion, aluminum particles may agglomerate, resulting in slag deposition, incomplete combustion of metal particles, increased two‐phase flow losses, and reduced motor specific impulse. Therefore, it is of great scientific significance and engineering value to understand the agglomeration mechanism of aluminum particles and to explore the method of agglomeration suppression. Based on this, this paper firstly briefly introduced the agglomeration process of aluminum particles during propellant combustion. Subsequently, factors influencing the agglomeration of aluminium particles were analysed. The influencing factors can be roughly divided into two aspects: propellant‘s own formulation and external environment. Immediately afterwards, the existing agglomeration suppression methods were emphasized and summarized and analyzed. Presently, agglomeration suppression methods can be broadly classified into four categories, namely, conventional formulation optimization, use of aluminum nanoparticles, and modification of aluminum particles using fluorine‐containing compounds or alloy particles. Finally, several directions that need to be focused on in the future are proposed to address the problems in the study of aluminum particle agglomeration suppression methods.

Effect of Na2SiO3 and TEA Electrolyte Additives on the Corrosion Inhibition of Zinc Electrodes and Electrochemical Performance of Rechargeable Alkaline Manganese Batteries

To inhibit hydrogen evolution corrosion, passivation, and zinc dendrite growth during the charging and discharging of the zinc negative electrode of rechargeable alkaline manganese battery containing ultra-fine zinc powders, the effects of the single addition amounts of inorganic corrosion inhibitor Na2SiO3 and organic corrosion inhibitor TEA and their compounding ratio on the corrosion inhibition effect and the charging and discharging performance of alkaline manganese battery were systematically investigated in this paper. SEM and XPS were used to observe the microscopic morphology of the zinc anode, and the inhibition mechanisms of the relevant inhibitors were explored. The results show that, the addition of Na2SiO3 and TEA can synergistically improve the coverage of the protective film, thereby inhibiting hydrogen evolution corrosion, passivation and dendrites of zinc electrodes. Compared to blank electrolyte, when the composite concentration of Na2SiO3 and TEA is 1 g l−1 Na2SiO3+56.25 mg l−1 TEA, the hydrogen evolution corrosion inhibition efficiency can reach 70.56%, the initial specific capacity and the specific capacity after 50 cycles can increase from 160.7 mAh g−1, 58 mAh g−1 to 198.4 mAh g−1, 74 mAh g−1, respectively. This study has great theoretical and engineering value for guiding the design of electrolytes for rechargeable alkaline manganese batteries.

The Molecular Regulatory Mechanism in Multipotency and Differentiation of Wharton's Jelly Stem Cells.

Wharton's jelly-derived mesenchymal stem cells (WJ-MSCs) are isolated from Wharton's jelly tissue of umbilical cords. They possess the ability to differentiate into lineage cells of three germ layers. WJ-MSCs have robust proliferative ability and strong immune modulation capacity. They can be easily collected and there are no ethical problems associated with their use. Therefore, WJ-MSCs have great tissue engineering value and clinical application prospects. The identity and functions of WJ-MSCs are regulated by multiple interrelated regulatory mechanisms, including transcriptional regulation and epigenetic modifications. In this article, we summarize the latest research progress on the genetic/epigenetic regulation mechanisms and essential signaling pathways that play crucial roles in pluripotency and differentiation of WJ-MSCs.

Theoretical analysis of stress intensity factors and interactions of collinear flaws with unequal lengths in brittle solids under uniaxial tensile conditions

Interactions between multiple flaws with different sizes in brittle solids are a key factor that induce failure. Previous studies have focused on the initiation, propagation and coalescence behaviors of multiple flaws in brittle solids. Nevertheless, there have been few theoretical or quantitative analyses of interactions between multiple flaws. In the present study, based on the Kachanov method, we first proposed theoretical analytical solutions of the stress intensity factors (SIFs) for two and three collinear flaws with unequal lengths under uniaxial tensile conditions. Then, a theoretical analysis of the effects of various geometric factors, such as flaw interval, flaw length and flaw number, was performed. The results supported the following findings: (1) For two collinear flaws, interactions between the primary and secondary flaws gradually weakened with increasing flaw interval, and the flaw length ratio gradually became the main factor that determined the interaction. (2) For three collinear flaws, when the interval between the primary and secondary flaws was not less than 1.5 times the length of the secondary flaw, the interaction had no effect on the propagation of the primary flaw. (3) The increase in the number of collinear flaws significantly enhanced the effect on propagation reinforcement between the flaws. Finally, numerical simulations were conducted to verify the results of the theoretical analysis, and good consistency was found. These research results are of great theoretical significance and engineering value for quantitatively understanding the failure mechanism of brittle solids containing multiple flaws and proposing effective measures to prevent cracking and ensure the safety of brittle solid structures.

A Hybrid Deep Learning Framework Based on Diffusion Model and Deep Residual Neural Network for Defect Detection in Composite Plates

The establishment of a structural health monitoring (SHM) system for the damage and defects of composite structures is of great theoretical and engineering value to ensure their production and operational safety. Advanced machine learning technologies, such as deep learning, have become one of the main driving forces for state monitoring and predictive analysis of these structures. However, it is difficult to obtain sufficient data to train the deep learning model, which may fail to build an accurate and efficient SHM model. To overcome this problem, a new method based on Lamb waves and the diffusion model (DM) is proposed to realize the identification and classification of different defects for carbon-fiber-reinforced polymer (CFRP) structures. In this study, DM is used as the generation model of data enhancement, and the optimized and improved DDPM model is constructed in this experiment. The deep residual neural network (DenseNet) is used to identify and classify the defect features from the Lamb wave signals. Experimental and test results show that the deep learning framework designed in this study based on DenseNet classification and DDPM data enhancement can accurately detect and classify damage signals of common defects in CFRP composite plates.

Study on “decoupling” of inerter

The braking device is regarded as the core of the vehicle deceleration, and it also does great help to the stability and reliability of the vehicle. The disc brake is one of the most important brake devices, and its main structure contains a brake disc and a friction block. The working principle is to provide the normal pressure to the friction block through the clamp, and through the friction between the friction block and the brake disc to achieve deceleration and parking. In this process, the vehicle may produce sharp noise, and the unreasonable design may lead to braking instability and noise. Therefore, it is of great engineering value and practical significance to study the dynamic characteristics of disc brakes, add new structures, and put forward the method of system parameter optimization. The main content of this paper is to study the modal coupling in the braking process and optimize it with the mechanical structure with an inerter.

Time-Varying Wind-Resistance Global Reliability Analysis of In-Service Transmission Tower Using High-Order Moments-Based Improved Maximum Entropy Method

The transmission tower is an important infrastructure for transmission lines. To secure the operation of the power grid, it is particularly important to evaluate the safety of the in-service transmission tower under the action of random wind loads throughout their entire life cycle. Thus, this paper firstly establishes the time-varying equivalent performance function of the in-service transmission tower under the action of random wind loads. Then, in order to address the shortcomings of the traditional maximum entropy method, the high-order moments-based improved maximum entropy method (HM-IMEM) is proposed and extended to assess the wind resistance global reliability of the in-service transmission tower. Finally, the effectiveness of the proposed method is demonstrated evaluating the wind resistance global reliability of an in-service transmission tower in an engineering setting. Analytic results indicate that: (1) The proposed method can ensure a balance between calculation accuracy and efficiency. Compared with Monte Carlo simulation (MCS) method, the relative error is only 0.11% and the computational cost is much lower than that of the MCS method. (2) The reliability of the in-service transmission tower significantly decreased over time. In order to guide maintenance and reinforcement by predicting the time-varying performance of in-service transmission towers, it is of great engineering value to evaluate the wind resistance global reliability of the in-service transmission tower.