Internal Structural Parameters Research Articles

Performance and regression analysis of air-cooled thermoelectric cooling system using response surface methodology and numerical simulation

In this study, the response surface methodology (RSM) combined with numerical simulation (NS) techniques is used to perform regression model of an air-cooled thermoelectric cooler (TEC) system. To obtain the interaction models between the thermal resistance (Rh) of the external hot-side heat sink and the internal structure parameters of the TEC (leg height, h; leg width, w; numbers of P/N leg pairs, N), regarding the key performance of the TEC. According to the NS and RMS results Imax, Qcmax, and Qh decline with the rise of Rh under different N, h, and w. The decline rate is rise with the elevation of N, the increase of the w, and the decrease of the h. COP and Tcmin decrease with an increase in h, while increase with an increase in w, N, and Rh. The key factors Rh, w, h and N in the air-cooled TEC system are studied using RSM. The second-order response models for the response variables (COP, Tcmin, Qcmax,Imax and dTmax) with respect to the influencing factors (Rh, w, h and N) are established using the Box-Behnkn Design (BBD) method in RSM.

Fabrication of controlled porous and ultrafast dissolution porous microneedles by organic-solvent-free ice templating method

Porous Microneedles (PMNs) have been widely used in drug delivery and medical diagnosis owing to their abundant interconnected pores. However, the mechanical strength, the use of organic solvent, and drug loading capacity have long been challenging. Herein, a novel strategy of PMNs fabrication based on the Ice Templating Method is proposed that is suitable for insoluble, soluble, and nanosystem drug loading. The preparation process simplifies the traditional microneedle preparation process with a shorter preparation time. It endows the highly tunable porous morphology, enhanced mechanical strength, and rapid dissolution performance. Micro-CT three-dimensional reconstruction was used to better quantify the internal structures of PMNs, and we further established the equivalent pore network model to statistically analyze the internal pore structure parameters of PMNs. In particular, the mechanical strength is mainly negatively correlated with the surface porosity, while the dissolution velocity is mainly positively correlated with the permeability coefficient by the correlation heatmap. The poorly water-soluble Asiatic acid was encapsulated in PMNs in nanostructured lipid carriers, showing prominent hypertrophic scar healing trends. This work offers a quick and easy way of preparation that may be used to expand PMNs function and be introduced in industrial manufacturing development.

FORMATION OF TWO-PHASE ZONES DURING INTERNAL OXIDATION OF BINARY ALLOYS

In the paper the formation patterns of two-phase regions during the internal oxidation process in low-alloyed binary alloys is studied. The goal of the research is the creation of a mathematical model for the internal oxidation process, which is to describe the kinetics of formation and evolution of internal oxidation zones, the study of the patterns governing the two-phase zone formation during internal oxidation, the study of the space-time dynamics of the structural parameters of the two-phase area, namely the number of the oxide particles, their average radius and the phase volume, at different stages of the internal oxidation zone evolution. The two-phase process of diffusion saturation with light components applied to binary alloys is analyzed theoretically. The conditions for formation of disperse oxide particles are formulated. A mathematical model for the formation of two-phase areas as well as the numerical solution for the system of equations describing the kinet- ics of formation and evolution of the two-phase area for different values of the process parameters is proposed. The modeling and experiments demonstrate that the distribution of structural parameters of the two-phase area has complex, non-monotonous nature. The influence of the main parameters of the process on the kinetics of the formation of the two-phase area in a lightly-alloyed binary nickel-based alloy plate is also determined. All stages of the plate’s oxidation process are studied – from the inception of the particles to the coalescence of second-stage particles. The results of the work could be used for developing new technologies in thermal and chemical-thermal treatments for disperse strengthening of materials using internal oxidation, as a physical basis for seeking ways of providing certain distributions of the internal oxidation zone structural parameters, which are required to give the al- loy a necessary set of physical and mechanical properties. The comparison of the modeling and experimental results shows a good correlation, which allows them to be recommended for developing new technologies in disperse strengthening, new heat-resistant steels, disperse-strengthened magnetic materials and electrotechnical alloys.

Artificial neural network for deciphering the structural transformation of condensed ZnO by extended x-ray absorption fine structure spectroscopy

Pressure-induced structural phase transitions play a pivotal role in unlocking novel material functionalities and facilitating innovations in materials science. Nonetheless, unveiling the mechanisms of densification, which relies heavily on precise and comprehensive structural analysis, remains a challenge. Herein, we investigated the archetypal B4 → B1 phase transition pathway in ZnO by combining x-ray absorption fine structure (XAFS) spectroscopy with machine learning. Specifically, we developed an artificial neural network (NN) to decipher the extended-XAFS spectra by reconstructing the partial radial distribution functions of Zn–O/Zn pairs. This provided us with access to the evolution of the structural statistics for all the coordination shells in condensed ZnO, enabling us to accurately track the changes in the internal structural parameter u and the anharmonic effect. We observed a clear decrease in u and an increased anharmonicity near the onset of the B4 → B1 phase transition, indicating a preference for the iT phase as the intermediate state to initiate the phase transition that can arise from the softening of shear phonon modes. This study suggests that NN-based approach can facilitate a more comprehensive and efficient interpretation of XAFS under complex in-situ conditions, which paves the way for highly automated data processing pipelines for high-throughput and real-time characterizations in next-generation synchrotron photon sources.

Modeling and analysis of ice condensation on bridge deck pavement surface based on heat transfer theory and finite element method

Bridge surfaces usually freeze more easily than road surfaces in wet and cold conditions, which is unfavorable to traffic safety. This study aims to develop an ice prediction model for bridge deck pavement structures by integrating external climatic factors and internal structure parameters, and to analyze the mechanism of ice condensation. This model adopted finite element analysis to deal with the heat transfer problem and the latent heat during the phase change process. A series of experiments were designed to validate the model, and the relative difference was around 10 %. Results shown that: among external climatic factors, the impact of changes in water accumulation on ice formation is not significant. Meanwhile, the air temperature has the greatest impact, and there is a non-linear relationship between wind speed and the initial freezing time. In the study on the effect of aging, it was found that aged asphalt concrete pavement would freeze earlier and melt later compared to new. When comparing different structures, it was observed that the initial freezing time of the bridge deck pavement structure was 0.8 h earlier than the road structure, and the total freezing time was 2.8 h shorter than the road structure. It was also found that the lower thermal conductivity would delay the occurrence of icing when the bridge deck pavement structure was in a cooling stage. Finally, it was observed that the vehicle speed played a critical role in determining the direction of the heat flow with a specific value, and the value would increase as the temperature difference decreased. This prediction model is useful for transportation agencies to understand the mechanism of pavement ice formation and ensure traffic safety in winter.

Preservation of strawberries using chitosan incorporated with lemongrass essential oil: An X-ray computed tomography analysis of the internal structure and quality parameters

Preservation of strawberries using chitosan incorporated with lemongrass essential oil: An X-ray computed tomography analysis of the internal structure and quality parameters

Micromechanics study of short carbon fiber-reinforced thermoplastics fabricated via 3D printing using design of experiments

In this study, short carbon fiber-reinforced thermoplastic (sCFRTP) was 3D-printed under different printing parameters, and the influence of the combination of printing parameters on the tensile properties and internal structure (void volume fraction, fiber orientation, and fiber length) of the 3D-printed sCFRTP was investigated through tensile testing, X-ray computed tomography, microscopic observations and theoretical analysis based on a micromechanics model (MM). A total of ten printings and characterizations were performed via the design of experiments, and the outcomes displayed specimens that were fabricated under optimal printing parameters (specimen DoE) exhibited a Young's modulus of 5.1 ± 0.3 GPa and a tensile strength of 73.3 ± 0.9 MPa, resulting in the highest Young's modulus and tensile strength. The MM analysis successfully reproduced the experimental stress-strain response as well as the equivalent stiffness of the sCFRTPs with a much shorter time than finite element analysis by inputting the measured fiber length, void volume fraction, and fiber orientation distribution into the in-house MM code. From this MM analysis, it was suggested the higher Young's modulus and tensile strength observed in the specimen DoE is due to more of the relatively long fibers are oriented in the print direction with fewer voids. Furthermore, the influence of internal structure parameters on the mechanical properties of the 3D-printed sCFRTPs was analyzed, revealing that fiber length has a greater impact on the mechanical properties than void volume fraction and fiber orientation distribution.

Relationship between external and internal structures in deciduous teeth: a multidisciplinary study.

The different dental structures of deciduous teeth have always been regarded with great interest in endodontics and restorative dentistry. Nevertheless, there are still few investigations on the morphology of deciduous teeth compared to the permanent ones, due to the difficulty in obtaining sound deciduous teeth suitable for measurement. The aim of this research is to evaluate and compare the internal and external structures of deciduous teeth from completely preserved hominid findings, using X-ray and micro-CT examination. Samples were photographed using a digital camera and were then analysed by X-ray and micro-CT. Different parameters of external and internal structures were calculated to obtain a normalisation coefficient, called the P-factor. There is a constant correlation between external and internal structure, regardless of gender, type, shape or arch sector.

Theoretical study of heat transfer model of silica aerogel based on the porous structure of secondary particles

In this paper, the secondary particles of silica aerogels are equivalently modeled using the spherical hollow cube model, and the heat transfer of porous silica aerogels are linked to their internal structural parameters, thus establishing a theoretical model of the heat transmission process of porous silica aerogels formed by the interconnected accumulation of secondary particles. The model analyzes and calculates the pertinent parameters as well as the overall thermal conductivity while accounting for the secondary particles' porous structure. It then compares its predictions with experimental results and predictions from other models for various pressures and temperatures. The results demonstrate good agreement between the constructed model and the experimental data, the deviation is controlled within 12% and the minimum deviation can reach 1.6%. The model is beneficial for enhancing the thermal insulation performance of nanoporous aerogels because it is effective in predicting the heat transmission process within the porous medium silica aerogel.

Study on the microscale structure and sulfate attack resistance of cement mortars containing graphene oxide nanoplatelets

This study investigates the corrosion resistance of cement-based materials modified with GO (graphene oxide) against sulfate, employing a series of experiments. The results demonstrate that the inclusion of GO enhances the corrosion resistance of cement in terms of mechanical properties, sulfate ion diffusion, and microstructural characteristics. The internal pore network structural parameters of the composite were analyzed using X-ray microcomputed tomography processing techniques at a microscopic scale. The permeability of the composites was numerically simulated using hydrodynamic equations, such as the Hagen-Poiseuille and Kozeny-Carman equations. The additional amount of GO in the composite cement was varied as follows: 0%, 0.01%, 0.03%, 0.05%, and 0.1%, with 0% serving as the reference specimen. In the flexural and compressive strength tests, the strength of the GO-modified specimens exhibited varied improvements after 180 days of exposure to a sodium sulfate solution. The flexural and compressive corrosion resistance coefficients were optimized by 12.34% and 11.07%, respectively, with the addition of 0.03% GO. The diffusion coefficients of sulfate ions were consistently observed at a level of 10-6 mm2/s and decreased over time. Furthermore, the presence of GO hindered the transport of sulfate ions. The gas permeability test results indicated that the GO-modified cement mortar exhibited lower porosity and permeability compared to the reference mortar. The pore network structure model revealed that the reference specimen possessed a connected porosity of 8%, an average porosity of 10%, and a wide distribution of pore and throat radii. In contrast, the 0.03% GO composite cement specimens exhibited a connected porosity of 5.3% and an average porosity of 8%. Through simulations using the Kozeny-Carman equation, it was determined that the reference specimen had higher permeability and faster internal flow rates.

Environmental impacts of La2O3 on the optical and ligand field parameters of Ni ions inside Na2O-B2O3 glass

In this work, a glass system of La2O3, NiO, and Na2O borate glass was prepared by changing the concentrations of La2O3/B2O3 contents. Further, the internal structure, optical absorbance, and ligand field parameters of Ni ions were studied. The internal structure was investigated using the Fourier transform infrared technique. The optical absorbance was measured, and the optical band gaps were obtained using Tauc's plot. According to the internal structure studies, BO4 contents increase with increasing La2O3/B2O3 concentrations, while BO3 contents decrease. Furthermore, the brown color and the absorption band at 424–428 nm of the prepared glass samples confirm the existence of Ni2+ cations in the form of NiO4 species and they act as glass formers. Additionally, the observed bands at 424–428, 490–500 and 798–806 nm are associated with the spin-allowed electron transitions of Ni2+ in octahedral coordination. Furthermore, the observed bands at 710–718 and 940–950 nm are related to the electronic transitions for Ni2+ in tetrahedral coordination. Moreover, the positions of all absorption bands shift toward higher wavelengths (redshift) with higher La2O3 concentrations. Additionally, the fundamental glass absorption edges move toward lower energy values as La2O3/B2O3 contents increase, confirming the band gaps behavior. Also, with increasing La2O3/B2O3 contents, the linear and nonlinear refractive indices increase. These behaviors were justified by the optical basicity and the electronic polarizability increase. On the other hand, the ligand field parameters of Ni ions; the crystal field splitting and Racah parameters (B and C), show opposite behaviors with further La2O3 additions. In detail, the crystal field splitting shows decreasing values and Racah parameters show increasing values. These results reflect the tendency of the bonds between the Ni cations and their surroundings towards a higher ionic nature (lower covalent nature).

The structural dimension parameter optimization method of tapered roller bearings for wind power gearbox

Taking the non-standardized internal structural dimension parameters of rolling bearings as the design variable, the constrained optimization mathematical model of tapered roller bearings under the maximum target of basic static load rating and basic dynamic load rating has been established. Optimization results of the mathematical model have been obtained by using the improved multi-objective genetic algorithm, NSGA-II. After the above-mentioned methods were used to the optimization of the tapered roller bearing on the high-speed shaft of a 750 kW wind turbine gearbox, its basic rated static load and basic rated dynamic load can be increased by 15 % and 17 % compared with its standard value. Thus, the proposed methods are feasible and reliable, and has certain application value for improving the bearing performance and prolonging its service life.

Influence of Internal Structural Parameters on the Inner Flow and Outer Spray Characteristics for Feedback-Free Fluidic Oscillator

Feedback-free fluidic oscillators, relying on the interaction of jets to oscillate, have a wide range of operation frequencies and no moving parts, which is promising for future applications. In this paper, the sweep angle, oscillation frequency, and volume flow rate of the feedback-free fluidic oscillator with a cavity width of 4.6 mm were measured experimentally, and the sweeping mechanism was analyzed based on the internal flow simulation. The influence of the impact angle, cavity exit width, and shoulder radius on the internal flow and external spray characteristics was analyzed by the numerical method. The results show that the sweep angle and oscillation frequency are affected throughout the increase in impact angle from 80° to 120°. However, only when the SR is greater than 0.88 mm does the internal flow and spray state change significantly. The volume flow rate is mainly affected by the cavity exit width and increases linearly from 5.3 mL/s to 9.3 mL/s as the width increases from 0.45 mm to 0.85 mm. It can be surmised that the sweep angle is approximately linear with the distance between the hit point and the impact cavity centerline.

The investigation of a unbalanced barrel pitching system’s characteristics degradation and compensation under gradual erosion behavior

The unbalanced barrel pitching system is a typical electro-hydraulic coupling servo control system, the performance of which determines the response speed and hit probability of vehicle mounted weapon equipment. However, in the actual service process, its core component, the high precision jet pipe servo valve, will produce the gradual erosion of the pilot stage’s receivers and the power stage’s throttling edges, which will induce the performance degradation of the unbalanced barrel pitching system, and finally greatly reduce the performance of barrel weapons. Therefore, a pressure and position double loop state space model of unbalanced barrel pitching system including the core parameters of performance degradation is established. The erosion behavior mechanism model of jet pipe servo valve is constructed, and the performance degradation characteristics of the unbalanced barrel pitching control system under the condition of erosion are further analyzed. Finally, aiming at the double loop structure of internal pressure loop and external position loop, the RBF Network Adaptive Robust Sliding Mode-Proportional Integral Derivative two-stage controller of barrel system is designed, based on which the experimental platform of unbalanced barrel pitching control is built. The experimental results are in good agreement with the theoretical results, so the proposed control method can effectively suppress the degradation of internal structural parameters induced by erosion, that is, it can better compensate the performance degradation of barrel pitching system induced by gradual erosion behavior.

Influence of ambient temperature and structural parameters on thermal conductivity of carbon nanotube arrays after secondary segmentation

Vertically arranged carbon nanotube (CNT) arrays have good flexibility, elasticity, and thermal conductivity. As a new type of thermal interface materials (TIMs), it is increasingly used in heat conduction applications. The thermal conductivity of CNT arrays is an order of magnitude higher than that of traditional silicone oil and solid-state interface composites. However, their thermal properties are susceptible to the ambient temperature and internal structural parameters, and the underlying influence mechanism remains unclear. This lack of understanding hinders the design and application of CNT arrays in practical settings. Therefore, a secondary segmentation method was proposed to establish the structural model of CNT microcolumn arrays. Then, the thermal properties of the array material were simulated, and the influence of different environmental temperatures and structural parameters on thermal properties were analyzed. Simultaneously, the dynamic thermal conductivity of the CNT array was explored by thermal cyclic loading. Simulation results indicate that the increase of structural parameters have a positive effect on the thermal conductivity of the array at different ambient temperatures, but the low temperature environment is more conducive to the improvement. Furthermore, the influence of different array densities predicted by the model on thermal properties is consistent with the corresponding experimental results, which illustrates the feasibility of the segmentation method of the model and provides a new theoretical method for studying the thermal properties of CNT arrays.

Dynamic Modelling of Common Rail Diesel Engines Combined with Amesim and Simulink

The fuel injector of the diesel engine is the core component of the high-pressure common rail system of the diesel engine. The ECU performs flexible control on the fuel injector to realize the precise adjustment of the fuel injection rate and fuel injection quantity of the engine under different working conditions, and achieve the purpose of reducing fuel consumption and noise. The internal structural parameters of the fuel injector have a significant impact on the fuel injection rate, and it is often necessary to make a large number of modifications to the structural parameters of the fuel injector in order to meet the increasingly stringent emission regulations. In this paper, in order to analyze the effect of various structural parameters of fuel injectors on fuel injection rate, increase fuel injection rate, and obtain the best effect, AMESim and simulink software are used to build a simulation model of a common rail fuel injection device and a diesel engine. This model provides a theoretical basis for the structure design of the fuel injector.

Exoplanet characterization using conditional invertible neural networks

Context. The characterization of the interior of an exoplanet is an inverse problem. The solution requires statistical methods such as Bayesian inference. Current methods employ Markov chain Monte Carlo (MCMC) sampling to infer the posterior probability of the planetary structure parameters for a given exoplanet. These methods are time-consuming because they require the evaluation of a planetary structure model ~105 times. Aims. To speed up the inference process when characterizing an exoplanet, we propose to use conditional invertible neural networks to calculate the posterior probability of the planetary structure parameters. Methods. Conditional invertible neural networks (cINNs) are a special type of neural network that excels at solving inverse problems. We constructed a cINN following the framework for easily invertible architectures (FreIA). This neural network was then trained on a database of 5.6 × 106 internal structure models to recover the inverse mapping between internal structure parameters and observable features (i.e., planetary mass, planetary radius, and elemental composition of the host star). We also show how observational uncertainties can be accounted for. Results. The cINN method was compared to a commonly used Metropolis-Hastings MCMC. To do this, we repeated the characterization of the exoplanet K2-111 b, using both the MCMC method and the trained cINN. We show that the inferred posterior probability distributions of the internal structure parameters from both methods are very similar; the largest differences are seen in the exoplanet water content. Thus, cINNs are a possible alternative to the standard time-consuming sampling methods. cINNs allow infering the composition of an exoplanet that is orders of magnitude faster than what is possible using an MCMC method. The computation of a large database of internal structures to train the neural network is still required, however. Because this database is only computed once, we found that using an invertible neural network is more efficient than an MCMC when more than ten exoplanets are characterized using the same neural network.

Unique morphological architecture of the hamstring muscles and its functional relevance revealed by analysis of isolated muscle specimens and quantification of structural parameters.

The structural and functional differences of individual hamstrings have not been sufficiently evaluated. This study aimed to clarify the morphological architecture of the hamstrings including the superficial tendons in detail using isolated muscle specimens, together with quantification of structural parameters of the muscle. Sixteen lower limbs of human cadavers were used in this study. The semimembranosus (SM), semitendinosus (ST), biceps femoris long head (BFlh), and biceps femoris short head (BFsh) were dissected from cadavers to prepare isolated muscle specimens. Structural parameters, including muscle volume, muscle length, fiber length, sarcomere length, pennation angle, and physiological cross-sectional area (PCSA) were measured. In addition, the proximal and distal attachment areas of the muscle fibers were measured, and the proximal/distal area ratio was calculated. The SM, ST, and BFlh were spindle-shaped with the superficial origin and insertion tendons on the muscle surface, and the BFsh was quadrate with direct attachment to the skeleton and BFlh tendon. The muscle architecture was pennate in the four muscles. The four hamstrings possessed either of two types of structural parameters, one with shorter fiber length and larger PCSA, as in the SM and BFlh, and the other with longer fiber length and smaller PCSA, as in the ST and BFsh. Sarcomere length was unique in each of the four hamstrings, and thus the fiber length was suitably normalized using the average sarcomere length for each, instead of uniform length of 2.7μm. The proximal/distal area ratio was even in the SM, large in the ST, and small in the BFsh and BFlh. This study clarified that the superficial origin and insertion tendons are critical determinants of the unique internal structure and structural parameters representing the functional properties of the hamstring muscles.

MCC-Net: A class attention-enhanced multi-scale model for internal structure segmentation of rice seedling stem

Internal structural parameters of rice seedling stems are of great significance for rice growth detection, rice selection, breeding, and damage examination. Aiming at the problems of non-repeatability and low detection accuracy in the existing plant internal structure phenotypic traits detection methods, this paper presents a non-destructive segmentation method for examining the internal structure of rice seedling stems based on deep learning. We use a standard X-ray CT imaging technology to obtain non-destructive tomographic images of rice seedling stems and then design a class attention-enhanced multi-scale segmentation model (MCC-Net), where UNet is used as the backbone network. Specifically, the proposed MCC-Net mainly consists of three core components: multi-scale convolutional block (MCB), coordinate spatial attention (CSA) module, and class attention enhancement (CAE) module. MCB is the main component of the encoder to improve the feature extraction ability of the model for regions of different sizes in the internal structure. CSA is embedded into the UNet skip connections to enhance the expression of effective features and automatically locate the regions with different structures of rice seedling stems. CAE is designed to calculate the dependencies between image pixels and categories, which can enhance the feature expression from the perspective of categories and correct the category errors in the segmentation results. The experimental results show that MIOU, average dice coefficient and average precision of our proposed MCC-Net model on the self-built rice seedling stem CT image dataset are 92.56%, 96.33% and 96.59% respectively. Compared with several state of the art models, the proposed model achieves better segmentation performance on the rice seedling stem CT image dataset.

Numerical simulation optimization of neutral flow dynamics in low-power Hall thruster

This paper utilizes a low-power Hall thruster to investigate its flow field’s neutral flow dynamics. Specifically, under a free molecular flow with a high Knudsen number (Kn>10), we employ the flow conductance theory to investigate the interplay between the internal structural parameters of the thruster flow field and its conductance, which is directly reflected in the neutral gas distribution.Hence, first, we increase the number and diameter of the orifices in the buffer chamber so that the baffle effectively increases the flow field conductance, and thus the number density (nn) of the neutral gas in the discharge channel increases. This phenomenon reduces the ionization mean free path (λi) and thus increases the utilization rate (ηi) of the neutral gas. Then, we alter the baffle orifices distribution to an unequally spaced distribution and stagger the outlet orifices, resulting in a highly homogeneity neutral gas distribution in the circumferential direction, ultimately increasing the effective outlet area and reducing the backflow probability of the neutral gas molecules. This operation reduces the low-frequency oscillation amplitude and thus enhances the thruster’s operation stability. Finally, we explore the influence of the entire operating conditions, especially temperature and mass flow rate variations, on the universality of the simulation results. Overall, this work provides a new concept for optimizing the neutral flow field dynamics of a Hall thruster.