Structure Parameter Research Articles

Fluid-Actuated Nano-Micro-Macro Structure Morphing Enables Smart Multispectrum Compatible Stealth.

Modern detection technology has driven camouflage technology toward multispectral compatibility and dynamic regulation. However, developing such stealth technologies is challenging due to different frequency-band principles. Here, this work proposes a design concept for a fluid-actuated multispectral compatible smart stealth device that employs a deformable mechanochromic layer/elastomer with a channeled dielectric layer. After fluid actuation, the deformable elastomer layer transmits mechanical strain to the mechanochromic layer, thereby altering the visible reflectance wavelengths in [568, 699] nm. Concurrently, the pumped-in liquid reconfigures the spatial structure parameter to alter microwave resonance and diffraction for dynamic radar absorption, enabling dynamic radar absorption with significant broadband absorption at [8.16, 18.0] GHz. Using the heat-absorption property also achieves dynamic infrared stealth, shown by a ΔT ≈ 16.5 °C temperature difference. Additionally, the device exhibits a rapid response time (∼1 s), excellent cycling performance (100 cycles), and programmability (10 codes), offering a new stealth strategy.

Modular Calabi-Yau fourfolds and connections to M-theory fluxes

In this work, we study the local zeta functions of Calabi-Yau fourfolds. This is done by developing arithmetic deformation techniques to compute the factor of the zeta function that is attributed to the horizontal four-form cohomology. This, in turn, is sensitive to the complex structure of the fourfold. Focusing mainly on examples of fourfolds with a single complex structure parameter, it is demonstrated that the proposed arithmetic techniques are both applicable and consistent. We present a Calabi-Yau fourfold for which a factor of the horizontal four-form cohomology further splits into two pieces of Hodge type (4, 0) + (2, 2) + (0, 4) and (3, 1) + (1, 3). The latter factor corresponds to a weight-3 modular form, which allows expressing the value of the periods in terms of critical values of the L-function of this modular form, in accordance with Deligne’s conjecture. The arithmetic considerations are related to M-theory Calabi-Yau fourfold compactifications with background four-form fluxes. We classify such background fluxes according to their Hodge type. For those fluxes associated to modular forms, we express their couplings in the low-energy effective action in terms of L-function values.

Studies of Structural and Optical Properties of Nickel Chloride and Glycine Doped Potassium Hydrogen Phthalate (KHP) Crystal

A semi-organic single crystal of potassium hydrogen phthalate (KHP, K(C6H4COOH.COO)) doped with Nickel Chloride (NiCl2) and Glycine (C₂H₅NO₂) was successfully harvested at room temperature to enhance the characteristics of KHP using a slow evaporation approach. The concentration of 1 mol % of Nickel Chloride and 6 mol % Glycine was used during the fabrication of the Nickel Chloride and Glycine doped KHP single crystal. Powder X-Ray diffraction (XRD), ultraviolet visible spectroscopy (UV-Vis), and Fourier transform Infrared (FTIR) analysis were used to analyze the grown single crystal. Powder XRD investigation verified an orthorhombic crystal structure and lattice parameter .To evaluate optical energy band gap and optical transparency using UV-Vis spectral. According to, FTIR analysis, and dielectric studies, it is evident that the crystal modification noticeably by adding dopant.

Working Condition Sensitivity Analysis and Optimal Structure Parameter Determination of IVT Based on CFD and Orthogonal Experiment

To address liquid accumulation in horizontal gas wells, a specialized internal vortex tool (IVT) was developed for use in the horizontal sections, functioning as a drainage gas recovery device. This tool operates by leveraging centrifugal forces generated during fluid swirl to separate liquid from gas. The study examined the performance of IVT under various operational conditions and sought to identify optimal structural parameters. Through a controlled variable approach, the impact of inlet velocity and the water-gas volume ratio on pressure drop range, MGV (maximum gas velocity), and MVFLP (maximum liquid phase volume fraction) was analyzed. The results indicated that when the inlet velocity is between 2-4m/s and the water to gas volume ratio is between 0.5-2m3/104m3, the smaller the inlet velocity and the smaller the water to gas volume ratio, the better the gas-liquid separation effect of the IVT. An orthogonal test was subsequently employed to fine-tune the tool's structural parameters for different conditions, culminating in the creation of a comprehensive optimization chart for IVT. This study can effectively design drainage gas production tools for gas wells under different working conditions, reduce energy loss during drainage gas production, effectively utilize downhole resources, and achieve the goal of increasing natural gas well production and reducing costs.

A DFT-based computational study on a highly and lead-free inorganic new fluoroperovskite of Mg3PF3

Inorganic fluoroperovskite materials are increasingly important in solar technology due to their exceptional structural, optical, electronic, and mechanical properties. This study uses DFT calculations to investigate the properties of Mg3PF3 fluoroperovskite. Our results show a crystal structure and lattice parameter of (a = 4.64 Å) which align with previous theoretical and experimental findings, confirming the accuracy of our calculations. Mechanical analysis reveals that Mg3PF3 is naturally ductile, elastically anisotropic, and stable according to established criteria. The band structure and PDOS indicate that it is a semiconductor with direct bandgap of 3.88 eV at the Γ point, making it suitable for electronic applications. Electron charge density mapping suggests a predominantly ionic bonding nature. Optical property analysis shows significant dielectric constant peaks in the photon energy range favorable for solar cells. Overall, these findings position Mg3PF3 as a promising candidate for solar cell technology, highlighting its potential for enhancing renewable energy solutions.

Synergistic effects of iron with alkali and alkaline earth metals on catalytic pyrolysis of biomass for highly graphitized carbon

To prepare highly graphitized carbon from biomass and understand the synergistic effects of iron with alkali and alkaline earth metals (AAEMs), K and Ca were introduced to iron-catalyzed graphitization of biomass. Results showed that both K and Ca accelerated the thermal decomposition rate of biomass, and the activation energy of the devolatilization stage with K and Ca reduced to 60.882 kJ/mol and 45.342 kJ/mol respectively, compared to 73.657 kJ/mol without K/Ca. The porous graphitic carbon obtained at 850 °C with the existence of K and Fe exhibited the highest graphitization degree parameter (g = 0.5193) with a big surface area (170.504 m2/g). The carbon with Ca and Fe showed a developed mesoporous structure (198.979 m2/g) and high graphitization parameter (g = 0.1783), compared to g = 0.0934 without K and Ca. Finally, the tailor-catalyzed mechanism of iron-catalyzed graphitization of biomass in the presence of K/Ca was proposed. K reduced the sp3 amorphous carbon structures and intercalated carbon framework while Ca produced the in-situ CaO template and extra gasification gas of CO2, resulting in an acceleration of the graphitization of biomass.

Atmospheric Turbulence Parameters Deduced from VerticalProfile of Cn2

The proposed framework can capture realistic spatiotemporal variations in atmospheric turbulence parameters based on local meteorological conditions, such as Fried's parameter r0, isoplanatic angles θ0, seeing ε, scintillation rate , and the wavefront coherence time τ0. Those parameters have been deduced from the refractive index structure parameter Two Iraqi locations were compared, specifically the middle and southern borders, and atmospheric turbulence parameters relevant to astronomical observation were measured, lines were drawn at latitudes 34.26° and 28.31°, respectively. The methodology included collecting meteorological data from both sites and performing numerical simulations based on atmospheric turbulence parameters. According to the criteria of air turbulence, the results showed that the middle of Iraq was better than the southern location for astronomical observation.

Alleviating H 0 and S 8 Tensions Simultaneously in K-essence Cosmology

The present work begins by examining the early-Universe inflationary epoch of a special K-essence model, which incorporates a linear coupling term between the scalar field potential and the canonical Lagrangian. For the power-law potential, we both numerically and analytically prove that the inflationary parameters such as the spectral index and tensor-to-scalar ratio are compatible with the recent BICEP/Keck observations. Continuing this work, our analysis based on comparing early-Universe observations with late-Universe measurements indicates that the tension on the Hubble parameter H 0 and the growth of structure parameter S 8 can be alleviated simultaneously. More precisely, compared to the standard ΛCDM model, our model can reduce H 0 tension to roughly 2.2σ, and the S 8 discrepancy diminishes to 0.82σ.

A New Hybrid Improved Arithmetic Optimization Algorithm for Solving Global and Engineering Optimization Problems

The Arithmetic Optimization Algorithm (AOA) is a novel metaheuristic inspired by mathematical arithmetic operators. Due to its simple structure and flexible parameter adjustment, the AOA has been applied to solve various engineering problems. However, the AOA still faces challenges such as poor exploitation ability and a tendency to fall into local optima, especially in complex, high-dimensional problems. In this paper, we propose a Hybrid Improved Arithmetic Optimization Algorithm (HIAOA) to address the issues of susceptibility to local optima in AOAs. First, grey wolf optimization is incorporated into the AOAs, where the group hunting behavior of GWO allows multiple individuals to perform local searches at the same time, enabling the solution to be more finely tuned and avoiding over-concentration in a particular region, which can improve the exploitation capability of the AOA. Second, at the end of each AOA run, the follower mechanism and the Cauchy mutation operation of the Sparrow Search Algorithm are selected with the same probability and perturbed to enhance the ability of the AOA to escape from the local optimum. The overall performance of the improved algorithm is assessed by selecting 23 benchmark functions and using the Wilcoxon rank-sum test. The results of the HIAOA are compared with other intelligent optimization algorithms. Furthermore, the HIAOA can also solve three engineering design problems successfully, demonstrating its competitiveness. According to the experimental results, the HIAOA has better test results than the comparator.

Study the Characteristic of the Coupling Parameter ( ? ) in Dusty Plasma by Computer modeling

Computer modeling has been used to investing the Coulomb coupling parameter ?. The effects of the structure parameter K, grain charge Z, plasma density N, temperature dust grain Td, on the Coulomb coupling parameter had been studied. It was seen that the ? was increasing with increasing Z and N, and decrease with increasing K and T. Also the critical value of ? that the phase transfer of the plasma state from liquid to solid was studied.

A Comprehensive Study on the Parameters Affecting Magnesium Plating/Stripping Kinetics in Rechargeable Mg Batteries

AbstractMg metal anode‐based battery is a more sustainable, lower cost, and higher energy density alternative to Li‐ion. However, this battery chemistry also faces several challenges associated with the high charge density of Mg2+, including achieving high reversibility and low voltage hysteresis for Mg metal plating/stripping. While significant improvements are achieved in last decades, they involve rather complex electrolyte formulations and/or Mg salts difficult to produce, and the use of unpractical substrates such as platinum. Here, significant improvement in terms of Mg plating kinetics is achieved in electrolytes containing commercial magnesium bis(trifluoromethanesulfonyl)imide salt (Mg(TFSI)2) by using titanium substrate with similar crystal structure and lattice parameter as Mg leading to lower nucleation overpotential. Low salt concentration electrolyte and addition of dibutyl magnesium (Mg(butyl)2) also enable the formation of thinner interphase, richer in solvent based decomposition products, further improving Mg plating kinetics. This work highlights the complex role of Mg(butyl)2, often considered as a simple drying agent, and how it impacts ion solvation favoring the mobility of electroactive cationic species, paving the way toward better electrolyte design with improved cation transference number.

Prediction of resilient modulus with pre-post experimental data of undisturbed subgrade soils using machine learning algorithms

The resilient modulus (MR) of subgrade, which shows relationship between stress and unit deformation of a pavement systems under traffic loads, is a design parameter of the pavement structure. Although a cyclic triaxial test apparatus can be used to directly determine the MR of the subgrade in the laboratory, utilizing prediction models based on easily obtainable soil parameters, is a more efficient method when taking time and cost considerations into account. A comprehensive laboratory testing program is designed to create MR prediction models using machine learning (ML) algorithms. 70 undisturbed soil samples are subjected to MR tests, as well as physical and engineering soil properties tests (water content, field density, specific gravity, gradation, consistency limits, unconfined compressive strength, swell pressure, swell percentage). Soil samples are drilled from a highway that has been in operation for over five years.First, a linear model like MLR is used in the study. Next, nonlinear regression models like RF, GBM, LightGBM, CatBoost, and XGBoost algorithms are used. Research findings showed that nonlinear regression models outperformed linear regression models in predicting the MR (R2 > 0.85), with the XGBoost algorithm yielding the best accuracy (R2 = 0.90). Apart from the primary effects such as confining pressure (σ3) and deviatoric stress (σd), it was found that unconfined compressive strength (qu), natural water content (wn), and swelling percentage (SR) are significant parameters in the prediction of MR among all parameters.

Heat transfer characteristic and optimization design of alter diameter array impingement cooling structure

The fine design of blade cooling is one of the leading directions in the development for blade manufacturing technology, attaining optimal and consistent cooling efficiency is the common research concern in the field of fine design. In the current work, the alter diameter hole arrays are applied to reasonably regulate the distribution of cold air flow, which aims to achieve uniform cooling performance of impinging cooling technology. Experiment involving temperature sensitive paint technology and simulation based on SST k-w turbulence model are conducted. Subsequently, the mechanism of cooling performance increasement is investigated; the impact of structural elements on the heat transfer properties is discussed. Moreover, the correlation between the Nu number of the target surface and the comprehensive influence factors was fitted based on response surface method; the optimal structure in the range of the structural parameters is calculated based on NSGA-II and TOPSIS method. The results reveal that the influence of d and x on average surface Nusselt number is remarkable. In addition, the response surface model fitting model is accurate to predict the structure parameter effect on cooling performance of alter impingement cooling, with the prediction error less than 2.67 %. Compared with the basic EDI, the Nu of the ADI structure with ∇T constraint is increased by 5.2 %, the temperature inhomogeneity is reduced by 53.4 %. The significant improvement of temperature inhomogeneity indicates the practicality of ADI structure and optimized procedure used in improving impingement cooling efficiency which shows promising performance increasement.

Assessing the potential and energy distribution calibration of ethanol-biodiesel based RCCI mode of compression ignition engine in a plugin parallel hybrid electric vehicle

The focus of this research is to develop the resilient powertrain to combat the enforcement of stringent emission regulations and elevate its feasibility to power with the sustainable fuels to support the fuel crisis. The current solution in the reliable and adaptability point of view is the low temperature combustion engine-based hybrid electric powertrain powered with sustainable fuel is the better choice. The present work proposes the concept of an ethanol-biodiesel fuel based RCCI plugin parallel hybrid electric vehicles (PHEVs). The significant examination of this work in the aspects of optimal torque structure and injector control parameter calibration. The calibration of the RCCI engine torque structure operation is performed based on the multi-objective constraints of variance of indicated mean effective pressure and the maximum rate of pressure rise for the combustion stability. While the equivalence ratio and combustion temperature with emphasis on limiting the amount of NOx and soot emissions. The maximum ethanol energy share proportion of 66.98% has been achieved. The RCCI engine is most frequently operating in the torque zone of 10 Nm and then 17.81 Nm while the BLDC motor is most frequently operated in the range of 55 Nm even at max torque of 60 Nm. When comparing to a standard diesel hybrid setup, the ethanol-biodiesel fuelled RCCI setup has a 18%–19% reduction in harmful NOx emissions, with an equivalent decrease of 22.7% in fuel economy. This is achieved by only having a 13.4% more CO emission while a minimal increase in soot emission throughout the overall course of the driving cycle. The result of this work shows evidence that implementing an ethanol-biodiesel fuelled RCCI engine in a parallel hybrid configuration achieves a significant reduction in NOx emissions while achieving the performance targets and managing the fuel and battery energy utilization over a driving cycle efficiently.

Deep learning neural networks for monitoring early-age concrete strength through a surface-bonded PZT sensor configuration

Monitoring the immediate evolution of concrete’s strength is essential to ensure structural integrity and construction efficiency, requiring Forecasting to avoid unforeseen and severe failures during construction. The present investigation introduces an Equivalent structural parametric (ESP) study using a surface-bonded piezo sensor and electromechanical impedance (EMI) methodology to monitor and forecast the strength of concrete by implementing machine learning and deep learning methods. The concrete hydration processes are simulated using COMSOL™ 5.5. The concrete cube’s hydration is represented by altering Young’s modulus and damping ratio to show the rate of curing. Concrete strength development is examined in terms of conductance resonant frequency (CRF) and Conductance resonant peak (CRP). Continuous conductance signature monitoring and data analysis show that CRF and CRP increase with compressive strength. The system’s mechanical impedance is measured, and EMI signatures vs. frequency plots within a specific frequency range are compared to healthy impedance graphs. A mass-spring-damper system with identical properties is identified, and relevant structural parameters are computed. Modern ML algorithms include linear regression (LR), interaction LR, fine, medium, and coarse Gaussian SVM, etc. reliably predict strength with an error rate of less than 2%. Convolutional neural networks (CNN) have advanced image-based recognition, but their usage in EMI-based structural strength assessment is still being studied. A unique strategy using 2D CNN, 2D CNN– Long short-term memory (LSTM), and 2D CNN Bidirectional-LSTM to forecast concrete structure compressive strength shows the potential of deep learning. The proposed 2D CNN-Bi-LSTM model excels in compressive strength prediction, obtaining an R2 value of 0.99 and stabilizing loss error over a few epochs.

Failure analysis of a frangible cover made of short‐cut basalt fiber reinforced epoxy composites

AbstractThe frangible cover made of continuous fiber reinforced composites has become widely used structure for the new generation launch canisters. However, destroying the continuity of fibers is needed during the hand lay‐up process to make the frangible cover fail in predetermined patterns. In this article, composite frangible covers were fabricated with short‐cut basalt fiber reinforced epoxy(BF/Epoxy) composites instead of continuous fiber‐reinforced composite materials, reducing the strength redundancy in the local structure of the frangible covers. Tensile tests were firstly conducted on material samples to obtain the stress–strain characteristics of the short‐cut BF/Epoxy composites. The constitutive model and failure criterion of the short‐cut BF/Epoxy composites material were established. Then failure pressure and failure mode of the frangible covers were predicted by finite element method. Two frangible covers with different geometric parameter were fabricated and subjected to static bursting strength tests. The influence of structure parameter on the bursting pressure of the frangible cover was investigated in detail. it was found that the bursting pressure of the BF/Epoxy composite fragile cover can be tailored by adjusting the geometry size of the weak zones on surface of the cover. Meanwhile, Failure modes and the bursting pressure of the BF/Epoxy composite fragile covers are highly consistent with the predictions.Highlights A frangible cover made of the short‐cut basalt fiber reinforced epoxy(BF/Epoxy) composites was fabricated. The constitutive model and failure criterion were established based on the mechanical properties of the short‐cut BF/Epoxy composites. The static burst strength of the short‐cut BF/Epoxy composite frangible cover subjected to uniform pressure was investigated via both theoretical and experimental approaches. The short‐cut BF/Epoxy composite frangible cover eventually failed in accordance with the predetermined pattern. The simulation error of the failure pressure of the short‐cut BF/Epoxy composite frangible cover was less than 20%.

Improved pore structure characterization and classification of strong diagenesis sandstones by data-mining analytics in Tazhong area, Tarim Basin.

The Silurian system in Tazhong area is characterized by extensive, low-abundance lithological reservoirs with strong diagenesis, resulting in significant heterogeneity. The complex pore structure in this area significantly impacts fluid control, making accurate characterization and classification of pore structures crucial for understanding reservoir properties and their influence on oil and gas distribution. Based on 314 Mercury Injection Capillary Pressure (MICP) samples in combination with core slices and thin casting slices observation, a pipeline of characterization and classification scheme by data-mining analytics of strong diagenesis sandstone pore structure types in the study zone is established, and the characteristics of different pore structures are clarified. According to the pore structure parameter abstracted by MICP data compression and variable analysis based on hierarchical clustering and principal component analysis (PCA) analysis, the variables are reasonably evaluated and screened, and the screened variables can be divided into three groups: mean pore throat radius-maximum pore throat radius-median pore throat radius-pore throat diameter mean variable group, microscopic mean coefficient variable group, and median pressure displacement pressure-relative sorting coefficient variable group. The combination of classification schemes analysed by decision tree model and linear discriminant analysis (LDA) model was determined. In the two-dimensional projection diagram of LDA model, a relatively obvious distribution of low displacement pressure, middle displacement pressure and high displacement pressure was obtained, and three distribution lines were nearly parallel. Based on the relevant information, 6 combined classification schemes suitable for final pore structure modelling were determined verified by microscopic observation. The correct characterization and classification of pore structure can be applied to the prediction of pore type, which can be used to improve the prediction of oil and gas distribution and oil and gas recovery in the future.

Macular Structure Characteristics in Unilateral Idiopathic Full-Thickness Macular Hole and the Healthy Fellow Eyes

Introduction: This study aimed to investigate the macular structure and foveal pit characteristics in the unilateral full-thickness macular hole (FTMH) patients and healthy fellow eyes. Methods: Our retrospective investigation included patients with unilateral FTMH as the study group, and age- and sex-matched individuals without vitreomacular diseases as the control group, all from one medical center. FTMHs were categorized into those with epiretinal proliferation, those without epiretinal proliferation, or those lacking vitreomacular separation. Macular parameters including foveal base width (FBW), central foveolar thickness (CFT), central subfield thickness (CST), central subfield volume, and retinal artery trajectory (RAT) were measured via optical coherence tomography and fundus photography. Comparisons of these parameters were made among lesioned eyes, contralateral healthy eyes and normal controls, as well as among different subgroups. Results: Sixty-eight unilateral FTMH patients (39 women and 29 men) and 68 normal controls were enrolled. The fellow eyes of unilateral FTMH showed larger FBWs (446.8 ± 98.2 μm) than controls (338.4 ± 80.6 μm, p < 0.001). The lesioned and fellow eyes of unilateral FTMH had smaller RAT values (0.19 ± 0.06 and 0.14 ± 0.04) than controls (0.37 ± 0.14, p < 0.001), indicating wider RAT in both groups. No significant macular structure parameter differences were observed among different FTMH subgroups. Females exhibited larger FBW, thinner CFT and CST, and wider RAT than the age-matched males (p < 0.05). Conclusions: Patients with unilateral FTMH had a wider RAT in both the lesioned and healthy eyes and a wider FBW in their healthy fellow eyes than in controls. Such macular structure characteristics may be prone to macular hole formation.

Research on integrated LiDAR and multi-parameter detection of atmospheric transmittance, turbulence, and wind

An integrated LiDAR system has been reported, which can be used for simultaneous detection of atmospheric transmittance, turbulence, and wind along the same path. Through the integrated design of optics and mechanics, the size and weight of the system were effectively reduced. The comprehensive detection distance of atmospheric transmittance, atmospheric coherence length, and radial wind had also been achieved at least 4 kilometers. Comparative experiments have demonstrated that the detection results of the integrated LiDAR system and the near-surface meteorological observation system have standard deviations of less than 0.03 km−1 for extinction coefficient, 0.2 m/s for wind velocity, and 7.15 × 10−14 m−2/3 for C 2 n (atmospheric refractive index structure parameter), thus verifying the accuracy of the system detection. The reliability of the integrated LiDAR system was validated through six consecutive nights of continuous detection experiments, measuring three parameters simultaneously. Through analysis, the influence laws among atmospheric transmittance, coherence length, and wind were preliminarily explored. Significant variations in wind velocity can induce substantial fluctuations in atmospheric coherence length, and it is positively correlated with atmospheric transmittance. The integrated LiDAR system can provide a variety of reliable real-time detection data for further research on the laser transmission process in the atmosphere.

A novel molecular structure parameter determination method for biomass thermochemical conversion mechanism investigation

The low-grade energy properties and high O content of biomass limit its efficient energy utilization. Torrefaction is known to be one of the most promising thermochemical conversion methods for upgrading biomass. 250 °C Gas-pressurized (GP) torrefaction realizes deep decomposition of hemicellulose in biomass to as high as 99.7% by deoxygenation and aromatization. However, the above thermochemical conversion mechanism at molecular-level is currently scant. Here, a novel molecular structural parameter method and pure hemicellulose torrefaction were employed to investigate the thermochemical conversion mechanism. Results demonstrate that O content of 250 °C GP torrefied hemicellulose was as low as 28.8 wt%, which was considerably lower than 44.6 wt% of traditional torrefied hemicellulose. There are five deoxygenation mechanisms of hemicellulose during the GP torrefaction: deacetylation, decarbonylation, dehydroxylation, ring opening and cyclization reactions to produce CO2/CH3COOH, CO, H2O, ketones/aldehydes and furans. The deoxygenation and aromatization reactions cause the chemical structure of hemicellulose evolution significantly, these mechanisms are: active hemicellulose undergo aromatization reaction through cyclization and deoxidation to generate preliminary 2-ring furans polymer, followed by stepwise polymerization reactions to form 4-ring and 6-ring furans polymers. These polymerization reactions further greatly enhance deoxygenation reaction. A thermochemical conversion mechanism model is developed based on the above investigation. This work provides a novel method for determining the molecular structure and reaction mechanism of thermochemical converted biomass.