Structure Parameter Research Articles

Experiment study on focusing pattern prediction of particles in asymmetric contraction-expansion array channel.

Contraction-expansion array (CEA) microchannel is a typical structure applied on particle/cell manipulation. The prediction of the particle focusing pattern in CEA microchannel is worthwhile to be investigate deeply. Here, we demonstrated a virtual boundary method by flow field analysis and theoretical derivation. The calculating method of the virtual boundary location, related to the Reynolds number (Re) and the structure parameter RW, was proposed. Combining the approximate Poiseuille flow pattern based on the virtual boundary method with the simulation results of Dean flow, the main line pattern and the main/lateral lines pattern were predicted and validated in experiments. The transformation from the main line pattern to the main/lateral lines pattern can be facilitated by increasing Re, decreasing RW , and decreasing α. An empirical formula was derived to characterize the critical condition of the transformation. The virtual boundary method can provide a guidance for asymmetric CEA channel design and contribute to the widespread application of microfluidic particle focusing.

A new method for mapping vegetation structure parameters in forested areas using GEDI data

The spatially continuous mapping of vegetation structure parameters in forested areas serves as a crucial foundation for research in various fields, including ecosystem ecology, climate change, hydrology, and forest management and protection. However, there is a notable scarcity of regional scale data regarding vegetation structure parameters. Therefore, our objective was to fill this data gap by providing a methodology for mapping vegetation structure parameters in forested areas at regional-scale. Global Ecosystem Dynamics Investigation (GEDI) provides precise observational data on vegetation structure parameters across the world. Using GEDI vegetation structure parameter point data, we developed a vegetation state coefficient based on the ratio of plant area index (PAI) and vegetation coverage (COVER). Subsequently, we proposed a method for decomposing vegetation coverage to simulate layered vegetation coverage. Taking Jiangxi Province as a case study, we integrated machine learning models to generate a spatially continuous map of vegetation structure parameters in forested areas, including layered coverage and layered leaf area index, in 2020. The map has a spatial resolution of 30 m and a vertical resolution of 5 m. The model exhibits excellent performance. Among the 140 sets of models, approximately 63 % of them achieved an R2 surpassing 0.6, while 89 % of the models achieved a root mean square error (RMSE) below 0.3. This study can serve as a valuable reference for the decomposition of vegetation structure parameters at the regional scale and provide a more precise depiction of the spatial characteristics of vertical vegetation structure at the regional scale. It contributes by providing data support and methodological guidance for research related to forest structure analysis, resource management, and ecological process simulation at the regional scale.

Carbon emission reduction in public buildings of extreme cold regions: A study on enclosure structure and HVAC system parameter optimization

AbstractThe implementation of strategies aimed at curtailing energy consumption and carbon emissions in buildings is of paramount importance. Priority should be accorded to the reduction of embodied carbon emissions from construction materials and operational carbon emissions during the usage phase. A public building situated in an extremely cold region is chosen as the subject of this study. An initial investigation is conducted into the impact of various enclosure structure materials on embodied carbon. The impact of different heating, ventilation and air conditioning (HVAC) systems on the total carbon emissions of public buildings are studied as well. The findings indicate that the amalgamation of W3 + R + G4 + H4 culminates in the least total carbon emissions. Upon establishing the foundational scheme for the public building, an optimization (nondominated sorting genetic algorithm II [NSGA II] and Criteria Importance Through Intercrieria Correlation [CRITIC]) of the enclosure structure parameters is initiated to examine the optimal parameters of the public building's enclosure structure. The findings reveal that a decrease in the heat transfer coefficient could trigger an increase in total carbon emissions. This is attributed to the fact that the carbon emissions embodied in the production process of these materials could potentially outweigh the reduction observed in operational carbon emissions. Further adjustments were also made to the parameters of the HVAC system in the buildings. The findings indicate that within the context of public buildings, given the presence of optimal parameters and an HVAC system that utilizes solar energy for both heating and cooling in the American Society of Heating, Refrigerating and Air‐Conditioning Engineers, Inc. 6 A climatic zone, the efficiency of the cooling system can exert a significant influence on the operations carbon emissions reduction.

MIM waveguide based nano refractive index sensor for hemoglobin and glucose concentration detection in human body

In this study, a nanoscale refractive index sensor structure is proposed, which is realised using a metal-insulator-metal (MIM) waveguide and a grooved circular ring with double disk cavity (GRDD) structure coupled to each other. The finite element method (FEM) was used to analyze and investigate the effects of the variations of each structural parameter on the transmittance spectra and the comprehensive performance of the sensor. Based on the simulation results, the optimum sensitivity parameter of the sensor structure is 2800 nm R−1IU−1 with a figure of merit (FOM) value of 51.9 RIU−1. The sensor structure is capable of being used in biomedical field with sensitivities of 3.895 nm g−L−1, 4.870 nm/gL−1, and 4.955 nm/gL−1, respectively, for detecting hemoglobin of blood types A, B, and O, and 4.48 nm/gL−1, for detecting glucose concentration.

Comparative analysis of C n2 estimation methods for sonic anemometer data

Wind speed and sonic temperature measured with ultrasonic anemometers are often utilized to estimate the refractive index structure parameter C n 2, a vital parameter for optical propagation. In this work, we compare four methods to estimate C n 2 from C T 2, using the same temporal sonic temperature data streams for two separated sonic anemometers on a homogenous path. Values of C n 2 obtained with these four methods using field trial data are compared to those from a commercial scintillometer and from the differential image motion method using a grid of light sources positioned at the end of a common path. In addition to the comparison between the methods, we also consider appropriate error bars for C n 2 based on sonic temperature considering only the errors from having a finite number of turbulent samples. The Bayesian and power spectral methods were found to give adequate estimates for strong turbulence levels but consistently overestimated the C n 2 for weak turbulence. The nearest neighbors and structure function methods performed well under all turbulence strengths tested.

Application of self-learning interval type-2 fuzzy neural network in PM2.5 concentration prediction

Abstract The change of PM2.5 concentration in air quality is nonlinear and difficult to predict. Therefore, a self-learning interval type-2 fuzzy neural network (SLIT2FNN) is proposed. SLIT2FNN has two parts: online structure learning and parameter learning. In structure learning, to improve the training accuracy and speed of the model, the Possibilistic Fuzzy C-Means (PFCM) algorithm is used to process the input data and obtain the number of initial rules before model training. The PFCM algorithm introduces the concept of possibility P to Fuzzy C-Means (FCM), allowing PFCM to overcome the shortcomings of FCM that cannot accurately cluster a large number of nonlinear problems. SLIT2FNN can establish an appropriate number of rules in the preparation stage, and then use the firing strength of the antecedents of the rules to judge whether to generate fuzzy rules for online self-learning, thereby optimizing its network structure. Then, the improved Levenberg–Marquardt (ILM) algorithm is used to modify the relevant parameters of SLIT2FNN. The ILM algorithm can address the challenge of numerous parameters in the Jacobian matrix and complex calculations and improve the calculation speed and adaptive ability of SLIT2FNN parameter learning. Finally, SLIT2FNN is applied to the prediction of air quality PM2.5 concentration, and the performance is compared with other models. The experiment proves that SLIT2FNN has a high prediction accuracy and fast convergence.

Long-term measurement and characterization of boundary layer optical turbulence

The United States Naval Academy long-term scintillation measurement campaign was a multi-year effort to characterize optical turbulence in the near-maritime atmospheric boundary layer (ABL). At its core, the field experiment consists of in situ measurements of bulk atmospheric and oceanographic parameters, as well as path-averaged measurements of the refractive index structure parameter, C n 2, collected using a large-aperture scintillometer. The field experiment ran from January 1st, 2020, through September 26th, 2023, representing the most comprehensive collection of optical turbulence measurements in the near-maritime ABL to date. Long-term measurements enable researchers to evaluate existing theory and develop new models applicable to this environment. The present study characterizes some of the physical relationships that affect optical turbulence. This characterization focuses on the relationship between local optical turbulence and select atmospheric and oceanographic parameters. The impact of temperature gradients on the extent of optical turbulence was analyzed, along with its interactions with relative humidity and wind speed. The diurnal and seasonal variations in measured C n 2 were examined, with comparisons drawn against other environments. Further information and the full dataset are publicly available through the optical turbulence benchmark repository [Jellen et al., GitHub, 2023].

Research Status of Deep-Sea Polymetallic Nodule Collection Technology

The bottom of the ocean is rich in mineral resources, and deep-sea mining has been a research hotspot in recent years. As a key part of deep-sea mining operation, polymetallic nodule collection technology has been researched in many countries around the world. The distribution of deep-sea polymetallic nodule mining areas and the characteristics of nodules are summarized, which provides a reference for the study of collection technology and the optimization of pick-up device structure. In order to further establish a deep-sea mining collection technology system, the current development status of polymetallic nodule mechanical, mechanical–hydraulic composite and hydraulic collection technologies are summarized, and the analysis shows that hydraulic collection technology has a more promising commercialization prospect. For the hydraulic collection technology, the research progress of suck-up-based collection technology, Coandă-effect-based collection technology, double-row hydraulic collection sluicing technology and other collection technologies are summarized from three aspects: collecting principle, device structure parameter optimization, and sea trial situation, and the key technical problems of hydraulic ore collection are put forward. Through the comparative analysis of the pick-up efficiency, energy consumption, environmental disturbance and other performances of different devices, it is found that the Coandă-effect-based hydraulic collection technology has better comprehensive performance. A structural design evaluation indicator for the collection head of hydraulic collection technology is proposed, and the prospect of further research on hydraulic collection technology is put forward.

Analysis of the electromagnetic effects on the large floating roof oil tanks by nearby lightning strike based on TLM

Lightning fire is one of the biggest dangers for chemical and petrochemical storage tank farms, particularly in floating roof oil tanks (FROTs). To improve the lightning protection of FROTs, the process of floating roof tanks affected by lightning is analyzed. Lightning inductive effects can result in the undesired operation of the above-ground storage tank equipment and endanger exploitation safety. The time domain finite element analysis based on the transmission line model (TLM) method is regarded as a numerical technique to solve field problems by implementing circuit equivalents. This study aims to analyze lightning strike characteristics using the Heidler current function and simulate electromagnetic field strength (EMFS) distribution and surface current density (SCD). Calculation of minimum possible effective strike distance and shielding effectiveness (SE) is performed. Parametric modeling ensures accurate modeling of the roof's bypass conductor to the shell. By utilizing the Parameter Sweep technique, multiple simulations can be carried out with varying structure parameter values. This approach ensures optimal efficiency and accuracy in the results obtained.

Research on light weight intelligent identification method of coal and gangue

Accurate identification of coal and gangue is essential for clean and efficient use of coal. Existing target detection algorithms are ineffective in detecting small-target and overlapping gangue, and contain complex network structure and large parameter volume, which cannot meet the demand of real-time detection of edge devices. To address the above problems, a lightweight detection and identification approach of coal gangue based on improved YOLOv5s is proposed. The depth-separable convolutions are used to replace ordinary convolutions, and the C3 (Concentrated-Comprehensive Convolution Block) Ghost module is constructed to replace all C3 modules in the YOLOv5s to reduce model computation and parameters. The CA (Coordinate Attention) attention mechanism is introduced to strengthen the attention to the target to be detected, suppress irrelevant background interference, and improve the detection accuracy of the model. The Focal- EIOU (Focal and Efficient Intersection Over Union) loss function was introduced to replace the original CIOU. Extensive experiments substantiated the proposed approach can effectively and quickly detect the small-target and overlapping coal gangue accurately, and the mAP (mean Average Presicion) reaches 97.7%. Compared with the original YOLOv5s, the proposed approach reduces the number of parameters and the amount of computation by 48.5% and 43%, respectively, under the premise of maintaining the same detection accuracy.

Enhancing heat transfer efficiency in corrugated tube heat exchangers: A comprehensive approach through structural optimization and field synergy analysis

In this paper, a precise and efficient method to optimize corrugated tube heat exchangers is proposed by combining computational fluid dynamics simulation with optimization. The optimization of tubular heat exchangers involves contradictory Colburn coefficient j, and the friction coefficient f, so it is a multi-objective optimization problem. The approximate model is obtained by an extreme learning machine, and the structure parameter of the heat exchanger is optimized by the nondominated sorting genetic algorithm-Ⅱ. Compared to the results between the original and optimized tube, the optimized structure Colburn coefficient increased by 5.1 % and the friction coefficient decreased by 9.3 %. Finally, the internal flow field is compared qualitatively from temperature, pressure, and velocity. The optimization effect is further emphasized by using the field synergy theory.

Characterization of Interfacial Corrosion Behavior of Hybrid Laminate EN AW-6082 ∪ CFRP.

The corrosion behavior of a hybrid laminate consisting of laser-structured aluminum EN AW-6082 ∪ carbon fiber-reinforced polymer was investigated. Specimens were corroded in aqueous NaCl electrolyte (0.1 mol/L) over a period of up to 31 days and characterized continuously by means of scanning electron and light microscopy, supplemented by energy dispersive X-ray spectroscopy. Comparative linear sweep voltammetry was employed on the first and seventh day of the corrosion experiment. The influence of different laser morphologies and production process parameters on corrosion behavior was compared. The corrosion reaction mainly arises from the aluminum component and shows distinct differences in long-term corrosion morphology between pure EN AW-6082 and the hybrid laminate. Compared to short-term investigations, a strong influence of galvanic corrosion on the interface is assumed. No distinct influences of different laser structuring and process parameters on the corrosion behavior were detected. Weight measurements suggest a continuous loss of mass attributed to the detachment of corrosion products.

Comparison of the imaginary parts of the atmospheric refractive index structure parameter and aerosol flux based on different measurement methods

Abstract. The complexity of aerosol particle properties and the diversity of characterizations make aerosol vertical transport flux measurements and analysis difficult. Although there are different methods, such as aerosol particle number concentration flux and aerosol mass flux based on the eddy covariance principle as well as aerosol mass flux measurements based on the light-propagated large-aperture scintillation principle, there is a lack of mutual validation among the different methods. In this paper, a comparison of aerosol mass flux measurements based on the eddy covariance principle and aerosol mass flux measurements based on the light-propagated large-aperture scintillation principle is carried out. The key idea of aerosol mass flux measurements based on the light-propagated large-aperture scintillation principle is the determination of the imaginary part of the atmospheric equivalent refractive index structure parameter (AERISP). In this paper, we first compare the AERISPs measured by two different methods and then compare the aerosol mass vertical transport fluxes obtained by different methods. The experiments were conducted on the campus of the University of Science and Technology of China (USTC). A light propagation experiment was carried out between two tall buildings to obtain the imaginary and real parts of the AERISPs for the whole path, which in turn can be used to obtain the aerosol vertical transport flux. An updated visibility meter is installed on the meteorological tower in the middle of the light path, which is utilized to obtain the single-point visibility, which is then converted to the imaginary part of the atmospheric equivalent refractive index (AERI). The imaginary parts of the AERISP were obtained via spectral analysis with visibility data. The results show that the imaginary parts of the AERISPs obtained by different methods are in good agreement. The imaginary part of the AERI measured by the visibility meter and the vertical wind speed obtained by the ultrasonic anemometer were used for covariance calculations to obtain the aerosol vertical transport flux. The trends in aerosol vertical transport fluxes obtained by the different methods are consistent, and there are differences in some details, which may be caused by the inhomogeneity in the vertical transport of aerosol fluxes. The experimental results also showed that urban green land is a sink area for aerosol particles.

An intelligent body frame structure modeling and optimization system based on conceptual design

The conceptual design stage is an indispensable and important stage in the development of the modern body. However, due to the lack of sufficient body structure parameter support, the design defects generated at this time are difficult to make up for in the subsequent design stage. Therefore, it is of great significance to develop a conceptual design software for body structure that integrates design, analysis, and optimization. This paper proposes an intelligent body frame structure modeling and optimization system based on conceptual design, S-iVCD (Intelligent System for Conceptual Design of Vehicle Body Structure). Based on deep learning methods and body design sketches, a conceptual model of body structure is quickly established. Based on the data parameters stored in the Excel table, the system is seamlessly connected to the domestic independent finite element software SIPESC to calculate the simulated working conditions. The body structure optimization module is driven by the MMA (method of moving asymptotes), and takes the body structure performance and total mass as the optimization goals or constraints of the mathematical model to achieve body structure performance improvement and lightweight design.

A proposal for a revision of the phlebographic classification of congenital venous malformations.

Venous malformation (VM) is the most frequent type of congenital vascular malformation. In terms of functional outcome local sclerotherapy remains the most important therapeutic tool. For planning and correct estimation and prevention of complications, an exact anatomical classification of the VM is crucial. Not only the drainage, as assessed in the established classification, but also the phlebographic aspect of the internal VM structure itself plays a decisive role. In order to integrate this aspect, we aim to validate a proposal for a revised phlebographic VM classification distinguishing non-lacunar (a) and lacunar (b) types. We retrospectively analyzed all patients with VM in whom a direct puncture phlebography was performed in our clinic between 2009 and 2018 to assess morphology and flow characteristics. Phlebographic assessment included: (I) differentiation of non-lacunar vs. lacunar type; (II) drainage assignment according to the existing classification; (III) adjusted classification combining both. Inter-reader agreement was measured in percentage as well as by the Cohen's kappa coefficient (κ). Overall 26 patients were classified as non-lacunar (a) and 41 patients as lacunar (b) VM. For this categorization, inter-reader agreement was 96% (κ=0.91). Classical Puig classification into types I, II, III and IV showed 87% inter-reader agreement (κ=0.78). For the adjusted classification adding the non-lacunar or lacunar characteristic to type I-IV an agreement of 82% (κ=0.77) was achieved. Phlebographic differentiation into non-lacunar and lacunar VM is feasible and reliable to distinguish phenotypic subgroups of patients with VM. We therefore propose to integrate this parameter of the internal VM structure into the existing classification.

The impact of thixotropic behavior on microfluidic mixing in a staggered-herringbone mixer

This study numerically explores the influence of thixotropy on flow and mixing in a staggered-herringbone micromixer (SHM), employing a structure-kinetics model to simulate the microstructure formation and breakup in thixotropic fluids. This study represents the first of its kind to incorporate a thixotropic fluid model into microfluidic mixing in channels with patterned grooves. Specifically, we examine the effects of the destruction factor (kd) and the thixotropy number (Th) on microstructure, flow, and mixing in the SHM, covering extensive ranges (0.01≤kd≤10 and 0.01≤Th≤100). Higher values of kd and Th, particularly for kd>1 and Th>1, lead to larger spatial variations of the structure parameter (λ) and viscosity (η), with a notable decrease in λ near the groove tops, leading to the lowest viscosity in these areas. Conversely, at the groove bottoms, where shear deformation is minimal, there is less reduction in λ, leading to increased viscosity and higher flow resistance. The viscosity variations inside the grooves impede lateral flows, adversely affecting mixing in the higher kd and Th regimes. Therefore, an in-depth understanding of the complex thixotropic behaviors, as influenced by kd and Th near the grooves, is essential for achieving effective mixing in the SHM when using thixotropic fluids. Our results suggest that lowering the channel height, for a given groove depth, slightly improves the mixing of thixotropic fluids. Further enhanced mixing is achieved by combining a reduced channel height with double-sided groove patterns.

Modeling the atmospheric refractive index structure parameter using macrometeorological observations

The dynamic fluctuations in the atmospheric refractive index, commonly referred to as optical turbulence, cause phase distortions of the electromagnetic waves propagating through the atmosphere. The consequent scintillations have large implications for free-space optical communication, laser remote sensing, and directed energy applications. The refractive index structure parameter (C n 2), quantifying the strength of these fluctuations, is usually estimated using high-frequency micrometeorological measurements, employing sonic anemometer-thermometers or scintillometers. Despite providing highly accurate information, these systems are immensely complex and costly, especially for frequent field applications and remote locations. In this study, we have developed an empirical multinomial model for estimating C n 2 using three-year macrometeorological data and validated it against collocated and concurrent micrometeorological measurements, from a tropical semi-arid location. This simpler model would be handy for applications in remote locations having weather station measurements alone.

Influences of hygrothermal conditions and structure parameters on moisture diffusion behavior in a system‐in‐package module by moisture-thermal-mechanical-coupled finite element modeling

Purpose This paper aims to investigate the moisture diffusion behavior in a system-in-package module systematically by moisture-thermalmechanical-coupled finite element modeling with different structure parameters under increasingly harsh environment. Design/methodology/approach A finite element model for a system-in-package module was built with moisture-thermal-mechanical-coupled effects to study the subsequences of hygrothermal conditions. Findings It was found in this paper that the moisture diffusion path was mainly dominated by hygrothermal conditions, though structure parameters can affect the moisture distribution. At lower temperatures (30°C~85°C), the direction of moisture diffusion was from the periphery to the center of the module, which was commonly found in simulations and literatures. However, at relatively higher temperatures (125°C~220°C), the diffusion was from printed circuit board (PCB) to EMC due to the concentration gradient from PCB to EMC across the EMC/PCB interface. It was also found that there exists a critical thickness for EMC and PCB during the moisture diffusion. When the thickness of EMC or PCB increased to a certain value, the diffusion of moisture reached a stable state, and the concentration on the die surface in the packaging module hardly changed. A quantified correlation between the moisture diffusion coefficient and the critical thickness was then proposed for structure parameter optimization in the design of system-in-package module. Originality/value The different moisture diffusion behaviors at low and high temperatures have seldom been reported before. This work can facilitate the understanding of moisture diffusion within a package and offer some methods about minimizing its effect by design optimization.

Static and Modal Analysis of a Box Structured Satellite Deployment Mechanism with self-actuated Torsion Joint

A brand-new satellite deployment mechanism with boxed structure and self-actuated torsion joints is proposed and an effective method to verify the feasibility of this mechanism is established in this paper. This mechanism has the characteristics of high base frequency, high ratio of deployed and folded space occupation ratio. In order to meet the design requirements, the related analysis and optimization need to be conducted, and several conclusions are obtained. Firstly, the modal analysis of deployment mechanism at folded and fully deployed state is analyzed, and the result showed that the proper wall thickness is the key parameter to satisfy the design requirement and an optimized value could be obtained; Secondly, the heat deformation analysis result showed that the material plays an more important roll on affecting the thermal deformation than structure parameter; Thirdly, Under the torsional moment of the joints, the stress distribution of the deployment mechanism under different folding angle is investigated, it could be clearly found that the maximum stress is always located on the bonded area of the rod and joint, and the maximum stress is increased with the opening angle generally. By combined analysis including thermal, static, and modal, the related characteristics are obtained which could be used for structure optimization and provide an effective solution for the design of box structured satellite unfolding mechanism with self-actuated torsional joints.

Reliability Analysis and Risk Assessment for Settlement of Cohesive Soil Layer Induced by Undercrossing Tunnel Excavation

Due to the complex urban geological environment and physicochemical interactions, the physical and mechanical parameters of the cohesive soil layer in the adjacent construction area show strong spatial variability and correlation. In addition, the actual exploration and test data are very limited because of limited technical and economic conditions. This severely restricts the ability to evaluate the stability of adjacent structures and to prevent and control instability disasters during subway construction. In this study, a generation method of limited sample data for the cohesive soil layer in the adjacent construction area is proposed. The spatial variability and correlation of uncertain mechanical parameters for the clay layer are quantified using incomplete probability data. A calculation method of uncertain settlement for the cohesive soil layer in the adjacent construction area is developed. The distribution fitting tests of settlement characteristics are conducted with different joint distribution functions and correlation structure. A reliability analysis and risk assessment methodology for the settlement of the cohesive soil layer is presented. The reliability value and failure probability induced by undercrossing tunnel excavation are analyzed and predicted. The results show that the bootstrap simulated sampling and random field method can quantify the cohesive soil layer heterogeneity reasonably under limited investigation data. Different joint distribution and correlation structure functions have different effects on the distribution fitting test. The uncertain settlement of the upper center of the tunnel is the largest, and the failure disaster is most likely to occur. The effects of a copula structure and correlation parameter on the failure probability of the cohesive soil layer are sensitive. This research can provide scientific support for public safety and sustainable development in urban subway construction.