Iterative Analysis Method Research Articles

Design and application of a prefabricated structure for large-span arch open-cut highway tunnels

To enhance construction efficiency, improve lining quality, and reduce project costs, this study proposes a prefabricated arch structure scheme for large-span open-cut highway tunnels, specifically targeting the ongoing construction of an eight-lane open-cut tunnel on Chongqing’s Xinsen Avenue. By establishing a finite element “load-structure” integrated calculation model and adopting an iterative analysis method, the impact of joint stiffness variations on internal force distribution was determined. Combined with long-term field monitoring and measurements, a thorough analysis was conducted on the performance of the prefabricated arch structure during different construction stages. The results indicate that after assembly into a ring, the structure undergoes a self-adaptive adjustment phase, during which the joints experience significant stress and deformation. Following top-layer backfilling and water level restoration, the axial force on the joints increases, while stress and deformation decrease, exerting a positive effect on the joint bearing capacity. From the construction period to post-opening operations, the stress variation experienced by the joints remains within a controllable range, demonstrating substantial safety margins. This fully validates the safety and reliability of the prefabricated arch structure scheme.

Research on factors that activate university students’ research work using the iterative examination process

Introduction. Many issues related to the activation of research work of university students remain insufficiently studied and are an urgent problem of higher professional education. Aim. The present research aimed to identify the main factors influencing the processes of activating students’ research work and to develop recommendations for increasing the activity of students’ participation in this activity. Methodology and research methods. The authors used iterative examination, analysis, comparison, synthesis, and systematisation methods to analyse the results obtained through empirical methods such as questionnaires and sociological surveys. Data collection was conducted through an online survey using the Google Forms Internet service and offline surveys at 16 universities in the Republic of Kazakhstan and the Russian Federation in 2023. A total of 351 scientific experts participated in the survey. The survey results were processed using the IBM SPSS statistical package. Results and scientific novelty. It has been established that a significant contribution to attracting students to research activities is made by the expansion of the use of information technologies in the research process and a system of incentives aimed at increasing the importance of students’ research work in the educational process. The scientific novelty lies in identifying and systematising the main factors that influence the activation of students’ research work in the learning process through the iterative examination process. Practical significance. The results of the conducted research can be used in the practical research work of university students.

An Efficient Iterative Method for Vehicle-Track Nonlinear Coupled Dynamic Analysis Based on Explicit and Implicit Algorithms

An Efficient Iterative Method for Vehicle-Track Nonlinear Coupled Dynamic Analysis Based on Explicit and Implicit Algorithms

Design of an Iterative Method for Crop Disease Analysis Incorporating Graph Attention with Spatial-Temporal Learning and Deep Q-Networks

Design of an Iterative Method for Crop Disease Analysis Incorporating Graph Attention with Spatial-Temporal Learning and Deep Q-Networks

A finite difference method on crack resistance of reinforced glass beam with non-linear adhesive

Reinforced glass beam (RG beam) is a type of structural glass member that has been developed in recent years. This RG beam consists of a glass beam to which reinforcement material, such as steel, is adhesively attached in the tensile side to improve crack resistance. The adhesive plays a critical role in the structural performance of RG beam. However, the effect of non-linear shear-slip behavior of the adhesive layer remains unclear and has been neglected in most previous studies, which can result in inaccurate estimations. To address this issue, this paper presents a finite difference model (FDM) that utilizes an explicit step-by-step method and trial-and-error iterative method for interfacial stress analysis. The model predicts the static structural response of a simply-supported RG beam that simulates the adhesive with non-linear stress-slip behavior. Furthermore, the model describes the adherend’s shear deformation in elastic. The FDM results are then compared with the finite element method (FEM), adopting discrete nonlinear connectors (springs) to simulate the adhesion, and available analytical methods. Detailed parametric studies are further conducted to investigate the influences of glass strength, load pattern, reinforcement ratio and height-to-span ratio for proposing design recommendations.

A Simple Iterative Method for Dynamic Analysis of MDOF Systems with Arbitrary Time-Varying Coefficients Based on Successive Differentiation

A Simple Iterative Method for Dynamic Analysis of MDOF Systems with Arbitrary Time-Varying Coefficients Based on Successive Differentiation

Numerical simulation of fluid-thermal-structural coupling characteristics of stratospheric non-rigid airship

The voluminous stratospheric non-rigid airship is very sensitive to the external thermal environment. The temperature change of internal gas caused by the variation in the external thermal environment and wind speed will lead to a change in the shape and buoyancy of the airship, thereby affecting its flight control. The traditional static analysis method is difficult to accurately reflect this fluid-thermal-structural coupling process. In this paper, the iterative analysis method was established for the fluid-thermal-structural coupling effect of stratospheric non-rigid airship based on the models of fluid, thermal, and structural deformation. Considering the load such as the internal thermal effect and external flow field of the airship, the simulation of the thermo-induced structural deformation effect was conducted using Fluent and Abaqus software. The influence of local time and external wind speed on the structural deformation, volume, and equilibrium altitude of the airship was analyzed. The results demonstrate that, at low wind speed, the influence of aerodynamic pressure on the deformation of the airship is negligible. However, a great amount of heat is carried away by the wind, then the structural deformation caused by internal and external pressure difference is alleviated and the equilibrium altitude of the airship change obviously. This can serve as a guideline for the design and flight test of the long-endurance stratospheric non-rigid airship.

Variational–hemivariational system for contaminant convection–reaction–diffusion model of recovered fracturing fluid

Abstract This work is devoted to study the convection–reaction–diffusion behavior of contaminant in the recovered fracturing fluid which flows in the wellbore from shale gas reservoir. First, we apply various constitutive laws for generalized non-Newtonian fluids, diffusion principles, and friction relations to formulate the recovered fracturing fluid model. The latter is a partial differential system composed of a nonlinear and nonsmooth stationary incompressible Navier-Stokes equation with a multivalued friction boundary condition, and a nonlinear convection–reaction–diffusion equation with mixed Neumann boundary conditions. Then, we provide the weak formulation of the fluid model which is a hemivariational inequality driven by a nonlinear variational equation. We establish existence of solutions to the recovered fracturing fluid model via a surjectivity theorem for multivalued operators combined with an alternative iterative method and elements of nonsmooth analysis.

Public Attitudes Towards Vaccine Passports in Alberta During the "Pandemic of the Unvaccinated": A Qualitative Analysis of Reddit Posts.

Objective: The goal of this study is to understand the attitudes and beliefs towards mandatory vaccination policies in Alberta, Canada in September 2021, during the fourth wave of COVID-19. Methods: 9400 posts between 1st September and 30th September 2021 were collected from the subreddit r/Alberta with Pushshift.io. Posts and comments were manually screened to determine their relevance to research objectives, and then coded using inductive coding and iterative qualitative analysis methods. Results: Inductive coding methods yielded five key themes: 1) opinions related to autonomy and consent, 2) concerns about COVID-19 vaccine passport enforcement, 3) concerns about government, 4) concerns about the logistics of passports, and 5) opinions relating to the necessity of passports to prevent lockdowns. Conclusion: Overall, the data presented favorable opinions towards an Albertan vaccine passport within r/Alberta. Anti-vaccine and anti-mandate opinions were often less extreme than those present in the literature, although this may be due to r/Alberta subreddit moderators removing those more extreme comments. Most reservations were due to issues of bodily autonomy, though concerns about the government and logistics also played a meaningful role.

Quantification of polycyclic aromatic hydrocarbons in roasted Tan lamb using fluorescence hyperspectral imaging technology

Polycyclic aromatic hydrocarbons (PAHs) are one of the main harmful substances produced during the roasting of lamb. In this study, fluorescence hyperspectral imaging (FHSI) at different excitation wavelengths was used for the rapid determination of total PAHs (T-PAHs) content in roasted Tan lamb. Heterogeneous two-dimensional correlation spectroscopy (H2D-COS) was performed to resolve the fluorescence hyperspectral peaks. Competitive adaptive reweighed sampling (CARS), uninformative variable elimination (UVE), variable combination population analysis (VCPA), iterative retained information variable (IRIV) and interval variable iterative spatial shrinkage analysis (iVISSA) methods were employed to extract effective wavelengths to reduce data dimensionality. Partial least squares regression (PLSR), least squares support vector machine (LS-SVM) and convolutional neural network (CNN) algorithms were used to develop the T-PAHs content prediction model. For the FHSI at 357 nm excitation wavelength, the Smoothing-CARS-PLSR quantitative prediction model worked the best, with RC2 and RP2 reaching 0.9011 and 0.9169, and RMSEC and RMSEP reaching 0.0179 mg/kg and 0.0181 mg/kg, respectively. For the FHSI at 452 nm excitation wavelength, Smoothing-VCPA-CNN showed the best results, with RC2 and RP2 of 0.9199 and 0.9189, and RMSEC and RMSEP reaching 0.0175 mg/kg and 0.0171 mg/kg, respectively. This study provided a reference for the quantitative detection of PAHs.

A combined iterative complex eigenvalue method and finite element-boundary element method for acoustic analysis of the railway steel bridge deck damped with constrained layer damping

This paper presents a combined method to predict structure-borne noise from the railway steel bridge deck damped with constrained layer damping (CLD), in which the frequency-dependent properties of the viscoelastic material are accurately considered through the iterative complex eigenvalue method (ICEM). Then, a 1:4 steel bridge deck model is designed and manufactured, and a series of hammer tests of the CLD-damped steel bridge deck are carried out in a semi-anechoic chamber to verify the proposed method. Then, the noise reduction effect of CLD is discussed in detail. It shows that the overall SPLs at the near field point S-3 and the far field point S-8 are reduced by 7.5 dB and 11.1 dB, respectively, and the noise attenuation rate along with distance is also improved significantly after damped with CLD. Finally, the influences of the key design parameters of CLD on noise reduction are quantitatively analyzed, so as to provide reference for the research and application of CLD in railway bridge engineering.

THE GREEN-RVACHOV QUASI-FUNCTION METHOD IN THE NUMERICAL ANALYSIS OF MICROELECTROMECHANICAL SYSTEMS USING TWO-SIDED APPROXIMATIONS

The work is devoted to developing a bilateral iterative method of numerical analysis of one electrostatic microelectromechanical system based on the use of the Green – Rvachev quasi-function. Microelectromechanical systems are miniature devices that combine electronic and mechanical components of micron size. Electrostatically activated microelectromechanical systems have certain disadvantages that limit the range of their operation. One of these is the pull-in instability of the functional components of the system, which occurs if the applied voltage difference is above a particular critical value. The mathematical model of the system under consideration in the work is a semi-linear elliptic equation with the Laplace operator and the Dirichlet condition. To construct an approximate solution of the problem, it is proposed to use the methods of nonlinear analysis in semi-ordered spaces, particularly the results of V. I. Opoitsev on the solvability of nonlinear operator equations with a heterotonic operator. The boundary value problem simulating the most straightforward microelectromechanical system under the action of external pressure is reduced to the Urison integral equation using the Green – Rvachev quasi-function method, which makes it possible to expand the application of the method of two-sided approximations for problems in areas of somewhat arbitrary geometry. The paper substantiates the possibility of constructing iterative sequences with two-sided convergence to a positive solution of the problem: the computational scheme is given, the conditions for its convergence to the desired solution are obtained, and the a posteriori error estimate is derived. The method is illustrated by a computational experiment for a problem considered in a rectangular area. The computational experiment results are presented in the form of the surface and lines of the level of the approximate solution, and the two-sided nature of the convergence of the proposed method is also graphically illustrated.

Understanding Breast Cancer Disparities Affecting Black Women: Obtaining Diverse Perspectives Through Focus Groups Comprised of Patients, Providers, and Others.

Black women have the highest death rate from breast cancer and a higher chance of developing breast cancer before the age of 40 than White women. Mammography screening is recommended for early detection which has led to decreased mortality and improved survival. Unfortunately, Black women are less likely to have breast cancer screenings. Environmental justice communities represent place-based structural disparity/racism leading to health inequality. Environmental justice specifically addresses situations where minority or low-income communities bear disproportionately poor human health outcomes and environmental risks. The purpose of this qualitative study was to gain a deep understanding of breast cancer screening disparity from multiple perspectives to enable collective solutions to barriers faced by Black women in an environmental justice community. Data were collected from 22 participants using a focus group approach from Black women with breast cancer (n = 5) and without it (n = 5), healthcare providers (n = 6), and community leaders (n = 6). An iterative and inductive thematic data analysis method was used to analyze data. The themes that emerged from the data included: (1) misconceptions and fear of mammograms; (2) breast cancer screening beyond mammograms; and (3) barriers beyond mammograms. These themes reflected personal, community, and policy barriers leading to breast cancer screening disparity. This study was an initial step to develop multi-level interventions targeting the personal, community, and policy barriers that are needed to advance breast cancer screening equity for Black women living in environmental justice communities.

An interval iterative method for response bounds analysis of structures with spatially uncertain parameters

Parameters with spatial uncertainties are very common in practical engineering, which could have a significant effect on structural performances. Different from the framework of probability theory, the interval field model describes the spatial uncertainty with upper and lower bounds rather than the probability distribution function or other statistical characteristics. By introducing the interval field model into finite element analysis and solving the resulting interval finite element equilibrium equation, the upper and lower bounds of structural responses can then be obtained. This paper proposes an interval iterative method for static displacement response analysis of structures with spatial uncertainties, effectively improving the overestimation existing in traditional interval analysis due to dependency problems and obtaining a compact interval envelope of the exact response bounds. Firstly, the spatially uncertain parameters described by the interval field are represented by the interval Karhunen–Loève (K-L) expansion, based on which the interval finite element equilibrium equation is formulated. Secondly, the interval finite element problem is decomposed into several subproblems, and an interval iterative method is developed for an envelope solution of the structural response bounds. Finally, the accuracy and efficiency of the proposed method are verified by several numerical examples.

Study on a Novel Hybrid Thermal Network of Homopolar Inductor Machine

The thermal analysis is necessary for the design and safe operation of the homopolar inductor machine (HIM) applied in the flywheel energy storage system (FESS). However, due to its unique three-dimensional (3-D) structure, the thermal analysis of HIM relies on the 3-D finite element analysis (FEA) or computational fluid dynamics (CFD), which is time-consuming and computationally inefficient. To facilitate the thermal analysis and design of HIM, a fast and accurate analytical model is essential. In this article, the novel 2-D and 3-D hybrid thermal networks combined with a coupled iterative analysis method are proposed to predict the temperature of HIM. First, the structure, operation principle, and material properties of HIM are illustrated. Second, the heat sources of HIM, including iron loss, rotor eddy current loss, rotor air friction loss, copper loss, and bearing loss, are fully analyzed and investigated. Third, the proposed hybrid thermal model (HTM) and coupled iterative analysis method are demonstrated and applied to predict its temperature. The proposed thermal model and analysis methods are explained in detail. The influences of different speeds and operation conditions on the temperature rise of HIM are analyzed based on the proposed thermal model and FEA. Finally, the temperature of an HIM prototype is tested, which proves the accuracy of FEA and the proposed method. The proposed HTM can quickly and accurately predict the temperature of HIM, which provides a new idea for the temperature prediction of this kind of machine.

An Efficient High-to-Low Iterative Method for Light Water Reactor Analysis Based on NEAMS Tools

The so-called two-step method involving the consecutive lattice physics and core simulation has been successfully and widely used in large-scale nuclear reactor calculations thanks to its superior computational efficiency and a satisfactory level of accuracy. However, its performance is challenged by the ever-increasing level of heterogeneity in core designs due to the use of infinite lattice approximation in the lattice calculation and its inability to update cross-section sets according to the core environment change. This paper introduces an alternative approach for light water reactor steady-state core analysis. During the core calculation process, iterations between the local lattice transport calculation and the global core nodal calculation are conducted. These iterations continuously update the boundary condition applied to the lattice model and generate updated cross-section sets. This is done through the iteration between the local lattice transport calculation and the global core nodal simulation. The neutronics high-to-low (Hi2Lo) scheme was formulated using Nuclear Energy Advanced Modeling and Simulation or NEAMS codes, in particular, with the modified PROTEUS-MOC and PROTEUS-NODAL serving as the transport lattice solver and full-core nodal solver, respectively. The verification of the implemented Hi2Lo iterative scheme on the two-dimensional C5G7-TD benchmark problem shows that the Hi2Lo scheme outperforms the two-step approach in terms of prediction accuracy for the key responses of interest (e.g., the system eigenvalue and power distribution) at a computational cost lower than that of the direct full-core transport calculation. To further improve its efficiency, an acceleration method has been developed and implemented for the Hi2Lo approach, and the results indicate that the acceleration method can significantly reduce the run time of a full-core transport solution by a factor of 14 while generating solutions with comparable accuracy.

Improved Estimation of O-B Bias and Standard Deviation by an RFI Restoration Method for AMSR-2 C-Band Observations over North America

Spaceborne microwave radiometer observations play vital roles in surface parameter retrievals and data assimilation, but widespread radio-frequency interference (RFI) signals in the C-band channel result in a lack of valuable data over large areas. Establishing repaired data based on existing observation information is crucial. In this study, Advanced Microwave Scanning Radiometer (AMSR)-2 C-band data affected by RFI were accurately repaired through the iterative principal component analysis (PCA) method in 2016 over the U.S. land area. The standard deviation (STD) and bias characteristics of the brightness temperature in the C-band vertical polarization channel were compared and analyzed before and after the restoration to verify the assimilation application prospect of the repaired data. Not only was the spatial continuity of the microwave imager observations significantly improved following restoration; the STD and bias of the observation minus background (OMB) of the restored data were basically consistent with those of the RFI-free data. The STD of OMB exhibited obvious seasonal variations, which were approximately 4.0 K from January to May and 3.0 K from June to December, whereas the biases were near zero in winter but negative (approximately −2.0 K) in summer. The surface type and terrain height also critically affected the STD and bias. The STD decreased with increasing terrain height, whereas the bias exhibited the opposite trend. The STD was largest in low-vegetation areas (4.0 K) but only approximately 2.0–3.0 K in pine forest and brush areas. These results show that the restored data have a high prospect for retrieval application and assimilation, and the STD and bias estimation results also provide a reference for land-based AMSR-2 data assimilation.

Effect of Radio Frequency Interference-Contaminated AMSR2 Signal Restoration on Soil Moisture Retrieval

Soil moisture is a key variable of the climate system. Microwave remote sensing has become an essential means of obtaining soil moisture because of the unique advantages of its all-day and all-weather observation capability. Theoretically, low-frequency C-band observations are highly suitable for soil moisture retrieval because of their high sensitivity to soil moisture at vegetation roots. However, the quality of C-band observations suffers from radio frequency interference (RFI) over the United States. This paper used the iterative principal component analysis (PCA) method to repair RFI-contaminated second-generation Advanced Microwave Scanning Radiometer (AMSR-2) C-band observations, and the results of soil moisture retrieval based on restored data were evaluated. It was found that RFI could lead to nonconvergence in the retrieval of a large amount of data, and the application of repaired data in retrieval could result in the recovery of more than 80% of nonconvergent data, especially in spring and autumn. The retrieval results based on restored data attained a satisfactory correlation with ERA5 reanalysis data and European Space Agency Climate Change Initiative (ESA-CCI) soil moisture data and suitably agreed with precipitation observation data. Soil moisture generally exhibited a gradual increase from west to north and east. This feature was weakened due to the influence of monsoons in the east in summer. The western side of the Cascade Mountains is the wettest area of the United States, with soil moisture exceeding 0.4 m3 m−3. The driest region of the United States is located between the Rockies and Cordillera Mountains, and the soil moisture value is lower than 0.1 m3 m−3.

Improving estimation of urban land cover fractions with rigorous spatial endmember modeling

The spatial information has been widely utilized in Spectral Mixture Analysis (SMA) studies over the years. However, the spatial autocorrelation, as a prerequisite of these studies, was seldomly examined. In the complex urban systems, it remains largely unknown whether and how land cover spectra at different locations are spatially autocorrelated and to which extent spatial autocorrelation can explain the great spectral variability. This study proposed an SMA method with Spatial Endmember Modeling (SEMSMA) to improve the fraction estimation of major urban land cover types. SEMSMA used the Incremental Spatial Autocorrelation (ISA) analysis to quantify spatial autocorrelation patterns in broadband reflectance. With the patterns, SEMSMA predicted endmember signatures that incorporated both spatial (location-oriented) and non-spatial spectral variability via the Restricted Maximum Likelihood-Empirical Best Linear Unbiased Predictor (REML-EBLUP) and Monte Carlo sampling. The spectral variabilities were then addressed in pixel unmixing by an iterative mixture analysis method. Results of ISA demonstrated diverse spatial autocorrelation patterns in reflectance of urban land covers. These patterns can be related to the pathways that spatial processes acted on land cover properties. The predicted endmember signatures explained most of the spectral variability for all land cover types. Subpixel fraction estimates showed that SEMSMA outperformed multiple endmember SMA (MESMA) and spatially adaptive SMA (SASMA), based on the root mean square error (0.04–0.15), the mean absolute error (0.01–0.09), and the Systematic Error (SE) (−80.00–0.01). The low SE of SEMSMA revealed unbiased estimation of land cover fractions. Results of this study underscored the necessity of spatial autocorrelation examination and the advantage of rigorous spatial endmember modeling when incorporating spatial information into SMA.

An iterative interval analysis method based on Kriging-HDMR for uncertainty problems

An iterative interval analysis method based on Kriging-HDMR for uncertainty problems