Modularized and Parametric Modeling Technology for Finite Element Simulations of Underground Engineering under Complicated Geological Conditions

The surrounding geological conditions and supporting structures of underground engineering are often updated during construction,and these updates require repeated numerical modeling.To improve the numerical modeling efficiency of underground engineering,a modularized and parametric modeling cloud server is developed by using Python codes.The basic framework of the cloud server is as follows:input the modeling parameters into the web platform,implement Rhino software and FLAC3D software to model and run simulations in the cloud server,and return the simulation results to the web platform.The modeling program can automatically generate instructions that can run the modeling process in Rhino based on the input modeling parameters.The main modules of the modeling program include modeling the 3D geological structures,the underground engineering structures,and the supporting structures as well as meshing the geometric models.In particular,various cross-sections of underground caverns are crafted as parametricmodules in themodeling program.Themodularized and parametric modeling program is used for a finite element simulation of the underground powerhouse of the Shuangjiangkou Hydropower Station.This complicatedmodel is rapidly generated for the simulation,and the simulation results are reasonable.Thus,this modularized and parametric modeling program is applicable for three-dimensional finite element simulations and analyses.

Research on Urban Building Parametric Modelling Method Based on CityEngine

With the advancement of technology and the development of cities,urban planning and management methods are also constantly improving.From paper-based assignments to modern digitization,new technologies have enabled more efficient design and management for cities.3D modeling can used to simulate the urban environment,which can assist in urban planning and management.However,large-scale modeling cannot be achieved through existing modeling methods,and there are still some shortcomings in the maintenance of the model.Therefore,this article proposes a Computer Generated Architecture(CGA)parametric 3D modeling method based on CityEngine.Research on expanding and customizing modeling rules to create indoor and outdoor modeling rule templates for buildings and methods for generating urban 3D models have been carried out.The results have shown that the completed model can be displayed on different platforms thanks to parameterized modeling.The model can be modified easily and directly applied to the analysis and decision-making of urban planning schemes.

Comparisons of three data storage models in parametric temporal databases

The parametric temporal data model captures a real world entity in a single tuple, which reduces query language complexity. Such a data model, however, is difficult to be implemented on top of conventional databases because of its unfixed attribute sizes. XML is a matured technology and can be an elegant solution for such challenge. Representing data in XML trigger a question about storage efficiency. The goal of this work is to provide a straightforward answer to such a question. To this end, we compare three different storage models for the parametric temporal data model and show that XML is not worse than any other approaches. Furthermore, XML outperforms the other storages under certain conditions. Therefore, our simulation results provide a positive indication that the myth about XML is not true in the parametric temporal data model.

Derivation of Parametric Tropical Cyclone Models for Storm Surge Modeling

In this paper, the parametric tropical cyclone models for storm surge modeling are further developed. Instead of tangential wind speed via cyclostrophic balance and radial wind speed using a simple formulation of defection angle, the analyrical expressions of tangential and radial wind speed distribution are derived from the governing momentum equations based on the general symmetric pressure distribution of Holland and Fujita. The radius of the maximum wind is estimated by tropical cyclone wind structure which is characterized by the radial extent of special wind speed. The shape parameter in the pressure model is estimated by the data of several tropical cyclones that occurred in the East China Sea. Finally, the Fred cyclone （typhoon 199417） is calculated, and comparisons of the measured and calculated air pressures and wind speed are presented.

Two parametric tropical cyclone models for storm surge modeling

In this paper,the two parametric tropical cyclone models for storm surge modeling are further developed.The analytical expressions of tangential and radial velocity distribution are derived from the governing momentum equations,based on the general symmetric pressure distribution proposed by Holland and Fujita.On the basis of the data of several tropical cyclones that occurred in East China Ocean,the shape parameter in pressure model is estimated.Finally,the Fred cyclone(typhoon 199417)is calculated,and comparisons of measured and calculated air pressures and wind speed are presented.

Impact of cancer diagnosis on life expectancy by area-level socioeconomic groups in New South Wales, Australia: a population-based study

Objective: Improvement in cancer survival over recent decades has not been accompanied by a narrowing of socioeconomic disparities. This study aimed to quantify the loss of life expectancy(LOLE) resulting from a cancer diagnosis and examine disparities in LOLE based on area-level socioeconomic status(SES).Methods: Data were collected for all people between 50 and 89 years of age who were diagnosed with cancer, registered in the NSW Cancer Registry between 2001 and 2019, and underwent mortality follow-up evaluations until December 2020. Flexible parametric survival models were fitted to estimate the LOLE by gender and area-level SES for 12 common cancers.Results: Of 422,680 people with cancer, 24% and 18% lived in the most and least disadvantaged areas, respectively. Patients from the most disadvantaged areas had a significantly greater average LOLE than patients from the least disadvantaged areas for cancers with high survival rates, including prostate [2.9 years(95% CI: 2.5±3.2 years) vs. 1.6 years(95% CI: 1.3±1.9 years)] and breast cancer [1.6 years(95% CI: 1.4±1.8 years) vs. 1.2 years(95% CI: 1.0±1.4 years)]. The highest average LOLE occurred in males residing in the most disadvantaged areas with pancreatic [16.5 years(95% CI: 16.1±16.8 years) vs. 16.2 years(95% CI: 15.7±16.7 years)] and liver cancer [15.5 years(95% CI: 15.0±16.0 years) vs. 14.7 years(95% CI: 14.0±15.5 years)]. Females residing in the least disadvantaged areas with thyroid cancer [0.9 years(95% CI: 0.4±1.4 years) vs. 0.6 years(95% CI: 0.2±1.0 years)] or melanoma [0.9 years(95% CI: 0.8±1.1 years) vs. 0.7 years(95% CI: 0.5±0.8 years)] had the lowest average LOLE.Conclusions: Patients from the most disadvantaged areas had the highest LOLE with SES-based differences greatest for patients diagnosed with cancer at an early stage or cancers with higher survival rates, suggesting the need to prioritise early detection and reduce treatment-related barriers and survivorship challenges to improve life expectancy.

Multi-Objective Optimization of Aluminum Alloy Electric Bus Frame Connectors for Enhanced Durability

The widespread adoption of aluminumalloy electric buses,known for their energy efficiency and eco-friendliness,faces a challenge due to the aluminum frame’s susceptibility to deformation compared to steel.This issue is further exacerbated by the stringent requirements imposed by the flammability and explosiveness of batteries,necessitating robust frame protection.Our study aims to optimize the connectors of aluminum alloy bus frames,emphasizing durability,energy efficiency,and safety.This research delves into Multi-Objective Coordinated Optimization(MCO)techniques for lightweight design in aluminum alloy bus body connectors.Our goal is to enhance lightweighting,reinforce energy absorption,and improve deformation resistance in connector components.Three typical aluminum alloy connectors were selected and a design optimization platform was built for their MCO using a variety of software and methods.Firstly,through three-point bending experiments and finite element analysis on three types of connector components,we identified optimized design parameters based on deformation patterns.Then,employing Optimal Latin hypercube design(OLHD),parametric modeling,and neural network approximation,we developed high-precision approximate models for the design parameters of each connector component,targeting energy absorption,mass,and logarithmic strain.Lastly,utilizing the Archive-based Micro Genetic Algorithm(AMGA),Multi-Objective Particle Swarm Optimization(MOPSO),and Non-dominated SortingGenetic Algorithm(NSGA2),we explored optimized design solutions for these joint components.Subsequently,we simulated joint assembly buckling during bus rollover crash scenarios to verify and analyze the optimized solutions in three-point bending simulations.Each joint component showcased a remarkable 30%–40%mass reduction while boosting energy absorption.Our design optimization method exhibits high efficiency and costeffectiveness.Leveraging contemporary automation technology,the design optimization platform developed in this study is poised to facilitate intelligent optimization of lightweight metal components in future applications.

Measuring Causal Effect with ARDL-BART: A Macroeconomic Application

Modeling dynamic systems with linear parametric models usually suffer limitation which affects forecasting performance and policy implications. This paper advances a non-parametric autoregressive distributed lag model that employs a Bayesian additive regression tree (BART). The performance of the BART model is compared with selection models like Lasso, Elastic Net, and Bayesian networks in simulation experiments with linear and non-linear data generating processes (DGP), and on US macroeconomic time series data. The results show that the BART model is quite competitive against the linear parametric methods when the DGP is linear, and outperforms the competing methods when the DGP is non-linear. The empirical results suggest that the BART estimators are generally more efficient than the traditional linear methods when modeling and forecasting macroeconomic time series.

The Key Path of the Shape Optimization Design of Isotropic Material Pressure Vessels

An optimization design was conducted for the shape of the pressure vessel with a thin-shell shell. During this process, the optimization calculation was performed with the aid of the genetic algorithm toolbox included in Matlab. Firstly, through the parametric modeling function of APDL, models such as arc-shaped, parabolic, elliptical, and those generated by the fitting curve command were successfully constructed. Meanwhile, the relevant settings of material properties were accomplished, and the static analysis was conducted. Secondly, the optimization calculation process was initiated using the genetic algorithm toolbox in Matlab. Eventually, through analysis and judgment, the model generated by the fitting curve command was relatively superior within the category of the best shape.

Exploration on the Optimization Strategy for the Layup of Composite Material Pressure Vessels Based on Advanced Algorithms

This study aims to explore the influence of the laying angle on the pressure shell structure made of composite materials under the condition of a fixed shape. By using a composite material composed of a mixture of T800 carbon fiber and AG80 epoxy resin to design pressure vessels, this material combination can significantly improve the interlaminar shear strength and heat resistance. The article elaborates on the basic concepts and failure criteria of composite materials, such as the maximum stress criterion, the maximum strain criterion, the Tsai-Hill criterion, etc. With the help of the APDL parametric modeling language, the arc-shaped, parabolic, elliptical, and fitting curve-shaped pressure vessel models are accurately constructed, and the material property settings and mesh division are completed. Subsequently, APDL is used for static analysis, and the genetic algorithm toolbox built into Matlab is combined to carry out optimization calculations to determine the optimal laying angle. The research results show that the equivalent stress corresponding to the optimal laying angle of the arc-shaped pressure vessel is 5.3685e+08 Pa, the elliptical one is 5.1969e+08 Pa, the parabolic one is 5.8692e+08 Pa, and the fitting curve-shaped one is 5.36862e+08 Pa. Among them, the stress distribution of the fitting curve-shaped pressure vessel is relatively more uniform, with a deformation of 0.568E−03 m, a minimum equivalent stress value of 0.261E+09 Pa, a maximum equivalent stress value of 0.537E+09 Pa, and a ratio of 0.48, which conforms to the equivalent stress criterion. In addition, the fitting curve of this model can adapt to various models and has higher practical value. However, the stress distribution of the elliptical and parabolic pressure vessels is uneven, and their applicability is poor. In the future, further exploration can be conducted on the application of the fitting curve model in composite materials to optimize the design of pressure vessels. This study provides important theoretical support and practical guidance for the design of composite material pressure vessels.

Using fuzzy-AHP and parametric technique to assess soil fertility status in Northeast of Iran

A good understanding of the levels and distribution patterns of soil properties and/or quality indicators is a prerequisite for developing sustainable agricultural land management programs. Traditional assessments of these parameters of soil fertility status are somewhat costly, in both economics and time aspects. Different modelling techniques have been proposed as a useful tool for determination of soil quality indicators and development of soil fertility maps, but to what extent these results are reliable remains under-quantified in many regions worldwide. To address this uncertainty, Fuzzy-Analytical Hierarchy Process(Fuzzy-AHP) and Parametric analyses were conducted to ascertain the soil fertility status of a semiarid region in the Northeast of Iran for some selected crops: alfalfa, corn silage, potato, sugar beet, tomato and wheat. The Fuzzy-AHP and Parametric techniques using soil suitability indices were estimated for each crop and each soil delineation was achieved by Ordinary Kriging. The Technique for Order of Preference by Similarity to Ideal Solution(TOPSIS) was used as a compensatory method to allow tradeoffs among the selected criteria. Our results demonstrated that from the Fuzzy-AHP analysis, the soil fertility indices ranged from moderate to high for production of alfalfa;from low to high for production of corn silage and sugar beet;moderate to high for production of potato and tomato;and from low to moderate for production of wheat. However, the parametric analysis showed soil fertility classes ranging from very low to high for production of all the selected crops. High correlations were also observed between soil fertility indices predicted by both models. Similarly, the capacities of both models to predict soil fertility status for production of the selected crops were also highly correlated. The preference for the cultivation of the selected crops based on the Fuzzy-AHP analysis was sugar beet > corn silage > wheat > alfalfa > tomato > potato. On the other hand, using Parametric techniques, the crops preferences for cultivation ranked as corn silage > wheat > alfalfa > sugar beet > tomato > potato. We concluded that the findings would help to develop sustainable plans of cultivation based on patterns related to soil fertility classes depending on each crop’s requirement.

Parametric Modeling System for Cooling Turbine Blade Based on Feature Design

Based on feature modeling and mathematical analysis methods,a process-oriented and modular parametric design system for advanced turbine cooling blade is developed with UG API,aiming at the structural complexity and high design difficulty of aero-engine cooling turbine blade.The relationship between the external and internal body features,the body attached feature is analyzed as viewed from the feature and parameter terms.The parametric design processes and design examples of the external body shape,tenon,platform and internal body shape,ribs,pin fins are introduced.The system improves the design efficiency of cooling turbine blade and establishes the foundation of multidisciplinary design optimization procedure for it.

Parametric design of a part with free-form surfaces

3D solid models for parts with regular-form surfaces (PRFSs) are effectively generated using traditional parametric design techniques. A new model is obtained by changing some parameters defining the model. The parts with free-form surfaces (PFFSs), however, cannot be defined by several parameters. Usually they are defined by some geometric elements like profile curves. The traditional parametric design approaches have not easily dealt with the PFFSs. A method for generating a solid model and an engineering drawing for PFFSs is proposed in this paper: First, the new profiles are generated from input point data. Second, the profile information is extracted from the existing model. Last, the old profiles are replaced with the new profiles. This method can preserve the associative information of the existing model and automatically generate the drawing including views, dimen- sions, and annotations. The proposed method has been implemented using a commercial CAD/CAM system, Unigraphics, and API functions written in C-language, and were applied to the blades of a turbine generator. Some illustrative examples are pro- vided in order to show the effectiveness of the proposed method.

Nonparametric estimations of the sea state bias for a radar altimeter

To estimate the sea state bias（SSB） for radar altimeter, two nonparametric models, including a Nadaraya-Watson（NW） kernel estimator and a local linear regression（LLR） estimator, are studied based on the Jason-2 altimeter data. Selecting from different combinations of the Gaussian kernel function, spherical Epanechnikov kernel function, a fixed bandwidth and a local adjustable bandwidth, it is observed that the LLR method with the spherical Epanechnikov kernel function and the local adjustable bandwidth is the optimal nonparametric model for the SSB estimation. The comparisons between the nonparametric and parametric models are conducted and the results show that the nonparametric model performs relatively better at high-latitudes of the Northern Hemisphere. This method has been applied to the HY-2A altimeter as well and the same conclusion can be obtained.

Parametric modeling on spatial effect of excavation-damaged zone of underground cavern

Regarding excavation-damaged zone （EDZ） around underground opening as non-homogeneous rockmass with spatial deterioration effect on stuffiness and strength, a parametric model of EDZ using radius-displacement-dependent deformation modulus （RDDM） was proposed. Considering the nonlinearity characteristic of deformation and locality otherness of surrounding rock, deterioration parameter field of deformation modulus of rockmass around opening was quantitatively calculated through a given function. Applicability for multi-cavern condition and parameter sensibility of the model was analyzed by numerical experiments using synthetic data. Furthermore, the model was applied to identify EDZ of underground caverns of Pubugou hydropower station by calculating deterioration parameter field. Based on the parametric analysis of spatial effect and geological investigation, it is recognized that large radial deformation of deep fractured rock at the spandrel position and insufficient supporting bolts mainly result in great deformation pressure to act on the shotcrete and cause partial crack and spalling. It is shown that deterioration parameter field along the longitudinal axis of main powerhouse is evidently non-homogeneous in space and distributes exponentially along the radius from the opening. The model provides a simple and convenient way to identify the EDZ in the working state for rapid construction feedback analysis and support optimization of underground cavem from quantitative point of view and also aids in interpreting monitoring displacements and estimating support requirements.

Additive mixed models to study the effect of tree age and climatic factors on stem radial growth of Eucalyptus trees

The effect of tree age and climatic variables on stem radial growth of two hybrid clones of Eucalyptus was determined using longitudinal data from eastern South Africa.The stem radius of was measured weekly as the response variable.In addition to tree age,average weekly temperature,solar radiation,relative humidity and wind speed were simultaneously recorded with total rainfall at the site.An additive mixed effects model that incorporates a non-parametric smooth function was used.The results of the analysis indicate that the relationship between stem radius and each of the covariates can be explained by nonlinear functions.Models that account for the effect of clone and season together with their interaction in the parametric part of the additive mixed model were also fitted.The interaction between clone and season was not significant in all cases.For analyzing the joint effect all the covariates,additive mixed models that included two or more covariates were fitted.A significant effect of tree age was found in all cases.Although tree age was the key determinant of stem radial growth,weather variables also had a significant effect that was dependent on season.

Set-based parametric modeling, buckling and ultimate strength estimation of stiffened ship structures

There have been a great demand for a suitable and convenient method in the field of buckling analysis of stiffened ship structures, which is essential to structural safety assessment and is significantly time-consuming. Modeling, buckling behaviors and ultimate strength prediction of stiffened panels were investigated. The modeling specification including nonlinear finite element model and imperfections generation, and post-buckling analysis procedure of stiffened plates were demonstrated. And a software tool using set-based finite element method was developed and executed in the MSC. Marc environment. Different types of stiffen panels of marine structures have been employed to investigate the buckling behavior and assess the validity in the estimation of ultimate strength. A comparison between results of the generally accepted methods, experiments and the software tool developed was demonstrated. It is shown that the software tool can predict the ultimate capacity of stiffened panels with imperfections with a good accuracy.

Research on parametric modeling and computing of multi-tower suspension bridge based on ANSYS

Based on FEM (finite element method) program ANSYS and the OpenGL graphics, this paper develops the parametric modeling module and the computing module of the multi-tower suspension bridge, the modules being embedded into the ANSYS system, and the parametric modeling module parameters can be entered by way of interface, which can fast establish a multi-tower suspension bridge model. Calculation module can establish load conditions for the features of road bridge and specifications, in which multiple conditions can be defined and solved automatically. Post-processing part of the solution also serves the results of the subtotals and selects the output, so that the results of the output and finishing work have become more convenient and easier, and also the results can be saved in word, excel and other different file types.

On the Parametric Modeling of Turbine Blade Section Curve

Geometric parameters of the turbine blade are classified according to their destined functions, and the mathematical definition of those parameters in the section curve is introduced in detail. Some parts of the section curve shape can be adjusted freely, offering more flexibility to designers.

Parametric Modeling of Circuit Model for AC Glow Discharge in Air

In the parametric modeling of the circuit model for glow discharge in air,a new method for the design of glow discharge circuit model is presented.The new circuit model is an important reference for the design of plasma power supply,the simulation of glow discharge plasma actuator and the simulation of glow discharge plasma anemometer.The modeling approach consists in developing an electrical model of the glow discharge in air based on circuit components.The structure of the circuit model is established according to the theoretical analysis and the experimental device.Then the parameters of the circuit model are obtained based on the circuit analysis.Finally,the circuit model is verified by comparing the simulation current with the experimental current.This model takes into account the whole framework of the air glow discharge including the sheath and the plasma area.The built circuit model is feasible and reliable,thus being instructive for the investigation of the glow discharge in air.