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.

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.

Parametric CAD Modelling of Aircraft Wings for FEA Vibration Analysis

Excessive vibration of aircraft wings during flight is harmful and may cause propagation of existing cracks in the material, leading to catastrophic failures as a result of material fatigue. This study investigates the variations of modal characteristics of aircraft wings with respect to changes in the structural configurations. We develop parametric Computer-Aided Design (CAD) models to capture new design intend on the aircraft wing architectures. Subsequent Finite Element Analysis (FEA) based vibration analysis is performed to study the effects of architecture changes on the wing’s natural frequencies and mode shapes. It is concluded that the spar placement and the number of ribs have significant influence on the wing’s natural vibration properties. Integrating CAD modelling and FEA vibration analysis enables designers to develop alternative wing architectures to implement design requirements in the preliminary design stage.

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.

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.

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.

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 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.

On parametric approach of aerial robots' visual navigation

In aerial robots＇ visual navigation, it is essential yet very difficult to detect the attitude and position of the robots operated in real time. By introducing a new parametric model, the problem can be reduced from almost unmanageable to be partly solved, though not fully, as per the requirement. In this parametric approach, a multi-scale least square method is formulated first. By propagating as well as improving the parameters down from layer to layer of the image pyramid, a new global feature line can then be detected to parameterize the attitude of the robots. Furthermore, this approach paves the way for segmenting the image into distinct parts, which can be realized by deploying a Bayesian classifier on the picture cell level. Comparison with the Hough transform based method in terms of robustness and precision shows that this multi-scale least square algorithm is considerably more robust to noises. Some discussions are also given.

PARAMETRIC MODELING OF COMPONENT LIBRARY FOR LANDING GEAR BASED ON CATIA/CAA

The design of landing gear is complicated due to the numerous considered elements.And the initial elements related to each other can also be influenced by different factors.Landing gear design often involves a very large variety of configurations,especially in the conceptual design phase.However,traditional method costs more time to complete the whole procedure for suitable configurations of landing gears.Therefore,the parametric modeling of component library for landing gear based on computer aided three-dimensional interface application/component application architecutre(CATIA/CAA)is proposed.According to the analysis of the characteristics of landing gear components,a method is presented to extract the primary parameters of landing gear components so that a systematic classification can be established.Further,the related theories and methods,including receiving geometrical parameters of the components and updating the parametrical model,displaying the component parts,are also illustrated.Finally,the development technology for component library is explained.The proposed modeling method can improve the efficiency of the whole design cycle for landing gear.

Parametric Regression Approach for Gompertz Survival Times with Competing Risks

Regression models play a vital role in the study of data regarding survival of subjects.The Cox proportional hazards model for regression analysis has been frequently used in sur-vival modelling.In survival studies,it is also possible that survival time may occur with multiple occurrences of event or competing risks.The situation of competing risks arises when there are more than one mutually exclusive causes of death(or failure)for the person(or subject).In this paper,we developed a parametric regression model using Gompertz distribution via the Cox proportional hazards model with competing risks.We discussed point and interval estimation of unknown parameters and cumulative cause-specific hazard function with maximum-likelihood method and Bayesian method of estimation.The Bayes estimates are obtained based on non-informative priors and symmetric as well as asym-metric loss functions.To observe the finite sample behaviour of the proposed model under both estimation procedures,we carried out a Monte Carlo simulation analysis.To demon-strate our methodology,we also included real data analysis.

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.

On a Standard Parametric Modeling Method of Micro-Structure of Plain Woven Composite

A new standard parametric modeling method of the micro-structure of plain woven composite is proposed. It is based on good analysis of the mechanical property of the yarn, weaving law of plain woven, and other factors. The method implements a woven fabric composite visual engineering modeling process standardization, and it gives five steps to calculate the key micro-structural parameters of the yarn including the cross-section and the trajectory of the central Line. On the basis, the digital model of a plain woven composite has been constructed. The experimental result shows that the forecast for the mechanical property of the model using finite-element simulation analysis is consistent with the actual value. The shape and the structure of the model are also consistent with the solid.

PARAMETRIC MATCHING SELECTION OF MULTI-MEDIUM COUPLING SHOCK ABSORBER

To achieve the dual demand of resisting violent impact and attenuating vibration in vibration-impact-safety of protection for precision equipment such as MEMS packaging system, a theo- retical mathematical model of multi-medium coupling shock absorber is presented. The coupling of quadratic damping, linear damping, Coulomb damping and nonlinear spring are considered in the model. The approximate theoretical calculating formulae are deduced by introducing transformation-tactics. The contrasts between the analytical results and numerical integration results are developed. The resisting impact characteristics of the model are also analyzed in progress. In the meantime, the optimum model of the parameters matching selection for design of the shock absorber is built. The example design is illustrated to confirm the validity of the modeling method and the theoretical solution.

Parametric Design and Expression Method of Hui-Style

In this paper, we propose a parametric modeling method to reconstruct the Hui-Style and solve the problem that the user can＇t effectively reconstruct the Hui-Style three dimensional models because of the various style and complicated structure of Hui-Style components. This model includes summarizing and defining a variety of Hui-Style components parameter types. Determine the relationship between the parameter according to building formulas and design the parametric modeling process. First, set the depth of platform as the given user value. Then, calculate the component properties and the corresponding size according to the style of the Hui-Style architecture components and the constraint relation between Hui-Style architecture components. This needs only one parameter that is needed as the basic parameter in this method and the entire modeling process can be achieved based on it. The experimental result shows that the proposed method can well solve the complex parameters relationship of the Hui-Style architecture components and help the general users to construct the Hui-Style architecture components more effective.

A Turbine Blade Parametric Modeling Method Considering 1-D Heat Transfer Analysis

Traditional feature-based turbine blade models can match the needs of geometric modeling but could hardly meet the requirement of data extraction in 1-D heat transfer analysis. In this paper, the requirements of data extraction in 1-D heat transfer analysis are taken into consideration as well as geometric representation in parametric design process. An improved turbine blade parametric modeling method is proposed. Based on the modeling method proposed, a system structure of blade modeling process considering 1-D heat transfer analysis is devised. Eventually, a turbine blade parametric modeling system is constructed to test and verify the feasibility of the proposed modeling method and system structure. Experiments show that the blade parametric modeling method proposed can make geometric models better adapt to the specific requirements of 1-D heat transfer analysis and has certain reference value to the creation of high quality digital models.

Assembly-oriented reliability analysis method for the top-connection structure of a nuclear fuel assembly

The nuclear fuel assembly is the core component of a nuclear reactor.In a pressurized water reactor fuel assembly,the top-connection structure connects the top nozzle to the guide thimble.Its performance reliability is essential for the stability of the nuclear fuel assembly.In this study,an assembly-oriented reliability analysis method for top-connection structures is presented by establishing an assembly-oriented top-connection structure parameter modeling method and a nonlinear contact gap and penetration correction method.A reliability model of the top-connection assembly structure,including multiple stochastic design variables,was constructed,and the overall reliability of the top-connection assembly structure was obtained via a Kriging model and Monte Carlo simulation.The acquired experimental data were consistent with real-world failure conditions,which verified the practicability and feasibility of the reliability analysis method proposed in this study.

AWSD:An Aircraft Wing Dataset Created by an Automatic Workflow for Data Mining in Geometric Processing

This paper introduces an aircraft wing simulation data set(AWSD)created by an automatic workflow based on creating models,meshing.simulating the wing flight flow field solution,and parameterizing solution results.AWSD is a flexible,independent wing collection of simulations with specific engineering requirements.The data set is applicable to handle computer geometry processing tasks.In contrast to the existing 3D model data set,there are some advantages the scale of this data set is not limited by the collection source,the data files have high quality,no defects,redundancy,and other problems,and the models and simulation are all designed for the specific actual engineering demand.Moreover,AWSD has the characteristics of rich information and a similar model structure,which contributes to the construction of the surrogate model.On the other hand,this data set is suitable for advancing research of data mining in computational geometry graphics.To solve the problem that the CFD flows field results are not intuitive,this paper used the resampling method of surface data to sample the result to the model surface,then segmented the re sampled 3D mesh surface,and compared with the diferences among K-means algorithm,Mini_Batch K means algorithm,and Spectral Clustering algorithm.AWSD provides 300 sets of models,meshes,CFD simulation results,and parametric results based on ARAP(As-Rigid-As Posible)and Harmonic mapping for advancing the construction of engineering surrogate models,3D mesh segmentation,surface resampling,and related geometric processing tasks.