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.

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.

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.

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.

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.

A fnite element parametric modeling technique of aircraft wing structures

A finite element parametric modeling method of aircraft wing structures is proposed in this paper because of time-consuming characteristics of finite element analysis pre-processing. The main research is positioned during the preliminary design phase of aircraft structures. A knowledge- driven system of fast finite element modeling is built. Based on this method, employing a template parametric technique, knowledge including design methods, rules, and expert experience in the process of modeling is encapsulated and a finite element model is established automatically, which greatly improves the speed, accuracy, and standardization degree of modeling. Skeleton model, geometric mesh model, and finite element model including finite element mesh and property data are established on parametric description and automatic update. The outcomes of research show that the method settles a series of problems of parameter association and model update in the process of finite element modeling which establishes a key technical basis for finite element parametric analysis and optimization design.

Parametric modeling of hypersonic ballistic data based on time varying auto-regressive model

For describing target motion in hypersonic vehicle defense,a parametric analyzing and modeling method on ballistic data is proposed based on time varying auto-regressive method.Ballistic data are regarded as non-stationary random signal,where the hidden internal law is studied.Firstly,ballistic data are decomposed into smooth linear trend signal and non-stationary periodic skip signal with ensemble empirical mode decomposition method to avoid mutual interference between different modal data.Secondly,the linear trend signal and the periodic skip signal are modeled separately.The linear trend signal is approximated by power function regressive estimator and the periodic skip signal is modeled based on time varying auto-regressive method.In order to determine optimal model orders,a novel method is presented based on information theoretic criteria and the criteria of minimizing the mean absolute error.Finally,the consistency test is conducted by investigating the time-frequency spectrum characteristics and statistical properties of outputs of the parametric model established above and dynamics model under the same initial condition.Simulation results demonstrate that the parametric model established by the proposed method shares a high consistency with the original dynamics model.

Dynamic parametric modeling-based model updating strategy of aeroengine casings

For accurate Finite Element(FE)modeling for the structural dynamics of aeroengine casings,Parametric Modeling-based Model Updating Strategy(PM-MUS)is proposed based on efficient FE parametric modeling and model updating techniques regarding uncorrelated/correlated mode shapes.Casings structure is parametrically modeled by simplifying initial structural FE model and equivalently simulating mechanical characteristics.Uncorrelated modes between FE model and experiment are reasonably handled by adopting an objective function to recognize correct correlated modes pairs.The parametrized FE model is updated to effectively describe structural dynamic characteristics in respect of testing data.The model updating technology is firstly validated by the detailed FE model updating of one fixed–fixed beam structure in light of correlated/uncorrelated mode shapes and measured mode data.The PM-MUS is applied to the FE parametrized model updating of an aeroengine stator system(casings)which is constructed by the proposed parametric modeling approach.As revealed in this study,(A)the updated models by the proposed updating strategy and dynamic test data is accurate,and(B)the uncorrelated modes like close modes can be effectively handled and precisely identify the FE model mode associated the corresponding experimental mode,and(C)parametric modeling can enhance the dynamic modeling updating of complex structure in the accuracy of mode matching.The efforts of this study provide an efficient dynamic model updating strategy(PM-MUS)for aeroengine casings by parametric modeling and experimental test data regarding uncorrelated modes.

Shape optimization design of a heaving buoy of wave energy converter based on fully parametric modeling and CFD method

The hydrodynamic shape of the heaving buoy is an important factor of the motion response in waves and thus concerns the energy conversion efficiency for the point absorbers(PAs).The current experience-based designs are time consuming and not very efficient,hence,faster and smarter methods are desirable.An automated optimization method based on a fully parametric modeling method and computational fluid dynamics(CFD),is proposed in this paper.Using this method,a benchmark buoy is screen designed and then optimized by maximizing the heave motion response.The geometry is described parametrically and deformed by means of the free-form deformation(FFD)method.During the optimization process,the expansion factor of control points is the basis for the variations.A combination of the Sobol and the non-dominated sorting genetic algorithm II(NSGA-II)is used to search for the solutions.After several iterations,the heaving buoy shape with optimal heave motion response is obtained.The analyses show that the heave motion response has increased 55.3%after optimization.The developed methodology is valid and seems to be a promising way to design a novel buoy that can significantly improve the wave energy conversion efficiency of the PAs in future.

Visual recognition of cardiac pathology based on 3D parametric model reconstruction

Visual recognition of cardiac images is important for cardiac pathology diagnosis and treatment.Due to the limited availability of annotated datasets,traditional methods usually extract features directly from twodimensional slices of three-dimensional(3D)heart images,followed by pathological classification.This process may not ensure the overall anatomical consistency in 3D heart.A new method for classification of cardiac pathology is therefore proposed based on 3D parametric model reconstruction.First,3D heart models are reconstructed based on multiple 3D volumes of cardiac imaging data at the end-systole(ES)and end-diastole(ED)phases.Next,based on these reconstructed 3D hearts,3D parametric models are constructed through the statistical shape model(SSM),and then the heart data are augmented via the variation in shape parameters of one 3D parametric model with visual knowledge constraints.Finally,shape and motion features of 3D heart models across two phases are extracted to classify cardiac pathology.Comprehensive experiments on the automated cardiac diagnosis challenge(ACDC)dataset of the Statistical Atlases and Computational Modelling of the Heart(STACOM)workshop confirm the superior performance and efficiency of this proposed approach.

Fast optimization of impulsive perturbed orbit rendezvous using simplified parametric model

A novel simplified parametric model for long-duration impulsive orbit rendezvous is proposed.Based on an existing fast estimation method,the optimal impulses and trajectory can be expressed by only ten parameters whose initial values can be easily determined.Then,these parameters are used to predict orbital deviations with a target orbit.A simple correction process is designed to sequentially update the parameters based on the J_(2) perturbed analytical dynamic equations of circular orbits.Finally,an iteration loop is formed to obtain the precise parameters and optimal trajectory.The simulation results confirm that the simplified parametric optimization method can be applied to elliptical orbits of small eccentricity and adapts well to both analytical and high-precision dynamics.The deviations could always converge within five iterations and the calculation was more efficient than the existing methods.

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.

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.

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.

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.

3D Modeling of the preparation process of metal rubber material

Based on the analysis of the preparation of metal rubber （MR） and two pivotal hypotheses, the uniform distribution and the unaltered topological structure of wires in the radial direction of columns in the punch process, a 3D parametrical model was established based on four approaches： helix-making, planar roughcast-weaving, planar roughcast-rolling, and 3D roughcast punching. In the modeling process, 5 lattice types of weave patterns in planar roughcast were put forward, and 10 quantificational modeling parameters were picked up to exclusively define the column MR component structure. The wire distribution was visualized by CAD techniques. The important performance parameter of column MR components （relative density ρ^- ） can be forecasted by modeling computing, which provides the necessary foundation for the design and optimization of MR materials.