浅论Tod项目中的参数化应用

Tod项目是一个创新性的建筑设计项目,通过参数化应用技术,实现了高效、灵活和可持续的设计过程。本文将讨论Tod项目中参数化应用的意义、方法以,希望通过本文的研究,可以为行业相关人员提供一些可行性的建议,从而为建筑行业注入一些新鲜的血液,促进建筑行业的创新,基于建筑事业的角度推动国民经济的转型,给人们提供更好的居住品质和环境。

Inventor参数化应用带来改变

这个故事来自于众多使用Inventor客户的其中一个．先简单介绍一下公司情况。

BIM技术在折达公路跨越桥项目中的应用分析

近年来在市政建设领域,国家大力投入资金完善基础交通路网设施,高速公路、铁路以及城市快速路等,提高了人们交通出行的便利。随着农田耕地保护基本红线限制和现有路网影响,新建道路在复杂地形及跨线部分多采用桥梁设计。考虑到公路桥梁跨越复杂地形与施工场地限制等因素,采用BIM技术对公路桥梁进行施工阶段辅助设计,成为近些年的研究热点。对公路桥梁设计方案采用BIM优化,能很大程度上控制成本,降低安全隐患,优化施工难点技术交底。

An Immune Self-adaptive Differential Evolution Algorithm with Application to Estimate Kinetic Parameters for Homogeneous Mercury Oxidation

A new version of differential evolution （DE） algorithm, in which immune concepts and methods are applied to determine the parameter setting, named immune self-adaptive differential evolution （ISDE）, is proposed to improve the performance of the DE algorithm. During the actual operation, ISDE seeks the optimal parameters arising from the evolutionary process, which enable ISDE to alter the algorithm for different optimization problems and improve the performance of ISDE by the control parameters＇ self-adaptation. The .performance of the proposed method is studied with the use of nine benchmark problems and compared with original DE algorithm ~nd-other well-known self-adaptive DE algorithms. The experiments conducted show that the ISDE clearly outperforms the other DE algorithms in all benchmark functions. Furthermore, ISDE is applied to develop the kinetic model for homogeneous mercury. （Hg） oxidation in flue gas, and satisfactory results are obtained.

Application of Discrete Lumped Kinetic Modeling on Vacuum Gas Oil Hydrocracking

The kinetic model of vacuum gas oil （VGO） hydrocracking based on discrete lumped approach was investigated, and some improvement was put forward at the same time in this article. A parallel reaction scheme to describe the conver- sion of VGO into products （gases, gasoline, and diesel） proposed by Orochko was used. The different experimental data were analyzed statistically and then the product distribution and kinetic parameters were simulated by available data. Fur- thermore, the kinetic parameters were correlated based on the feed property, reaction temperature, and catalyst activity. An optimization code in Matlab 2011b was written to fine-me these parameters. The model had a favorable ability to predict the product distribution and there was a good agreement between the model predictions and experiment data. Hence, the ki- netic parameters indeed had something to do with feed properties, reaction temperature and catalyst activity.

A new improved Alopex-based evolutionary algorithm and its application to parameter estimation

In this work, focusing on the demerit of AEA (Alopex-based evolutionary algorithm) algorithm, an improved AEA algorithm (AEA-C) which was fused AEA with clonal selection algorithm was proposed. Considering the irrationality of the method that generated candidate solutions at each iteration of AEA, clonal selection algorithm could be applied to improve the method. The performance of the proposed new algorithm was studied by using 22 benchmark functions and was compared with original AEA given the same conditions. The experimental results show that the AEA-C clearly outperforms the original AEA for almost all the 22 benchmark functions with 10, 30, 50 dimensions in success rates, solution quality and stability. Furthermore, AEA-C was applied to estimate 6 kinetics parameters of the fermentation dynamics models. The standard deviation of the objective function calculated by the AEA-C is 41.46 and is far less than that of other literatures' results, and the fitting curves obtained by AEA-C are more in line with the actual fermentation process curves.

Process optimization with consideration of uncertainties——An overview

Optimization under uncertainty is a challenging topic of practical importance in the Process Systems Engineering.Since the solution of an optimization problem generally exhibits high sensitivity to the parameter variations, the deterministic model which neglects the parametric uncertainties is not suitable for practical applications. This paper provides an overview of the key contributions and recent advances in the field of process optimization under uncertainty over the past ten years and discusses their advantages and limitations thoroughly. The discussion is focused on three specific research areas, namely robust optimization, stochastic programming and chance constrained programming, based on which a systematic analysis of their applications, developments and future directions are presented. It shows that the more recent trend has been to integrate different optimization methods to leverage their respective superiority and compensate for their drawbacks. Moreover, data-driven optimization, which combines mathematical programming methods and machine learning algorithms, has become an emerging and competitive tool to handle optimization problems in the presence of uncertainty based on massive historical data.

Synthesis and optimization of utility system using parameter adaptive differential evolution algorithm

Synthesis and optimization of utility system usually involve grassroots design, retrofitting and operation optimization, which should be considered in modeling process. This paper presents a general method for synthesis and optimization of a utility system. In this method, superstructure based mathematical model is established, in which different modeling methods are chosen based on the application. A binary code based parameter adaptive differential evolution algorithm is used to obtain the optimal con figuration and operation conditions of the system. The evolution algorithm and models are interactively used in the calculation, which ensures the feasibility of con figuration and improves computational ef ficiency. The capability and effectiveness of the proposed approach are demonstrated by three typical case studies.

Development of a toy column model and its application in testing cumulus convection parameterizations

A single-column model is constructed based on parameterizations inherited from the Finite-volume/Spectral Atmospheric Model F/SAMIL and tested in simulations of tropical convective systems. Two representative convection schemes are compared in terms of their performances on precipitation types, individual physical tendencies, and temperature and moisture fields. The main difference between the two selected schemes is in their representation of entraining/detraining process. The Tiedtke scheme assumes bulk entrainment, while the Zhang–Mc Farlane scheme parameterizes entrainment/detrainment rates under the spectrum concept. Large-scale forcing and verification data are taken from the GATE phase III field campaign, during which abundant convective events were observed. Given the same triggering function and closure assumption, results show that entrainment/detrainment representation remains the dominant factor on the simulation of cumulus mass flux and of temperature and moisture fields. By analyzing sources and sinks of heat and moisture, this study reveals how parameterization components compensate for each other and make model results insensitive to parameterization changes in certain fields, thus suggesting the need to treat parameterizations as systems rather than individual components.

The four dimensional variational data assimilation with multiple regularization parameters as a weak constraint(Tikh-4D-Var) and its preliminary application on typhoon initialization

Traditional variational data assimilation （VDA） with only one regularization parameter constraint cannot produce optimal error tuning for all observations. In this paper, a new data assimilation method of ＂four dimensional variational data assimilation （4D-Var） with multiple regularization parameters as a weak constraint （Tikh-4D-Var）＂ is proposed by imposing different reg- ularization parameters for different observations. Meanwhile, a new multiple regularization parameters selection method, which is suitable for actual high-dimensional data assimilation system, is proposed based on the posterior information of 4D-Var system. Compared with the traditional single regularization parameter selection method, computation of the proposed multiple regularization parameters selection method is smaller. Based on WRF3.3.1 4D-Vat data assimilation system, initiali- zation and simulation of typhoon Chaba （2010） with the new Tikh-4D-Var method are compared with its counterpart 4D-Var to demonstrate the effectiveness of the new method. Results show that the new Tikh-4D-Var method can accelerate the con vergence with less iterations. Moreover, compared with 4D-Var method, the typhoon track, intensity （including center surface pressure and maximum wind speed） and structure prediction are obviously improved with Tikh-4D-Var method for 72-h pre- diction. In addition, the accuracy of the observation error variances can be reflected by the multiple regularization parameters.

Toric Difference Variety

In this paper, the concept of toric difference varieties is defined and four equivalent descriptions for toric difference varieties are presented in terms of difference rational parametrization,difference coordinate rings, toric difference ideals, and group actions by difference tori. Connections between toric difference varieties and affine N[x]-semimodules are established by proving the one-to-one correspondence between irreducible invariant difference subvarieties and faces of N[x]-semimodules and the orbit-face correspondence. Finally, an algorithm is given to decide whether a binomial difference ideal represented by a Z[x]-lattice defines a toric difference variety.

Easy cross parameterization for articulated shapes

This paper presents a novel interactive system for establishing compatible meshes for articulated shapes.Given two mesh surfaces,our system automatically generates both the global level component correspondence and the local level feature correspondence.Users can use some sketch-based tools to specify the correspondence in an intuitive and easy way.Then all the other vertex correspondences could be generated automatically.The cross parameterization preserves both high level and low level features of the shapes.The technique showed in the system benefits various applications in graphics including mesh inter-polation,deformation transfer,and texture transfer.