基于虚拟样机的胶印机虚拟试验及串墨初始相位优化

针对胶印机结构复杂的特点,提出基于虚拟试验获得胶印机整机性能数据的方法.以SolidWorks,COSMOS/Motion和ADAMS为虚拟样机建模平台,构建了某型胶印机印刷色组的虚拟样机模型.在ADAMS中对胶印机虚拟样机进行虚拟试验,获得了胶印机整机的静力学、运动学和动力学仿真数据.通过对虚拟试验数据的分析,明确了该型胶印机振动的主要来源及激振力的时域、频域特征,为胶印机的动态优化提供了参考.为了进一步降低串墨机构给整机带来的振动,进行了以4个串墨辊串墨运动初始相位为因素的试验设计,优选出了一组最佳的串墨初始相位搭配方案,基本上消除了串墨运动对整机的影响,取得了较好的优化效果.     

虚拟技术在轧钢机械中的应用

基于工程实际中的轧钢机械进行虚拟参数化设计、分析、实验平台等的建设应用,分析轧钢工艺数据以及轧钢机械设备输入参数特点及可靠性分析,并就机械设备中的主要零部件进行单元分析,满足实际工程需要的虚拟样机试制,旨在提高轧钢机械的设计、分析、快速建模和高效创建工程设计图纸的能力。     

虚拟技术在轧钢机械中的应用

本文基于工程实际中的轧钢机械进行虚拟参数化设计、分析、实验平台等的建设应用,分析轧钢工艺数据以及轧钢机械设备输入参数特点及可靠性分析,并就机械设备中的主要零部件进行单元分析,满足实际工程需要的虚拟样机试制,旨在提高轧钢机械的设计、分析、快速建模和高效创建工程设计图纸的能力。     

虚拟样机技术在立式行星磨设计中的应用研究

介绍虚拟样机技术,在对立式行星磨系统动力学分析的基础上,对其采用了虚拟样机技术,开发了立式行星磨的虚拟样机并进行了虚拟试验,得到了虚拟样机的优化模型,显示了虚拟样机技术的强大优势,同时,虚拟试验结果将对立式行星磨的实际生产制造具有理论的指导意义.     

虚拟技术在轧钢机械中的应用

本文基于工程实际中的轧钢机械进行虚拟参数化设计、分析、实验平台等的建设应用,分析轧钢工艺数据以及轧钢机械设备输入参数特点及可靠性分析,并就机械设备中的主要零部件进行单元分析,满足实际工程需要的虚拟样机试制,旨在提高轧钢机械的设计、分析、快速建模和高效创建工程设计图纸的能力。     

虚拟样机技术在大型液压泥炮研发过程中的应用

借助虚拟样机技术,运用Solidworks建立了新型液压泥炮的虚拟样机模型,并将模型导入ADAMS软件对其进行运动学、动力学仿真分析,研究了关键点的运动轨迹及其速度变化,分析了主要零部件铰接点的受力大小和变化趋势。通过样机建模与仿真分析,为大型液压泥炮的合理设计和使用提供了可靠的依据,同时也缩短了开发周期,降低成本。     

支撑掩护式液压支架虚拟样机的设计

液压支架是综采工作面高产、高效得以实现的关键设备。本文对虚拟样机进行了充分的了解,并结合其在全世界的发展现状,对液压支架设计过程中融入虚拟样机技术进行了必要性的论证,采用Pro/E软件建立液压支架三维实体模型和进行运动仿真分析。通过有限元专用工具进行了有限元的论证分析,并对数据做了总结,为液压支架的设计和分析提供了理论参考。     

炸药破碎机开发中的虚拟装配与运动仿真研究

基于CAD/CAE的一体化软件CATIA建立炸药破碎机的零件三维实体模型,对所建零件模型进行虚拟装配,然后对装配模型进行运动仿真分析,在数字化样机中对初始的运动机构进行干涉分析和运动仿真,实现了产品的装配效果模拟功能,验证了设计的可行性和实用性.     

热轧卷取机助卷系统的仿真分析

借助虚拟样机技术,建立了热轧卷取机助卷系统虚拟样机模型。通过对虚拟样机进行仿真分析,得出压力补偿系数、重力补偿系数以及液压缸行程随助卷辊辊缝值的变化规律。从而为实际生产的助卷辊位置控制和压力控制提供了可靠的依据。     

虚拟样机技术在矿山机械领域中的应用

虚拟样机技术的投入使用为解决矿山机械领域出现的问题提供了必要的方案和手段。运用虚拟样机技术的优势,一方面可以缩短工程时间和周期,降低产品造价,避免成本浪费;另一方面,可以提高产品的开发活力,激发市场活力,增强产品的竞争力。虚拟样机技术在矿山机械领域中的具体应用,通过电子技术建设样品的数据化模型,可以完成物理仪器无法继续的试验,因而不必进行设计和试验就可获得最佳方案。     

圆盘铸锭机锌锭模的改进

通过对锭模的改进设计,规范造型工艺,提高了圆盘铸锭的冷却效率和锌锭的表面质量,并解决了商标清晰度的问题。     

Mathematical Modeling of the Solidification Structure Evolution in the Presence of Ultrasonic Stirring

Ultrasonic treatment (UST) was studied in this work to improve the quality of the cast ingots as well as to control the solidification structure evolution. Ultrasonically induced cavitation consists of the formation of small cavities (bubbles) in the molten metal followed by their growth, pulsation, and collapse. These cavities are created by the tensile stresses that are produced by acoustic waves in the rarefaction phase. The pressure for nucleation of the bubbles (e.g., cavitation threshold pressure) may decrease with increasing the amount of dissolved gases and especially with the amount of inclusions in the melt. Modeling and simulation of casting solidification of alloys with UST requires complex multiscale computations, from computational fluid dynamics (CFD) macroscopic modeling through mesoscopic to microscopic modeling, as well as strategies to link various length-scales emerged in modeling of microstructural evolution. The developed UST modeling approach is based on the numerical solution of the Lilley model (that is founded on Lighthills’s acoustic analogy), fluid flow, heat transfer equations, and mesoscopic modeling of the grain structure. The CFD analysis tool is capable of modeling acoustic streaming and ultrasonic cavitation. It is used in this work to study ingot solidification under the presence of ultrasound. The UST model was applied to low-temperature alloys including Al- and Mg-based alloys. Although the predicted ultrasonic cavitation region is relatively small, the acoustic streaming is strong and, thus, the created/survived bubbles/nuclei are transported into the bulk liquid quickly. The predicted grain size under UST condition is at least one order of magnitude lower than that without UST.     

基于Voronoi图的晶体塑性有限元多晶几何建模

通常用规则的六边形或四边形等来表示晶粒,不能够反映出晶界的不规则性,本文使用Voronoi方法在大型有限元软件ABAQUS中建立了多晶材料的几何模型,能够表达出晶粒的几何形状与晶界的不规则性;在此基础上提出了一种控制晶粒大小分布及织构的方法,通过调整参数能够建立具有不同晶粒尺寸分布及织构的模型.     

Analysis of interaction terms in structural equation models: A non-technical demonstration using the deviation score approach.

One of the major shortcomings in using structural equation modeling (SEM) data analytic techniques has been the difficulty in handling interaction terms in the modeling process. The issue is that interaction terms that are created by cross-multiplying raw scores result in the matrix of covariances or correlations being singular (there is at least 1 linear dependency in the matrix). The data analyses will not proceed as the matrix is not positive definite. This paper shows a valid and easy way to cope with the problem of interaction terms by using deviation scores or "centred" variables as the interaction terms. The authors expand on the work of L. S. Aiken and S. G. West (1991), which discussed interaction effects within a multiple regression framework, by taking it into the SEM domain for the benefit of users of SEM programs. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Modeling the thermal state of the intermediate capacity of the electron-beam furnace

A mathematical model of the temperature field distribution in an intermediate capacity of the electron-beam furnace taking into account the electron beam power, its parametric scan functions, water-cooling parameters, phase transformations of the treated material, and the convective flow of the melt from its feeding place to pouring into the crystallizer is created. Program software making it possible to find the quantitative characteristics and visualize the heat flux distribution over the scan surface and the unsteady temperature field in the intermediate capacity volume is developed. Examples of modeling the temperature field distribution and the position of the solid-liquid interface in the intermediate capacity at various electron beam powers are shown.     

Developmental mechanics determine long bone allometry

Evolutionary and developmental factors responsible for the scaling relationships observed in animal skeletons are poorly understood. We have created a mathematical model for long bone cross-sectional development which incorporates both intrinsic growth and extrinsic, adaptive bone modeling in response to changes in bone mechanical strains during ontogeny. The model successfully simulates the developing morphology in individual animals and the bone geometric allometric relationships among adults across many species (range from mouse to elephant in size). Our results suggest that long bone scaling characteristics are not a result of intrinsic genetic factors but are the results of highly conserved, extrinsic biophysical processes whereby bone tissue strains modulate skeletal morphogenesis.     

Modeling the Effects of Macrophytes on Hydrodynamics

A computer model was created as a scientific and management tool for understanding the effects of macrophytes on hydrodynamics and water quality. A model was required that could simulate macrophytes in a complex water body and could be coupled to a multicompartment water quality model of phytoplankton, dissolved oxygen, nutrients, pH, and organic matter. This would permit the investigation of water resource issues where macrophyte growth, phytoplankton growth, nutrient loadings, and flood control were all contributing factors. The model was added as a compartment to the U.S. Army Corps of Engineers two-dimensional, laterally averaged, dynamic water quality model, CE-QUAL-W2 (Corps of Engineers, water quality, width averaged, two dimensional) and applied to the Columbia Slough, Ore. Features of the macrophyte model include the capability to simulate multiple submerged macrophyte species; transport of nutrient fluxes between plant biomass and the water column and/or sediments; growth limitation due to nutrient, light and temperature; simulation of the spatial distribution of macrophytes vertically and horizontally; the modeling of light attenuation in the water column caused by macrophyte concentration; and the modeling of open channel flow with channel friction due to macrophytes. The macrophyte model was tested through mass balances and sensitivity analyses. The modeling of channel friction was evaluated by comparing predicted water levels with data from tests conducted in a laboratory flume. Use of the model in the Columbia Slough showed reasonable predictive capability regarding estimated biomass and water level dynamics.     

Scoring Approach to Construction Bond Underwriting

This paper introduces a conceptual scoring-based contractor evaluation system to address the problems created by the subjective nature of surety underwriting process. The methodology presented in this paper provides the surety underwriters with an objective tool for estimating the probability that the evaluated contractor would perform in a satisfactory manner with respect to the main decision factors considered in the bond underwriting process. The proposed model could be used by decision makers to prescreen contractors and make underwriting decisions. The paper first discusses the construction bond underwriting process and provides a brief introduction to the scoring technique as the modeling environment used in this paper. Then, the three steps included in the development of the proposed scoring system are presented in detail followed by an example demonstrating the application of the final product.     

Prediction of protein side-chain rotamers from a backbone-dependent rotamer library: a new homology modeling tool

Modeling by homology is the most accurate computational method for translating an amino acid sequence into a protein structure. Homology modeling can be divided into two sub-problems, placing the polypeptide backbone and adding side-chains. We present a method for rapidly predicting the conformations of protein side-chains, starting from main-chain coordinates alone. The method involves using fewer than ten rotamers per residue from a backbone-dependent rotamer library and a search to remove steric conflicts. The method is initially tested on 299 high resolution crystal structures by rebuilding side-chains onto the experimentally determined backbone structures. A total of 77% of chi1 and 66% of chi(1 + 2) dihedral angles are predicted within 40 degrees of their crystal structure values. We then tested the method on the entire database of known structures in the Protein Data Bank. The predictive accuracy of the algorithm was strongly correlated with the resolution of the structures. In an effort to simulate a realistic homology modeling problem, 9424 homology models were created using three different modeling strategies. For prediction purposes, pairs of structures were identified which shared between 30% and 90% sequence identity. One strategy results in 82% of chi1 and 72% chi(1 + 2) dihedral angles predicted within 40 degrees of the target crystal structure values, suggesting that movements of the backbone associated with this degree of sequence identity are not large enough to disrupt the predictive ability of our method for non-native backbones. These results compared favorably with existing methods over a comprehensive data set.     

Numbers and space: A computational model of the SNARC effect.

The SNARC (spatial numerical associations of response codes) effect reflects the tendency to respond faster with the left hand to relatively small numbers and with the right hand to relatively large numbers (S. Dehaene, S. Bossini, & P. Giraux, 1993). Using computational modeling, the present article aims to provide a framework for conceptualizing the SNARC effect. In line with models of spatial stimulus-response congruency, the authors modeled the SNARC effect as the result of parallel activation of preexisting links between magnitude and spatial representation and short-term links created on the basis of task instructions. This basic dual-route model simulated all characteristics associated with the SNARC effect. In addition, 2 experiments tested and confirmed new predictions derived from the model. (PsycINFO Database Record (c) 2010 APA, all rights reserved)