Design of a 6-DOF force device for virtual assembly (FDVA-6) of mechanical parts

Among different interaction modalities, force feedback is one of the key technologies to increase the interactivity and immersion of a virtual assembly process. This paper presents a 6-DOF force device with its forward kinematic analysis, workspace simulation, and gravity compensation. To evaluate the device, a prototype system is developed and a case study is conducted to assemble a mechanical product. The users have given positive feedback on the gravity compensation implemented and the general performance of the device.     

大型偏心结构吊装欠约束问题研究

吊装施工过程中被吊模块的水平度是作业要求的重要指标,通常需要增加配重调平。传统有限元方法需要补充约束以消除单元刚体位移,且需要重复计算平衡方程来求解调平载荷,效率不高。将模块的运动分解为随动坐标系的整体运动以及相对该坐标系的弹性变形,可将欠约束问题化为多体系统的静平衡问题。基于虚功率原理推导了吊装平顺时刻的节点力平衡方程以及相应的切线刚度矩阵,并将配重表示为基础配重与载荷系数相乘的形式。通过对节点力平衡方程求导,得到一组以载荷系数为自变量的微分方程,通过求解微分方程并结合水平度判据,可快速搜寻满足水平度要求的载荷系数。数值算例表明,该方法在解决偏心模块吊装欠约束问题方面具有明显的优势,在确定配重载荷方面具有较快的速度和合理的精度。     

塞曼效应仿真实验平台

塞曼效应实验是学生了解原子具有磁矩和空间取向量子化现象的重要实验,至今塞曼效应仍是研究能级结构的重要方法之一.为了能够让学生更加清楚地了解塞曼效应实验的基本原理和操作规程,针对教学中的重点和难点,运用flash软件制作出塞曼效应仿真实验.该程序可全程高度仿真实验过程,具有界面友好、易于操作、无需安装等优点.为实验教学提供了一种新的辅助方式.     

虚拟震源测深法及其在INDEPTH-3台阵中的应用

基于中美合作项目INDEPTH第3期在青藏高原布设的台站，使用虚拟震源测深法研究青藏高原中部的地壳厚度。结果显示，拉萨地体和羌塘地体的地壳结构存在巨大差异。拉萨地体的地壳厚度大约为57 km，与艾里均衡说预测的地壳厚度基本一致，说明拉萨地体的地壳结构比较简单。羌塘地体的地壳厚度为60~75 km，向北有增厚趋势，明显较艾里均衡说预测的地壳厚，说明羌塘地体地壳结构比较复杂，原因有可能是羌塘地体下存在高温流体和低速带，或者与印度板块岩石圈在班公湖-怒江缝合带以北向下俯冲有关。     

利用三维虚拟技术突破物质结构教学*——从演示型工具到探索型工具的转变

针对物质结构教学的抽象性,开发了一套基于三维虚拟技术的物质结构教学软件,可对结构模型进行旋转、平移、缩放、切割、镜像、插入或删除原子(团)及启停预先设置的动画等操作,强大的交互功能不仅能对分子或晶体结构如构造异构、立体异构、晶体的堆积方式、晶胞的划分、配位数、晶体结构中的空隙及空间利用率等问题进行效果极佳的可视化教学,另一方面,通过对B₁₂与C₆₀分子空间构型转变的探究揭示数学构型的重要性,通过对六方晶胞占有原子个数的探究修正晶胞模型,通过对金属晶体的4种基本堆积方式成因的探究提出“半密置层”概念来完善紧密堆积规律等案例,展示出三维虚拟技术在微观结构探索发现方面的巨大潜力。     

基于虚拟现实的分子对接教学软件*

由于其强大的沉浸性和交互性等特征,虚拟现实技术在教育教学方面有着独特的优势。基于分子建模工具和虚拟现实技术构建了一种关于分子对接的教学软件,该软件将语音讲解、动画演示、分子可视化、交互操作等内容有机整合在虚拟现实环境中,从理论知识讲解和VR实验操作2个方面展开,深入浅出地讲解了分子对接的知识点,达到辅助教学的目的。     

正溴丁烷合成虚拟仿真系统的设计与辅助实验教学研究*

介绍了正溴丁烷合成虚拟仿真系统的设计与功能,并结合具体的教学实践和研究结果的对比分析,提出了虚实结合的混合式教学模式,这种教学模式能有效解决传统实验教学过程中实验预习效果差、过程性评价难的教学痛点。     

基于虚拟相位平面的相位展开方法

在基于相位分析的三维测量系统中,为了准确地得到物体的高度,相位展开扮演着很重要的角色。传统的相位展开方法常常需要额外的投影图,而傅里叶变换轮廓术只需要采集一幅或两幅变形条纹图就可以实现对物体轮廓的测量,其方法速度快,易于实现。针对傅里叶变换轮廓术方法计算得到的截断相位分布,本文提出了一种利用截断相位与参考平面相位差值2π的整数倍数获得截断相位的正确级次,辅助相位展开的方法。当被测物体较复杂,或者相位截断次数较多时,该方法在已有参考平面相位的基础上虚拟新的相位平面,依次比较截断相位和虚拟相位,进行多次分级相位展开,结合多个展开相位结果,最终得到正确的展开相位。该方法展开速度快,展开错误不会蔓延传递。仿真和实物实验结果证明了该方法的可行性,说明该方法可用于傅里叶变换轮廓术中进行截断相位的快速展开。     

Combining Different Docking Engines and Consensus Strategies to Design and Validate Optimized Virtual Screening Protocols for the SARS-CoV-2 3CL Protease

The 3CL-Protease appears to be a very promising medicinal target to develop anti-SARS-CoV-2 agents. The availability of resolved structures allows structure-based computational approaches to be carried out even though the lack of known inhibitors prevents a proper validation of the performed simulations. The innovative idea of the study is to exploit known inhibitors of SARS-CoV 3CL-Pro as a training set to perform and validate multiple virtual screening campaigns. Docking simulations using four different programs (Fred, Glide, LiGen, and PLANTS) were performed investigating the role of both multiple binding modes (by binding space) and multiple isomers/states (by developing the corresponding isomeric space). The computed docking scores were used to develop consensus models, which allow an in-depth comparison of the resulting performances. On average, the reached performances revealed the different sensitivity to isomeric differences and multiple binding modes between the four docking engines. In detail, Glide and LiGen are the tools that best benefit from isomeric and binding space, respectively, while Fred is the most insensitive program. The obtained results emphasize the fruitful role of combining various docking tools to optimize the predictive performances. Taken together, the performed simulations allowed the rational development of highly performing virtual screening workflows, which could be further optimized by considering different 3CL-Pro structures and, more importantly, by including true SARS-CoV-2 3CL-Pro inhibitors (as learning set) when available.     

Computational Approaches to Discover Novel Natural Compounds for SARS-CoV-2 Therapeutics

Scientists all over the world are facing a challenging task of finding effective therapeutics for the coronavirus disease (COVID-19). One of the fastest ways of finding putative drug candidates is the use of computational drug discovery approaches. The purpose of the current study is to retrieve natural compounds that have obeyed to drug-like properties as potential inhibitors. Computational molecular modelling techniques were employed to discover compounds with potential SARS-CoV-2 inhibition properties. Accordingly, the InterBioScreen (IBS) database was obtained and was prepared by minimizing the compounds. To the resultant compounds, the absorption, distribution, metabolism, excretion and toxicity (ADMET) and Lipinski's Rule of Five was applied to yield drug-like compounds. The obtained compounds were subjected to molecular dynamics simulation studies to evaluate their stabilities. In the current article, we have employed the docking based virtual screening method using InterBioScreen (IBS) natural compound database yielding two compounds has potential hits. These compounds have demonstrated higher binding affinity scores than the reference compound together with good pharmacokinetic properties. Additionally, the identified hits have displayed stable interaction results inferred by molecular dynamics simulation results. Taken together, we advocate the use of two natural compounds, STOCK1N-71493 and STOCK1N-45683 as SARS-CoV-2 treatment regime.