机械制图课改中三维模型库的开发和研究

针对机械制图课程教学中普遍存在的教学模型及挂图数量不足、教学难度大等问题,简述了使用SolidWorks软件建立三维实体模型的过程以及机械制图虚拟模型库的设计流程、内容组成、网络发布等。实践证明,该模型库的设计是成功的,不仅弥补了实物模型库的不足,而且具有更多优势。     

Methods and Applications of In Silico Aptamer Design and Modeling

Aptamers are nucleic acid analogues of antibodies with high affinity to different targets, such as cells, viruses, proteins, inorganic materials, and coenzymes. Empirical approaches allow the design of in vitro aptamers that bind particularly to a target molecule with high affinity and selectivity. Theoretical methods allow significant expansion of the possibilities of aptamer design. In this study, we review theoretical and joint theoretical-experimental studies dedicated to aptamer design and modeling. We consider aptamers with different targets, such as proteins, antibiotics, organophosphates, nucleobases, amino acids, and drugs. During nucleic acid modeling and in silico design, a full set of in silico methods can be applied, such as docking, molecular dynamics (MD), and statistical analysis. The typical modeling workflow starts with structure prediction. Then, docking of target and aptamer is performed. Next, MD simulations are performed, which allows for an evaluation of the stability of aptamer/ligand complexes and determination of the binding energies with higher accuracy. Then, aptamer/ligand interactions are analyzed, and mutations of studied aptamers made. Subsequently, the whole procedure of molecular modeling can be reiterated. Thus, the interactions between aptamers and their ligands are complex and difficult to understand using only experimental approaches. Docking and MD are irreplaceable when aptamers are studied in silico.     

Selective Binding of Cyclodextrins with Leflunomide and Its Pharmacologically Active Metabolite Teriflunomide

The selectivity of encapsulation of leflunomide and teriflunomide by native α-, β- and γ-cyclodextrins was investigated through ¹H NMR and molecular modeling. Thermodynamic analysis revealed the main driving forces involved in the binding. For α-cyclodextrin, the partial encapsulation was obtained while deep penetration was characterized for the other two cyclodextrins, where the remaining polar fragment of the molecule is located outside the macrocyclic cavity. The interactions via hydrogen bonding are responsible for high negative enthalpy and entropy changes accompanying the complexation of cyclodextrins with teriflunomide. These results were in agreement with the molecular modeling calculations, which provide a clearer picture of the involved interactions at the atomic level.     

基于BIM技术和有限元的检测与分析在PC结构中的应用研究

本文建立了PC结构施工全过程的BIM模型及有限元分析模型,对施工过程进行数值模拟与动态、静态监测,对装配式结构进行了结构性能评价,为结构可视化施工监测提供了技术支持。     

Computational Analysis of the Solid-State and Solvation Properties of Carbamazepine in Relation to its Polymorphism

The solvent-dependent polymorphism of the active pharmaceutical ingredient (API) carbamazepine is interpreted from calculations of the solid-state and API-solvent intermolecular interactions. These simulations suggested that apolar solute-solute interactions could be disrupted by apolar solvents. In contrast, the polar solute-solute interactions were found to be easily disrupted by polar and protic solvents. This is consistent with experimental observations that the crystallization of the metastable form II is more dominant in apolar solvents. The Mercury program remains the gold standard in terms of usability; however, further expansion into more complex simulation techniques could make this package of even greater use in pharmaceutical manufacturing workflows.     

球头铣刀铣削球面的表面形貌建模与仿真研究

基于齐次坐标矩阵变换原理和矢量运算法则，建立了工件坐标系下球头铣刀扫掠面的数学模型，基于Z-MAP法设计了球形表面形貌的生成算法，利用该算法对球头铣刀分别采用3D环绕法和放射加工法这两种典型走刀路线加工凸球面，并对加工后的表面形貌进行了仿真，通过分析对比仿真结果，发现3D环绕法更有利于减小表面粗糙度。同时，仿真结果和试验结果具有较高的吻合度，表明该仿真方法是可靠的，可以用于实际生产中球头铣刀铣削球面表面形貌的预测。     

Coupling in situ experiments and modeling – Opportunities for data fusion,machine learning,and discovery of emergent behavior

This paper reviews recent studies, that not only includes both experiments and modeling components, but celebrates a close coupling between these techniques, in order to provide insights into the plasticity and failure of polycrystalline metals. Examples are provided of studies across multiple-scales, including, but not limited to, density functional theory combined with atom probe tomography, molecular dynamics combined with in situ transmission electron miscopy, discrete dislocation dynamics combined with nanopillars experiments, crystal plasticity combined with digital image correlation, and crystal plasticity combined with in situ high energy X-ray diffraction. The close synergy between in situ experiments and modeling provides new opportunities for model calibration, verification, and validation, by providing direct means of comparison, thus removing aspects of epistemic uncertainty in the approach. Further, data fusion between in situ experimental and model-based data, along with data driven approaches, provides a paradigm shift for determining the emergent behavior of deformation and failure, which is the foundation that underpins the mechanical behavior of polycrystalline materials.     

Spray Drying of Lactobacillus plantarum WCFS1 Guided by Predictive Modeling

Shelf life of probiotic microorganisms can be retained by drying. Spray drying is an economically interesting alternative to freeze drying with that respect. However, the viability can decrease due to the drying process and testing it is laborious and expensive. This research shows that the viability of Lactobacillus plantarum WCFS1 during pilot scale drying can be predicted with kinetics gathered at a single droplet level. Using this approach, it could be demonstrated that the viability of L. plantarum WCFS1 during spray drying is mainly determined by the combination of temperature and moisture content during the first 0.5 seconds after atomization. The combination of a high moisture content and a high temperature appeared most detrimental to the residual viability. Moreover, it was found to be important to take into account the particle size distribution during atomization when predicting viability, since this has a large effect on the moisture content during this first 0.5 seconds. Finally, it was observed that shelf life during storage was mainly determined by the moisture content of the powder. A lower moisture content resulted in a higher viability. Above a moisture content of 6%, shelf life stability rapidly decreased in the applied maltodextrin (DE = 16) matrix.     

Mathematical Modeling of a Simulated Moving‐Bed Adsorption Process: Parex™ Technology as a Case Study

A simplified dynamic mathematical model for a simulated moving‐bed adsorption process is presented. The model is adopted to simulate the separation process of p‐xylene from the other 8‐carbon aromatics by means of the Parex^? technology. Operating conditions and the moving‐bed structure for a commercial plant were used and the performance of the unit was simulated. The model results are in good agreement with the findings of similar existing studies. Comparison of the results of this simplified model with those obtained by other researches indicates a considerable decrease in central processing unit (CPU) time.     

Multiple surrogate based optimization of a bidirectional impulse turbine for wave energy conversion

Oscillating water column based wave energy extracting system has a low efficiency due to the poor performance of its principal power extracting component, the bidirectional turbine. In the present work, flow over a bidirectional impulse turbine was simulated using CFD technique and optimized using multiple surrogates approach. The surrogates being problem dependent may produce unreliable results, if a wrong surrogate is selected. Hence, multiple surrogates such as response surface approximation, radial basis function, Kriging and weighted average surrogates were incorporated in this problem. Same design points were used to generate multiple optima via multiple surrogates to enhance the robustness of the optimization process. Numbers of guide vanes and rotor blades were chosen as the design variables, and the objective was to maximize the blade efficiency. Reynolds-averaged Navier–Stokes equations were solved for analyzing the flow physics. The computed results were used to train the surrogates and find the optimal points via hybrid genetic algorithm. The surrogates were further applied to find the optimal flow parameters by changing flow velocity and turbine speed. The relative efficiency enhancement through our present approach was about 16%. Detailed methodologies, analysis of the results and surrogate applicability have been presented in this paper.