Nonlinear dynamic behaviors and control based on simulation of high-purity heat integrated air separation column

In this paper, the dynamic behaviors on the basis of simulation for high-purity heat integrated air separation column (HIASC) are studied. A nonlinear generic model control (GMC) scheme is proposed based on the nonlinear behavior analyses of a HIASC process, and an adaptive generic model control (AGMC) scheme is further presented to correct the model parameters online. Related internal model control (IMC) scheme and multi-loop PID (M-PID) scheme are also developed as the comparative base. The comparative researches are carried out among these linear and nonlinear control schemes in detail. The simulation research results show that the proposed AGMC schemes present advantages in both servo control and regulatory control for the high-purity HIASC.     

Simulation of thermal barrier coating spallation induced by the initiation/growth/coalescence of internal crack and interfacial crack based on a real image model

In the furnace cycle test, the growth of oxide film leads to the propagation and coalescence of multiple cracks near the interface, which should be responsible for the spallation of thermal barrier coatings (TBCs). A TBC model with real interface morphology is created, and the near-interface large pore is retained. The purpose of this work is to clarify the mechanism of TBC spallation caused by successive initiation, propagation, and linkage of cracks near the interface during thermal cycle. The dynamic growth of thermally grown oxide (TGO) is carried out by applying a stress-free strain. The crack nucleation and arbitrary path propagation in YSZ and TGO are simulated by the extended finite element method (XFEM). The debonding along the YSZ/TGO/BC interface is evaluated using a surface-based cohesive behavior. The large-scale pore in YSZ near the interface can initiate a new crack. The ceramic crack can propagate to the YSZ/TGO interface, which will accelerate the interfacial damage and debonding. For the TGO/BC interface, the normal compressive stress and small shear stress at the valley hinder the further crack propagation. The growth of YSZ crack and the formation of through-TGO crack are the main causes of TBC delamination. The accelerated BC oxidation increases the lateral growth strain of TGO, which will promote crack propagation and coalescence. The optimization design proposed in this work can provide another option for developing TBC with high durability.     

Revisiting the Parallel Strategy for DOACROSS Loops

Journal of Computer Science and Technology - DOACROSS loops are significant parts in many important scientific and engineering applications, which are generally exploited pipeline/wave-front...     

Mixture ratio modeling of dynamic systems

Any knowledge extraction relies (possibly implicitly) on a hypothesis about the modelled-data dependence. The extracted knowledge ultimately serves to a decision-making (DM). DM always faces uncertainty and this makes probabilistic modelling adequate. The inspected black-box modeling deals with “universal” approximators of the relevant probabilistic model. Finite mixtures with components in the exponential family are often exploited. Their attractiveness stems from their flexibility, the cluster interpretability of components and the existence of algorithms for processing high-dimensional data streams. They are even used in dynamic cases with mutually dependent data records while regression and auto-regression mixture components serve to the dependence modeling. These dynamic models, however, mostly assume data-independent component weights, that is, memoryless transitions between dynamic mixture components. Such mixtures are not universal approximators of dynamic probabilistic models. Formally, this follows from the fact that the set of finite probabilistic mixtures is not closed with respect to the conditioning, which is the key estimation and predictive operation. The paper overcomes this drawback by using ratios of finite mixtures as universally approximating dynamic parametric models. The paper motivates them, elaborates their approximate Bayesian recursive estimation and reveals their application potential.     

Growth,mechanical properties,and tribological performance of TiAlN/NbN and NbN/TiAlN bilayer coatings

Three different coatings, namely TiAlN, TiAlN (external)/NbN (internal) and NbN (external)/TiAlN (internal), were deposited on cemented carbides by arc ion plating. The comparative investigation conducted in this study elucidates the effect of the NbN layer and coating systems on the growth, mechanical properties, and tribological performance of the coatings. The results showed that the surface of the TiAlN and TiAlN/NbN coatings was smoother when TiAlN served as the external layer. The NbN/TiAlN coating, wherein NbN formed the external layer, had a much rougher but more symmetrical surface. With the introduction of the NbN layer, the increased micro stress induced a lower adhesion strength in the TiAlN/NbN and NbN/TiAlN coatings. The TiAlN/NbN and NbN/TiAlN coatings exhibited higher hardness and hardness/effective elastic modulus (H/E*). During the friction test, when the temperature was elevated to 700 °C, the tribological performance of the monolayer TiAlN coating was the lowest because of the TiO₂-induced breakage of the dense tribo-oxide film. The NbN layer participated in the formation of a NbO_x film at elevated temperatures, which was responsible for the high tribological performance of the two bilayer coatings. When the NbN layer was on the outermost layer and in direct contact with the elevated temperature atmosphere, the NbN/TiAlN coating generated a tribo-oxide film with high integrity, and its coefficient of friction decreased by 27% of that at room temperature. Therefore, the NbN/TiAlN coating exhibited the highest wear resistance at 700 °C.     

Supramolecular Glyco‐nanoparticles Toward Immunological Applications

Glyco‐mimicking nanoparticles (glyco‐NPs) with Förster resonance energy transfer (FRET) donor and acceptor groups formed via dynamic covalent bond of benzoboroxole and sugar from two complementary polymers are prepared. The glyco‐NPs are proved to be quite stable under physiological conditions but sensitive to pH. So the glyco‐NPs can be internalized by dendritic cells with integrity and nontoxicity and then dissociate within the acidic organelles. This particle dissociation is directly observed and visualized in vitro, for the first time via the FRET measurements and fluorescent microscopy. This feature makes controlled release of drug or protein by glyco‐NPs possible, i.e., when model antigen Ovalbumin is loaded in the glyco‐NPs, the released Ovalbumin in dendritic cells stimulates T cells more efficiently than the free Ovalbumin itself as a result of the enhanced antigen processing and presentation. Thus, the results enlighten a bright future of the glyco‐NPs in immunotherapy.     

Crystallization of progesterone polymorphs using polymer-induced heteronucleation (PIHn) method

Progesterone is a natural hormone steroid used in humans for several treatments and in livestock for artificial insemination, which exhibits two polymorphic forms at ambient conditions: form 1 and form 2. Form 2 is metastable and more soluble than form 1; however, it is not suitable to use as powder raw material because it transforms into form 1 by the effects of grinding. A polymorphic screening of progesterone based on polymer-induced heteronucleation method was performed as an alternative to prepare the metastable form. Polyvinyl alcohol, hydroxypropyl methylcellulose (HPMC), dextran, gelatin, polyisoprene (PI) and acrylonitrile-butadiene (NBR) copolymer were used. Crystals were prepared from 0.5, 10 and 40?mg/mL solutions in acetone at room temperature by solvent evaporation. The samples were characterized by X-ray powder diffraction, differential scanning calorimetry (DSC), scanning electron microcopy and attenuated total reflectance infrared Fourier transform spectroscopy. Form 1 was nucleated from 40?mg/mL solutions on the six polymers and from 10?mg/mL solutions on PI and NBR. The mixture of form 1 and form 2 was obtained from 10?mg/mL solution on HPMC, dextran and gelatin and from 0.5?mg/mL solution crystallizations. Therefore, the polymeric devices, which crystallized the metastable and more soluble polymorph (2) of progesterone, would be a promissory alternative for the pharmaceutical applications.     

动态高压微射流处理对方竹笋膳食纤维理化及结构特性的影响

以方竹笋中提取的膳食纤维为研究对象，采用动态高压微射流（dynamic high-pressure micro-fluidization, DHPM）在不同压力条件（0，50，100，150，200 MPa）下进行处理，探究其对竹笋膳食纤维（bamboo shoots dietary fiber, BSDF）理化和结构特性的影响。结果表明，随着处理压力的增大，BSDF粒径先增大后减小，当处理压力为150 MPa时，粒径最小，为（370±11） nm，此条件下BSDF的持水力、持油力和膨胀力达到最大，较对照组分别提高了47.74%，50.54%，61.27%，且差异显著（P<0.05）。红外光谱分析表明DHPM处理不会改变BSDF的官能团，但会使BSDF内部的部分氢键断裂和半纤维素、木质素等发生降解；X射线衍射和热重分析表明DHPM处理不会引起BSDF的晶体结构改变，但晶体有序度会下降，进而导致其热稳定性降低；微观结构分析显示DHPM处理会使BSDF颗粒尺寸减小、表面粗糙、组织松散，且当处理压力为200 MPa时，颗粒发生团聚。综上，DHPM可以有效改善BSDF的理化性质，在膳食纤维改性方面具有一定的应用价值。     

光照水电站装设筒形阀分析

筒形阀是一种新型的水轮机进水阀,它与球阀或蝴蝶阀相比较有防止机组飞逸事故扩大效果明显、减轻导叶全关时导水机构的快速破坏并减少漏水量,以及动水开启方便、所需时间短等优点,但对运行条件也有一定的要求。光照水电站是贵州省第1个拟采用筒形阀的电站,为此对装设筒形阀的可行性和必要性进行了认真的分析。     

Model Selection for Unsupervised Learning of Visual Context

This study addresses the problem of choosing the most suitable probabilistic model selection criterion for unsupervised learning of visual context of a dynamic scene using mixture models. A rectified Bayesian Information Criterion (BICr) and a Completed Likelihood Akaike’s Information Criterion (CL-AIC) are formulated to estimate the optimal model order (complexity) for a given visual scene. Both criteria are designed to overcome poor model selection by existing popular criteria when the data sample size varies from small to large and the true mixture distribution kernel functions differ from the assumed ones. Extensive experiments on learning visual context for dynamic scene modelling are carried out to demonstrate the effectiveness of BICr and CL-AIC, compared to that of existing popular model selection criteria including BIC, AIC and Integrated Completed Likelihood (ICL). Our study suggests that for learning visual context using a mixture model, BICr is the most appropriate criterion given sparse data, while CL-AIC should be chosen given moderate or large data sample sizes.