Second-order SM approach to SISO time-delay system output tracking

A fully linearizable single-input-single-output relative-degree n system with an output time delay is considered in this paper. Using the approach of Pade approximation, system center approach, and second-order sliding-mode (SM) control, we have obtained good output tracking results. The Smith predictor is used to compensate the difference between the actual delayed output and its approximation. A second-order supertwisting SM observer observes the disturbance in the plant. A nonlinear example is studied to show the effect of this methodology

Output tracking via sliding modes in causal systems with time delay modeled by higher order pade approximations

Output tracking in a SISO causal uncertain nonlinear system with an output subject to a time delay is considered using sliding mode control. A higher order Pade approximation to a delay function with a known time delay is used to construct a model of a transformed system without a time delayed output and is employed in a feedback sliding mode control. This model functions as a predictor of the plant states and the plant output, but is of nonminimum phase due to the application of the Pade approximation. The method of the stable system center is used to stabilize the internal dynamics of this plant model, and a control is developed using a sliding surface to allow the plant to track an arbitrary reference profile given by an exogenous system with a known characteristic equation. Simulations of the system are performed for the plant model using a first, second and third order Pade approximations and a controller in plant feedback mode. Numerical examples for Pade approximations of increasing order are considered and compare

Study on TBCs insulation characteristics of a turbine blade under serving conditions

AbstractIt is a key problem to study thermal barrier coatings (TBCs) insulation and followed stresses for the coated blade. This article focused on the insulation characteristics of TBCs by coupling heat transfer and flow with a multilayer blade. We found that the coated blade can benefit more in the decline of average temperature than the decline of maximum temperature, compared to the uncoated case. Temperature fluctuation on TBCs surface is evident. The inlet temperature of main flow (Tin) more than the heat transfer coefficient of cooling passages (hcool) impacted the fluctuation. And there is a non-homogeneous distribution of the temperature decline (ΔT) across the coatings around the blade. At the suction side and the head, ΔT was generally higher than that of the pressure side and the tail. The TBCs thickness and Tin can affect ΔT more than hcool. We suggest that in the sequential TBCs stresses simulation the actual temperature distribution should be prescribed

Improving gas sensing properties of graphene by introducing dopants and defects: a first-principles study

The interactions between four different graphenes (including pristine, B- or N-doped and defective graphenes) and small gas molecules (CO, NO, NO2 and NH3) were investigated by using density functional computations to exploit their potential applications as gas sensors. The structural and electronic properties of the graphene-molecule adsorption adducts are strongly dependent on the graphene structure and the molecular adsorption configuration. All four gas molecules show much stronger adsorption on the doped or defective graphenes than that on the pristine graphene. The defective graphene shows the highest adsorption energy with CO, NO and NO2 molecules, while the B- doped graphene gives the tightest binding with NH3. Meanwhile, the strong interactions between the adsorbed molecules and the modified graphenes induce dramatic changes to graphene's electronic properties. The transport behavior of a gas sensor using B- doped graphene shows a sensitivity two orders of magnitude higher than that of pristine graphene. This work reveals that the sensitivity of graphene-based chemical gas sensors could be drastically improved by introducing the appropriate dopant or defect

Efficient Multiscale Prediction of Cantilever Distortion by Selective Laser Melting

Large tensile residual stress is one major issue for metal components made by selective laser melting (SLM). Residual stress is induced by non-uniform heat input, which leads to part distortion and detrimentally affects product performance. The conventional single track simulation method is not feasible to predict the distortion of a macro part since it demands an exceedingly long computational time. The coupling multiphysics phenomenon during the SLM process further complicates this issue. In this study, a temperature-thread multiscale modeling approach has been developed to predict part distortion of a twin cantilever. An equivalent body heat flux calculated from the micro scan model was imported as the “temperature-thread” to the subsequent layer hatch model. Then the hatched layer with temperature field can be used as a basic unit to build up the macro part. The temperature history and residual stress fields during the SLM process were predicted. And the distortion of twin cantilever was calculated with a reasonable accuracy compared to the experimental data.Mechanical Engineerin

Long-distant contribution and χc1\chi_{c1} radiative decays to light vector meson

The discrepancy between the PQCD calculation and the CLEO data for $\chi_{c1}\to \gamma V$ ($V=\rho^0,\,\omega,\,\phi$) stimulates our interest in exploring extra mechanism of $\chi_{c1}$ decay. In this work, we apply an important non-perturbative QCD effect, i.e., hadronic loop mechanism, to study $\chi_{c1}\to \gamma V$ radiative decay. Our numerical result shows that the theoretical results including the hadronic loop contribution and the PQCD calculation of $\chi_{c1}\to \gamma V$ are consistent with the corresponding CLEO data of $\chi_{c1}\to \gamma V$. We expect further experimental measurement of $\chi_{c1}\to \gamma V$ at BES-III, which will be helpful to test the hadronic loop effect on $\chi_{c1}$ decay.Comment: 7 pages, 2 figures. Accepted for publication in Eur. Phys. J.

A Temperature-Thread Multiscale Modeling Approach for Efficient Prediction of Part Distortion by Selective Laser Melting

Selective laser melting (SLM) is a powder bed based additive manufacturing process to manufacture functional parts. The high-temperature process will produce large tensile residual stress which leads to part distortion and negatively affect product performance. Due to the complex process mechanism and coupling multi-physics phenomena, the micro-scale single laser scan modeling approach is not practical to predict macro part distortion since it demands an exceedingly long computational time. In this study, a temperature-based multiscale modeling approach has been developed to simulate material phase transition of powder-liquid-solid for fast prediction of part distortion. An equivalent body heat flux obtained from the micro-scale laser scan can be imported as “temperature-thread” to the subsequent layer hatching process. Then the hatched layer with temperature filed can be used as a basic unit to build up the macro-scale part with different scanning strategies. The temperature history and residual stress fields during the SLM process were obtained. In addition, the part distortion can be predicted with a reasonable accuracy by comparing with the experimental data.Mechanical Engineerin

Preparation and characterization of diamond–silicon carbide–silicon composites by gaseous silicon vacuum infiltration process

Diamond–SiC–Si composites have been prepared using gaseous silicon vacuum infiltration. The evolution of the phases and microstructures of the composites have been analyzed using X-ray diffraction technique and scanning electron microscopy. It has been found that the diamond–SiC–Si composite is composed of β-SiC, diamond, and residual Si. The diamond particles were distributed homogeneously in the dense matrix of the composites. Besides, the effects of particle size and content of diamond on the properties of diamond–SiC–Si composites have been analyzed. The thermal conductivity of the composites increases with particle size and content of diamond. When the particle size and content of diamond are 300 µm and 80 wt %, respectively, the thermal conductivity of the composites approaches the value of 280 W·m⁻¹·K⁻¹.Проведен анализ эволюции фаз и микроструктуры композитов алмаз–SiC–Si, изготовленных с использованием процесса вакуумной инфильтрации газообразного кремния. Исследование выполнено с помощью дифракции рентгеновских лучей и сканирующей электронной микроскопии. Установлено, что композит алмаз–SiC–Si состоит из β-SiC, алмаза и остаточного Si. Алмазные частицы распределены однородно в плотной матрице композитов. Также проанализировано влияние размера частиц и содержания алмазов на свойства композитов алмаз–SiC–Si. Показано, что теплопроводность композитов возрастает с увеличением размера частиц и содержания алмазов. Теплопроводность композитов приближается к значению 280 Вт∙м⁻¹∙K⁻¹ при размере частиц и содержании алмаза 300 мкм и 80 % (по массе), соответственно.Проведено аналіз еволюції фаз і мікроструктури композитів алмаз–SiC–Si, виготовлених з використанням процесу вакуумної інфільтрації газоподібного кремнію. Дослідження виконано за допомогою дифракції рентгенівських променів і скануючої електронної мікроскопії. Встановлено, що композит алмаз–SiC–Si складається з β-SiC, алмазу і залишкового Si. Алмазні частки розподілені однорідно в щільній матриці композитів. Також проаналізовано вплив розміру частинок і вмісту алмазів на властивості композитів алмаз–SiC–Si. Показано, що теплопровідність композитів зростає зі збільшенням розміру частинок і вмісту алмазів. Теплопровідність композитів наближається до значення 280 Вт∙м⁻¹∙K⁻¹ при розмірі частинок і вмісту алмазу 300 мкм і 80 % (за масою) відповідно.This work was financially supported by the National Natural Science Foundation of China (grant no. 51102282) and Aid Program for Science and Technology Innovative Research Team in Higher Educational Institutions of Hunan Province

Enhanced iron and zinc accumulation in genetically engineered wheat plants using sickle alfalfa (Medicago falcata L.) ferritin gene

Iron deficiency is the most common nutritional disorder, affecting over 30% of the world’s human population. The primary method used to alleviate this problem is nutrient biofortification of crops so as to improve the iron content and its availability in food sources. The over-expression of ferritin is an effective method to increase iron concentration in transgenic crops. For the research reported herein, sickle alfalfa (Medicago falcata L.) ferritin was transformed into wheat driven by the seed-storage protein glutelin GluB-1 gene promoter. The integration of ferritin into the wheat was assessed by PCR, RT-PCR and Western blotting. The concentration of certain minerals in the transgenic wheat grain was determined by inductively coupled plasma-atomic emission spectrometry, the results showed that grain Fe and Zn concentration of transgenic wheat increased by 73% and 44% compared to nontransformed wheat, respectively. However, grain Cu and Cd concentration of transgenic wheat grain decreased significantly in comparison with non-transformed wheat. The results suggest that the over-expression of sickle alfalfa ferritin, controlled by the seed-storage protein glutelin GluB-1 gene promoter, increases the grain Fe and Zn concentration, but also affects the homeostasis of other minerals in transgenic wheat grain

Simulation of the stochastic wave loads using a physical modeling approach

In analyzing stochastic dynamic systems, analysis of the system uncertainty due to randomness in the loads plays a crucial role. Typically time series of the stochastic loads are simulated using traditional random phase method. This approach combined with fast Fourier transform algorithm makes an efficient way of simulating realizations of the stochastic load processes. However it requires many random variables, i.e. in the order of magnitude of 1000, to be included in the load model. Unfortunately having too many random variables in the problem makes considerable difficulties in analyzing system reliability or its uncertainty. Moreover applicability of the probability density evolution method on engineering problems faces critical difficulties when the system embeds too many random variables. Hence it is useful to devise a method which can make realization of the stochastic load processes with low, say less than 20, number of random variables. In this article we introduce an approach, so-called "physical modeling of stochastic processes", and show its applicability for simulation of the wave surface elevation.</jats:p