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.     

Adaptive robust boundary control of shaft vibrations under perturbations with unknown upper bounds

This paper presents robust and adaptive boundary control designs to stabilize the two‐dimensional vibration of hybrid shaft model. The hybrid shaft is mathematically represented by a set of partial differential equations, governing the shaft vibrations, coupled to ordinary differential equations, describing rigid body spinning and dynamic boundary conditions. The control objective is to stabilize the transverse vibrations of the perturbed shaft while regulating the spinning rate. To achieve this, the paper first establishes robust boundary control laws that fulfil the control objective in the presence of modeling uncertainties and external disturbances operating over the shaft domain and boundary. Lyapunov‐based analyses show that the proposed robust control exponentially stabilizes the shaft with vanishing distributive perturbations, while assuring ultimately bounded vibrations in the case of nonvanishing perturbations. Then, adaptive control philosophy is utilized to achieve redesigned robust controllers that only use online adaptation of control gains without acquiring the knowledge of bounds on perturbations, as well as dynamic parameters. An advantage of this design is avoiding an overconservative robust control law, which may induce poor stability and chattering in tackling system perturbations with unknown upper bounds. Simulations through finite element method illustrate the results. Copyright © 2014 John Wiley & Sons, Ltd.     

Combined hardware–software multi-parallel prefiltering on the Convey HC-1 for fast homology detection

Protein databases used in research are huge and still grow at a fast pace. Many comparisons need to be done when searching similar (homologous) sequences for a given query sequence in these databases. Comparing a query sequence against all sequences of a huge database using the well-known Smith–Waterman algorithm is very time-consuming. Hidden Markov Models pose an opportunity for reducing the number of entries of a database and also enable to find distantly homologous sequences. Fewer entries are achieved by clustering similar sequences in a Hidden Markov Model. Such an approach is used by the bioinformatics tool HHblits. To further reduce the runtime, HHblits uses two-level prefiltering to reduce the number of time-consuming Viterbi comparisons. Still, prefiltering is very time-consuming. Highly parallel architectures and huge bandwidth are required for processing and transferring the massive amounts of data. In this article, we present an approach exploiting the reconfigurable, hybrid computer architecture Convey HC-1 for migrating the most time-consuming part. The Convey HC-1 with four FPGAs and high memory bandwidth of up to 76.8 GB/s serves as the platform of choice. Other bioinformatics applications have already been successfully supported by the HC-1. Limited by FPGA size only, we present a design that calculates four first-level prefiltering scores per FPGA concurrently, i.e. 16 calculations in total. This score calculation for the query profile against database sequences is done by a modified Smith–Waterman scheme that is internally parallelized 128 times in contrast to the original Streaming ‘Single Instruction Multiple Data (SIMD)’ Extensions (SSE)-supported implementation where only 16-fold parallelism can be exploited and where memory bandwidth poses the limiting factor. Preloading the query profile, we are able to transform the memory-bound implementation to a compute- and resource-bound FPGA design. We tightly integrated the FPGA-based coprocessor into the hybrid computing system by employing task-parallelism for the two-level prefiltering. Despite much lower clock rates, the FPGAs outperform SSE-based execution for the calculation of the prefiltering scores by a factor of 7.9.     

Rapid detection of viable Bacillus cereus emetic and enterotoxic strains in food by coupling propidium monoazide and multiplex PCR (PMA-mPCR)

Bacillus cereus can cause emetic and diarrheal food poisoning. It is widespread in nature and therefore, considered a major foodborne pathogen. To develop a sensitive and reliable assay for detecting enterotoxin genes (nheA, entFM, hblD, cytK) and emetic toxin (ces), specific primers each targeting one individual gene were designed. Propidium monoazide (PMA) was coupled with the developed multiplex PCR (mPCR) for the detection of viable B. cereus. The inclusivity and exclusivity of the PMA-mPCR was confirmed using a panel of 44 strains including 17 emetic and 9 enterotoxic B. cereus reference strains and 18 non-target strains. The limit of detection (LOD) without PMA treatment in pure DNA was 2 pg/reaction tube. The LOD of mPCR assay in pure heat-killed dead bacteria was 4.0 × 10² CFU/mL. Also, the LOD on the viable bacteria with or without PMA treatment was similar (3.8 × 10² CFU/mL) showing that the PMA treatment did not significantly decrease sensitivity. Finally, the newly developed PMA-mPCR successfully detected 4.8 × 10³ and 3.6 × 10³ CFU/g of viable B. cereus F4810/72 (emetic) and B. cereus ATCC 12480 (enterotoxic) reference strains, respectively, in food samples. Hence, this study combines PMA and mPCR to detect viable B. cereus with a wide range of toxin detection (5 toxins). Thus, the novel PMA-mPCR assay developed in this study is a rapid and efficient diagnostic tool for the monitoring of viable B. cereus in food samples and potentially other samples via appropriate DNA extraction.     

Hydrocarbon-based electrode ionomer for proton exchange membrane fuel cells

The electrode ionomer is a key factor that significantly affects the catalyst layer morphology and fuel cell performance. Herein, sulfonated poly(arylene ether sulfone)-based electrode ionomers with polymers of various molecular weights and alcohol/water mixtures were prepared, and those comprising the alcohol/water mixture showed a higher performance than the ones prepared using higher boiling solvents, such as dimethylacetamide; this is owing to the formation of the uniformly dispersed ionomer catalyst layer. The relation between ionomer molecular weight for the same polymer structure and the sulfonation degree was investigated. Because the chain length of polymer varies with molecular weight and chain entanglement degree, its molecular weight affects the electrode morphology. As the ionomer covered the catalyst, the agglomerates formed were of different morphologies according to their molecular weight, which could be deduced indirectly through dynamic light scattering and scanning electron microscopy. Additionally, the fuel cell performance was confirmed in the current-voltage curve.     

基于空气质量模拟的江苏省大气污染物排放清单比较研究

大气污染物排放清单是空气质量模拟和空气污染治理的重要依据.本研究比较分析了两套覆盖江苏省的2017年大气污染物排放清单，即分别由上海市环境科学研究院、江苏省环境科学研究院编制的"长三角清单"和"江苏省清单"，并结合区域空气质量模型CMAQ评估不同清单对长三角地区2017年1、4、7、10月的空气质量模拟的影响.清单比较结果表明，除二氧化硫（SO₂）以外，江苏省清单估算的各污染物排放量较长三角清单低.通过与观测数据比较，发现两套清单对SO₂、氮氧化物（NO_x）、臭氧（O₃）和细颗粒物（PM_2.5）的模型模拟性能均较好.江苏省清单与长三角清单两者的模拟结果空间分布接近，其中江苏省清单模拟的PM_2.5和O₃在长三角多数地区略低于长三角清单的模拟结果（1月O₃除外）.江苏省清单与长三角清单均能够用于空气质量模式模拟，可为江苏地区的细颗粒物和光化学烟雾污染的控制策略制定提供参考.     

Formulation of sage essential oil (Salvia officinalis,L.) monoterpenes into chitosan hydrogels and permeation study with GC-MS analysis

This study deals with the formulation of natural drugs into hydrogels. For the first time, compounds from the sage essential oil were formulated into chitosan hydrogels. A sample preparation procedure for hydrophobic volatile analytes present in a hydrophilic water matrix along with an analytical method based on the gas chromatography coupled with the mass spectrometry (GC-MS) was developed and applied for the evaluation of the identity and quantity of essential oil components in the hydrogels and saline samples. The experimental results revealed that the chitosan hydrogels are suitable for the formulation of sage essential oil. The monoterpene release can be effectively controlled by both chitosan and caffeine concentration in the hydrogels. Permeation experiment, based on a hydrogel with the optimized composition [3.5% (w/w) sage essential oil, 2.0% (w/w) caffeine, 2.5% (w/w) chitosan and 0.1% (w/w) Tween-80] in donor compartment, saline solution in acceptor compartment, and semi-permeable cellophane membrane, demonstrated the useful permeation selectivity. Here, (according to lipophilicity) an enhanced permeation of the bicyclic monoterpenes with antiflogistic and antiseptic properties (eucalyptol, camphor and borneol) and, at the same time, suppressed permeation of toxic thujone (not exceeding its permitted applicable concentration) was observed. These properties highlight the pharmaceutical importance of the developed chitosan hydrogel formulating sage essential oil in the dermal applications.     

Simultaneous synthesis of a heat exchanger network with multiple utilities using utility substages

Heat exchanger network synthesis (HENS) has progressed by using mathematical programming-based simultaneous methodology. Although various considerations such as non-isothermal mixing and bypass streams are applied to consider real world alternatives in modeling phase, many challenges are faced because of its properties within non-convex mixed-integer nonlinear programming (MINLP). We propose a modified superstructure, which contains a utility substage for use in considering multiple utilities in a simultaneous MINLP model. To improve model size and convergence, fixed utility locations according to temperature and series connections between utilities are suggested. The numbers of constraints, discrete, and continuous variables show that overall model size decreases compared with previous research. Thus, it is possible to expand the feasible search area for reaching the nearest global solution. The model's effectiveness and applications are exemplified by several literature problems, where it is used to deduce a network superior to that of any other reported methodology.     

Friction compensation controller for load varying machine tool feed drive

The load applied to a machine tool feed drive changes during the machining process as material is removed. This load change alters the Coulomb friction of the feed drive. Because Coulomb friction accounts for a large part of the total friction the friction compensation control accuracy of the feed drives is limited if this nonlinear change in the applied load is not considered. This paper presents a new friction compensation method that estimates the machine tool load in real time and considers its effect on friction characteristics. A friction observer based on a Kalman filter with load estimation is proposed for friction compensation control considering the applied load change. A specially designed feed drive testbed that enables the applied load to be modified easily was constructed for experimental verification. Control performance and friction estimation accuracy are demonstrated experimentally using the testbed.