Physical evaluation of a maize‐based extruded snack with curry powder

Response surface methodology was used to analyze the effect of screw speed (200–280 rpm), feed moisture (13.0–17.0%, wet basis), and curry powder (6.0–9.0%) on the bulk density, lateral expansion, and firmness of maize‐based extruded snack with curry powder. Regression equations describing the effect of each variable on the responses were obtained. Responses were most affected by changes in feed moisture followed by screw speed and curry powder (p < 0.05). Lateral expansion increased linearly as the amount of curry powder added was increased whereas a quadratic increase was obtained in lateral expansion with decreasing feed moisture. The firmness of samples was increased with an increase in feed moisture. The bulk density of samples was increased with increasing feed moisture and screw speeds. Radial expansion was found to be a better index to measure the physical properties of the extruded product indicated by a higher correlation coefficient.     

Plastic Torsional Buckling of Cruciform Compression Members

In this paper the plastic torsional buckling of a cruciform column is revisited. The interest in this classical problem resurfaced from a practical application in the area of seismic protection of structures. The theoretical challenges associated with this problem emerge from the “paradoxial” differences between the plastic buckling strength that results from the total deformation and the incremental theories of plasticity. The paper shows that when the flanges of the column are not perfectly straight, the incremental theory of plasticity predicts that at the onset of plastic torsional buckling, the shear stress and the shear strain are related with the tangent shear modulus. The analysis presented herein involves a small-strain theory, examines the column at its slightly deformed configuration, and results are obtained with hand calculations. Experimental evidence supporting the theoretical findings is presented.     

Photomodulated thermoreflectance investigation of semiconducting implanted wafers

The non contact character of the photothermal technique makes it particularly attractive for the nondestructive evaluation of implanted materials. Photomodulated thermoreflectance (PMTR) can detect local variation in the reflectivity of the material caused by the modulated excursions of the surface temperature and plasma surface concentration. These measurements allow the estimation of certain characteristics such as local electronic, optical, and thermal parameters. In the case of implanted semiconductors, PMTR provides an indication of local degree of damage.     

Photothermal radiometry on nickel (pigmented aluminium oxide) selective solar absorbing surface coatings

Photothermal radiometry (PTR) is applied to characterize nickel-pigmented aluminium oxide solar absorbing coatings. A modulated laser beam is used to heat the solar samples. The subsequent emission of thermal radiation is measured as a function of modulated frequency in the range of 10 Hz to 10 kHz. A simple one-dimensional model is used to fit the experimental PTR results, allowing for the extraction of some thermal parameters for the solar absorbing coatings. Finally, comparison of the emissivity measured by traditional technique and the photothermal radiometry is made.     

开放创新与互操作性推动开放标准

信息技术（IT）行业正处于一个前所未有的互操作性和创新的时代。在不断增加的选择机会和创新产品中,用户是直接受益人。本文针对当今的IT行业,简要地论述了一些关键性问题,包括：（1）IT行业（以及其它行业）从“封闭创新”向“开放创新”转型;（2）在实现互操作性的过程中,互操作性的类型和行业、政府应起的作用;（3）“开放标准”公平的定义的重要性是确保知识产权（IP）所有者和使用者都有积极性,并一起努力开发和实施创新技术的解决方案。在本文的第四部分提出了一些建议,以期政府和决策者在制定影响这些重要领域的政策时,予以考虑。     

A feedback control framework for safe and economically‐optimal operation of nonlinear processes

Maintaining safe operation of chemical processes and meeting environmental constraints are issues of paramount importance in the area of process systems and control engineering, and are ideally achieved while maximizing economic profit. It has long been argued that process safety is fundamentally a process control problem, yet few research efforts have been directed toward integrating the rather disparate domains of process safety and process control. Economic model predictive control (EMPC) has attracted significant attention recently due to its ability to optimize process operation accounting directly for process economics considerations. However, there is very limited work on the problem of integrating safety considerations in EMPC to ensure simultaneous safe operation and maximization of process profit. Motivated by the above considerations, this work develops three EMPC schemes that adjust in real‐time the size of the safety sets in which the process state should reside to ensure safe process operation and feedback control of the process state while optimizing economics via time‐varying process operation. Recursive feasibility and closed‐loop stability are established for a sufficiently small EMPC sampling period. The proposed schemes, which effectively integrate feedback control, process economics, and safety considerations, are demonstrated with a chemical process example. © 2016 American Institute of Chemical Engineers AIChE J, 62: 2391–2409, 2016     

Proactive fault‐tolerant model predictive control

Fault‐tolerant control methods have been extensively researched over the last 10 years in the context of chemical process control applications, and provide a natural framework for integrating process monitoring and control aspects in a way that not only fault detection and isolation but also control system reconfiguration is achieved in the event of a process or actuator fault. But almost all the efforts are focused on the reactive fault‐tolerant control. As another way for fault‐tolerant control, proactive fault‐tolerant control has been a popular topic in the communication systems and aerospace control systems communities for the last 10 years. At this point, no work has been done on proactive fault‐tolerant control within the context of chemical process control. Motivated by this, a proactive fault‐tolerant Lyapunov‐based model predictive controller (LMPC) that can effectively deal with an incipient control actuator fault is proposed. This approach to proactive fault‐tolerant control combines the unique stability and robustness properties of LMPC as well as explicitly accounting for incipient control actuator faults in the formulation of the MPC. Our theoretical results are applied to a chemical process example, and different scenaria were simulated to demonstrate that the proposed proactive fault‐tolerant model predictive control method can achieve practical stability and efficiently deal with a control actuator fault. © 2013 American Institute of Chemical Engineers AIChE J, 59: 2810–2820, 2013     

A methodology for reliability analysis in health networks

A reliability model for a health care domain based on requirement analysis at the early stage of design of regional health network (RHN) is introduced. RHNs are considered as systems supporting the services provided by health units, hospitals, and the regional authority. Reliability assessment in health care domain constitutes a field-of-quality assessment for RHN. A novel approach for predicting system reliability in the early stage of designing RHN systems is presented in this paper. The uppermost scope is to identify the critical processes of an RHN system prior to its implementation. In the methodology, Unified Modeling Language activity diagrams are used to identify megaprocesses at regional level and the customer behavior model graph (CBMG) to describe the states transitions of the processes. CBMG is annotated with: 1) the reliability of each component state and 2) the transition probabilities between states within the scope of the life cycle of the process. A stochastic reliability model (Markov model) is applied to predict the reliability of the business process as well as to identify the critical states and compare them with other processes to reveal the most critical ones. The ultimate benefit of the applied methodology is the design of more reliable components in an RHN system. The innovation of the approach of reliability modeling lies with the analysis of severity classes of failures and the application of stochastic modeling using discrete-time Markov chain in RHNs.     

Dynamic optimization of dissipative PDE systems using nonlinear order reduction

This article presents computationally efficient methods for the solution of dynamic constraint optimization problems arising in the context of spatially distributed processes governed by highly dissipative nonlinear partial differential equations (PDEs). The methods are based on spatial discretization using the method of weighted residuals with spatially global basis functions (i.e., functions that cover the entire domain of definition of the process and satisfy the boundary conditions). More specifically, we perform spatial discretization of the optimization problems using the method of weighted residuals with analytical or empirical (obtained via Karhunen-Loève expansion) eigenfunctions as basis functions, and combination of the method of weighted residuals with approximate inertial manifolds. The proposed methods account for the fact that the dominant dynamics of highly dissipative PDE systems are low dimensional in nature and lead to approximate optimization problems that are of significantly lower order compared to the ones obtained from spatial discretization using finite-difference and finite-element techniques, and thus, they can be solved with significantly smaller computational demand. The resulting dynamic nonlinear programs include equality constraints that constitute a low-order system of coupled ordinary differential equations and algebraic equations, which can then be solved with combination of standard temporal discretization and nonlinear programming techniques. We employ backward finite differences (implicit Euler) to perform temporal discretization and solve the nonlinear programs resulting from temporal and spatial discretization using reduced gradient techniques (MINOS). We use two representative examples of dissipative PDEs, a diffusion-reaction process with constant and spatially varying coefficients, and the Kuramoto-Sivashinsky equation, a model that describes incipient instabilities in a variety of physical and chemical systems, to demonstrate the implementation and evaluate the effectiveness of the proposed optimization algorithms.