Evaluation of decision fusion strategies for effective collaboration among heterogeneous fault diagnostic methods

Numerous methodologies for fault detection and identification (FDI) in chemical processes have been proposed in literature. However, it is extremely difficult to design a perfect FDI method to efficiently monitor an industrial-scale process. In this work, we seek to overcome this difficulty by using multiple heterogeneous FDI methods and fusing their results so that the strengths of the individual FDI methods are combined and their shortcomings overcome. Several decision fusion strategies can be used for this purpose. In this paper, we study the relative benefits of utility-based and evidence-based decision fusion strategies. Our results from a lab-scale distillation column and the popular Tennessee Eastman challenge problem show that in situations where no single FDI method offers adequate performance, evidence-based fusion strategies such as weighted voting, Bayesian, and Dempster-Shafer based fusion can provide (i) complete fault coverage, (ii) more than 40% increase in overall fault recognition rate, (iii) significant improvement in monitoring performance, and (iv) reduction in fault detection and diagnosis delays.     

Sequential methodology for integrated optimization of energy and water use during batch process scheduling

Though commonly encountered in practice, energy and water minimization simultaneously during batch process scheduling has been largely neglected in literature. In this paper, we present a novel framework for incorporating simultaneous energy and water minimization in batch process scheduling. The overall problem is decomposed into three parts - scheduling, heat integration, and water reuse optimization - and solved sequentially. Our approach is based on the precept that in any production plant, utilities (energy and water) consumption is subordinate to the production target. Hence, batch scheduling is solved first to meet an economic objective function. Next, alternate schedules are generated through a stochastic search-based integer cut procedure. For each resulting schedule, minimum energy and water reuse targets are established and networks identified. As illustrated using two well-known case studies, a key feature of this approach is its ability to handle problems that are too complex to be solved using simultaneous methods.     

镍-磷-硫酸钡化学复合镀层的研制

在由硫酸镍31g/L、次磷酸钠22g/L、乙醇酸30g/L、乙酸钠13g/L、二甲胺0.8g/L、全氟乙基碘化铵0.1g/L及重晶石(即硫酸钡)0～25g/L组成的稳定镀液中,采用化学镀的方法在低碳钢上制备了Ni-P-BaSO4复合镀层.其表面形貌采用扫描电镜进行分析,耐蚀性以动电位极化及电化学阻抗谱测试.镍-磷合金基...     

镍–磷–碳化硼化学复合镀层的研制(英文)

在由碳酸镍15g/L、次磷酸32mL/L、次磷酸钠15g/L、乳酸32mL/L、乙酸18g/L、丙酸3mL/L、二甲胺1.7g/L及碳化硼(即B4C)0～25g/L组成的稳定镀液中,采用化学镀的方法在低碳钢上制备了Ni–P–B4C复合镀层。其显微硬度采用韦氏硬度法测量,耐磨性用Taber磨耗试验机测量,微观形貌和组织采用扫描电镜和X射线衍射进行分析,耐蚀性以动电位极化及电化学阻抗谱测定。碳化硼的掺入提高了镍–磷合金基体的显微硬度、耐磨性和耐蚀性。Ni–P–B4C复合镀层颗粒粗大,具有爆米花式组织结构。     

Phase-based supervisory control for fermentation process development

Supervisory control of fed-batch fermentation processes is a difficult problem because the process is inherently non-linear, operated at unsteady state, and often poorly modeled. This problem is exacerbated in laboratory and pilot-plant applications due to lack of historical data from similarly operated batches. In this paper, we propose an approach for the supervisory control of fed-batch fermentation during process development. Transitions in the process are explicitly modeled and characterized using simple multivariate rules. Online data is then used to identify the occurrence of transitions and thus track the process across different phases. Supervisory control actions such as sequence control, phase-specific regulatory controllers and alarm settings are then subsequently executed based on this knowledge of the current phase. One key advantage of this approach is that it does not require detailed process knowledge or extensive process data and is thus well suited for application in process development. This approach has been implemented as an online expert system, called iProphet, and successfully tested on two laboratory-scale process development case studies—a bacterial (Escherichia coli) fermentation and laboratory-scale yeast (Pichia pastoris) fermentation. The approach and results from the two case studies are presented.     

A feedback-based implementation scheme for batch process optimization

The terminal-cost optimization of a control–affine nonlinear system leads to a discontinuous solution that can be characterized in a piecewise manner. To implement such an optimal trajectory despite disturbances and parametric uncertainty, a cascade optimization scheme is proposed in this paper, where optimal reference signals are tracked. Optimality is achieved by the appropriate definition of reference signals (input bounds, state constraints, or switching functions) to track in various sub-intervals. Furthermore, conservatism is introduced into the optimization problem to ensure satisfaction of path constraints in the presence of uncertainty. Finally, the proposed cascade optimization scheme is illustrated on a simulation of a fed-batch penicillin fermentation plant.     

Synthesis,Characterization, and Evaluation of Gel‐Type Poly(4‐Vinylpyridine) Resins for Plutonium Sorption

Abstract

Three different cross‐linked (4, 8, and 12%) gel‐type strong‐base poly(4‐vinylpyridine) resins (PVP) have been synthesized and characterized by elemental analysis, IR, exchange capacity, and moisture content. The uptake of plutonium and uranium was measured as a function of nitric acid concentration using all the three PVP resins. Plutonium sorption and elution kinetics experiments were also performed on all three PVP resins and compared with the benchmark, a gel‐type quarternary ammonium type anion‐exchange resin. The plutonium sorption rate decreases with the increase in cross‐linkage of the resin. All the three PVP resins exhibit better elution kinetics compared to the benchmark. The results on kinetic experiments performed on all three‐gel‐type resins indicated 8% gel‐type PVP resin with 50–100 mesh as a better candidate for plutonium processing or purification. Radiation degradation studies were carried out on the 8% PVP resin by gamma irradiation up to 200 MRad. The irradiated resins were characterized by IR, TGA, and SEM.

The exchange capacity, moisture content, and plutonium uptake were also evaluated for the irradiated PVP resins in comparison with the benchmark. The results indicated a better radiation stability for PVP resin over the benchmark.     

EXTRACTION OF U(VI), Pu(IV) AND Th(IV) BY SOME TRIALKYL PHOSPHATES

ABSTRACT

This paper reports the data on the extraction of U(VI), Pu(IV) and Th(IV) from nitric acid by tri-isobutyl phosphate, tri-n-amyl phosphate, tri-isoamyl phosphate and tri-n-hexyl phosphate and provides a comparison of their extract ion behaviour with that of tri-n-butyl phosphate. Data on the third phase formation in the system Th(NO₃) ₄ ^?HNO₃ ^?1.1 M trialkyl phosphate/n-dodecane are also presented.     

Design characteristics of in situ and operando ultraviolet-visible and vibrational spectroscopic reaction cells for heterogeneous catalysis

This article focuses on reaction cells for in situ/operando studies of heterogeneous catalysts by ultraviolet-visible (UV-vis) and vibrational (IR and Raman) spectroscopies and mainly focuses on transmission, internal reflection, diffuse reflectance, and scattering techniques. Its objective is to present a general overview of the most common commercial and homemade reaction cell designs, their main design characteristics, and limitations to serve as a guide for their selection or the design of new in situ/operando cells. It will be shown that there are currently many designs for different specific catalytic applications. However, an ideal reaction cell for a wide range of catalytic in situ and operando reaction conditions does not exist (yet), that is, with low dead volume (i.e., for fast dynamic response to process feed changes, within tens of seconds), high temperatures (> 500°C), high pressures (>30 bar), low cost, enough sample capacity (for operando studies, in the tens of mg), good spectroscopic response, resemblance to laboratory scale reactors, and reactor wall inertness, among others.     

Decision support for green supply chain operations by integrating dynamic simulation and LCA indicators: diaper case study

As the issue of environmental sustainability is becoming an important business factor, companies are now looking for decision support tools to assess the fuller picture of the environmental impacts associated with their manufacturing operations and supply chain (SC) activities. Lifecycle assessment (LCA) is widely used to measure the environmental consequences assignable to a product. However, it is usually limited to a high-level snapshot of the environmental implications over the product value chain without consideration of the dynamics arising from the multitiered structure and the interactions along the SC. This paper proposes a framework for green supply chain management by integrating a SC dynamic simulation and LCA indicators to evaluate both the economic and environmental impacts of various SC decisions such as inventories, distribution network configuration, and ordering policy. The advantages of this framework are demonstrated through an industrially motivated case study involving diaper production. Three distinct scenarios are evaluated to highlight how the proposed approach enables integrated decision support for green SC design and operation.