Experimental strategies for combinatorial and high-throughput materials development

As high-throughput experimental techniques have become common in the area of materials research, entirely new types of experimental strategies have appeared. The kinds of problems, the desired outcomes, and the appropriate patterns are significantly different from those associated with conventional experimentation. Classical experimental design (design of experiments, DOE) strategies grew up in a period of slow, laborious, error-prone experimentation; a modern high-throughput laboratory can test more materials in a week than was previously done in a year. The goal of this Account is to identify and critically discuss some of the strategies that are being developed and used in this new, exciting area of research.     

Strategien kinetischer Experimente mit desaktivierenden Katalysatoren

Strategies of kinetic experiments with decaying catalysts . Rate expressions for solid-catalyzed gas-phase reactions may be misleading, useless, or at least incomplete, unless they cover the changing catalyst activity and selectivity. To prepare the ground for complete kinetic modelling of such systems, concentration-controlled rate measurements in gradient-free reactors appear the most appropriate method. They allow uncoupling of concentration and activity effects upon the rates. Based on this possibility, strategies have been developed for testing the rate laws, prior to modelling them, for separability into reaction and deactivation terms. Not only in connection with such strategies, but also apart from any catalyst decay, concentration control allows decomposing reaction networks into smaller and more amenable subsets by adjustment of partial equilibrium, as well as carrying out rate measurements at selected concentrations, i. e. according to experimental designs.     

Performance evaluation of a full-scale advanced phase isolation ditch process by using real-time control strategies

This paper proposes real-time control strategies that can be applied in a full-scale advanced phase isolation ditch (APID) process. Real-time operation mode control (OMC) and aeration section control (ASC) strategies were developed to cope more stably with fluctuations in the influent loading and to increase the nitrification and denitrification reactions within the entire volume. The real-time OMC and ASC strategies were evaluated using mathematical models. When the NH₄-N in the reactor was maintained at a high level, appropriate control actions, such as continuing the aeration state, stopping the influent inflow and increasing the aeration section, were applied in the APID process. In contrast, when the NO _X -N in the reactor was maintained at a high level, the non-aeration state, influent inflow, and decreased aeration section were continued. It was concluded that stable operation in the APID process could be achieved by applying real-time OMC and ASC strategies developed in this study.     

A Procedure for Feasible and Optimal Operational Strategies for Control of CARE Systems

In Biochemical Engineering, the downstream stage to recover and purify product obtained from fermentation plays a central role in the commercial success of the process. Previously, the continuous adsorption recycle extraction (CARE) process was optimized using experimental design and surface response analysis. Such an approach did not require the use of reduced models. Thus, through a detailed model of the system and extensive simulation, operational restrictions, the whole set of process variables and design details in the analysis were accounted for. Through this procedure, a new optimal set-point was applied to the control algorithm developed to give higher system performance. The appropriate manipulated variable was determined from the dynamic responses and control strategies could be defined. The classical proportional integral (PI) and proportional integral derivative (PID) feedback and non-conventional feedback-feedforward controllers were studied. The results show that the performance was good even with time delays up to 24 and 36 min, respectively. © 1997 SCI.     

Ammonium bisulfate formation temperature in a bench-scale single-channel air preheater

Ammonium bisulfate (ABS) forms in coal-fired power plant exhaust systems when ammonia slip from the NO_x control system reacts with the sulfur oxides and water in the flue gas. The critical temperature range for ABS formation occurs in the air preheater, where ABS is known to cause corrosion and pluggage that can require unplanned outages and expensive cleaning. To develop mitigation strategies for the deleterious effects of ABS in air preheaters, it is important to know its formation temperature and deposition process. This paper describes a bench-scale experimental simulation of a single-channel air preheater, with the appropriate temperature gradient, used in conjunction with simulated coal combustion flue gas, including sulfur oxides, ammonia, and water vapor, to investigate the formation of ABS. Formation was observed optically, and the formation temperature, as well as deposition characteristics for a realistic range of reactant concentrations are presented and compared with previous studies on ABS formation. This study presents data at realistic concentrations not earlier tested, and the reported data has smaller experimental uncertainty than previously obtained. We found that the measured ABS formation temperatures under air preheater channel conditions lies between the temperatures reported by others, and is in the range of 500-520 K for typical flue gas concentrations of ammonia and sulfur oxide species. The results also show that, at least for this experimental configuration, ABS forms predominantly as an aerosol in the gas phase rather than as a condensate on the channel walls.     

Iterative model-based experimental design for spherical agglomeration processes

Spherical agglomeration (SA) is a process intensification strategy, which can reduce the number of unit operations in pharmaceutical manufacturing. SA merges drug substance crystallization with drug product wet granulation, reducing capital, and operating costs. However, SA is a highly nonlinear process, thus for its efficient operation model-based design and control strategies are beneficial. These require the development of a high-fidelity process model with appropriately estimated parameters. There are two major problems associated with the development of a high-fidelity process models—(i) selection of the appropriate model corresponding to the underlying process mechanisms, and (ii) accurate estimation of the parameters. This work focuses on the identification of the best fitting model that correlates with experimental observations using cross-validation experiments. Further, an iterative model-based experimental design strategy is developed, which uses D-optimal experimental design criterion to minimize the number of experiments necessary to obtain accurate parameter estimates.     

Real‐time control of a semi‐industrial fed‐batch evaporative crystallizer using different direct optimization strategies

This article presents a model‐based control approach for optimal operation of a seeded fed‐batch evaporative crystallizer. Various direct optimization strategies, namely, single shooting, multiple shooting, and simultaneous strategies, are used to examine real‐time implementation of the control approach on a semi‐industrial crystallizer. The dynamic optimizer utilizes a nonlinear moment model for on‐line computation of the optimal operating policy. An extended Luenberger‐type observer is designed to enable closed‐loop implementation of the dynamic optimizer. In addition, the observer estimates the unmeasured process variable, namely, the solute concentration, which is essential for the intended control application. The model‐based control approach aims to maximize the batch productivity, as satisfying the product quality requirements. Optimal control of crystal growth rate is the key to fulfill this objective. This is due to the close relation of the crystal growth rate to product attributes and batch productivity. The experimental results suggest that real‐time application of the control approach leads to a substantial increase, i.e., up to 30%, in the batch productivity. The reproducibility of batch runs with respect to the product crystal size distribution is achieved by thorough seeding. The simulation and experimental results indicate that the direct optimization strategies perform similarly in terms of optimal process operation. However, the single shooting strategy is computationally more expensive. © 2010 American Institute of Chemical Engineers AIChE J, 57: 1557–1569, 2011     

REDUCING STATIC DEVIATIONS OF PRODUCT QUALITIES IN THE TEMPERATURE CONTROL OF AN IDEAL HEAT-INTEGRATED DISTILLATION COLUMN

Two strategies are proposed in this work for the reduction of static deviations of product qualities in the dual-point temperature control of a simulated ideal heat-integrated distillation column. The key to achieve this purpose is to sense the changes in operating conditions and make appropriate adjustments simultaneously to the set-points of the top and bottom control loops. The first method is based on the inferential signals extracted from the composition of products and the second one from the temperatures of the top and bottom stages. Both strategies are intensively studied through the operation of the simulated ideal heat-integrated distillation column separating a binary equimolar mixture of benzene and toluene, and it is found that they could work effectively to decrease the static deviations in product qualities. The strategies are characterized by great simplicity in principle and a relatively small effort in process modeling, thereby allowing wide applications in the operation of various distillation columns with a dual-point temperature control scheme.     

采用同步策略的化工动态优化求解(英文)

An approach of simultaneous strategies with two novel techniques is proposed to improve the solution accuracy of chemical dynamic optimization problems. The first technique is to handle constraints on control variables based on the finite-element collocation so as to control the approximation error for discrete optimal problems, where a set of control constraints at element knots are integrated with the procedure for optimization leading to a significant gain in the accuracy of the simultaneous strategies. The second technique is to make the mesh refinement more feasible and reliable by introducing length constraints and guideline in designing appropriate element length boundaries, so that the proposed approach becomes more efficient in adjusting elements to track optimal control profile breakpoints and ensure accurate state and control profiles. Four classic benchmarks of dynamic optimization problems are used as illustrations, and the proposed approach is compared with literature reports. The research results reveal that the proposed approach is preferable in improving the solution accuracy of chemical dynamic optimization problem.     

Evaluation of multiloop chemical dosage control strategies for total phosphorus removal of enhanced biological nutrient removal process

We developed several control algorithms and compare their control performances for controlling the total phosphorous (TP) concentration in wastewater treatment plant, which has strong influent disturbances and the disturbance effects should be removed while maintaining better effluent quality. An anaerobic - anoxic - oxic (AAO) process, which is a well-known advanced nutrient removal process, was selected as a case study, which is modeled with activated sludge model no. 2. Six control strategies for TP control with a polymer addition were implemented in AAO process and evaluated by the plant’s performance, where the costs of the dosed chemical were compared among the six controllers. The experimental work showed that the advanced control techniques with feedback, feedforward and feedratio controllers were able to control the TP concentration in the effluent, which must be less than 1.50 g P/m³ which is the legal limitation, while reducing the necessary chemical cost. The results showed that the best TP removal performance in the effluent TP removal could be achieved by advanced feedback controller with the tuned control parameters, which showed the best effluent quality and control performance index as well as the cheapest cost of chemical dosage among the six TP control strategies.     

脱除硫酸装置中的NOx

分析上游操作中NOx的生成机理,论述各类硫酸装置NOx的来源及控制策略,其中包括防止NOx形成、在气体净化过程中除去、部分脱除以及选择性催化还原（SCR）。通过采取合适的措施,硫酸产品中以硝酸根计的氮氧化物含量可达到低于5mg／m^3的典型工业硫酸标准。     

MODELING,OPTIMIZATION, AND CONTROL OF REVERSE OSMOSIS WATER TREATMENT IN KAZEROON POWER PLANT USING NEURAL NETWORK

Neural network modeling and the back-propagation concept were utilized to develop data-driven models for predicting reverse osmosis (RO) plant performance and finding control strategies. Considering different commissioning times, the process of three RO plants was successfully modeled using an artificial neural network (ANN). Moreover, long-term forecasting of performance degradation was developed. Time (h), transmembrane pressure (TMP; bar), conductivity (µs/cm), and flow rate (m³/h) were utilized as ANN inputs. The effects of operating time and TMP on performance at mean values of feed conductivity and flow rate were investigated using three-dimensional figures. Genetic algorithm (GA) was employed to find optimum paths of TMP, feed flow rate, and control strategies during a specific period of time. The RO plant was monitored for 5000 h corresponding to the results generated by GA (optimum paths), and experimental results were compared to the prediction made by the model. The differences strongly implied the robustness of the ANN model.     

Fusarium oxysporum f. sp. niveum Molecular Diagnostics Past,Present and Future

Watermelon is an important commercial crop in the Southeastern United States and around the world. However, production is significantly limited by biotic factors including fusarium wilt caused by the hemibiotrophic fungus Fusarium oxysporum forma specialis niveum (Fon). Unfortunately, this disease has increased significantly in its presence over the last several decades as races have emerged which can overcome the available commercial resistance. Management strategies include rotation, improved crop resistance, and chemical control, but early and accurate diagnostics are required for appropriate management. Accurate diagnostics require molecular and genomic strategies due to the near identical genomic sequences of the various races. Bioassays exist for evaluating both the pathogenicity and virulence of an isolate but are limited by the time and resources required. Molecular strategies are still imperfect but greatly reduce the time to complete the diagnosis. This article presents the current state of the research surrounding races, both how races have been detected and diagnosed in the past and future prospects for improving the system of differentiation. Additionally, the available Fon genomes were analyzed using a strategy previously described in separate formae speciales avirulence gene association studies in Fusarium oxysporum races.     

Filtration mit kompressiblen Kuchen: Effiziente Konzeptefür eine anspruchsvolle Trennaufgabe

Efficient Process Strategies for Compressible Cake Filtration Compressible cake filtration is a challenging and often critical task in many industrial processes. Conventional design methods are not always appropriate as they fail to address the specifics of compressible structures. Efficient strategies for compressible cake filtration will be presented. The guidelines for process design and optimization are the outcome of experimental investigations, utilizing an innovative compression‐permeability‐filter cell, and a process simulation based on a rigorous model of compressible cake formation and consolidation.     

Achieving state estimation equivalence for misassigned disturbances in offset‐free model predictive control

Integrated white noise disturbance models are included in advanced control strategies, such as Model Predictive Control, to remove offset when there are unmodeled disturbances or plant/model mismatch. These integrating disturbances are usually modeled to enter either through the plant inputs or the plant outputs or partially through both. There is currently a lack of consensus in the literature on the best choice for the structure of this disturbance model to obtain good feedback control. We show that the choice of the disturbance model does not affect the closed‐ loop performance if appropriate covariances are used in specifying the state estimator. We also present a data based autocovariance technique to estimate the appropriate covariances regardless of the plant's true unknown disturbance source. The covariances estimated using the autocovariance technique and the resulting estimator gain are shown to compensate for an incorrect choice of the source of the disturbance in the disturbance model. © 2009 American Institute of Chemical Engineers AIChE J, 2009     

基于仿人智能控制的恒温水(油)浴箱温度控制的研究

通过分析传统的PID控制算法与仿人智能控制算法的优缺点,基于ATmega16(L)单片机设计开发出了一种基于仿人智能控制算法的恒温水(油)浴箱,模拟人的启发式和直觉推理逻辑,通过特征辨识与特征记忆,识别系统当前的特征状态,然后采取适当的控制模态,从而实现针对不同目标采取不同策略的控制,通过单片机实现整个控制过程.介绍了...     

Multidimensional control of profile extrusion

Dimensional changes in complex profile extrusions are classified as overall size and local shape changes which can be related naturally and systematically to changes in operating conditions. The theoretical basis and supporting experimental data for simultaneous, independent control of certain classes of extrudate dimensions are presented for the following strategies: (1) size control by manipulating line speed relative to extruder output rate, (2) shape control by manipulating extrudate swell through adjustments in stock temperature, and (3) shape control by manipulating local die flow by adjusting the die temperature set point.     

A control perspective on process intensification in dividing-wall columns

During the last decades, process intensification led to major developments also in separation technology. Particularly in distillation, dividing-wall column (DWC) is the next best thing as it allows significant energy savings combined with reduced investment costs. However, in spite of these clear advantages and the steady increase of DWC applications, the spreading of DWC at industrial scale is still limited to only a few companies. One of the major reasons for this status quo is the insufficient insight with regard to the operation and control of a DWC - this lack of knowledge making most chemical companies reticent to large-scale implementations. This study gives an overview of the available control strategies for DWC, varying from the classic three-point control structure and PID controllers in a multi-loop framework to model predictive control (MPC) and other advanced control strategies (LQG, LSDP, H_∞ and μ-synthesis). The previous studies prove that the DWC is not difficult to control providing that an appropriate control structure is selected. The available results show that MIMO controllers perform better than multi-loop PID controllers. However, among the decentralized multivariable PI structured controllers, LSV and DSV are the best control structures being able to handle persistent disturbances in reasonably short times. All things considered, this study clearly concludes that the DWC controllability is only perceived as a problem, but in fact there are no real solid grounds for concern.     

Adeno-Associated Viral Vectors as Versatile Tools for Parkinson’s Research,Both for Disease Modeling Purposes and for Therapeutic Uses

It is without any doubt that precision medicine therapeutic strategies targeting neurodegenerative disorders are currently witnessing the spectacular rise of newly designed approaches based on the use of viral vectors as Trojan horses for the controlled release of a given genetic payload. Among the different types of viral vectors, adeno-associated viruses (AAVs) rank as the ones most commonly used for the purposes of either disease modeling or for therapeutic strategies. Here, we reviewed the current literature dealing with the use of AAVs within the field of Parkinson’s disease with the aim to provide neuroscientists with the advice and background required when facing a choice on which AAV might be best suited for addressing a given experimental challenge. Accordingly, here we will be summarizing some insights on different AAV serotypes, and which would be the most appropriate AAV delivery route. Next, the use of AAVs for modeling synucleinopathies is highlighted, providing potential readers with a landscape view of ongoing pre-clinical and clinical initiatives pushing forward AAV-based therapeutic approaches for Parkinson’s disease and related synucleinopathies.     

Injection-molding process control—A review

This paper reviews control strategies employed in the injection-molding process. For clarity, the controlled variables have been categorized into all-phase control, phase-dependent control, and cycle-to-cycle control. All-phase control includes variables that must be monitored and controlled at all times; i.e., in all the phases. Control of variables that are triggered during a specific phase are discussed under phase-dependent control. In cycle-to-cycle control, previous data are used to predict future trends and take appropriate corrective actions, The cyclic, dynamic, and unsteady state nature of the injection-molding process is discussed with respect to the conventional proportional-integral (PI) and proportional- integral-derivative (PID) controllers as well as the more advanced control schemes such as self-tuning control, optimal control, and statistical process control. Suggestions involving specific advanced control schemes and recommendations for future research in injection-molding process control also are made.