Industrial waste heat recovery is an attractive option having the simultaneous benefits of reducing energy costs as well as carbon emissions. In this context, thermal energy storage can be used along with an optimal operation strategy like model predictive control (MPC) to realize significant energy savings. However, conventional control methods offer little robustness against uncertainty in terms of daily operation, where supply and demand of energy in the cluster can vary significantly from their predicted profiles. A major concern is that ignoring the uncertainties in the system may lead to the system violating critical constraints that affect the quality of the end-product of the participating processes. To this end, we present a method to make optimal energy storage and discharge decisions, while rigorously handling this uncertainty. We employ multivariate data analysis on historical industrial data to implement a multistage nonlinear MPC scheme based on a scenario-tree formulatio... [more]

This work presents a critical review of the use of exergy based control and optimization for efficiency improvements in energy networks, with a background of exergy based analysis given for context. Over the past three decades, a number of studies using exergy were conducted to gain a performance advantage for high energy consumption systems and networks. Due to their complexity and the increased scale of the systems, the opportunity to misuse energy inevitability leads to inefficient operations. The studies accomplished in this area are grouped into either control or optimization to highlight each method’s ability to minimize system irreversibilities that lead to exergy destruction. The exergy based optimization and control studies featured demonstrate substantial improvements (as high as 40%) over traditional methods based on the first law of thermodynamics. This paper reviews the work completed in the area of exergy based optimization and control as of the end of September 2019, out... [more]

This paper demonstrates the use of a combined software package including IPSEpro and MATLAB in the optimisation of a modern thermal cycle. A 900 MW power plant unit (operating at ultra-supercritical conditions) was considered as the study object. The Nelder-Mead simplex-based, direct search method was used to increase power plant efficiency and to find the optimal thermal cycle configuration. As the literature reveals, the Nelder-Mead approach is very sensitive to the simplex size and to the choice of method coefficients, i.e., reflection, expansion and contraction. When these coefficients are improperly chosen, the finding of the optimal solution cannot be guaranteed, particularly in such complex systems as thermal cycles. Hence, the main goal of the present work was to demonstrate the capability of an integrated software package including IPSEpro, MATLAB and MS Excel in the optimisation process of a complex thermal cycle, as well as to examine the effectiveness of the most popular se... [more]

Bletilla ochracea Schltr. polysaccharides (BOP) have a similar structure to Bletilla striata (Thunb.) Reichb.f. (Orchidaceae) polysaccharides (BSP). Therefore, BOP can be considered as a substitute for BSP in the food, pharmaceuticals and cosmetics fields. To the best of our knowledge, little information is available regarding the optimization of extraction and antioxidant activity of BOP. In this study, response surface methodology (RSM) was firstly used for optimizing the extraction parameters of BOP. The results suggested that the optimal conditions included a temperature of 82 °C, a duration of 85 min and a liquid/material ratio of 30 mL/g. In these conditions, we received 26.45% ± 0.18% as the experimental yield. In addition, BOP exhibited strong concentration-dependent antioxidant abilities in vitro. The half-maximal effective concentration (EC50) values of BOP against 1,1-diphenyl-2-picrylhydrazyl (DPPH·), 2,2′-azino-bis (3-ethylbenzothiazoline-6-sulphonate) (ABTS+·), hydroxyl (... [more]

The objective of this work is to determine the influence of blanching time on moisture content, sugars, protein, and processing recovery (degree of cut corn) of sweet corn kernels. Sweetcorn cobs of the Jubilee variety were blanched in the water at the temperature 85 °C during the period of 2, 4, 6, and 8 min. Non-blanched cobs were used as control samples. Blanched cobs were made subject to a mechanical process of cutting-off the kernels. It was stated that the blanching time has significant statistical influence on the content of moisture, sugars, and protein in kernel as well as on the quantity of the cut-off kernel mass.

Biohydrogen production by fermentation has become a promising technology developed in the world. In this study, diluted normal molasses wastewater is used as the raw material, and biohydrogen production efficiency and operation characteristics of an anaerobic baffled reactor (ABR) are studied. The effect of hydraulic retention time (HRT) on biohydrogen production efficiency and operating characteristics of ABR is extensively discussed. Experimental results showed that methanogen residuals were still observed in the last three compartments under HRT of 24 h and COD(Chemical oxygen demand) concentration of 8000 mg/L. Meanwhile, the first three compartments presented an ethanol fermentation type. The characteristics of butyric acid fermentation in Compartment IV were also enhanced. The average removal efficiency of COD was reduced to 15.4%. The average rates of biohydrogen production and specific biohydrogen production were 12.85 and 360.22 L/kg COD, respectively. The extension of HRT was... [more]

Background: Freeze-drying or lyophilization is a dehydration process employed in high added-value food and biochemical goods. It helps to maintain product organoleptic and nutritional properties. The proper handling of the product temperature during the operation is critical to preserve quality and to reduce the process duration. Methods: Mathematical models are useful tools that can be used to design optimal policies that minimize production costs while keeping product quality. In this work, we derive an operational mathematical model to describe product quality and stability during the freeze-drying process. Model identification techniques are used to provide the model with predictive capabilities. Then, the model is used to design optimal control policies that minimize process time. Results and conclusion: Experimental measurements suggest splitting the process into two subsystems, product and chamber, to facilitate the calibration task. Both models are successfully validated using... [more]

The Integrated Gasification Combined Cycle (IGCC) possesses a number of advantages over traditional power generation plants, including increased efficiency, flex-fuel, and carbon capture. A lesser-known advantage of the IGCC system is the ability to coordinate with the smart grid. The idea is that process modifications can enable dispatch capabilities in the sense of shifting power production away from periods of low electricity price to periods of high price and thus generate greater revenue. The work begins with a demonstration of Economic Model Predictive Control (EMPC) as a strategy to determine the dispatch policy by directly pursuing the objective of maximizing plant revenue. However, the numeric nature of EMPC creates an inherent limitation when it comes to process design. Thus, Economic Linear Optimal Control (ELOC) is proposed as a surrogate for EMPC in the formulation of the integrated design and control problem for IGCC power plants with smart grid coordination.

The industry is generally preoccupied with the evolution towards Industry 4.0 principles and the associated advantages as cost reduction, respectively safety, availability, and productivity increase. So far, it is not completely clear how to reach these advantages and what their exact representation or impact is. It is necessary for industrial systems, even legacy ones, to assure interoperability in the context of chronologically dispersed and currently functional solutions, respectively; the Open Platform Communications Unified Architecture (OPC UA) protocol is an essential requirement. Then, following data accumulation, the resulting process-aware strategies have to present learning capabilities, pattern identification, and conclusions to increase efficiency or safety. Finally, model-based analysis and decision and control procedures applied in a non-invasive manner over functioning systems close the optimizing loop. Drinking water facilities, as generally the entire water sector, ar... [more]

The article presents the findings of a study investigating the effects of storing Jonagold apples for six weeks in a condition in which the vertical component of the geomagnetic field has been eliminated (near null GMF) and in control conditions representing those applied in traditional storage (i.e., in the local geomagnetic field (local GMF)). Analyses of the fruit were performed before the start of and three times during the experiment (i.e., following four, five and six weeks in storage). The contents of simple sugars were measured using the HPLC (high performance liquid chromatography) method; refractometry was applied to identify total extract; thermogravimetry was used to measure the water content, volatile substances and total ash; calorific value and intensity of respiration were examined by measuring CO2 emissions. Significant differences were found between the apples stored in the experimental and under control conditions, showing an advantage of storage in a condition with... [more]

The switched inertance hydraulic converter (SIHC) is a new technology providing an alternative to conventional proportional or servo-valve-controlled systems in the area of fluid power. SIHCs can adjust or control flow and pressure by means of using digital control signals that do not rely on throttling the flow and dissipation of power, and provide hydraulic systems with high-energy efficiency, flexible control, and insensitivity to contamination. In this article, the analytical models of an SIHC in a three-port flow-booster configuration were used and validated at high operating pressure, with the low- and high-pressure supplies of 30 and 90 bar and a high delivery flow rate of 21 L/min. The system dynamics, flow responses, and power consumption were investigated and theoretically and experimentally validated. Results were compared to previous results achieved using low operating pressures, where low- and high-pressure supplies were 20 and 30 bar, and the delivery flow rate was 7 L/m... [more]

In this work a comprehensive analysis of the environmental impact of the operation of a wastewater treatment plant (WWTP) using different control strategies is carried out considering the dynamic evolution of some environmental indicators and average operation costs. The selected strategies are PI (proportional integral) control schemes such as dissolved oxygen control in the aerobic zone (DO control), DO control and nitrates control in the anoxic zone (DO + NO control) and regulation of ammonium control at the end of aerobic zone (Cascade SNHSP) commonly used in WWTPs to maintain the conditions that ensure the desired effluent quality in a variable influent scenario. The main novelty of the work is the integration of potential insights into environmental impact from the analysis of dynamic evolution of environmental indicators at different time scales. The consideration of annual, bimonthly and weekly temporal windows to evaluate performance indicators makes it possible to capture sea... [more]

To achieve the optimal operation of chemical processes in the presence of disturbances and uncertainty, a retrofit hierarchical architecture (HA) integrating real-time optimization (RTO) and control was proposed. The proposed architecture features two main components. The first is a fast extremum-seeking control (ESC) approach using transient measurements that is employed in the upper RTO layer. The fast ESC approach can effectively suppress the impact of plant-model mismatch and steady-state wait time. The second is a global self-optimizing control (SOC) scheme that is introduced to integrate the RTO and control layers. The proposed SOC scheme minimizes the global average loss based on the approximation of necessary conditions of optimality (NCO) over the entire operating region. A least-squares regression technique was adopted to select the controlled variables (CVs) as linear combinations of measurements. The proposed method does not require the second order derivative information,... [more]

Tuckeroo (Cupaniopsis anacardioides) is an Australian native tree, possessing high level bioactivity and antioxidant activity. To prevent deterioration of active constituents, appropriate drying practices must be determined. This study comparatively evaluates the impact of a range of drying methods including freeze-, microwave-, vacuum-, hot air- and sun-drying on the physical, phytochemical and antioxidant characteristics of Tuckeroo fruit. Experimental results showed that the five drying methods had significant impact on the physicochemical properties and antioxidant activity of the fruits. Of the drying methods assessed, freeze drying best preserved Tuckeroo activity, recording higher total phenolic content (TPC) (81.88 mg gallic acid equivalent (GAE)/g), total flavonoids (TFC) (107.71 mg catechin equivalent (CAE)/g), proanthocyanidins (TPro) (83.86 mg CAE/g) and exhibited the strongest antioxidant capacity. However, vacuum drying at 65 kPa, 100 °C for 5 h is recommended for drying... [more]

Medium voltage insulators are essential and versatile components in electrical engineering. Quality control of the manufacturing process for the insulators has a significant role in their economic production and reliable operation. As the quality of medium voltage insulator is mainly affected by the process parameters of the automatic pressure gelation process (APG), the optimal process settings are required to achieve a satisfactory quality target. However, traditional process parameters’ optimization methods are often cumbersome and cost-consuming. Moreover, the operational cost of APG for insulator production is relatively high. Therefore, the determination of the optimal settings becomes a significant challenge for the quality control of insulators. To address the above issues, an idea of knowledge-informed optimization was proposed in this study. Based on the above idea, a knowledge-informed simultaneous perturbation stochastic approximation (SPSA) methodology was formulated to re... [more]

In order to study the influence of eccentricity on hydrodynamic characteristics of nuclear reactor coolant pump under different cavitation conditions, five different schemes were obtained by analyzing and optimizing the existing structural schemes. Based on the RNG k-ε model (Renormalization Group with k-epsilon turbulence models) and two-fluid two-phase flow model, the unsteady numerical analysis and test verification of different designed schemes are carried out by using the flow field software ANSYS CFX. The results of research show that different eccentricities will affect the nuclear reactor coolant pump’s head under different cavitation conditions, and the corresponding head in the scheme with the eccentricity of 5mm under the fracture cavitation condition is lower than that of the other schemes. When the impeller rotates at a certain angle from the initial position under critical and severe cavitation conditions, the radial force acting on the rotor system will fluctuate greatly... [more]

As interest in the modularization and intensification of chemical processes continues to grow, more research must be directed towards the modeling and analysis of these units. Intensified process units such as polymer membrane reactors pose unique challenges pertaining to design and operation that have not been fully addressed. In this work, a novel approach for modeling membrane reactors is developed in AVEVA’s Simcentral Simulation Platform. The produced model allows for the simulation of polymer membrane reactors under nonisothermal and countercurrent operation for the first time. This model is then applied to generate an operability mapping to study how operating points translate to overall unit performance. This work demonstrates how operability analyses can be used to identify areas of improvement in membrane reactor design, other than just using operability mapping studies to identify optimal input conditions. The performed analysis enables the quantification of the Pareto front... [more]

In the traditional performance assessment method, different modes of data are classified mainly by expert knowledge. Thus, human interference is highly probable. The traditional method is also incapable of distinguishing transition data from steady-state data, which reduces the accuracy of the monitor model. To solve these problems, this paper proposes a method of multimode operating performance visualization and nonoptimal cause identification. First, multimode data identification is realized by subtractive clustering algorithm (SCA), which can reduce human influence and eliminate transition data. Then, the multi-space principal component analysis (MsPCA) is used to characterize the independent characteristics of different datasets, which enhances the robustness of the model with respect to the performance of independent variables. Furthermore, a self-organizing map (SOM) is used to train these characteristics and map them into a two-dimensional plane, by which the visualization of th... [more]

The ability to predict and control the outcome of the sheet metal forming process demands holistic knowledge of the product/process parameter influences and their contribution in shaping the output product quality. Recent improvements in the ability to harvest in-line production data and the increased capability to understand complex process behaviour through computer simulations open up the possibility for new approaches to monitor and control production process performance and output product quality. This research presents an overview of the common process monitoring and control approaches while highlighting their limitations in handling the dynamics of the sheet metal forming process. The current paper envisions the need for a collaborative monitoring and control system for enhancing production process performance. Such a system must incorporate comprehensive knowledge regarding process behaviour and parameter influences in addition to the current-system-state derived using in-line... [more]

Cross-flow fans are widely used in numerous applications such as low-pressure ventilation, household appliances, laser instruments, and air-conditioning equipment. Cross-flow fans have superior characteristics, including simple structure, small size, stable airflow, high dynamic pressure coefficient, and low noise. In the present study, numerical simulation and experimental research were carried out to study the unique secondary flow and eccentric vortex flow characteristics of the internal flow field in multi-operating conditions. To this end the vorticity and the circumferential pressure distribution in the air duct are obtained based on the performed experiments and the correlation between spectral characteristics of multiple operating conditions and the inflow state is established. The obtained results show that when the area of the airflow passage decreases while the area of the eccentric vortex area gradually increases, then the airflow of the cross-flow fan decreases, the outlet... [more]

The diagnosis of product defects is an important task in manufacturing, and machine learning-based approaches have attracted interest from both the industry and academia. A high-quality dataset is necessary to develop a machine learning model, but the manufacturing industry faces several data-collection issues including partially shuffled data, which arises when a product ID is not perfectly inferred and yields an unstable machine learning model. This paper introduces latent variables to formulate a supervised learning model that addresses the problem of partially shuffled data. The experimental results show that our graphical model deals with the shuffling of product order and can detect a defective product far more effectively than a model that ignores shuffling.

Online prediction of key parameters (e.g., process indices) is essential in many industrial processes because online measurement is not available. Data-based modeling is widely used for parameter prediction. However, model mismatch usually occurs owing to the variation of the feed properties, which changes the process dynamics. The current neural network online prediction models usually use fixed activation functions, and it is not easy to perform dynamic modification. Therefore, a few methods are proposed here. Firstly, an extreme learning machine (ELM)-based single-layer feedforward neural network with activation-function learning (AFL−SLFN) is proposed. The activation functions of the ELM are adjusted to enhance the ELM network structure and accuracy. Then, a hybrid model with adaptive weights is established by using the AFL−SLFN as a sub-model, which improves the prediction accuracy. To track the process dynamics and maintain the generalization ability of the model, a multiscale mo... [more]

Evaporative cooling can be integrated into fresh-air-handling units, to reduce cooling demand. This study considers a hybrid fresh-air-handling unit which incorporates a vapor-compression cooling cycle and indirect evaporative cooling to condition an ambient primary airstream to a desired supply air state. The cooling effects of using various modes (vapor compression only; direct expansion with mist; direct expansion with water shower; and direct expansion with mist and water shower) are compared when the fresh-air-handling unit operates in harsh (hot and humid) climatic conditions experienced in Qatar. Experimental analysis is based on actual ambient conditions measured from August 2018 to July 2019. It is found that the best-performing wet mode of operation saves more than 60% of the energy required by a conventional direct expansion cooling system operating under the same ambient conditions. In hot, dry conditions, the coefficient of performance of the fresh-air-handling unit when u... [more]

Process capability indices (PCIs) have always been used to improve the quality of products and services. Traditional PCIs are based on the assumption that the data obtained from the quality characteristic (QC) under consideration are normally distributed. However, most data on manufacturing processes violate this assumption. Furthermore, the products and services of the manufacturing industry usually have more than one QC; these QCs are functionally correlated and, thus, should be evaluated together to evaluate the overall quality of a product. This study investigates and extends the existing multivariate non-normal PCIs. First, a multivariate non-normal PCI model from the literature is modeled and validated. An algorithm to generate non-normal multivariate data with the desired correlations is also modeled. Then, this model is extended using two different approaches that depend on the well-known Box−Cox and Johnson transformations. The skewness reduction is further improved by applyin... [more]

The gun head is the end effector of the fire-fighting jet system. Compared with a traditional fixed gun head, an adaptive gun head has the advantages of having an adjustable nozzle opening, a wide applicable flow range, and a high fire-extinguishing efficiency. Thus, the adaptive gun head can extinguish large fires quickly and efficiently. The fire-fighting jet system with an adaptive gun head has fluid-structure interaction and discrete-continuous coupling characteristics, and the influence of key design parameters on its natural frequencies needs to be determined by a sensitivity analysis. In this paper, the dynamic model and equations of the jet system were established based on the lumped parameter method, and the sensitivity calculation formulas of the natural frequency of the jet system to typical design parameters were derived. Natural frequencies and mode shapes of the jet system were determined based on a mode analysis. The variation law of the sensitivity of the natural freque... [more]