Kernel methods are a class of learning machines for the fast recognition of nonlinear patterns in any data set. In this paper, the applications of kernel methods for feature extraction in industrial process monitoring are systematically reviewed. First, we describe the reasons for using kernel methods and contextualize them among other machine learning tools. Second, by reviewing a total of 230 papers, this work has identified 12 major issues surrounding the use of kernel methods for nonlinear feature extraction. Each issue was discussed as to why they are important and how they were addressed through the years by many researchers. We also present a breakdown of the commonly used kernel functions, parameter selection routes, and case studies. Lastly, this review provides an outlook into the future of kernel-based process monitoring, which can hopefully instigate more advanced yet practical solutions in the process industries.

Food flavor quality evaluation is attracting continuous attention, but a suitable evaluation system is severely lacking. Gas chromatography-mass spectrometry/olfactometry (GC-MS/O) is widely used to solve the food flavor evaluation problem, but the olfactometry evaluation is unfeasible to be carried out in large batches and is unreliable due to potential issue of an operator or systematic laboratory effect. Thus, a novel fingerprint modeling and profiling process was proposed based on several machine learning models including convolutional neural network (CNN). The fingerprint template was created by the data analysis of existing GC-MS spectrum dataset. Then the fingerprint image generation program was applied for structuring the complex instrumental data. Food olfactometry result was obtained by a machine learning method based on CNN using fingerprint image as the input. The case study on peanut oil samples demonstrated the model accuracy of around 93%. By structure optimization and f... [more]

A titanium nitride (TiN) coating using microwaves can be accomplished in air, and satisfies the required conditions of an on-demand TiN coating process. However, the coating mechanism using microwaves is not completely clear. In this study, to understand the detailed mechanism of microwave titanium nitridation in air, the quantity of nitrogen and oxygen in reacted TiN powder has been investigated by an inert melting method. Titanium powders were irradiated with microwaves by a multi-mode type 2.45 GHz microwave irradiation apparatus, while also being held at various temperatures for two different dwell times. X-ray diffraction (XRD) results revealed that nitridation of the powder progressed with increasing process temperature, and the nitridation corresponds to the powder color after microwave irradiation. The nitrogen contents of the samples increased with increasing processing temperature and dwell time, unlike oxygen. It is postulated that the reaction of convected air with titanium... [more]

Renewed interest in freeze desalination has emerged due to its advantages over other desalination technologies. A major advantage of the freeze desalination process over evaporative methods is its lower energy consumption (latent heat of freezing is 333.5 kJ/kg and latent heat of evaporation is 2256.7 kJ/kg). Cryogenic fluids like LN2/LAir are emerging as an effective energy storage medium to maximise utilisation of intermittent renewable energy sources. The recovery of this stored cold energy has the potential to be used for freeze desalination. Computational Fluid Dynamics (CFD) modelling was developed to simulate the evaporation of liquid nitrogen to simultaneously conduct freeze desalination to investigate the feasibility of using cryogenic energy for freeze desalination. This integrated CFD model was validated using experimental heat exchanger test facility constructed, to evaporate liquid nitrogen to supply the cooling required for freezing. Parametric study on the LN2 flow rate... [more]

High energy demand has led to excessive fuel consumption and high-concentration CO2 production. CO2 release causes serious environmental problems such as the rise in the Earth’s temperature, leading to global warming. Thus, chemical industries are under severe pressure to provide a solution to the problems associated with fuel consumption and to reduce CO2 emission at the source. To this effect, herein, four highly porous aromatic Schiff bases derived from melamine were investigated as potential media for CO2 capture. Since these Schiff bases are highly aromatic, porous, and have a high content of heteroatoms (nitrogen and oxygen), they can serve as CO2 storage media. The surface morphology of the Schiff bases was investigated through field emission scanning electron microscopy, and their physical properties were determined by gas adsorption experiments. The Schiff bases had a pore volume of 0.005−0.036 cm3/g, an average pore diameter of 1.69−3.363 nm, and a small Brunauer−Emmett−Telle... [more]

Sugar beet fibre (fibrex) is an abundant side-stream from the sugar refining industry. A self-produced laccase from Funalia trogii (LccFtr) (0.05 U/µg FA) successfully cross-linked fibrex to an edible gel. Dynamic oscillation measurements of the 10% fibrex gels showed a storage modulus of 5.52 kPa and loss factors ≤ 0.36 in the range from 20 to 80 Hz. Comparing storage stability of sweetened 10% fibrex gels with sweetened commercial 6% gelatin gels (10% and 30% d-sucrose) indicated a constant storage modulus and loss factors ≤ 0.7 during four weeks of storage in fibrex gels. Loss factors of sweetened gelatin gels were ≤0.2, and their storage modulus decreased from 9 to 7 kPa after adding d-sucrose and remained steady for four weeks of storage. Fibrex gel characteristics, including high water holding capacity, swelling ratio in saliva, and heat resistance are attributed to a covalently cross-linked network. Vanillin, as a mediator, and citrus pectin did not enhance covalent cross-links... [more]

The yield and composition of the biocrude obtained by hydrothermal liquefaction (HTL) of Nannocloropsis gaditana using heterogeneous catalysts were evaluated. The catalysts were based on metal oxides (CaO, CeO2, La2O3, MnO2, and Al2O3). The reactions were performed in a batch autoclave reactor at 320 °C for 10 min with a 1:10 (wt/wt) microalga:water ratio. These catalysts increased the yield of the liquefaction phase (from 94.14 ± 0.30 wt% for La2O3 to 99.49 ± 0.11 wt% for MnO2) as compared with the thermal reaction (92.60 ± 1.20 wt%). Consequently, the biocrude yields also raised in the metal oxides catalysed HTL, showing values remarkably higher for the CaO (49.73 ± 0.9 wt%) in comparison to the HTL without catalyst (42.60 ± 0.70 wt%). The N and O content of the biocrude obtained from non-catalytic HTL were 6.11 ± 0.02 wt% and 10.50 ± 0.50 wt%, respectively. In this sense, the use of the metal oxides decreased the N content of the biocrude (4.62 ± 0.15−5.45 ± 0.11 wt%), although, the... [more]

Entropy generation and dual solutions are rarely studied in the literature. An analysis is attempted here. More exactly, the present paper looks at the impact of radiation of a micropolar fluid on mixed convective flow containing the titanium alloy Ti6Al4V nanoparticle along with a Riga plate. The study of dual-nature solution for the entropy generation along a Riga surface was not being explored in the literature; therefore, the current model focuses on the dual solutions of this complex nature model. Riga surface is identified as an actuator of electromagnetic in which electrodes are accumulated alternatively. This array produces the behavior of electromagnetic hydrodynamic in the flow field. The transmuted leading equations were worked out through the formula of 3-stage Lobatto IIIA. Influences of exercising enormous parameters on temperature distribution, velocity, and micro rotation fields are portrayed and argued. More than one solution is achieved in opposing flow, while in the... [more]

This work presents a molecular level investigation on the nature and mode of binding between imidazolium-based ionic liquids (ILs) ([Cnbim]Br where n = 2, 4, 6) with calf thymus DNA. This investigation offers valuable insight into the mechanisms of interactions that can affect the structural features of DNA and possibly cause the alteration or inhibition of DNA function. To expedite analysis, the study resorted to using molecular docking and COnductor like Screening MOdel for Real Solvents (COSMO-RS) in conjunction with fluorescence spectroscopic data for confirmation and validation of computational results. Both the fluorescence and docking studies consistently revealed a weak interaction between the two molecules, which corresponded to the binding energy of a stable docking conformation in the range of −5.19 to −7.75 kcal mol−1. As predicted, the rod-like structure of imidazolium-based ILs prefers to bind to the double-helix DNA through a minor groove. Interestingly, the occurrence o... [more]

This contribution describes the effect of the quality of the catalyst coating of cathodes for wastewater treatment by microbial fuel cells (MFC). The increase in coating quality led to a strong increase in MFC performance in terms of peak power density and long-term stability. This more uniform coating was realized by an airbrush coating method for applying a self-developed polymeric solution containing different catalysts (MnO2, MoS2, Co3O4). In addition to the possible automation of the presented coating, this method did not require a calcination step. A cathode coated with catalysts, for instance, MnO2/MoS2 (weight ratio 2:1), by airbrush method reached a peak and long-term power density of 320 and 200−240 mW/m2, respectively, in a two-chamber MFC. The long-term performance was approximately three times higher than a cathode with the same catalyst system but coated with the former paintbrush method on a smaller cathode surface area. This extraordinary increase in MFC performance con... [more]

Tire cord steel is widely used in the tire production process of the vehicle manufacturing industry due to its excellent strength and toughness. Titanium nitride (TiN) inclusion, existing in tire rod, has a seriously detrimental effect on the fatigue and drawing performances of the tire steel. In order to control its amount and morphology, the precipitation behavior of TiN during solidification in SWRH 92A tire cord steel was analyzed by selected thermodynamic models. The calculated results showed that TiN cannot precipitate in the liquid phase region regardless of the selected models. However, the precipitation of TiN in the mushy zone would occur at the final stage during the solidification process (at solid fractions greater than 0.98) if the LRSM (Lever-rule model was applied for the N and Scheil model for Ti) or Ohnaka models (without considering the effect of carbon on secondary dendrite arm spacing (SDAS)) were adopted. For the Ohnaka model, in the case when the effect of carbon... [more]

In this study, a solvent dehydration column of purified terephthalic acid (PTA) plant was used as the research object. Based on a dynamic model of the solvent dehydration column, a dynamic sensitivity analysis of the key parameters was carried out using Aspen Dynamics. After the dynamic model reached stability, the reflux rate, methyl acetate concentration, and reflux temperature of the solvent dehydration column were adjusted and the changes of the key separation indexes under the corresponding disturbance were analyzed. According to the analysis results, a sensitive plate temperature controller was added to carry out the dynamic sensitivity analysis. In addition, the acetic acid (HAc) concentration of the bottom of the column was found to be unstable in the dynamic sensitivity analysis. Considering the HAc concentration controller of the column bottom, two control strategies were designed. By analyzing the dynamic response of the feed flow disturbance under different control strategi... [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]

Objectives: The current study aimed to measure the antioxidant and antibacterial activities of 25 wild Palestinian edible plants, which were subjected to extraction by polar and non-polar solvents. Correlations between free radical scavenging activity and antibacterial activity of the extracts were assessed for both polar and non-polar fractions. Materials: Twenty-five wild edible plant species that are frequently consumed by people in Palestine (mainly in a rural area) were examined. Among them, 10 plant species were among those with the highest mean cultural importance values, according to an ethnobotanical survey that was conducted in the West Bank, Palestine, a few years ago. Method: The protocol of the DPPH assay for testing free-radical scavenging was utilized for determining EC50 values, while microdilution tests were conducted to determine the 50% inhibitory concentration (IC50) of the extracts for the microorganism Staphylococcus mutans. Results and Discussion: Eight extracts... [more]

Aimed at the coordination control problem of each unit caused by microgrid participation in the spot market and considering the randomness of wind and solar output and the uncertainty of spot market prices, a day-ahead real-time two-stage optimal scheduling model for microgrid was established by using the chance-constrained programming theory. On this basis, an improved particle swarm optimization (PSO) algorithm based on stochastic simulation technology was used to solve the problem and the effect of demand side management and confidence level on scheduling results is discussed. The example results verified the correctness and effectiveness of the proposed model, which can provide a theoretical basis in terms of reasonably coordinating the output of each unit in the microgrid in the spot market.

Based on the comprehensive utilization of energy storage, photovoltaic power generation, and intelligent charging piles, photovoltaic (PV)-storage charging stations can provide green energy for electric vehicles (EVs), which can significantly improve the green level of the transportation industry. However, there are many challenges in the PV-storage charging station planning process, making it theoretically and practically significant to study approaches to planning. This paper promotes a bi-level optimization planning approach for PV-storage charging stations. First, taking PV-storage charging stations and EV users as the upper- and lower-level problems, respectively, during the planning process, a bi-level optimization model for PV-storage charging stations considering user utility is established for capacity allocation and user behavior-based electricity pricing. Second, the model is converted into a single-level mixed-integer linear programming model using the piecewise linear util... [more]

Batch-type hot rolling planning highly affects electricity costs in a steel plant, but previous research models seldom considered time-of-use (TOU) electricity pricing. Based on an analysis of the hot-rolling process and TOU electricity pricing, a batch-processing plan optimization model for hot rolling was established, using an objective function with the goal of minimizing the total penalty incurred by the differences in width, thickness, and hardness among adjacent slabs, as well as the electricity cost of the rolling process. A method was provided to solve the model through improved genetic algorithm. An analysis of the batch processing of the hot rolling of 240 slabs of different sizes at a steel plant proved the effectiveness of the proposed model. Compared to the man−machine interaction model and the model in which TOU electricity pricing was not considered, the batch-processing model that included TOU electricity pricing produced significantly better results with respect to bot... [more]

Wind speed forecasting helps to increase the efficacy of wind farms and prompts the comparative superiority of wind energy in the global electricity system. Many wind speed forecasting theories have been widely applied to forecast wind speed, which is nonlinear, and unstable. Current forecasting strategies can be applied to various wind speed time series. However, some models neglect the prerequisite of data preprocessing and the objective of simultaneously optimizing accuracy and stability, which results in poor forecast. In this research, we developed a combined wind speed forecasting strategy that includes several components: data pretreatment, optimization, forecasting, and assessment. The developed system remedies some deficiencies in traditional single models and markedly enhances wind speed forecasting performance. To evaluate the performance of this combined strategy, 10-min wind speed sequences gathered from large wind farms in Shandong province in China were adopted as a case... [more]

Identifying abnormal process operation with spatial-temporal data remains an important and challenging work in many practical situations. Although spatial-temporal data identification has been extensively studied in some domains, such as public health, geological condition, and environment pollution, the challenge associated with designing accurate and convenient recognition schemes is very rarely addressed in modern manufacturing processes. This paper proposes a general recognition framework for identifying abnormal process with spatial-temporal data by employing a convolutional neural network (CNN) model. Firstly, motivated by the pasting case study, the spatial-temporal data are transformed into process images for capturing spatial and temporal interrelationship. Then, the CNN recognition model is presented for identifying different types of these process images, leading to the identification of abnormal process with spatial-temporal data. The specific architecture parameters of CNN... [more]

A framework is introduced for the systematic development of preparative chromatographic processes. It is intended for the optimal design of conventional and advanced concepts that exploit strategies, such as recycling, side streams, bypasses, using single or multiple columns, and combinations thereof. The Python-based platform simplifies the implementation of new processes and design problems by decoupling design tasks into individual modules for modelling, simulation, assertion of cyclic stationarity, product fractionation, and optimization. Interfaces to external libraries provide flexibility regarding the choice of column model, solver, and optimizer. The current implementation, named CADET-Process, uses the software CADET for solving the model equations. The structure of the framework is discussed and its application for optimal design of existing and identification of new chromatographic operating concepts is demonstrated by case studies.

Anti-solvent crystallization is frequently applied in pharmaceutical processes for the separation and purification of intermediate compounds and active ingredients. The selection of optimal solvent types is important to improve the economic performance and sustainability of the process, but is challenged by the discrete nature and large number of possible solvent combinations and the inherent relations between solvent selection and optimal process design. A computational framework is presented for the simultaneous solvent selection and optimization for a continuous process involving crystallization and distillation for recycling of the anti-solvent. The method is based on the perturbed-chain statistical associated fluid theory (PC-SAFT) equation of state to predict relevant thermodynamic properties of mixtures within the process. Alternative process configurations were represented by a superstructure. Due to the high nonlinearity of the thermodynamic models and rigorous models for dist... [more]

The demand on biologics has been constantly rising over the past decades and has become crucial in modern medicine. Promising approaches to cope with widespread diseases like cancer and diabetes are gene therapy, plasmid DNA, virus-like particles, and exosomes. Due to progress that has been made in upstream processing (USP), difficulties arise in downstream processing and demand for innovative solutions. This work focuses on the integration of precipitation using a quality by design (QbD) approach for process development. Selective precipitation is achieved with PEG 4000 resulting in an HCP depletion of ≥80% respectively to IgG. Dissolution was executed with a sodium phosphate buffer (pH = 5/50 mM) reaching an IgG recovery of ≥95%. However, the central challenge in process development is still an optimal process design, which is transferable for a broad molecular variety of new products. This is where rigorous modeling becomes vital in order to generate digital twins to support early-s... [more]

Tunnel Boring Machines (TBMs) are a cutting-edge excavating equipment, but are barely applied in underground coal mines. For TBM excavation projects involving the Zhangji coal mine, the surrounding rock properties, stress field, cross section geometry, as well as the excavation-induced stress path of TBM-excavated coal mine roadways are different from those of traditional tunnels or roadways. Consequently, traditional roadway supporting technologies and experiences cannot be relied on for this project. In order to research an appropriate supporting pattern for a TBM-excavated coal mine roadway, first of all, the constitutive model of roadway surrounding rocks was derived, and a rock failure criterion was proposed based on rock mechanical tests. Secondly, a three-dimension finite element model was established and computer simulations under three different supporting patterns were conducted. Stress redistribution, roadway convergence, and excavation damage zone ranges of surrounding rock... [more]

Two of the methods for converting biomass to fuel are hydrothermal carbonization (HTC) and anaerobic digestion (AD). This study is aimed at designing and analyzing two scenarios for bioenergy production from undervalued biomass (sawdust). In one of the scenarios (direct combustion or DC), raw biomass is burned in a combustor to provide the heat that is required by the Rankine cycle to generate electricity. In the other scenario (HTC-AD), the raw biomass first undergoes HTC treatment. While the solid product (hydrochar) is used to produce power by a Rankine cycle, the liquid by-product undergoes an AD process. This results in fuel gas production and it can be used in a Brayton cycle to generate more power. Energy and mass balance analysis of both scenarios were developed for each unit process by using Engineering Equation Solver (EES). The required data were obtained experimentally or from the literature. The performances of the proposed systems were evaluated, and a sensitivity analysi... [more]

This paper presents a multi-objective particle swarm optimization (MOPSO) method for optimal sizing of the standalone photovoltaic (SAPV) systems. Loss of load probability (LLP) analysis is considered to determine the technical evaluation of the system. Life cycle cost (LCC) and levelized cost of energy (LCE) are treated as the economic criteria. The two variants of the proposed PSO method, referred to as adaptive weights PSO ( A W P S O c f ) and sigmoid function PSO ( S F P S O c f ) , are implemented using MATLAB software to the optimize the number of PV modules in (series and parallel) and number of the storage battery. The case study of the proposed SAPV system is executed using the hourly meteorological data and typical load demand for one year in a rural area in Malaysia. The performance outcomes of the proposed A W / S F P S O c f methods give various configurations at desired levels of LLP values and the corresponding minimum cost. The perform... [more]