Processes, Volume 8, Issue 3 (March 2020) – 123 articles

The aim of this study is to indicate the influence of pretreatment, consisting of grinding vegetables and then freezing and thawing the raw material before pressing on the process efficiency and quality of obtained juice. The subject of the research was celeriac root (Apium graveolens L) of the Edward variety. Juice pressing was carried out in a laboratory basket press. The pressing yield and specific energy were values characterizing the pressing process, while pH and the extracted content in the juice were used to assess the juice quality. The experiment was performed according to three procedures. In each of them, the ground celeriac root (pulp or chips) was initially pretreated through freezing and thawing and then pressed twice. Among the examined methods of obtaining juice, the most beneficial method was pressing juice from the pulp, then freezing and thawing the pomace obtained in the first cycle, and finally, pressing the pomace. It is an energy-optimal method and guarantees a high pressing yield as well as obtaining juice with a higher soluble solid content than during the process of pressing chips. Full article

Metal–organic frameworks (MOFs) have been of great interest for their outstanding properties, such as large surface area, low density, tunable pore size and functionality, excellent structural flexibility, and good chemical stability. A significant advancement in the preparation of MOF thin films according to the needs of a variety of applications has been achieved in the past decades. Yet there is still high demand in advancing the understanding of the processes to realize more scalable, controllable, and greener synthesis. This review provides a summary of the current progress on the manufacturing of MOF thin films, including the various thin-film deposition processes, the approaches to modify the MOF structure and pore functionality, and the means to prepare patterned MOF thin films. The suitability of different synthesis techniques under various processing environments is analyzed. Finally, we discuss opportunities for future development in the manufacturing of MOF thin films. Full article

Pelleted biomass has a low, uniform moisture content and can be handled and stored cheaply and safely. Pellets can be made of industrial waste, food waste, agricultural residues, energy crops, and virgin lumber. Despite their many desirable attributes, they cannot compete with fossil fuel sources because the process of densifying the biomass and the price of the raw materials make pellet production costly. Leaves collected from street sweeping are generally discarded in landfills, but they can potentially be valorized as a biofuel if they are pelleted. However, the lignin content in leaves is not high enough to ensure the physical stability of the pellets, so they break easily during storage and transportation. In this study, the use of eucalyptus kraft lignin as an additive in tree-leaf pellet production was studied. Results showed that when 2% lignin is added the abrasion resistance can be increased to an acceptable value. Pellets with added lignin fulfilled all requirements of European standards for certification except for ash content. However, as the raw material has no cost, this method can add value or contribute to financing continued sweeping and is an example of a circular economy scenario. Full article

We investigated the effect of chlorine dioxide (ClO₂) under low temperature drying to suppress rice cake stickiness during the cutting process by initiating the onset of retrogradation until the stickiness is minimized for shelf-life extension. The intermittent ClO₂ application at low-temperature drying was conducted at 10 °C for different drying periods (0, 6, 12, 18, and 24 h). Texture analysis showed significant differences with increasing values of hardness (901.39 ± 53.87 to 12,653 ± 1689.35 g) and reduced values of modified adhesiveness (3614.37 ±578.23 to 534.81 ± 89.37 g). The evaluation of rice cake stickiness during the cutting process revealed an optimum drying period of 18 h with no significant difference (p ≤ 0.05) compared to the 24 h drying process. Microbial contamination during the drying process increased, with microbial load from 6.39 ± 0.37 to 7.94 ± 0.29 CFU/g. Intermittent ClO₂ application at 22 ppm successfully reduced the microbial load by 63% during drying process. The inhibitory property of ClO₂ was further analyzed on a sample with high initial microbial load (3.01 ± 0.14 CFU/g) using primary and modified secondary growth models fitted to all experimental storage temperatures (5–25 °C) with R² values > 0.99. The model demonstrated a strong inhibition by ClO₂ with microbial growth not exceeding the accepted population threshold (10⁶ CFU/g) for toxin production. The shelf-life of rice cake was increased by 86 h and 432 h at room temperature (25 °C) and 5 °C respectively. Microbial inactivation via ClO₂ treatment is a novel method for improved food storage without additional thermal sterilization or the use of an additional processing unit. Full article

Since the 1950s, Process Systems Engineering (PSE) concepts have traditionally been applied to the process industries, with great effect and with significant benefit. However, the same general approaches and principles in designing complex process designs can be applied to the design of higher education (HE) curricula. Curricula represent intended learning journeys, these being similar to the design of process flowsheets. In this paper, we set out the formal framework and concepts that underlie the challenges in design of curricula. The approaches use generic and fundamental concepts that can be applied by any discipline to curriculum design. We show how integration of discipline-specific concepts, across time and space, can be combined through design choices, to create learning journeys for students. These concepts are captured within a web-based design tool that permits wide choices for designers to build innovative curricula. The importance of visualization of curricula is discussed and illustrated, using a range of tools that permit insight into the nature of the designs. The framework and tool presented in this paper have been widely used across many disciplines, such as science, engineering, nursing, philosophy and pharmacy. As a special issue in memory of Professor Roger W.H. Sargent; we show these new developments in curriculum design are similar to the development of process flowsheets. Professor Sargent was not only an eminent research leader and pioneer, but an influential educator who gave rise to a new area in Chemical Engineering, influencing its many directions for more than 50 years. Full article

Carbon-silica composites with nanoporous structures were synthesized for the adsorption of volatile organic compounds (VOCs), taking tetraethyl orthosilicate (TEOS) as the silicon source and activated carbon powder as the carbon source. The preparation conditions were as follows: the pH of the reaction system was 5.5, the hydrophobic modification time was 50 h, and the dosage of activated carbon was 2 wt%. Infrared spectrum analysis showed that the activated carbon was dispersed in the pores of aerogel to form the carbon-silica composites material. The static adsorption experiments, dynamic adsorption-desorption experiments, and regeneration experiments show that the prepared carbon-silica composites have microporous and mesoporous structures, the adsorption capacity for n-hexane is better than that of conventional hydrophobic silica gel, and the desorption performance is better than that of activated carbon. It still has a high retention rate of adsorption capacity after multiple adsorption-desorption cycles. The prepared carbon-silica composites material has good industrial application prospects in oil vapor recovery, providing a new alternative for solving organic waste gas pollution. Full article

A machine learning-based analysis was applied to process data obtained from a Basic Oxygen Steelmaking (BOS) pilot plant. The first purpose was to identify correlations between operating parameters and reactor performance, defined as rate of decarburization (dc/dt). Correlation analysis showed, as expected a strong positive correlation between the rate of decarburization (dc/dt) and total oxygen flow. On the other hand, the decarburization rate exhibited a negative correlation with lance height. Less obviously, the decarburization rate, also showed a positive correlation with temperature of the waste gas and CO₂ content in the waste gas. The second purpose was to train the pilot-plant dataset and develop a neural network based regression to predict the decarburization rate. This was used to predict the decarburization rate in a BOS furnace in an actual manufacturing plant based on lance height and total oxygen flow. The performance was satisfactory with a coefficient of determination of 0.98, confirming that the trained model can adequately predict the variation in the decarburization rate (dc/dt) within BOS reactors. Full article

Considering the communication resources limitation, the hybrid-triggered mechanism based distributed control of islanded microgrids cluster is proposed, which can restore the frequency to the rated value and realize the active power sharing when the disturbance occurs. The hybrid-triggered mechanism consists of the self- and event-triggered mechanisms, which are configured at each leader and follower distributed generation to determine the inter-microgrids and intra-microgrid information transmission, respectively. The communication burdens can be sharply reduced since the information is transmitted aperiodically only when the proposed triggering conditions are satisfied under the hybrid-triggered mechanism. Moreover, Zeno behavior is analyzed to be avoided to make the hybrid-triggered mechanism reasonable and practicable for practical islanded microgrids cluster. The simulation verifies the effectiveness of theoretical results. Full article

In the mobile wireless sensor network (MWSN) field, there exists an important problem—how can we quickly form an MWSN to cover a designated working area on the ground using an unmanned aerial vehicle (UAV) swarm? This problem is of significance in many military and civilian applications. In this paper, inspired by intermolecular forces, a novel molecular force field-based optimal deployment algorithm for a UAV swarm is proposed to solve this problem. A multi-rotor UAV swarm is used to carry sensors and quickly build an MWSN in a designated working area. The necessary minimum number of UAVs is determined according to the principle that the coverage area of any three UAVs has the smallest overlap. Based on the geometric properties of a convex polygon, two initialization methods are proposed to make the initial deployment more uniform, following which, the positions of all UAVs are subsequently optimized by the proposed molecular force field-based deployment algorithm. Simulation experiment results show that the proposed algorithm, when compared with three existing algorithms, can obtain the maximum coverage ratio for the designated working area thanks to the proposed initialization methods. The probability of falling into a local optimum and the computational complexity are reduced, while the convergence rate is improved. Full article

In this paper, the Q-learning method for quadratic optimal control problem of discrete-time linear systems is reconsidered. The theoretical results prove that the quadratic optimal controller cannot be solved directly due to the linear correlation of the data sets. The following corollaries have been made: (1) The correlation of data is the key factor in the success for the calculation of quadratic optimal control laws by Q-learning method; (2) The control laws for linear systems cannot be derived directly by the existing Q-learning method; (3) For nonlinear systems, there are some doubts about the data independence of current method. Therefore, it is necessary to discuss the probability of the controllers established by the existing Q-learning method. To solve this problem, based on the ridge regression, an improved model-free Q-learning quadratic optimal control method for discrete-time linear systems is proposed in this paper. Therefore, the computation process can be implemented correctly, and the effective controller can be solved. The simulation results show that the proposed method can not only overcome the problem caused by the data correlation, but also derive proper control laws for discrete-time linear systems. Full article

Solar energy is considered one of the most important renewable energy resources, and can be used to power a stand-alone photovoltaic (SAPV) system for supplying electricity in a remote area. However, inconstancy and unpredictable amounts of solar radiation are considered major obstacles in designing SAPV systems. Therefore, an accurate sizing method is necessary to apply in order to find an optimal configuration and fulfil the required load demand. In this study, a novel hybrid sizing approach was developed on the basis of techno-economic objectives to optimally size the SAPV system. The proposed hybrid method consisted of an intuitive method to estimate initial numbers of PV modules and storage battery, an iterative approach to accurately generate a set of wide ranges of optimal configurations, and a Pareto envelope-based selection algorithm (PESA-II) to reduce large configuration by efficacy obtaining a set of Pareto front (PF) solutions. Subsequently, the optimal configurations were ranked by using an integrated analytic hierarchy process (AHP) and vlsekeriterijumskaoptimizacija i kompromisonoresenje (VIKOR). The techno-economic objectives were loss of load probability, life cycle cost, and levelized cost of energy. The performance analysis results demonstrated that the lead–acid battery was reliable and more cost-effective than the other types of storage battery. Full article

Recently, the interest in converting waste cooking oils (WCOs) to raw materials has grown exponentially. The driving force of such a trend is mainly represented by the increasing number of WCO applications, combined with the definition, in many countries, of new regulations on waste management. From an industrial perspective, the simple chemical composition of WCOs make them suitable as valuable chemical building blocks, in fuel, materials, and lubricant productions. The sustainability of such applications is sprightly related to proper recycling procedures. In this context, the development of new recycling processes, as well as the optimization of the existing ones, represents a priority for applied chemistry, chemical engineering, and material science. With the aim of providing useful updates to the scientific community involved in vegetable oil processing, the current available technologies for WCO recycling are herein reported, described, and discussed. In detail, two main types of WCO treatments will be considered: chemical transformations, to exploit the chemical functional groups present in the waste for the synthesis of added value products, and physical treatments as extraction, filtration, and distillation procedures. The first part, regarding chemical synthesis, will be connected mostly to the production of fuels. The second part, concerning physical treatments, will focus on bio-lubricant production. Moreover, during the description of filtering procedures, a special focus will be given to the development and applicability of new materials and technologies for WCO treatments. Full article

In this study, a roasting-hydrolysis-acid leaching process is used to extract scandium from the scandium rough concentrate. The scandium rough concentrate containing Sc₂O₃ of 76.98 g/t was obtained by magnetic separation, gravity separation, and electric separation from Sc-bearing Vi-Ti magnetite tailings in the Panxi area of China. The majority of scandium in scandium rough concentrate mainly occurs in diopside, titanopyroxene, montmorillonite, chlorite, talc, aluminosilicate minerals, and isomorphism. Sodium salt and scandium coarse concentrate are added into the roasting furnace for roasting, which makes the fusion reaction of silicon, aluminum and sodium salt to produce soluble salts such as sodium silicate and sodium metaaluminate. Scandium is further recovered from the hydrolysis residue by acid leaching. Test results show scandium leaching recovery of 95.12% and the acid leaching residue with Sc₂O₃ content of 8.12 g/t are obtained, while the extraction of scandium is obvious. There is no obvious peak value of Scandium spectrum in hydrochloric acid leach residue. Most of scandium in hydrolytic residue is dissolved into Sc³⁺ and enters into the liquid phase. The main minerals in leach residue are perovskite, ferric silicate, and olivine. Full article

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, outlines the progress made, and identifies specific areas where future work can advance this area of study. A relatively small amount of publications are available compared to other fields, with most work occurring in the area of exergy based multi-objective optimization. Full article

The aim of the present paper is to investigate the deformation–stress state of fillings of V-shaped tooth defects by finite element analysis (FEA). Two different materials are used—auto-cured resin-reinforced glass-ionomer cement (GIC) and flowable photo-cured composite (FPC). Two materials are placed into the cavity in one portion, as before the application of the composite the cavity walls are covered with a thin adhesive layer. Deformations and equivalent von Mises stresses are evaluated by FEA. Experimental study of micro-leakage is performed. It is established that there is an analogous non-homogeneous distribution of equivalent Von Mises stresses at fillings of V-shaped defects, made with GIC and FPC. Maximum stresses are generated along the boundaries of the filling on the vestibular surface of the tooth and at the bottom of the filling itself. Values of equivalent Von Mises stresses of GIC fillings are higher than that of FPC. Magnitude and character of deformation distribution at GIC and FPC fillings are similar—deformation is maximum along the vestibular surface of the filling and is 0.056 and 0.053 mm, respectively. In FPC fillings, the adhesive layer, located along the cavity/filling boundary, is characterized with greatest strain. The experimental study of micro-leakage has confirmed the adequacy of models used in FEA. Full article

Recently, pore network modelling has been attracting attention in the investigation of electrolysis. This study focuses on a 2D pore network model with the purpose to study the drainage of water by oxygen in anodic porous transport layers (PTL). The oxygen gas produced at the anode catalyst layer by the oxidation of water flows counter currently to the educt through the PTL. When it invades the water-filled pores of the PTL, the liquid is drained from the porous medium. For the pore network model presented here, we assume that this process occurs in distinct steps and applies classical rules of invasion percolation with quasi-static drainage. As the invasion occurs in the capillary-dominated regime, it is dictated by the pore structure and the pore size distribution. Viscous and liquid film flows are neglected and gravity forces are disregarded. The curvature of the two-phase interface within the pores, which essentially dictates the invasion process, is computed from the Young Laplace equation. We show and discuss results from Monte Carlo pore network simulations and compare them qualitatively to microfluidic experiments from literature. The invasion patterns of different types of PTLs, i.e., felt, foam, sintered, are compared with pore network simulations. In addition to this, we study the impact of pore size distribution on the phase patterns of oxygen and water inside the pore network. Based on these results, it can be recommended that pore network modeling is a valuable tool to study the correlation between kinetic losses of water electrolysis processes and current density. Full article

Polymer flooding is a promising enhanced oil recovery (EOR) technique; sweeping a reservoir with a dilute polymer solution can significantly improve the overall oil recovery. In this overview, polymeric materials for enhanced oil recovery are described in general terms, with specific emphasis on desirable characteristics for the application. Application-specific properties should be considered when selecting or developing polymers for enhanced oil recovery and should be carefully evaluated. Characterization techniques should be informed by current best practices; several are described herein. Evaluation of fundamental polymer properties (including polymer composition, microstructure, and molecular weight averages); resistance to shear/thermal/chemical degradation; and salinity/hardness compatibility are discussed. Finally, evaluation techniques to establish the polymer flooding performance of candidate EOR materials are described. Full article

This paper experimentally analyzes the chemical additives, i.e., methanol and ethanol, as alcohol solvents, and acetone as a ketone solvent, and the temperature influencing the minimum miscibility pressure (MMP) that is essential to design miscible CO₂ flooding at an oil field, the South Sumatra basin, Indonesia. The experiments were designed to measure CO₂-oil interfacial tension with the vanishing interfacial tension (VIT) method in the ranges up to 3000 psi (208.6 bar) and 300 degrees Celsius. The experiment results show that lower temperatures, larger solvent volumes, and the acetone were effective in reducing MMP. The acetone, an aprotic ketone solvent, reduced MMP more than the methanol and the ethanol in the CO₂-oil system. The high temperature was negative to obtain the high CO₂ solubility into the oil as well as the lower MMP. The experimental results confirm that the aprotic ketone solvent could be effective in decreasing the MMP for the design of miscible CO₂ flooding at the shallow mature oilfields with a low reservoir temperature. Full article

In order to achieve better dynamics performances of a class of automobile active suspensions with the model uncertainties and input delays, this paper proposes a generalized robust linear H₂/H_∞ state feedback control approach. First, the mathematical model of a half-automobile active suspension is established. In this model, the H_∞ norm of body acceleration is determined as the performance index of the designed controller, and the hard constraints of suspension dynamic deflection, tire dynamic load and actuator saturation are selected as the generalized H₂ performance output index of the designed controller to satisfy the suspension safety requirements. Second, a generalized H₂/H_∞ guaranteed cost state-feedback controller is developed in terms of Lyapunov stability theory. In addition, the Cone Complementarity Linearization (CCL) algorithm is employed to convert the generalized H₂/H_∞ output-feedback control problem into a finite convex optimization problem (COP) in a linear matrix inequality framework. Finally, a numerical simulation case of this half-automobile active suspension is presented to illustrate the effectiveness of the proposed controller in frequency-domain and time-domain. Full article

The invention of reconfigurable manufacturing systems (RMSs) has created a challenging problem: how to quickly and effectively modify an RMS to address dynamic changes in a manufacturing system, such as processing failures and rework, machine breakdowns, addition of new machines, addition of new products, removal of old machines, and changes in processing routes induced by the competitive global market. This paper proposes a new model, the intelligent colored token Petri net (ICTPN), to simulate dynamic changes or reconfigurations of a system. The main idea is that intelligent colored tokens denote part types that represent real-time knowledge about changes and status of a system. Thus, dynamic configurations of a system can be effectively modeled. The developed ICTPN can model dynamic changes of a system in a modular manner, resulting in the development of a very compact model. In addition, when configurations appear, only the changed colored token of the part type from the current model has to be modified. Based on the resultant ICTPN model, deadlock-free, conservative, and reversible behavioral properties, among others, are guaranteed. The developed ICTPN model was tested and validated using the GPenSIM tool and compared with existing methods from the literature. Full article

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 sets of Nelder-Mead coefficients previously proposed by other researchers. For the investigation purposes, the bleed and outlet pressures from the turbines were considered as decision variables, and the power plant efficiency was used as an objective function. Full article

The conventional maximum power point tracking (MPPT) method fails in partially shaded conditions, because multiple peaks may appear on the power–voltage characteristic curve. The Pigeon-Inspired Optimization (PIO) algorithm is a new type of meta-heuristic algorithm. Aiming at this situation, this paper proposes a new type of algorithm that combines a new pigeon population algorithm named Parallel and Compact Pigeon-Inspired Optimization (PCPIO) with MPPT, which can solve the problem that MPPT cannot reach the near global maximum power point. This hybrid algorithm is fast, stable, and capable of globally optimizing the maximum power point tracking algorithm. Therefore, the purpose of this article is to study the performance of two optimization techniques. The two algorithms are Particle Swarm Algorithm (PSO) and improved pigeon algorithm. This paper first studies the mechanism of multi-peak output characteristics of photovoltaic arrays in complex environments, and then proposes a multi-peak MPPT algorithm based on a combination of an improved pigeon population algorithm and an incremental conductivity method. The improved pigeon algorithm is used to quickly locate near the maximum power point, and then the variable step size incremental method INC (incremental conductance) is used to accurately locate the maximum power point. A simulation was performed on Matlab/Simulink platform. The results prove that the method can achieve fast and accurate optimization under complex environmental conditions, effectively reduce power oscillations, enhance system stability, and achieve better control results. Full article

Among a large number of current biomedical applications in the use of medical devices, carbon-based nanomaterials such as graphene (G), graphene oxides (GO), reduced graphene oxide (rGO), and carbon nanotube (CNT) are frontline materials that are suitable for developing medical devices. Carbon Based Nanomaterials (CBNs) are becoming promising materials due to the existence of both inorganic semiconducting properties and organic π-π stacking characteristics. Hence, it could effectively simultaneously interact with biomolecules and response to the light. By taking advantage of such aspects in a single entity, CBNs could be used for developing biomedical applications in the future. The recent studies in developing carbon-based nanomaterials and its applications in targeting drug delivery, cancer therapy, and biosensors. The development of conjugated and modified carbon-based nanomaterials contributes to positive outcomes in various therapies and achieved emerging challenges in preclinical biomedical applications. Subsequently, diverse biomedical applications of carbon nanotube were also deliberately discussed in the light of various therapeutic advantages. Full article

Freeze-drying is an important processing unit operation in food powder production. It offers dehydrated products with extended shelf life and high quality. Unfortunately, food quality attributes and grinding characteristics are affected significantly during the drying process due to the glass transition temperature (during drying operation) and stress generated (during grinding operation) in the food structure. However, it has been successfully applied to several biological materials ranging from animal products to plants products owning to its specific advantages. Recently, the market demands for freeze-dried and ground food products such as spices, vegetables, and fruits are on the increase. In this study, the effect of the freeze-drying process on quality attributes, such as structural changes, the influence of glass transition during grinding, together with the effect on grinding efficiency in terms of energy requirement, grinding yield, and morphological changes in the powder as a result of temperature, drying time were discussed. An overview of models for drying kinetics for freeze-dried food sample, and grinding characteristics developed to optimize the drying processes, and a prediction of the grinding characteristics are also provided. Some limitations of the drying process during grinding are also discussed together with innovative methods to improve the drying and grinding processes. Full article

Directmethanol fuel cells (DMFCs) offer one of the most promising alternatives for the replacement of fossil fuels. A DMFC that had an active Membrane Electrode Assembly (MEA) area of 45 cm², a squoval-shaped manifold hole design, and a Pt-Ru/C catalyst combination at the anode was taken for analysis in simulation and real-time experimentation. A mathematical model was developed using dynamic equations of a DMFC. Simulation of a DMFC model using MATLAB software was carried out to identify the most influencing process variables, namely cell temperature, methanol flow rate and methanol concentration during a DMFC operation. Simulation results were recorded and analyzed. It was observed from the results that the cell temperature was the most influencing process variable in the DMFC operation, more so than the methanol flow rate and the methanol concentration. In the DMFC, real-time experimentation was carried out at different cell temperatures to find out the optimum temperature at which maximum power density was obtained. The results obtained in simulation and the experiment were compared and it was concluded that the temperature was the most influencing process variable and 333K was the optimum operating temperature required to achieve the most productive performance in power density of the DMFC. Full article

Modeling and optimization of a double-inlet pulse tube refrigerator (DIPTR) is very difficult due to its geometry and nature. The objective of this paper was to optimize-DIPTR through experiments with the cold heat exchanger (CHX) along the comparison of cooling load with experimental data using different boundary conditions. To predict its performance, a detailed two-dimensional DIPTR model was developed. A double-drop pulse pipe cooler was used for solving continuity, dynamic and power calculations. External conditions for applicable boundaries include sinusoidal pressure from an end of the tube from a user-defined function and constant temperature or limitations of thermal flux within the outer walls of exchanger walls under colder conditions. The results of the system’s cooling behavior were reported, along with the connection between the mass flow rates, heat distribution along pulse tube and cold-end pressure, the cooler load’s wall temp profile and cooler loads with varied boundary conditions i.e. opening of 20% double-inlet and 40-60% orifice valves, respectively. Different loading conditions of 1 and 5 W were applied on the CHX. At 150 K temperature of the cold-end heat exchanger, a maximum load of 3.7 W was achieved. The results also reveal a strong correlation between computational fluid dynamics modeling results and experimental results of the DIPTR. Full article

The combined cooling, heating and power (CCHP) system not only has high energy efficiency but also has different load structures. Traditional separate production (SP) system and power supply system do not consider the land cost in terms of the environmental benefits, and in the aspect of the power supply reliability, the grid-connected inverter cost is also ignored. Considering the deficiency of the traditional energy supply system, this paper builds the CCHP system construction cost model. The particle swarm optimization (PSO) is adopted to find out the minimum value of the construction cost, and the optimal system construction scheme is constructed from three aspects which are system reliability, economic benefits and environmental benefits. In this paper, the typical daily data, as well as the meteorological data and the load data, in the last four years are taken as experimental dataset. The experimental results show that compared with the traditional SP system and power supply system, the CCHP system established in this paper not only achieves lower cumulative investment cost, but also has a good power supply reliability and environmental benefits. Full article

Growing concern on global warming directly related to CO₂ emissions is steering the implementation of carbon capture and storage (CCS). With Malaysia having an estimated 37 Tscfd (Trillion standard cubic feet) of natural gas remains undeveloped in CO₂ containing natural gas fields, there is a need to assess the viability of CCS implementation. This study performs a techno-economic analysis for CCS at an offshore natural gas field in Malaysia. The framework includes a gas field model, revenue model, and cost model. A techno-economic spreadsheet consisting of Net Present Value (NPV), Payback Period (PBP), and Internal Rate of Return (IRR) is developed over the gas field’s production life of 15 years for four distinctive CO₂ capture technologies, which are membrane, chemical absorption, physical absorption, and cryogenics. Results predict that physical absorption solvent (Selexol) as CO₂ capture technology is most feasible with IRR of 15% and PBP of 7.94 years. The output from the techno-economic model and associated risks of the CCS project are quantified by employing sensitivity analysis (SA), which indicated that the project NPV is exceptionally sensitive to gas price. On this basis, the economic performance of the project is reliant on revenues from gas sales, which is dictated by gas market price uncertainties. Full article

Polymeric flocculants are widely used due to their ability to efficiently promote flocculation at low dosages. However, fundamental background knowledge about how they act and interact with the substrates is often scarce, or insufficient to infer the best chemical configuration for treating a specific effluent. Inductive, data-driven approaches offer a viable solution, enabling the development of effective solutions for each type of effluent, overcoming the knowledge gap. In this work, we present such an inductive workflow that combines the statistical design of experiments and predictive modelling, and demonstrates its effectiveness in the development of anionic polymeric flocculants for the treatment of a real effluent from the potato crisps manufacturing industry. Based on the results presented, it is possible to conclude that the hydrodynamic diameter, charged fraction and concentration are the parameters with a stronger influence on the characteristics of flocs obtained when using copolymers, while the charged fraction, concentration and hydrophobic content present a stronger influence on the characteristics of flocs obtained using terpolymers containing a hydrophobic monomer. Full article