Chemical Engineering Research & Design最新文献

Recently, nanofluids (NFs) have gathered significant attention among researchers due to their varied properties, which can be made per the requirements. NFs, created by infusing nanoparticles into a base-fluid, enhance their fundamental properties. A hybrid nanofluid (HNF) is a nanofluid (NF) containing different types of nanoparticles, and it is being studied for its customizable properties. Recently, researchers delved into the applications regarding HNFs, particularly in cases relating to heat transfer (HT). This study analyzes HNFs’ preparation methods and thermophysical properties, giving more importance to their applications in HT, including heat-exchange, solar thermal, and cooling systems. Considering stability, the two-step synthesis method is preferred over the single-step method. Multiple research efforts have led to the development of a fluid that possesses superior HT capabilities compared to the base-fluid. However, while bettering HT, an increase in volume concentration (VC) also raised challenges such as increased viscosity and pressure drop, particularly in porous media, necessitating additional pumping power. The use of turbulators and other configurations, along with HNF in systems like parabolic trough solar collectors (PTSCs), enhances solar thermal systems (STSs) by improving their HT capabilities. An advantageous use of EG-based multiwalled carbon nanotubes (MWCNTs) NF in solar collectors (SCs) is their ability to increase thermal efficiency and decrease carbon dioxide emissions, making them an attractive choice for use in SCs. Researchers face significant challenges in determining the ideal composition and concentration of nanoparticles in HNFs to attain optimal HT without causing excessive viscosity that could impede practical usability. Specifically, this study examines the distinctive thermophysical characteristics of HNFs that substantially improve their efficacy in HT applications.

This paper presents the techno-economics insights of projects of diethyl carbonate (DEC) production from ethanol and CO₂ in which the raw materials are proposed to be obtained from existing plants such as the bioethanol industry. The complete DEC plant was simulated using Aspen Plus®. The exothermic reaction system was modeled in multitubular PFR with CeO₂ catalyst and dehydrating agent 2-cyanopyridine (2-CP), achieving an EtOH conversion of 86.04 % and a yield of DEC of 83.34 %. Three different configurations were evaluated in the DEC separation stage aiming to intensify the plant with the use of a sidestream distillation column and reactive distillation column. The integration of the DEC plant with ethanol and sugar biorefineries, offering lower-cost acquisition of raw materials, is the key to making the process economically profitable. The process has the potential to capture 0.088–0.204 kg CO₂/kg DEC, demonstrating a promising pathway to extend the life cycle of renewable carbon.

The growing demand for sustainable and green energy sources has led to increasing interest in biohydrogen production from renewable biomass feedstocks. In this study, pulp and paper sludge (PPS), a widely available waste residue, was thermally treated at different temperatures (90^°C, 130^°C, and 165^°C) for varying durations (15, 30, and 60 min). Thermal hydrolysis of PPS increased the chemical oxygen demand (COD) solubilization from 11 % to 24.7 %, and volatile suspended solids (VSS) solubilization up to 15 % with increasing both hydrolysis temperature and reaction time. The resulting thermally treated samples were then evaluated for biohydrogen production through a batch assay. Among the different thermal treatment conditions, the sample treated at 165^°C for 60 min exhibited the highest biohydrogen production potential and yield (1287 mL-H₂ and 201 mL-H₂/g volatile solids (VS)), which is 72 % higher the control untreated PPS (747 mL-H₂ and 117 mL-H₂/gVS). To further enhance the biohydrogen yield, this optimal sample was mixed with two types of chemically synthesized nanoparticles, namely aluminium oxide (Al₂O₃) and magnetite (Fe₃O₄), at various concentrations (50, 100, and 200 mg/g VS). The addition of nanoparticles significantly influenced the biohydrogen production from the thermal-treated PPS. Remarkably, the batch assay mixed with 200 mg of Fe₃O₄ nanoparticles per gram of VS demonstrated the highest biohydrogen production potential, compared to the thermally treated PPS (1577 vs. 1226 mL-H₂). This finding suggests that the presence of Fe₃O₄ nanoparticles enhances the biohydrogen production process, possibly through improved microbial activity and substrate accessibility. The results of this study highlight the potential of utilizing PPS, an abundant waste product, as a valuable feedstock for biohydrogen production. Overall, this study contributes to the advancement of green energy technologies and underscores the potential of biohydrogen as a renewable and sustainable energy source.

The importance of free radicals in several chemical and biological systems has been extensively documented in the literature. Free radical detection is possible through techniques such as electron spin resonance (ESR), chemically induced dynamic nuclear polarization (CIDNP), and biochemiluminescence. Herein, we provide a comprehensive review of free radical detection, with an emphasis on free radical quantification. The ability to control free radical reactions of various matrices necessitates measuring free radical concentration, which can be obtained by quantifying free radicals. In the current work, we provide a review of various methods and procedures employed for free radical quantification in chemical systems. Procedures were discussed in detail and then grouped based on the instrument used, the operating conditions, and the methodology employed to convert the ESR signal obtained to free radical spins per unit mass of sample. We also provide a comparison with free radical quantification in biological systems. It was found that there is a notable dearth of work focused on quantification in chemical systems despite its potential to enhance control over free radicals. In the last part of this manuscript, we provide a summary and suggested methodology for free radical quantification in chemical systems using ESR focusing on factors affecting quantification.

The vortex tube is a potential candidate for sustainable cooling due to its unique feature of energy separation without using any synthetic refrigerant. However, the investigation of energy separation and performance optimization always has been challenging due to its complex physics. In previous literature, the performance of vortex tube has been found affected by several parameters. In order to find the impact of varying cold end diameters with different gases, this paper investigates temperature separation in seven vortex tubes of different cold end diameters operating with three different working gases: He, N₂, and CO₂. A detailed thermodynamic analysis of their thermal separation performances at different cold mass fractions is presented for each working gas. Exergy analysis has also been conducted and discussed separately. As a result of this extensive investigation, it is found that the larger cold end diameter improves the performance of the vortex tube. The cold and hot temperature separation, cooling, and heating power at higher cold mass fractions are found to improve when operated with helium compared to other gas. However, the COP of cooling and COP of heating at higher cold mass fractions is found to be lower with helium. Improvements in the physical and kinetic exergies at the inlet and both outlets are observed with increasing cold end diameter, except for the kinetic exergy at the hot outlet. Helium gas is found to show more exergy at the inlet and both outlets among all three gases. The performance of vortex tube operating at higher cold mass fraction shows an improvement in exergies at outlets, except kinetic exergies at hot outlet. The total exergy efficiency decreases at cold outlet on increasing cold end diameter. However, the results of actual (physical) exergy efficiency shows an improvement at both outlet for larger cold end diameter. The actual exergy efficiency is calculated by considering the physical exergy alone because the kinetic exergy completely lost into the open atmosphere. Physical exergy efficiency at hot outlet is also found to increase on increasing cold mass fraction, while it decreases at cold outlet. Physical exergy efficiency of cooling and heating are found to more when operated with helium compared to nitrogen and carbon dioxide.

Small sample size presents a significant challenge in process modeling, making machine learning (ML) models prone to overfitting and reduced accuracy. To address this issue, this study develops a novel inductive transfer regression framework called double-weight least squares support vector regression (DWLSSVR). First, sample weights are incorporated to minimize the multi-kernel maximum mean discrepancy (MK-MMD) between domains, thereby promoting joint distribution adaptation and decreasing domain discrepancy. Second, the impact of unrelated source domain samples is further mitigated by iterative weights derived from fitting errors. In addition, a two-step strategy is developed to optimize the hyperparameters in DWLSSVR, which introduces a new criterion based on Wasserstein distance (WD). A numerical simulation demonstrates the effectiveness of the developed framework. Then, the proposed method is applied to the small sample modeling of a complex chemical process. The results of predicting NO_x emissions from a coal-fired boiler demonstrate that the DWLSSVR model achieves superior prediction accuracy, with a coefficient of determination (R²) of 0.942 under the new operating condition. In contrast, the best LSSVR model achieves an R² of 0.844 under the same condition.

Vertical mixing plays a critical role in solar-driven processes using raceway pond reactors (RPRs). However, incorporating the time history of radiation for each fluid element is still an open issue. This work aims to develop an effective methodology using Computational Fluid Dynamics (CFD) tools that couples hydrodynamics and radiation fields into kinetic models of biomass growth or cell lysis enhanced from radiation. First, three methodologies to assess vertical mixing were investigated. It was found that, under typical RPR flow conditions, the velocity in the direction of solar light incidence can maintain particles in constant motion and a near-homogenous particle distribution. In addition, two RPR applications were studied regarding radiation influence analysis: the production of microalgae and an innovative approach for waste activated sludge (WAS) pre-treatment, fostering biogas production. Regarding microalgae production, coupling the biokinetic models with CFD data enables the development of a cost-effective computational methodology to describe the growth of microalgae cultures accounting for hydrodynamics and radiation fields. This work was successful in introducing hydrodynamics and radiation conditions in models to design and optimise RPRs. Reduced geometries based in 2D and Periodic Boundary Conditions were used for CFD simulations to make it feasible for RPRs design purposes.

Coagulation and flocculation processes are commonly used in conventional water treatment plants to remove suspended solids from water. However, these methods often suffer from drawbacks such as high chemical consumption, sludge generation, and the need for huge areas, leading to high construction costs. To address these limitations, this study investigated the performance of in-line coagulation and flocculation processes as an alternative to conventional methods. The objectives were to determine the efficiency of in-line coagulation and flocculation, understand the underlying mechanisms, establish optimal operating conditions and design criteria, and to develop theoretical models for predicting turbidity removal efficiency in the in-line coagulation-flocculation process. Experiments were conducted using a continuous setup consisting of a static mixer and a 35-m helically coiled hydraulic tube flocculator.

Various operating parameters, including water flow rate (100 – 800 L/hr), initial turbidity (20 – 200 NTU), and coagulant types (aluminum sulfate, poly aluminum chloride, aluminum chlorohydrate, and ferric chloride), were examined. The results demonstrated that aluminum sulfate was the appropriate coagulant for the water characteristics studied, and the in-line coagulation and flocculation processes achieved turbidity removal efficiencies of approximately 91 % under all operating conditions, with a notable 97 % removal efficiency achieved at a liquid flow rate of 600 L/hr, with a Gt value of 21,715 and an overflow rate of 2 m/hr. A prediction model of turbidity removal efficiency was developed, showing good agreement between experimental and predicted removal efficiency model, with an average deviation of about 20 %. This model can aid in determining optimal operating conditions and serve as a hybrid process in future water treatment systems, potentially applicable to other separation processes as well.

The optimal design of low-pollution emission burners plays an important role in controlling pollutant emissions of industrial equipment, and is crucial for the sustainable development of the national economy and environmental protection. However, many uncertain factors challenge the optimal design of low-pollution emission burners. The Latin hypercube sampling (LHS) method was used to obtain sampling data representing the distribution of the uncertain variable. The training dataset was obtained using the turbulent combustion coupling model. A high-precision sparse polynomial chaos expansion (PCE) model was constructed by the degree-adaptive scheme and least angle regression (LAR) algorithm. Furthermore, the Legendre polynomial is introduced to establish a continuous robust optimization model. The model is carried out by the non-dominated sorting genetic algorithm II (NSGA-II). The results show that the excess air coefficient of 1.227 is optimal. Compared with the excess air coefficient of 1.20 under the discrete robust optimization, the optimal coefficient can further reduce pollutant emissions and bring strong robustness to the ethylene cracking furnace. It has also been proven that the continuous robust optimization scheme improves the optimization granularity. Compared with discrete robust optimization, this method reduces the number of samples by 66.7 %.

This study conducted experiments to mimic petroleum emulsions for application in laboratory flow circuits. The science of emulsion formulation is still quite restricted when it comes to parameters that stabilize emulsions. The challenge is even greater when formulating emulsions of low dynamic viscosity. In this work, model emulsions were prepared with different oil phases, with 0.1 and 1.0 % v/v of the surfactants Span 60, Span 80, Triton X-100, and Triton X-114, with 10 and 30 % v/v of aqueous phase. The kinetic stability of the emulsions evaluated in terms of aqueous phase separation, droplet size distribution, dynamic viscosity, and interfacial tension. The homogenization process assessed to identify the emulsification regime of the emulsions, inertial or viscous, through the calculation of the smallest vortices formed. A study of the maximum superficial flow velocity conducted to provide users with a better understanding of the emulsions produced here. The results indicate that seven emulsions can used in laboratory flow circuits. Span 80 provided better stabilization of the emulsions for over 72 hours with droplet sizes in the range of 0.2–100.0 µm. As a novelty in this work, increasing the concentration of surfactant Span 80 causes a decrease in average velocity in flow, a reduction in droplet size, and a regime of turbulent viscous emulsification in axial flow.