Processes

23 pages, 5040 KB

Open AccessArticle

Reactive Power Collaborative Control Strategy and Verification Method for Suppressing Voltage Oscillation in Renewable Energy Clusters

by Yanzhang Liu, Lingzhi Zhu, Minhui Qian and Chen Jia

Processes 2026, 14(3), 580; https://doi.org/10.3390/pr14030580 - 6 Feb 2026

Viewed by 724

Abstract

The rapid integration of renewable energy into power systems has made voltage oscillations caused by the intermittency of wind and solar power a critical operational challenge. To mitigate these issues, this paper proposes a multi-mode coordinated reactive power control strategy to enhance voltage [...] Read more.

The rapid integration of renewable energy into power systems has made voltage oscillations caused by the intermittency of wind and solar power a critical operational challenge. To mitigate these issues, this paper proposes a multi-mode coordinated reactive power control strategy to enhance voltage stability in renewable energy clusters. The approach integrates two key indicators: voltage sensitivity for steady-state regulation and an improved multi-renewable energy station short circuit ratio (MRSCR) that accounts for dynamic power interactions. Validation is conducted using a hardware-in-the-loop (HIL) platform combining real-time RMS-based simulation with physical controllers. Case studies on an offshore wind cluster demonstrate that the proposed method reduces voltage fluctuation amplitude more effectively than conventional automatic voltage control (AVC), successfully suppressing oscillations. The results confirm that the strategy exhibits stronger adaptability to varying grid conditions and offers a scalable solution for oscillation mitigation in large-scale renewable energy integration. Full article

(This article belongs to the Special Issue Operation and Control of New Power System with Large-Scale Renewable Energy Integration)

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23 pages, 4367 KB

Open AccessArticle

Tuning Gas Fingering in SAGD/SAGP: Operating Windows for NCG Timing and Concentration

by Hao Peng, Siyuan Huang, Mingxi Ge, Zhongyuan Wang, Qi Jiang, Kuncheng Li, Guanchen Jiang and Ian Gates

Processes 2026, 14(3), 579; https://doi.org/10.3390/pr14030579 - 6 Feb 2026

Viewed by 821

Abstract

A Steam-and-Gas Push (SAGP) enhances energy efficiency in Steam-Assisted Gravity Drainage (SAGD) but induces gas fingering instabilities that limit the sweep efficiency. This study systematically investigates the impact of in situ-generated and externally injected Non-Condensable Gas (NCG) on fingering using fine-grid numerical simulations [...] Read more.

A Steam-and-Gas Push (SAGP) enhances energy efficiency in Steam-Assisted Gravity Drainage (SAGD) but induces gas fingering instabilities that limit the sweep efficiency. This study systematically investigates the impact of in situ-generated and externally injected Non-Condensable Gas (NCG) on fingering using fine-grid numerical simulations based on the Du-84 heavy oil reservoir. Two novel dimensionless indexes (heat–gas overlap index and Y-index) are introduced to quantitatively diagnose the fingering severity and heat transfer mechanisms. The results indicate that vertical chamber growth is convection-dominated by buoyant gas fingers, while lateral expansion remains conduction-dominated and stable. Reservoir heterogeneity significantly exacerbates fingering. An NCG concentration-dependent mechanism is established: low-dose co-injection (~0.5 mol%) suppresses minor fingering and increases oil production via a thin insulating gas cap. Conversely, excessive NCG (>5 mol%) thickens the gas cap, hindering heat transfer. Based on these mechanisms, a practical NCG operating window is proposed: a mid-stage, low-dose injection maximizes the production benefit (+4.4%), while a late-stage, moderate-dose injection (~5 mol%) enhances the oil–steam ratio (OSR) by 20.5% with minimal production loss (3.8%). This research offers critical guidance for optimizing NCG injections to mitigate fingering and improve recovery in heterogeneous reservoirs. Full article

(This article belongs to the Topic Enhanced Oil Recovery Technologies, 4th Edition)

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33 pages, 3096 KB

Open AccessReview

Valorization of Sustainable Antioxidant Sources and New Perspectives for Utilization

by Simona Gavrilaș

Processes 2026, 14(3), 578; https://doi.org/10.3390/pr14030578 - 6 Feb 2026

Cited by 1 | Viewed by 826

Abstract

Sustainable sources of natural antioxidants are increasingly important for circular bioeconomy strategies. Plant-derived waste streams represent an underexploited resource with significant potential for recovery of high-value antioxidant compounds such as carotenoids, polyphenols, and resveratrol. This review assesses potential alternative biomass sources, including nonhazardous [...] Read more.

Sustainable sources of natural antioxidants are increasingly important for circular bioeconomy strategies. Plant-derived waste streams represent an underexploited resource with significant potential for recovery of high-value antioxidant compounds such as carotenoids, polyphenols, and resveratrol. This review assesses potential alternative biomass sources, including nonhazardous wastes from agriculture, forestry, and fishing, as well as those from the manufacture of food products, beverages, and tobacco products. It evaluates their valorization potential using statistical evidence at the European level. EUROSTAT datasets were analyzed using XLSTAT 2025.2.0 through correlation analysis, Principal Component Analysis (PCA), Agglomerative Hierarchical Clustering (AHC), and k-means clustering. Variables included fresh vegetable production, plant waste generation, processed waste volumes, and national research and development expenditures and innovation. Correlation analysis revealed a strong association between total processed waste and research and development investments (r = 0.87), suggesting that technological capacity influences waste valorization. A moderate correlation (r = 0.55) between nonhazardous waste and processed quantities supports the operational feasibility of extracting antioxidants from residual biomass. PCA showed that Factor 1 (50.16% variance) is dominated by waste generation and processing capacity, whereas organic agriculture loads primarily on Factor 2 (21.6%). Cluster analyses grouped European countries by bioresource management efficiency, highlighting substantial heterogeneity in their readiness for valorization. The combined statistical evidence supports the use of plant-based waste streams as viable, sustainable feedstocks for antioxidant recovery. Strengthening processing infrastructure, harmonizing data reporting, and accelerating research and development investments are essential steps for integrating antioxidant extraction into circular bioeconomic processes. Full article

(This article belongs to the Special Issue Advances in Extraction and Characterization of Functional Properties of Bioactive Compounds Obtained from Food Processing)

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23 pages, 1741 KB

Open AccessReview

New Trends in the Valorisation of the Solid Fraction of Digestate for the Production of Value-Added Bioproducts

by Jana Font-Pomarol, Esther Molina-Peñate, Adriana Artola and Antoni Sánchez

Processes 2026, 14(3), 577; https://doi.org/10.3390/pr14030577 - 6 Feb 2026

Viewed by 1191

Abstract

The rapid expansion of anaerobic digestion (AD) as a key technology for producing renewable energy has led to a substantial increase in digestate generation. This has intensified the need for sustainable management strategies that align with circular economy principles. While the solid fraction [...] Read more.

The rapid expansion of anaerobic digestion (AD) as a key technology for producing renewable energy has led to a substantial increase in digestate generation. This has intensified the need for sustainable management strategies that align with circular economy principles. While the solid fraction of digestate (SD) is traditionally applied to land or composted, its heterogeneous composition, regulatory constraints, and handling challenges restrict its wider use. This review aims to clarify the current state of SD treatment and highlight emerging opportunities to convert this underexploited resource into value-added bioproducts. A systematic bibliographic analysis of the past decade was conducted to identify consolidated and emerging SD valorisation technologies, supported by an evaluation of EU-level regulatory frameworks and the role of mechanical solid–liquid separation in enabling downstream valorisation. In addition, a comprehensive comparative table compiling physicochemical characterisation data of SD from various feedstocks and separation methods is presented, emphasising the significant variability in composition and its implications for valorisation pathways. The results show that, while composting and thermochemical routes, particularly pyrolysis, remain predominant, novel approaches such as advanced drying, pelletisation, vermicomposting, insect bioconversion, and fermentation-based pathways (including submerged and solid-state fermentation) are rapidly gaining interest. These emerging technologies enable the production of high-value products such as biochar, pellets, enzymes, microbial biopesticides, protein sources, and fungal biomass. However, their adoption is currently limited by feedstock heterogeneity, process complexity, scalability constraints, and economic considerations. Overall, SD is a versatile feedstock whose valorisation is expanding beyond agricultural applications. However, regulatory harmonisation, quality assurance, and process optimisation are still needed to encourage industrial uptake and to fully integrate SD into circular bioeconomy frameworks. Full article

(This article belongs to the Special Issue Feature Review Papers in Section "Environmental and Green Processes")

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17 pages, 3705 KB

Open AccessArticle

A High-Throughput, Model-Free Marker Library Approach for Multivariate Adulteration Detection in Vegetable Oils: From Metabolomic Discovery to Regulatory Screening

by Hui Wang, Xiaotu Chang, Yan Zhang, Lu Wang, Lili Hu, Nan Deng, Jijun Qin, Feifei Zhong, Ben Li, Fangyun Xie, Dan Ran, Lei Lv and Peng Zhou

Processes 2026, 14(3), 576; https://doi.org/10.3390/pr14030576 - 6 Feb 2026

Cited by 2 | Viewed by 660

Abstract

Adulteration of high-value oils such as olive and camellia oil poses serious challenges to market integrity and consumer safety. This study develops a comprehensive, model-free marker library for high-throughput detection of single and multivariate adulteration across nine vegetable oils (olive, camellia, sesame, rapeseed, [...] Read more.

Adulteration of high-value oils such as olive and camellia oil poses serious challenges to market integrity and consumer safety. This study develops a comprehensive, model-free marker library for high-throughput detection of single and multivariate adulteration across nine vegetable oils (olive, camellia, sesame, rapeseed, flaxseed, soybean, peanut, industrial hemp seed, and sunflower seed oils) using untargeted metabolomics via UHPLC-Q-TOF-MS. We identified 34 characteristic markers, including 9 confirmed by reference standards, such as hydroxytyrosol in olive oil, camelliasaponins in camellia oil, and sesamin in sesame oil, which are uniquely present in specific oils and absent in others. The method enables reliable qualitative screening of adulteration at levels as low as 5% without dependence on chemometric models. Validation using binary and multicomponent blends confirmed its robustness and specificity. In commercial sample analysis, adulteration was detected in 16.0% of olive oils (4/25) and 12.7% of camellia oils (7/55), with results consistent with regulatory findings. This work establishes the first integrated marker library for simultaneous screening of nine vegetable oils, offering a standardized, high-throughput tool for large-scale market surveillance that bridges the gap between discovery-based omics and routine regulatory practice. Full article

(This article belongs to the Special Issue Green Technologies for Food Processing)

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26 pages, 3632 KB

Open AccessArticle

Clinoptilolite-Supported ZnO and TiO₂ Composites for High-Efficiency Adsorption of Methylene Blue

by Esra Altintig and Onur Kabadayi

Processes 2026, 14(3), 575; https://doi.org/10.3390/pr14030575 - 6 Feb 2026

Cited by 2 | Viewed by 1198

Abstract

This study aims to evaluate the adsorption performance of ZnO- and TiO₂-coated clinoptilolite composites for the removal of methylene blue (MB) from aqueous solutions and to clarify the governing adsorption mechanisms. Batch adsorption experiments were systematically conducted to investigate the effects [...] Read more.

This study aims to evaluate the adsorption performance of ZnO- and TiO₂-coated clinoptilolite composites for the removal of methylene blue (MB) from aqueous solutions and to clarify the governing adsorption mechanisms. Batch adsorption experiments were systematically conducted to investigate the effects of initial pH (3–10), MB concentration (50–200 mg/L), adsorbent dosage (0.05–1.00 g/100 mL), contact time (5–300 min), and temperature (298–313 K). Equilibrium, kinetic, and thermodynamic analyses were employed to comprehensively describe the adsorption behavior. The results demonstrated that MB adsorption onto both composites followed the Langmuir isotherm model, indicating monolayer adsorption on homogeneous surfaces. The maximum adsorption capacities were determined as 56 mg/g for ZnO-coated clinoptilolite and 106 mg/g for TiO₂-coated clinoptilolite, confirming the superior adsorption affinity of the TiO₂-modified composite. Thermodynamic parameters further indicated that the adsorption process was spontaneous, feasible, and thermodynamically favorable within the investigated temperature range. Physicochemical characterization by FTIR, SEM, BET, and XRD confirmed the successful surface modification of clinoptilolite and the enhancement of its structural and textural properties. Overall, the findings suggest that ZnO- and TiO₂-coated clinoptilolite composites are efficient and sustainable adsorbents with strong potential for wastewater treatment applications. Full article

(This article belongs to the Section Chemical Processes and Systems)

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17 pages, 2664 KB

Open AccessArticle

Accurate Hourly Forecasting of Wind Energy in Romania Using Deep Learning Models

by Grigore Cican, Adrian-Nicolae Buturache and Florin Popescu

Processes 2026, 14(3), 574; https://doi.org/10.3390/pr14030574 - 6 Feb 2026

Viewed by 613

Abstract

Wind energy plays a critical role in the European Union’s decarbonization strategy, including Romania’s growing renewable energy capacity. This study proposes a deep learning-based method for forecasting hourly wind energy production in Romania using feedforward neural networks (FFNNs) and recurrent neural networks (RNNs), [...] Read more.

Wind energy plays a critical role in the European Union’s decarbonization strategy, including Romania’s growing renewable energy capacity. This study proposes a deep learning-based method for forecasting hourly wind energy production in Romania using feedforward neural networks (FFNNs) and recurrent neural networks (RNNs), trained on a dataset spanning from 1 January to 31 December 2023. The dataset includes hourly wind energy output data (mean = 850.6 MW, std = 694.0 MW) and 13 meteorological variables (e.g., average wind speed = 4.7 km/h, temperature = 14.4 °C). A total of 1296 models were trained and evaluated, with the best-performing RNN model achieving a coefficient of determination of R² = 0.9680 and a mean absolute error (MAE) of 81.03 MW. The top three models all exceeded R² = 0.966, demonstrating strong generalization on unseen data. The models were also validated using two external time intervals outside the training/testing sets, confirming robustness. These results show that deep learning models can provide highly accurate, data-driven predictions of wind energy output, supporting grid stability and informed decision-making amid renewable energy variability. Full article

(This article belongs to the Special Issue Innovative Approaches to Modeling, Optimization, Control and Monitoring in Industrial Processes: Second Edition)

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18 pages, 898 KB

Open AccessSystematic Review

A Comparative Systematic Review of Life-Cycle Assessments of Treatment Strategies for Swine Slurry with a Focus on Anaerobic Co-Digestion

by Pedro Esperanço, António Ferreira and José Ferreira

Processes 2026, 14(3), 573; https://doi.org/10.3390/pr14030573 - 6 Feb 2026

Cited by 1 | Viewed by 986

Abstract

Intensive swine production contributes significantly to the global protein supply but generates considerable environmental pressure, particularly through greenhouse gas emissions and surplus slurry management. Anaerobic digestion (AD), especially (co-AD), has been widely investigated as a mitigation strategy to enhance renewable energy generation and [...] Read more.

Intensive swine production contributes significantly to the global protein supply but generates considerable environmental pressure, particularly through greenhouse gas emissions and surplus slurry management. Anaerobic digestion (AD), especially (co-AD), has been widely investigated as a mitigation strategy to enhance renewable energy generation and nutrient recovery. This systematic review synthesizes life cycle assessment (LCA) studies published between 2019 and 2025 that evaluated AD systems treating swine slurry, following the PRISMA 2020 guidelines. Across diverse methodological approaches and regional contexts, the literature consistently shows that AD can reduce global warming potential compared with conventional slurry management, with stronger environmental benefits when biogas is efficiently valorized and when swine slurry is co-digested with complementary organic substrat. Co-AD emerges as a key mitigation option by improving biogas yields, process stability, and overall environmental performance while also enabling better utilization of external organic waste. However, the results remain highly sensitive to operational factors such as methane leakage, digestate management, energy efficiency, and substrate selection. This review highlights the methodological inconsistencies among LCA studies and underscores the need for harmonized assessment frameworks and improved emission data. Overall, co-AD represents a promising pathway for enhancing the environmental sustainability of swine production systems when integrated into optimized, context-specific management strategies. Full article

(This article belongs to the Special Issue Advanced Technologies for Bioenergy Recovery from Organic Waste and Wastewater)

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17 pages, 1909 KB

Open AccessArticle

Efficient Mass Flow Prediction Through Adiabatic Capillary Tubes via Neural Networks Based on the Homogeneous Equilibrium Model

by Youyi Li and Liangliang Shao

Processes 2026, 14(3), 572; https://doi.org/10.3390/pr14030572 - 6 Feb 2026

Viewed by 541

Abstract

Capillary tubes are widely used as essential expansion devices in small refrigeration and air-conditioning systems. Accurate prediction of mass flow rate through adiabatic capillaries is a critical aspect of system design and optimization. While there are currently numerous models capable of predicting mass [...] Read more.

Capillary tubes are widely used as essential expansion devices in small refrigeration and air-conditioning systems. Accurate prediction of mass flow rate through adiabatic capillaries is a critical aspect of system design and optimization. While there are currently numerous models capable of predicting mass flow through capillaries, most rely on experimental data containing uncertainties, resulting in suboptimal generalization performance. Unlike previous ANN models and empirical correlations that rely on experimental data, this study addresses this limitation by introducing neural networks based on the homogeneous equilibrium model (HEM) of adiabatic capillaries. Two neural networks—a traditional multi-layer perceptron (MLP) and a deep residual network (ResNet)—are developed using a dataset generated by the HEM. The models are subsequently validated and compared against established models using experimental data for various refrigerants and operating conditions collected from the open literature. The results demonstrate that both neural networks exhibit exceptional generalization ability. The average deviations on the experimental dataset are 5.2% for the MLP and 4.5% for the ResNet, outperforming existing models. Their performance across different refrigerants is stable, with the ResNet demonstrating superior overall performance. Furthermore, the trained neural networks achieve a computational speed substantially superior to that of the HEM. Full article

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14 pages, 3905 KB

Open AccessArticle

Optimization of the Design and Manufacturing Processes for Metal Additive Manufacturing Through Digital Twin

by Hüseyin Botsalı and Cevat Özarpa

Processes 2026, 14(3), 571; https://doi.org/10.3390/pr14030571 - 6 Feb 2026

Cited by 1 | Viewed by 1184

Abstract

The aim of this study is to develop a digital twin hierarchy that fully examines the design and manufacturing processes of an automotive component for metal additive manufacturing. Initially, a lighter model was obtained that was more resistant to static, dynamic, and fatigue [...] Read more.

The aim of this study is to develop a digital twin hierarchy that fully examines the design and manufacturing processes of an automotive component for metal additive manufacturing. Initially, a lighter model was obtained that was more resistant to static, dynamic, and fatigue loads under various operating conditions. This step improved product strength and resulted in a 28.5% mass reduction. After the product was validated, the orientation of the part direction and the generation of support structures were performed for the manufacturing process. These processes were implemented with the criterion of minimizing production time. Finally, the manufacturing process was digitally implemented using the selective laser melting method and Ti6Al4V material. The design of the experiment was created using the three most frequently preferred values for each of the three important process parameters. After performing process simulations with thermomechanical analyses, Taguchi and ANOVA were applied to the process parameters. The optimum process parameters for layer thickness, hatch spacing, and scanning speed were found to be 50 µm, 120 µm, and 1200 mm/s, respectively. Full article

(This article belongs to the Special Issue Additive Manufacturing of Materials: Process and Applications)

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14 pages, 1734 KB

Open AccessArticle

Biodecolorization of Textile Azo Dyes and Phytotoxicity Assessment of Metabolites by Bacillus subtilis CKCC

by Chanchao Chem, Sarawut Cheunkar, Prattana Ketbot, Sirilak Baramee, Apinya Singkhala, Rattiya Waeonukul, Patthra Pason, Khanok Ratanakhanokchai and Chakrit Tachaapaikoon

Processes 2026, 14(3), 570; https://doi.org/10.3390/pr14030570 - 6 Feb 2026

Viewed by 1199

Abstract

Synthetic azo dyes are widely used in the textile industry; however, their use often poses environmental challenges. Here, we characterized the compost bacterium Bacillus subtilis strain CKCC for the decolorization of various azo dyes, including Congo Red, Reactive Black 5, Reactive Green 19, [...] Read more.

Synthetic azo dyes are widely used in the textile industry; however, their use often poses environmental challenges. Here, we characterized the compost bacterium Bacillus subtilis strain CKCC for the decolorization of various azo dyes, including Congo Red, Reactive Black 5, Reactive Green 19, Reactive Red 120, and Reactive Blue 4. The application of strain CKCC exhibited high decolorization efficiency by utilizing various extracellular enzymes, including azoreductase and ligninolytic enzymes such as laccase, lignin peroxidase, and manganese peroxidase, which are essential for the decolorization of azo dyes. Fourier transform infrared spectroscopy (FTIR) analysis revealed structural changes during decolorization, consistent with the degradation of key functional groups. This transformation was attributed to the cleavage of azo linkages by azoreductase, with ligninolytic enzymes functioning on phenolic and aromatic moieties. While FTIR confirmed these structural changes, our findings only provided insights at the functional-group level, and the presence or absence of specific decolorized metabolites, such as aromatic amines, requires additional analytical techniques. In this study, the phytotoxic metabolites positively affected the germination and growth of Vigna radiata, confirming that decolorization using strain CKCC significantly reduced the toxic properties of the metabolites produced during dye decolorization. Hence, our isolated strain CKCC offers a potentially effective and environmentally sustainable method for treating azo-dye effluent in the textile industry. Full article

(This article belongs to the Special Issue Environmental Pollution Control and Renewable Energy Conversion Technologies)

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24 pages, 1951 KB

Open AccessArticle

Unveiling Capability Structures for Resilient Supply Chains in Cruise Shipbuilding: A Hybrid DEMATEL-ISM-MICMAC Approach

by Dandan Fan, Guanghua Fu and Yibo Shi

Processes 2026, 14(3), 569; https://doi.org/10.3390/pr14030569 - 6 Feb 2026

Cited by 1 | Viewed by 641

Abstract

The cruise shipbuilding industry faces significant disruptions stemming from escalating trade frictions and regional conflicts which threaten its operational and economic sustainability. Enhancing supply chain resilience is thus crucial for sustainable development. This study identifies critical resilience factors and examines their interrelationships within [...] Read more.

The cruise shipbuilding industry faces significant disruptions stemming from escalating trade frictions and regional conflicts which threaten its operational and economic sustainability. Enhancing supply chain resilience is thus crucial for sustainable development. This study identifies critical resilience factors and examines their interrelationships within growth-stage cruise shipbuilding supply chains. Fuzzy Decision-Making Trial and Evaluation Laboratory (DEMATEL), Interpretive Structural Modeling (ISM), and Cross-Impact Matrix Multiplication Applied to Classification (MICMAC) analysis are integrated to explore causal linkages, hierarchical structures, and driver-dependence dynamics. The analysis reveals that customized demand responsiveness, learning organization, specialized industrial clusters, and inter-industry collaboration are fundamental causal drivers. In contrast, knowledge stock, risk culture, and final-assembly orchestration serve as critical mediators. Based on these findings, we propose distinct resource-contingent strategic pathways for managers. This study provides an actionable framework for building resilience, offering critical guidance for securing the sustainable development of the cruise shipbuilding industry amid uncertainty. Full article

(This article belongs to the Section Sustainable Processes)

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17 pages, 3990 KB

Open AccessArticle

Rapid Identification and Traceability of Groundwater Pollution Using Fluorescence Spectroscopy Coupled with Hydrochemistry in a Chemical Industrial Park, Southwest, China

by Guo Liu, Yongchang Zhang, Guoming Liu and Guo Liu

Processes 2026, 14(3), 568; https://doi.org/10.3390/pr14030568 - 6 Feb 2026

Viewed by 747

Abstract

Groundwater contamination in chemical industrial parks (CIPs) is a significant threat to global water security due to spills, leaks, and discharges, as well as the complexity of concealing a diverse range of industrial pollutants. In this article, we collected 30 groundwater samples from [...] Read more.

Groundwater contamination in chemical industrial parks (CIPs) is a significant threat to global water security due to spills, leaks, and discharges, as well as the complexity of concealing a diverse range of industrial pollutants. In this article, we collected 30 groundwater samples from zones of presumed influence across a CIP, including upstream background, within-park, periphery, and downstream, located in Luxian County, Sichuan, China. We employed excitation–emission matrix (EEM) fluorescence spectroscopy with parallel factor analysis (PARAFAC) coupled with comprehensive hydrochemical analysis to deconvolve the dissolved organic matter (DOM) signature and statistically link its fluorescent components to specific hydrogeochemical processes and anthropogenic sources. Results revealed that industrial activities have transformed the groundwater to Ca-HCO₃·Cl and Ca·Na-HCO₃·Cl types from the hydrochemical facies comprising Ca-HCO₃ and Ca·Mg-HCO₃ types. Hydrogeology and groundwater chemistry depend primarily on weathering and atmospheric precipitation, but industrial effluents and evaporation concentration also significantly affect them. EEM-PARAFAC identified three dominant fluorescent components: fulvic-like (C1), humic-like (C2), and tryptophan-like (C3), with the latter serving as a sensitive indicator of recent anthropogenic inputs. The spatial distribution of these components, particularly the enrichment of C3, is primarily governed by anthropogenic inputs (e.g., sewage leakage), modulated by local hydrological conditions. This work demonstrates the integration of optical spectroscopy with conventional hydrochemistry for source apportionment in complex industrial settings. It provides a mechanistic understanding of pollution propagation and a practical, rapid diagnostic tool for targeted groundwater protection in CIPs. Full article

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1 pages, 122 KB

Open AccessCorrection

Correction: Evrendilek, F.; Evrendilek, G.A. Holistic Estuarine Monitoring: Data-Driven and Process-Based Coupling of Biogeochemical Cycles of Per- and Polyfluoroalkyl Substances. Processes 2026, 14, 391

by Fatih Evrendilek and Gulsun Akdemir Evrendilek

Processes 2026, 14(3), 567; https://doi.org/10.3390/pr14030567 - 6 Feb 2026

Viewed by 448

Abstract

In the published publication [...] Full article

(This article belongs to the Special Issue Advances in Water Resource Pollution Mitigation Processes)

19 pages, 3951 KB

Open AccessArticle

Study on the Characteristics and Mechanisms of Drilling Fluid Loss in Kuqa, Tarim Oilfield

by Jinzhi Zhu, Hongjun Liang, Chengli Li, Guochuan Qin, Shaojun Zhang, Aisheng Sun and Dan Bao

Processes 2026, 14(3), 566; https://doi.org/10.3390/pr14030566 - 5 Feb 2026

Viewed by 556

Abstract

Frequent drilling fluid lost circulation in the Kuqa foreland area of the Tarim Oilfield severely constrains drilling efficiency and safety. The complex formation structures and diverse lost circulation types in this region are compounded by a lack of systematic classification in existing studies [...] Read more.

Frequent drilling fluid lost circulation in the Kuqa foreland area of the Tarim Oilfield severely constrains drilling efficiency and safety. The complex formation structures and diverse lost circulation types in this region are compounded by a lack of systematic classification in existing studies and weak correlation between mechanism analysis and field plugging measures, leading to a deficiency in quantitative decision-making for lost circulation prevention and control. Based on lithology analysis, loss zone pressure differential calculation, well log interpretation, and core observations, this study establishes an integrated “formation–lithology–pressure” diagnostic and classification method for lost circulation. A systematic classification framework comprising five types of lost circulation channels and mechanisms was developed. Based on this, the dominant lost circulation types and characteristics of three typical vertical formations in the Kuqa foreland were clarified: ① The supra-salt sandy conglomerate formations (e.g., Q1x, N2k) are dominated by permeability loss, where the loss rate (V) and bottomhole pressure differential (ΔP) exhibit a strong positive correlation (V ∝ ΔP). On-site application of graded bridging plugging formulations achieved a first-attempt success rate of ≥90%. ② The salt–gypsum formations (E1-2km) are primarily characterized by induced fracture loss, with a weak correlation between V and ΔP and dynamic fracture opening/closing behavior. Conventional rigid plugging materials showed limited effectiveness, resulting in a first-attempt success rate of <50%. ③ The K1bs formation is dominated by vertically developed natural fracture loss, where V and ΔP also demonstrate a strong positive correlation. In a specific Keshen block, a power-law relationship between the fracture aperture (W) and loss rate was established (W = 0.26·V^0.62, R² = 0.98), providing a basis for predicting fracture aperture and optimizing plugging formulations, with a plugging success rate of ≥80%. The classification system and quantitative criteria developed in this study effectively link lost circulation mechanisms, dynamic characteristics, and engineering countermeasures, offering theoretical support and a decision-making framework for optimizing lost circulation prevention and control measures and improving success rates in the Kuqa foreland area. Full article

(This article belongs to the Special Issue Environmentally Friendly Production of Energy from Natural Gas Hydrates)

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26 pages, 6333 KB

Open AccessArticle

Research on the Response Mechanism of Overlying Strata Failure and Ground Fissures Development Under High-Intensity Mining

by Pengyu Li, Yanjun Zhang, Lingyun Zhang and Jiayuan Kong

Processes 2026, 14(3), 565; https://doi.org/10.3390/pr14030565 - 5 Feb 2026

Cited by 2 | Viewed by 569

Abstract

Mining-induced ground fissures in the Ordos Basin pose critical threats to coal mine safety and ecological stability. This study integrated multi-source monitoring data (improves data acquisition efficiency by 60%) with theoretical models to elucidate the dynamic response mechanism between overlying strata failure and [...] Read more.

Mining-induced ground fissures in the Ordos Basin pose critical threats to coal mine safety and ecological stability. This study integrated multi-source monitoring data (improves data acquisition efficiency by 60%) with theoretical models to elucidate the dynamic response mechanism between overlying strata failure and ground fissure development. The results demonstrate that: (1) Two rock beam structural models for initial and periodic fracturing of thick, hard rock strata are established, demonstrating that both failure modes are dominated by tensile–shear mechanisms. (2) Ground fissures exhibit distinct zonal characteristics, displaying a gradient pattern of “strong disturbance in the near field and weak response in the far field.” Quantitative data support this pattern: average fissure density is 36/hm², with a maximum of 45/hm² recorded in the immediate vicinity of the working face, declining steadily outward. (3) Overlying strata failure forms three distinct zones—caving zone (42 m), fissure zone (158 m), and longitudinal penetrating zone—reflecting the heterogeneous fracture characteristics of medium-hard rock strata under mining influence. (3) The proposed “virtual main arch—virtual auxiliary arch” equivalent support system theory elucidates the mechanistic differences between step fissures (attributed to local support system instability) and collapse fissures (driven by global support system instability) from a mechanical perspective. The developed chain response theory fills a critical theoretical gap and provides a novel method for predicting and preventing geological disasters in mining areas. Full article

(This article belongs to the Special Issue Process Safety and Intelligent Monitoring for Mining Engineering)

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22 pages, 1890 KB

Open AccessArticle

A Dual-Objective Voltage Optimization Method for Distribution Networks Based on a Holomorphic Embedding Time-Series Power Flow Model

by Jiajun Zhang, Jiarui Wang, Haifeng Zhang, Haitao Lan, Zhongwei Ma, Shihan Chen, Fengzhang Luo and Ranfeng Mu

Processes 2026, 14(3), 564; https://doi.org/10.3390/pr14030564 - 5 Feb 2026

Cited by 1 | Viewed by 513

Abstract

The high integration of renewables like distributed photovoltaic (PV) into medium- and low-voltage distribution networks causes bidirectional power flows, increased voltage fluctuations, and operational uncertainty. Traditional power flow models struggle to balance efficiency and accuracy for multi-period optimization. This paper proposes a dual-objective [...] Read more.

The high integration of renewables like distributed photovoltaic (PV) into medium- and low-voltage distribution networks causes bidirectional power flows, increased voltage fluctuations, and operational uncertainty. Traditional power flow models struggle to balance efficiency and accuracy for multi-period optimization. This paper proposes a dual-objective voltage optimization method based on a Holomorphic Embedding time-series power flow model. First, a recursive relationship for nodal voltage power series expansion is derived, revealing the linear superposition of first-order coefficients with power injection changes and the rapid decay of higher-order terms. A linearized analytical model neglecting higher-order terms is built, improving the computational efficiency of time-series power flow calculations while maintaining accuracy. Then, integrating energy storage systems and static var compensators, a dual-objective optimization model minimizing voltage deviation and daily operational cost is formulated. Tests on a practical 91-node rural distribution system show that the proposed power flow model maintains a voltage error below 0.25% compared to the Newton–Raphson method across various PV integration scenarios, and the optimization reduces computation time by about 61.3% versus the Second-Order Cone Programming method, validating its advantages in precision and efficiency for balancing voltage quality and economy. Full article

(This article belongs to the Section Energy Systems)

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18 pages, 3154 KB

Open AccessArticle

Study on Improvement of Acidizing Fracturing Formula in Carbonate Reservoir

by Leyan Shi and Fengpeng Lai

Processes 2026, 14(3), 563; https://doi.org/10.3390/pr14030563 - 5 Feb 2026

Cited by 3 | Viewed by 1231

Abstract

Addressing the challenges of poorly developed fractures and low individual well water yields within the Tianjin Ordovician–Wumishan carbonate thermal reservoir, alongside the rapid reaction rates and short effective distances observed during conventional acid fracturing operations, this study employed an XRD core analysis to [...] Read more.

Addressing the challenges of poorly developed fractures and low individual well water yields within the Tianjin Ordovician–Wumishan carbonate thermal reservoir, alongside the rapid reaction rates and short effective distances observed during conventional acid fracturing operations, this study employed an XRD core analysis to confirm reservoir calcite contents exceeding 90%. Based on this finding, an acid formulation incorporating a 2% SPR-12 retarder was developed. High-temperature high-pressure reactor experiments demonstrated that this system successfully reduced the acid–rock reaction rate from 0.122 g·min⁻¹·cm⁻² to 0.037 g·min⁻¹·cm⁻² and increased the retardation efficiency from 34.07% to 68%. This significantly extended the acid penetration distance and enhanced the fracture network connectivity within the reservoir. The field trial conditions informed the parameter optimization via E-StimPlan^® 3D simulations, ultimately determining that a fracture extension of 400 m could be achieved with a 20 MPa breakdown pressure. Conductivity experiments validated that a flow rate of 1.3 m³/min generated pillar-supported wormhole structures, yielding a final conductivity of 46.8 μm²·cm. The pumping pressure plummeted from 20 MPa to 1 MPa, confirming effective fracture network communication. Gas lift backflow for 20 h mitigated secondary precipitation risks. After implementation, the water production rate of this well increased from 12.33 m³/h to 95 m³/h, with a dynamic water level of 158.85 m. The water temperature rose from 62 °C to 88 °C and remained stable. Compared to current acidizing and fracturing methods applied in geothermal wells, the new acid fluid system and process have increased the geothermal production capacity by 275.8%, while reducing acid consumption by 50%, providing critical technological support for the efficient development of carbonate thermal reservoirs. Full article

(This article belongs to the Topic Polymer Gels for Oil Drilling and Enhanced Recovery)

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23 pages, 6240 KB

Open AccessArticle

Study on the Mechanism of Enhanced Water Injection for Improving Oil Recovery in Low-Permeability Reservoirs

by Fenghe Liu, Hongming Song, Chenggang Xian, Xiaofeng Lv and Fuchun Tian

Processes 2026, 14(3), 562; https://doi.org/10.3390/pr14030562 - 5 Feb 2026

Viewed by 967

Abstract

The development of low-permeability reservoirs faces significant challenges, particularly regarding low recovery rates. Conventional water injection is often limited by poor injectivity and low waterflood efficiency. As a key technology to enhance development effectiveness, enhanced water injection requires a systematic investigation into its [...] Read more.

The development of low-permeability reservoirs faces significant challenges, particularly regarding low recovery rates. Conventional water injection is often limited by poor injectivity and low waterflood efficiency. As a key technology to enhance development effectiveness, enhanced water injection requires a systematic investigation into its intrinsic mechanism for improving recovery. This study focuses on a typical low-permeability reservoir. Through laboratory experiments on rock fracturing and spontaneous imbibition, the mechanism by which enhanced water injection increases recovery rates is elucidated. COMSOL Multiphysics is employed to simulate the enhanced water injection process and examine the multi-field coupling patterns during injection. The results indicate that (1) low-permeability rocks in the study area exhibit strong oil–water exchange capabilities driven by capillary forces, with average imbibition capacity ranging from 0.6 to 0.7 g/cm³ and oil displacement efficiency between 20% and 30%; (2) fracturing experiments demonstrate that the injection of low-viscosity fluids at low flow rates (15 mL/min) can induce complex fracture propagation, thereby expanding flow pathways; and (3) the evolution of fluid–solid coupling is jointly governed by injection pressure and damage effects. Specifically, coupling intensity and fracture propagation potential increase with pressure, with optimal injection pressure ranging from 20 to 25 MPa. Rock damage exacerbates the nonlinear response of this coupling. This study combines experimental validation with numerical simulation to provide theoretical support for field practice. Full article

(This article belongs to the Special Issue Advances in Enhanced Oil Recovery Processes)

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20 pages, 846 KB

Open AccessReview

Recent Advances in Whey Protein Films Incorporated with Phenolic Compounds: A Review

by Tairine Osório Ferri, Fernanda Arnhold Pagnussatt, Viviane Patrícia Romani, Clarissa Helena Rosa, Márcia Helena Scherer Kurz, Márcia Victória Silveira, Lenise Guimarães de Oliveira and Meritaine da Rocha

Processes 2026, 14(3), 561; https://doi.org/10.3390/pr14030561 - 5 Feb 2026

Viewed by 1202

Abstract

The use of food packaging derived from petroleum-based polymers has developed significant environmental problems, as these materials require centuries to degrade and release hazardous pollutants. Consequently, the food industry is shifting toward biodegradable alternatives developed from agro-industrial by-products, such as proteins, polysaccharides, and [...] Read more.

The use of food packaging derived from petroleum-based polymers has developed significant environmental problems, as these materials require centuries to degrade and release hazardous pollutants. Consequently, the food industry is shifting toward biodegradable alternatives developed from agro-industrial by-products, such as proteins, polysaccharides, and lipids. Whey protein is a by-product of the cheese industry, which is emerging as a promising material for producing edible and biodegradable films with effective barrier properties. Whey-based films can be incorporated with bioactive compounds, particularly phenolic compounds. These substances, naturally present in fruits, legumes, and vegetable waste, possess potent antimicrobial and antioxidant activities that are essential for extending the shelf life of perishable foods. This review provides a systematic evaluation of how the incorporation of phenolic compounds influences the physicochemical and bioactive properties of whey-based films. Thus, an analysis of film-forming methods, the interaction between protein matrices and phenolic compounds, and a critical discussion of the challenges remaining for their industrial application as active food packaging were evaluated. The discussion focuses on how the incorporation of phenolic extracts influences the physicochemical, mechanical, and barrier properties of the films, as well as their antioxidant and antimicrobial efficiency. The novelty of this review lies in its comprehensive focus on the sustained release of phenolic compounds from a whey protein film and their application in real food systems. By utilizing these natural additives, the industry can provide sustainable alternatives to synthetic preservatives. Active whey protein packaging represents a viable strategy to inhibit food spoilage, prevent lipid oxidation, and maintain sensory quality, while reducing the environmental problems. Full article

(This article belongs to the Special Issue Advanced Thin Films for Antioxidant Food Packaging and Preservation)

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19 pages, 9445 KB

Open AccessArticle

Hydraulic Fracture Propagation and Fracturing Design Optimization in Deep Coalbed Methane Reservoirs of the Changqing Oilfield

by Xiaoyong Wen, Chuanrong Zhong and Shuo Zhai

Processes 2026, 14(3), 560; https://doi.org/10.3390/pr14030560 - 5 Feb 2026

Cited by 1 | Viewed by 862

Abstract

This study presents a novel approach for optimizing hydraulic fracture propagation and fracturing design in deep coalbed methane (CBM) reservoirs, specifically focusing on the Changqing Oilfield in the eastern Ordos Basin. The increasing demand for clean energy underscores the strategic importance of CBM [...] Read more.

This study presents a novel approach for optimizing hydraulic fracture propagation and fracturing design in deep coalbed methane (CBM) reservoirs, specifically focusing on the Changqing Oilfield in the eastern Ordos Basin. The increasing demand for clean energy underscores the strategic importance of CBM as an unconventional natural gas resource. However, significant variability in fracturing effectiveness has limited efficient production from deep CBM reservoirs. Unlike previous studies that primarily focus on shallow coal reservoirs, this work goes beyond existing efforts by developing detailed structural and geomechanical models incorporating well log data from 31 wells, allowing for a more accurate simulation of fracture propagation under varying fracturing conditions. Through numerical simulations, the study identifies key parameters—such as segment cluster ratio, fluid volume, and injection rate—that significantly influence fracture length and stimulated reservoir volume. The results indicate that optimizing fluid volume and segment cluster ratio can enhance fracture propagation and improve the total stimulated reservoir volume, particularly in reservoirs with stronger rock plasticity and higher permeability. These findings provide valuable insights into the optimization of hydraulic fracturing designs, contributing to improved gas production efficiency and better reservoir stimulation in deep CBM reservoirs. Full article

(This article belongs to the Section Petroleum and Low-Carbon Energy Process Engineering)

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21 pages, 4453 KB

Open AccessArticle

Early Warning of Lost Circulation Based on Physical Models and a Hybrid Neural Network

by Fangfei Huang, Yanwei Sun, Jin Yang, Zhibin Sha, Jingsong Lu and Rongrong Qi

Processes 2026, 14(3), 559; https://doi.org/10.3390/pr14030559 - 5 Feb 2026

Cited by 1 | Viewed by 644

Abstract

Lost Circulation (LC) is one of the most common and high-risk complex situations encountered during drilling operations, posing a serious threat to the safe extraction and economic viability of oil and gas resources. Traditional wellbore leakage detection methods based on human experience often [...] Read more.

Lost Circulation (LC) is one of the most common and high-risk complex situations encountered during drilling operations, posing a serious threat to the safe extraction and economic viability of oil and gas resources. Traditional wellbore leakage detection methods based on human experience often suffer from delays and uncertainties, making it difficult to meet real-time warning requirements under complex geological conditions. This paper proposes an LC warning method that combines a physical model with a combination of neural networks (Crested Porcupine Optimizer (CPO)–Long Short-Term Memory (LSTM)–Random Forest (RF)). The physical model utilises changes in mud pit volume, inlet–outlet flow rate differences, and riser pressure to construct interpretable event labels, thereby enhancing the physical plausibility of prediction results. The deep learning component employs LSTM networks to extract temporal features and RF for non-linear discrimination and introduces the CPO algorithm for feature selection and hyperparameter optimisation, thereby enhancing the model’s stability and generalisation capability. Validation using actual field data from the western Bohai Bay oilfield demonstrates that the proposed method outperforms traditional models in accuracy, precision, recall, and F1-score. It also offers a significant improvement in early warning time, detecting potential leakage about 17 min before traditional methods. These results highlight the effectiveness of the approach in managing risks during drilling operations. Full article

(This article belongs to the Special Issue 2nd Edition of Artificial Intelligent Techniques in the Optimal Operation of Oil and Gas Production Systems)

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20 pages, 7092 KB

Open AccessArticle

Techno-Economic and Environmental Assessment of an RCCI Diesel Engine Fuelled with Fusel Oil Addition

by Volkan Kalender, Muhammed Umar Bayer, Mustafa Yavuz and Ilker Turgut Yilmaz

Processes 2026, 14(3), 558; https://doi.org/10.3390/pr14030558 - 5 Feb 2026

Cited by 2 | Viewed by 665

Abstract

RCCI is a promising combustion strategy that can improve the controllability of combustion phasing. This study evaluates fusel oil (an inexpensive industrial by-product) as a low-reactivity supplementary fuel in an RCCI diesel engine. Fusel oil was injected into the intake air at 4, [...] Read more.

RCCI is a promising combustion strategy that can improve the controllability of combustion phasing. This study evaluates fusel oil (an inexpensive industrial by-product) as a low-reactivity supplementary fuel in an RCCI diesel engine. Fusel oil was injected into the intake air at 4, 6, 10, 12, and 16 g/min (DF4-DF16), and experiments were conducted on a four-cylinder, four-stroke diesel engine at 1750 rpm under 40, 60, 80, and 100 Nm. In-cylinder temperature/pressure-based combustion behaviour, air excess ratio (λ), NO and smoke emissions were assessed. The influence of fusel oil on combustion was strongest at low load. At 40 Nm, the highest fusel-oil energy share increased peak cylinder pressure by 14% and peak in-cylinder temperature by 4% compared to diesel fuel tests, while at 100 Nm the corresponding increases were 4% and less than 1%. NO increased at 40 Nm, with a maximum rise of 17.9% at the highest fusel-oil energy share, but decreased at medium and high loads, falling by 7.13 to 13.54% between 60 and 100 Nm. Smoke increased consistently with fusel oil, reaching about 42% at 40 Nm and remaining below 22% at 100 Nm. A techno-economic assessment showed that although capital costs increased slightly, the low price of fusel oil decreased operating costs by up to 33% and reduced life-cycle costs by up to 42%. Overall, fusel oil-assisted RCCI operation can provide notable cost benefits and conditional NO reductions, though with a smoke penalty that should be considered in application and after-treatment strategies. Full article

(This article belongs to the Special Issue Recent Advances and Technologies in Internal Combustion Engines: Combustion Analysis and Emission Control)

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16 pages, 951 KB

Open AccessArticle

Dynamic Innovation Portfolio Management: A Model Predictive Control Approach for Product-Process Innovation Trade-Offs

by Sobhi Mejjaouli and Lotfi Tadj

Processes 2026, 14(3), 557; https://doi.org/10.3390/pr14030557 - 5 Feb 2026

Viewed by 616

Abstract

The proposed model derives closed-form solutions for investment efforts in both product development and its associated production processes while balancing economic profit, product quality, and marginal production costs. The system dynamics, including state and control variables, as well as the relevant constraints, are [...] Read more.

The proposed model derives closed-form solutions for investment efforts in both product development and its associated production processes while balancing economic profit, product quality, and marginal production costs. The system dynamics, including state and control variables, as well as the relevant constraints, are explicitly formulated. To demonstrate the practical utility of the framework, a numerical example is investigated. Simulation results illustrate adaptive strategies that anticipate future market conditions, manage product–process innovation trade-offs, and respond effectively to changing innovation returns. In the baseline numerical scenario, the model achieves a cumulative profit of 7850 with an average period profit of 196. Finally, a sensitivity analysis is conducted to examine the impact of key model parameters on system performance. Full article

(This article belongs to the Special Issue Innovations in Manufacturing Processes and Systems for Sustainable Practices (2nd Edition))

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20 pages, 3324 KB

Open AccessFeature PaperEditor’s ChoiceArticle

Integrating Emerging Digital Technologies into Circular Economy Practices

by Elena Simina Lakatos, Andreea Loredana Rhazzali, Umberto Pernice, Oana Bianca Panait (Berce), Felix H. Arion and Lucian-Ionel Cioca

Processes 2026, 14(3), 556; https://doi.org/10.3390/pr14030556 - 5 Feb 2026

Cited by 2 | Viewed by 1522

Abstract

This study stems from the clear need to understand why and how organizations in Romania integrate emerging digital technologies into circular economy (CE) practices, given the critical role of this integration in improving resource efficiency and supporting sustainable business models. Data were collected [...] Read more.

This study stems from the clear need to understand why and how organizations in Romania integrate emerging digital technologies into circular economy (CE) practices, given the critical role of this integration in improving resource efficiency and supporting sustainable business models. Data were collected through a structured questionnaire applied to 149 organizations of different sizes, ranging from SMEs (fewer than 50 employees) to large corporations (over 500 employees), operating across multiple sectors, including agriculture, construction, security, services and research. The questionnaire assessed organizations’ familiarity with CE principles, their stage of CE implementation, and their adoption of digital technologies, including artificial intelligence (AI), Internet of Things (IoT), blockchain, cloud computing and robotics. The results indicate that most organizations are aware of the potential benefits of digital technologies, particularly in terms of resource efficiency, enhanced product traceability and support for sustainability goals. However, effective implementation remains quite limited in many cases due to inadequate or outdated infrastructure, lack of technical skills, and organizational resistance to changes. At the same time, the findings further reveal a growing strategic interest in digitalization: approximately 41% of SMEs and 59% of large organizations plan to increase investments in digitalization, primarily to improve sustainability performance and foster innovation. Overall, the study provides a comprehensive overview of the current state of digitalization in support of CE in Romania and proposes practical recommendations for organizations and decision-makers, highlighting both emerging opportunities and persistent barriers. Full article

(This article belongs to the Special Issue Circular Economy in Process Engineering: Impact Assessment and Directions for Sustainability)

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30 pages, 6352 KB

Open AccessReview

Research Progress on Numerical Simulation Methods for Metallurgical Fluidization

by Langfeng Fan, Mingzhuang Xie, Hongliang Zhao, Rongbin Li, Zhenglin Zhang and Fengqin Liu

Processes 2026, 14(3), 555; https://doi.org/10.3390/pr14030555 - 5 Feb 2026

Cited by 1 | Viewed by 1665

Abstract

Numerical simulation has become a powerful and versatile toolkit for investigating gas–solid flow behavior in metallurgical fluidization processes. This review summarizes recent advances in the application of computational fluid dynamics (CFD)-based approaches, particularly the Eulerian–Eulerian and Eulerian–Lagrangian methods, within the field of metallurgical [...] Read more.

Numerical simulation has become a powerful and versatile toolkit for investigating gas–solid flow behavior in metallurgical fluidization processes. This review summarizes recent advances in the application of computational fluid dynamics (CFD)-based approaches, particularly the Eulerian–Eulerian and Eulerian–Lagrangian methods, within the field of metallurgical fluidization. It covers model development, particle and bubble dynamics, reactor flow field analysis, and structural optimization. The study demonstrates that numerical simulation plays a crucial role in elucidating fluidization mechanisms, optimizing process parameters, and guiding reactor design. For example, numerical simulation provides key quantitative insights, such as the enhancement of iron ore reduction rates by up to 40% with increased gas velocity and the optimization of reactor cone angles to 5–10° for improved stability, in the design of hydrogen-based iron oxide reduction reactors. However, this review identifies that current research is predominantly focused on iron ore reduction, while numerical studies on fluidized-bed smelting of non-ferrous metals, such as zinc, copper, and aluminum, remain relatively limited. Future efforts should aim to broaden the application of numerical simulation in non-ferrous metallurgy, develop efficient multi-scale coupled computational methods, and integrate artificial intelligence technologies to advance metallurgical fluidization toward greater efficiency, energy savings, and intelligent operation. Full article

(This article belongs to the Special Issue Computational Fluid Dynamics Modeling and Simulation in Material Processing and Metallurgy)

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16 pages, 2980 KB

Open AccessArticle

An Improved Carbon Dioxide Monitoring Method Related to China’s Carbon Emissions Trading System in Cement Plants

by Tiejun Wu, Jingwei Fan, Li Zhou, Jueying Qian, Zhuotong Li and Wenhao Bai

Processes 2026, 14(3), 554; https://doi.org/10.3390/pr14030554 - 5 Feb 2026

Cited by 1 | Viewed by 687

Abstract

The cement industry will be officially regulated by China’s national carbon market. Authenticity and accuracy of emission data are prerequisites and the foundation for ensuring the healthy and stable operation of the market. At present, China’s carbon market mainly adopts the Calculation-Based Method [...] Read more.

The cement industry will be officially regulated by China’s national carbon market. Authenticity and accuracy of emission data are prerequisites and the foundation for ensuring the healthy and stable operation of the market. At present, China’s carbon market mainly adopts the Calculation-Based Method (CBM) for data accounting. However, in the cement sector, this method faces challenges due to the inherent complexity of both raw materials and fuels, making it difficult to obtain accurate emission data through CBM alone. Therefore, regulatory authorities are promoting the installation and application of the Continuous Emission Monitoring System (CEMS) by enterprises. Pilot studies, however, have revealed considerable discrepancies between the data from the two methods. In this study, a combined data monitoring and accounting method was proposed, in which CBM and CEMS were combined to improve emission data quality. The actual operational and emission data from a case enterprise was taken as an example, and this study conducted systematic analysis and research on data collection and preprocessing, operating condition classification, correlation model construction, and abnormal data diagnosis. The results revealed that this combined method can effectively improve the degree of correlation between CBM and CEMS carbon emissions. Moreover, higher accuracy of abnormal data identification can be achieved through statistical testing. This combined monitoring method not only strengthens data tamper-resistance at the enterprise level but also has the potential to reduce regulatory oversight costs, thereby providing reliable technical support for emission data quality control. Full article

(This article belongs to the Section Process Control, Modeling and Optimization)

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20 pages, 4863 KB

Open AccessArticle

Hydrodynamics, Oxygen Mass Transfer, and Sodium Methyl Mercaptan Oxidation in a Scaled-Up Airlift Loop Reactor

by Shutong Zhang, Hongxu Lu, Pu Ren, Dian Lin, Zhuoxuan Sun, Xiang Liu, Jinghao Bi, Yanjie Li and Xiao Xu

Processes 2026, 14(3), 553; https://doi.org/10.3390/pr14030553 - 5 Feb 2026

Cited by 1 | Viewed by 763

Abstract

This study investigates the hydrodynamics, oxygen mass transfer, and sodium methyl mercaptan (NaSR) oxidation in a scaled-up airlift loop reactor, aiming to clarify the interplay between operational parameters and reaction efficiency. Computational Fluid Dynamics (CFD) simulations, coupled with the Euler–Euler approach, population balance [...] Read more.

This study investigates the hydrodynamics, oxygen mass transfer, and sodium methyl mercaptan (NaSR) oxidation in a scaled-up airlift loop reactor, aiming to clarify the interplay between operational parameters and reaction efficiency. Computational Fluid Dynamics (CFD) simulations, coupled with the Euler–Euler approach, population balance model (PBM), Higbie’s penetration theory, and Arrhenius-type reaction kinetics, were employed. Experimental determination of reaction kinetics provided foundational data for model validation. Increasing superficial gas velocity Ug enhances

k_{L} a

magnitude and spatial distribution uniformity, promotes bubble circulation between the riser and downcomer, and improves dissolved oxygen concentration. Numerical simulations showed good agreement with industrial data, confirming their reliability. Notably, at Ug = 0.0045 m/s, insufficient oxygen mass fraction in the downcomer was observed due to slow bubble renewal. The volumetric mass transfer coefficient exhibits larger value in downcomer due to the reasonable liquid turbulence dissipation. These findings provide critical insights for optimizing operational parameters in large-scale airlift reactors for NaSR oxidation. Full article

(This article belongs to the Section Chemical Processes and Systems)

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20 pages, 4428 KB

Open AccessArticle

Aerodynamic Optimisation of a Tandem Blade Centrifugal Compressor Through Parametric Analysis of Blade Angles and Count

by Mustafa Ertürk Söylemez and Salih Özer

Processes 2026, 14(3), 552; https://doi.org/10.3390/pr14030552 - 4 Feb 2026

Cited by 2 | Viewed by 716

Abstract

This study advances the performance of a tandem-blade centrifugal compressor through a parametric Computational Fluid Dynamics (CFD) methodology integrated with Response Surface Methodology (RSM). Numerical simulations were executed by solving steady-state Reynolds-Averaged Navier–Stokes (RANS) equations utilising the Shear Stress Transport (SST) k-ω turbulence [...] Read more.

This study advances the performance of a tandem-blade centrifugal compressor through a parametric Computational Fluid Dynamics (CFD) methodology integrated with Response Surface Methodology (RSM). Numerical simulations were executed by solving steady-state Reynolds-Averaged Navier–Stokes (RANS) equations utilising the Shear Stress Transport (SST) k-ω turbulence model on a validated structured hexahedral mesh. Local sensitivity analysis identified the hub outlet angle and hub inlet angle as the primary geometric parameters affecting pressure ratio and isentropic efficiency, respectively. Flow-field visualisations confirmed that the tandem configuration effectively re-energises the boundary layer, thereby reducing separation and enhancing pressure recovery. Using a Multi-Objective Genetic Algorithm (MOGA), an optimal blade design comprising 22 blades was determined, achieving a maximum isentropic efficiency of 95.23% and a total pressure ratio of 1.416. These findings provide valuable quantitative insights for the optimal design of tandem impellers and highlight the effectiveness of integrating CFD-based sensitivity analysis with multi-objective optimisation techniques. Full article

(This article belongs to the Special Issue Fluid Dynamics and Thermodynamic Studies in Gas Turbine)

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22 pages, 5086 KB

Open AccessArticle

Kerr-Based Interrogation of Lightning-Impulse Field Transients in Oil–Cellulose Composites and Their Interfacial Charging Effect

by Xiaolin Zhao, Haoxuan Zhang, Chunjia Gao, Yuwei Zhong, Xiang Zhao, Bo Qi and Shuqi Zhang

Processes 2026, 14(3), 551; https://doi.org/10.3390/pr14030551 - 4 Feb 2026

Viewed by 526

Abstract

To address the stringent insulation safety requirements of modern high-voltage transformers, accurately characterizing the transient electric field is critical. However, a significant problem remains: current engineering models typically rely on static capacitive distributions, failing to capture the dynamic electric field distortion induced by [...] Read more.

To address the stringent insulation safety requirements of modern high-voltage transformers, accurately characterizing the transient electric field is critical. However, a significant problem remains: current engineering models typically rely on static capacitive distributions, failing to capture the dynamic electric field distortion induced by rapid space charge injection under lightning impulses. Therefore, a non-contact spatial electric field measurement method based on the optical Kerr effect was employed to analyze the influence of electrode material, voltage amplitude, and wavefront time. Unlike traditional simulation models that often assume constant mobility and focus solely on the shielding effect, this study reveals a non-monotonic electric field evolution driven by a ‘Static-Dynamic’ mode transition. The proposed model highlights two critical breakthroughs: (1) Mechanism Innovation: It experimentally verifies that charge injection is governed by the ion charge-to-mass ratio rather than just the work function, leading to a newly identified field enhancement phase during the wavefront that overcomes the limitations of capacitive models that underestimate transient stress. (2) Parameter Quantification: Precise spatiotemporal thresholds are established—negative charges traverse the gap within ~200 ns, while positive charges require ~10 μs to reach equilibrium. These findings provide experimentally calibrated time constants for simulation correction and offer new criteria for optimizing electrode materials in UHV transformers to mitigate transient field distortion. Full article

(This article belongs to the Section Materials Processes)

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