Processes

32 pages, 2043 KB

Open AccessReview

Myceliophthora thermophila as a Biotechnological Platform for Cellulase Production and Lignocellulose Valorization

by Julia Ortega, Martha I. Vélez-Mercado, Gabriela Martínez-Machado, Lizbeth A. Ibarra-Muñoz, Gabriela L. Berto and Fernando Segato

Processes 2026, 14(17), 2682; https://doi.org/10.3390/pr14172682 (registering DOI) - 22 Aug 2026

Abstract

Lignocellulosic biomass deconstruction requires robust biocatalysts capable of operating under demanding industrial conditions. The thermophilic fungus Myceliophthorathermophila is a promising biotechnological platform for cellulase production and lignocellulose valorization because of its naturally thermostable CAZyme repertoire. Extensive knowledge has accumulated across diverse research [...] Read more.

Lignocellulosic biomass deconstruction requires robust biocatalysts capable of operating under demanding industrial conditions. The thermophilic fungus Myceliophthorathermophila is a promising biotechnological platform for cellulase production and lignocellulose valorization because of its naturally thermostable CAZyme repertoire. Extensive knowledge has accumulated across diverse research fields, alongside its taxonomic reclassification as Thermothelomyces thermophila, emphasizing the need to integrate findings across research contexts. This review synthesizes knowledge generated using publicly available M. thermophila strains, retaining the historically prevalent name M. thermophila to facilitate cross-disciplinary comparison. Emphasis is placed on the C1 strain, whose longstanding use as a production platform provides a foundation for current advances in strain engineering and protein production. We provide a genetics-focused perspective on this biotechnological platform, integrating advances in genetic engineering, transcriptional regulation, and protein production. We discuss CRISPR systems applied to M. thermophila, strategies to improve protein production through extracellular protease elimination, optimization of secretion and unfolded protein response pathways, carrier proteins, and synthetic expression systems. We further summarize the transcriptional regulation of cellulase expression, the repertoire of characterized thermostable cellulases, and opportunities for protein engineering. Collectively, these advances position M. thermophila as a versatile biotechnological platform for producing industrial enzymes and other value-added bioproducts for biorefinery applications. Full article

(This article belongs to the Special Issue Advances in Enzymatic Biotechnology and Biological Systems for Sustainable Bioeconomy)

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56 pages, 2645 KB

Open AccessReview

Machine Learning Across the Heavy Oil Value Chain: A Review of Methodological Maturity and Industrial Deployability

by George Simonelli, Diogo Souza Neiva Cardoso, Adriana Vieira dos Santos and Luiz Carlos Lobato dos Santos

Processes 2026, 14(17), 2681; https://doi.org/10.3390/pr14172681 (registering DOI) - 22 Aug 2026

Abstract

Heavy and extra-heavy oils represent a large and growing share of recoverable hydrocarbon resources, yet their extreme viscosity, high heteroatom content, and non-Newtonian behavior routinely defeat empirical correlations developed for conventional crude. Machine learning has emerged as a candidate response to this modeling [...] Read more.

Heavy and extra-heavy oils represent a large and growing share of recoverable hydrocarbon resources, yet their extreme viscosity, high heteroatom content, and non-Newtonian behavior routinely defeat empirical correlations developed for conventional crude. Machine learning has emerged as a candidate response to this modeling gap, but existing reviews largely catalog applications without asking whether the technology is actually ready for industrial deployment. This critical review synthesizes machine learning applications across five thematic domains of the heavy-oil value chain: physicochemical property prediction, enhanced oil recovery, flow assurance, reactive recovery, and downstream upgrading. Studies are read through a three-phase historical lens, tracing the field’s progression from empirical-correlation replacement to methodological diversification to physics-informed and closed-loop integration, and evaluated against a Technology Readiness Level (TRL) scale adapted specifically for heavy-oil machine learning. The multilayer perceptron anchors more of the primary corpus than any other architecture, a pattern that, in our interpretation, reflects small-sample, low-dimensional regression needs rather than any demonstrated advantage over other architectures. Enhanced oil recovery is the only cluster to reach organizational-scale deployment, anchored by a single multi-decade operator program, Chevron’s San Joaquin Valley i-field; the remaining clusters are constrained less by modeling sophistication than by single-basin datasets and undisclosed uncertainty. Measured against three falsifiable deployability criteria, fidelity preservation below 10° API, operator-grade interpretability, and demonstrated laboratory-to-field transferability, no study in the reviewed corpus is documented to satisfy all three simultaneously; because industrial implementations are frequently proprietary, this is a statement about the published record identified by this search, not a claim that the capability does not exist. Federated learning, physics-informed architectures, and sequence-aware models emerge as the directions most likely to close this gap. Full article

(This article belongs to the Special Issue Recent Advances in Oil Reservoir Simulation and Multiphase Flow)

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25 pages, 5218 KB

Open AccessArticle

Multiscale Coupled Modeling of Shale Gas Horizontal Wells Considering Wellbore Friction Loss

by Yong Zhang, Jiajie Yang, Zhenbang Zhou, Chao Chen and Jia Wang

Processes 2026, 14(17), 2680; https://doi.org/10.3390/pr14172680 (registering DOI) - 22 Aug 2026

Abstract

Shale gas reservoirs are characterized by low permeability, nanoscale pore structures, and complex fracture networks. Multistage fractured horizontal wells are an important technology for commercial shale gas development. However, many shale gas productivity models primarily emphasize gas transport within the reservoir and fracture [...] Read more.

Shale gas reservoirs are characterized by low permeability, nanoscale pore structures, and complex fracture networks. Multistage fractured horizontal wells are an important technology for commercial shale gas development. However, many shale gas productivity models primarily emphasize gas transport within the reservoir and fracture system, while pressure variations caused by frictional losses along the horizontal wellbore are often simplified or treated separately. To address this issue, this study develops a fully coupled multiscale dual-porosity numerical model that integrates the shale matrix, hydraulic fractures, and horizontal wellbore within a unified simulation framework. The model incorporates key physical mechanisms governing shale gas transport, including Knudsen diffusion, Langmuir adsorption–desorption, stress sensitivity, and non-Darcy flow in fractures. Meanwhile, the Darcy–Weisbach equation is introduced to describe wellbore frictional pressure losses. The reliability of the proposed model is validated through history matching with field production data from the Changning shale gas reservoir. The results demonstrate that neglecting wellbore friction losses leads to a 30–50% overestimation of horizontal well productivity, indicating that wellbore friction has a significant impact on fracture flow distribution and productivity prediction. Furthermore, an exponent factor r is introduced to characterize and evaluate non-uniform fracture placement patterns. The results show that toe-dense fracture placement can increase cumulative gas production by approximately 37.8% compared with uniform fracture placement when r = 1.10, which yields the highest cumulative gas production among the tested cases. However, the additional production benefit becomes substantially smaller after the initial increase and remains relatively stable as r further increases. This study improves the understanding of friction-induced heel-to-toe effects and provides an effective numerical approach for productivity prediction and fracture placement design in shale gas horizontal wells. Full article

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

21 pages, 4285 KB

Open AccessArticle

Molecular-Level Crude Oil Distillation Unit Model

by Zhao Gao and Linzhou Zhang

Processes 2026, 14(17), 2679; https://doi.org/10.3390/pr14172679 (registering DOI) - 22 Aug 2026

Abstract

Crude oil distillation is often simulated with pseudo-components. This treatment is efficient, but it limits the prediction of molecular-level product information. In this work, a molecular-level model based on molecule-lump mapping was developed for crude oil distillation and applied to an atmospheric distillation [...] Read more.

Crude oil distillation is often simulated with pseudo-components. This treatment is efficient, but it limits the prediction of molecular-level product information. In this work, a molecular-level model based on molecule-lump mapping was developed for crude oil distillation and applied to an atmospheric distillation column. The model was used to calculate molecular distributions in straight-run products and at individual column stages, providing molecular information for the distillation process. A crude oil molecular composition model was constructed from bulk-property data and used as the feed input. Crude oil molecules were grouped into molecular lumps according to boiling-point ranges, and a molecule-lump mapping matrix was established to record the molecular composition of each lump. A mechanistic column model was solved with the inside-out algorithm. The molecular lumping reduced the number of components used in column calculations while retaining the molecule-lump mapping needed to calculate the molecular compositions of the products. The model calculated stage temperatures, vapor and liquid compositions, product yields, product bulk properties, and molecular distributions. Compared with the experimental data, the calculated stage temperatures had an MAE of 4.15 °C. The RMSE values of the calculated distillation curves for the straight-run products ranged from 9.32 to 47.62 °C. These results show that the model can provide both bulk-property predictions and calculated molecular distributions for crude oil distillation process. Full article

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

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13 pages, 4909 KB

Open AccessArticle

Recovery of High-Purity Grade B-Phycoerythrin from Porphyridium cruentum by the Two-Step Ultrasound-Based UltraBlu Process

by Rosaria Lauceri, Lyudmila Kamburska and Simona Musazzi

Processes 2026, 14(17), 2678; https://doi.org/10.3390/pr14172678 (registering DOI) - 22 Aug 2026

Abstract

Phycobiliproteins are water-soluble photosynthetic pigments extracted mainly from microalgae and cyanobacteria with many potential biotechnological applications, such as healthy food colorants, nutraceuticals, fluorescent tags, or non-toxic therapeutic agents. We have recently devised a green innovative two-step ultrasound-based process (named UltraBlu) to obtain blue [...] Read more.

Phycobiliproteins are water-soluble photosynthetic pigments extracted mainly from microalgae and cyanobacteria with many potential biotechnological applications, such as healthy food colorants, nutraceuticals, fluorescent tags, or non-toxic therapeutic agents. We have recently devised a green innovative two-step ultrasound-based process (named UltraBlu) to obtain blue phycocyanin (a phycobiliprotein) with a high-purity grade from the cyanobacterium Limnospira platensis. To assess the possibility of a wider use of the method, this study evaluates the UltraBlu process on an organism of a different taxonomic domain, the red microalga Porphyridium cruentum, for extracts rich in B-phycoerythrin (B-PE), the main phycobiliprotein produced by this organism. The UltraBlu process is characterized by the extraction of phycobiliproteins decoupled from biomass cell lysis, although the process is entirely carried out in an aqueous medium. Conversely, cell lysis is integrated with the purification step and is carried out by ultrasonication in ammonium sulfate solution before the pigment extraction/recovery step. B-PE, significantly purer than that obtained via conventional one-step direct ultrasound-assisted extraction, was recovered within a few hours from fresh biomass, only isolating the B-PE extract from the leftover biomass by centrifugation. Yields generally exceeded 9%, approaching the highest pigment contents reported for P. cruentum in the literature. Full article

(This article belongs to the Special Issue Process Intensification and Optimization in Microalgae Biomass Conversion and Biorefining)

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27 pages, 10085 KB

Open AccessArticle

Hierarchical Sensitivity Analysis of PV Converter Operating Profiles Under Climatic and Grid Uncertainty

by Ivelina Hinova, Silvia Baeva and Mirjana Kocaleva Vitanova

Processes 2026, 14(16), 2677; https://doi.org/10.3390/pr14162677 - 21 Aug 2026

Abstract

Photovoltaic converters operate under varying climatic conditions and non-ideal grid regimes, but factor importance is often assessed either through isolated local metrics or through pooled operating data that hide regime shifts and interaction effects. This study develops a hierarchical framework for sensitivity analysis [...] Read more.

Photovoltaic converters operate under varying climatic conditions and non-ideal grid regimes, but factor importance is often assessed either through isolated local metrics or through pooled operating data that hide regime shifts and interaction effects. This study develops a hierarchical framework for sensitivity analysis of operating profiles of grid-connected PV converters under climatic and grid uncertainty. A compact operating-profile formulation is introduced that relates solar radiation, cell and ambient temperature, grid voltage, load, and selected design/control parameters to active power, efficiency, power factor, harmonic distortion, DC bus ripple, clipping behavior, and thermal headroom. The proposed workflow combines local normalized sensitivities for fast ranking around nominal conditions, Morris screening for factor reduction, and Sobol/Saltelli variance-based indices for global prioritization under uncertainty. The framework is demonstrated on a 100 kW synthetic reduced-order benchmark representing a three-phase two-level grid-connected PV inverter with an LCL filter. To clarify the scope of validity, the reduced-order model is cross-checked against switching-level simulations for representative nominal, clipping-prone, high-temperature and grid-stress operating windows. The results show that factor importance is not universal, but depends on the selected KPI, operating regime and uncertainty scenario. In the considered benchmark, grid voltage, cell temperature and equivalent thermal resistance are the dominant total-effect contributors, while the strongest second-order contribution appears between grid voltage and filter inductance under grid-stress conditions. The proposed framework is therefore intended as a reproducible, regime-aware sensitivity workflow rather than as a universal ranking of PV converter parameters. Full article

(This article belongs to the Special Issue Adaptive Control and Optimization in Power Grids)

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34 pages, 841 KB

Open AccessArticle

A Multistage Sufficiency Test for Selecting Energy Performance Indicators in Industry: Beyond R² Toward the Variable Associated with Significant Energy Use

by Yoisdel Castillo Alvarez, Reinier Jiménez Borges, José Pedro Monteagudo Yanes, Ariadna Yaneli Resendiz Jaramillo, Luis Angel Iturralde Carrera, Hugo Rodríguez-Reséndiz and Juvenal Rodríguez-Reséndiz

Processes 2026, 14(16), 2676; https://doi.org/10.3390/pr14162676 - 21 Aug 2026

Abstract

Under ISO 50001, energy performance is monitored through Energy Performance Indicators (EnPIs) and energy baselines. In practice, the energy-to-production ratio (kWh/t) is commonly adopted by default and validated solely by the coefficient of determination (

R^{2}

), which is insensitive to systematic [...] Read more.

Under ISO 50001, energy performance is monitored through Energy Performance Indicators (EnPIs) and energy baselines. In practice, the energy-to-production ratio (kWh/t) is commonly adopted by default and validated solely by the coefficient of determination (

R^{2}

), which is insensitive to systematic bias, to the base load contained in the intercept, and to the residual structure that reveals an omitted explanatory variable. This work organizes well-established statistical and engineering checks into a sequential, four-outcome decision procedure anchored to the diagnosis of Significant Energy Uses (SEUs): retain the simple ratio, adopt a regression baseline with the same variable, switch to the SEU-associated variable, or reject the model as structurally misspecified. Relative to common practice, the procedure makes three methodological corrections explicit: in-sample NMBE is identically zero for OLS models with an intercept and is therefore defined out of sample; residual diagnostics are evaluated against exact, design-specific Durbin–Watson critical values with a Šidák-corrected family-wise error of 0.044–0.050 (versus ≈0.14 uncorrected); and the candidate-variable step uses a partial F-test on nested models, since the naive residual-versus-variable regression is attenuated by collinearity with production. The procedure is characterized on synthetic data with known truth (

N = 1000

replicates per cell): against an interannual drift of ≈2%/yr, its sensitivity reaches 1.00 at

n = 72

months while an

R^{2}

-only criterion has sensitivity 0.00, and with a base-load fraction of ≈0.28 the

R^{2}

-only rule retains the biased ratio in 100% of the replicates; specificity under a correct ratio is 0.95–0.96, and the adopted thresholds lie in a stable region of the (

R^{2}

,

f_{0}

) sensitivity sweep. The procedure is then demonstrated on six industrial cases; most notably, in a fuel oil power plant a pooled baseline with

R^{2} = 0.998

is rejected (Durbin–Watson

= 0.79

versus an exact critical value of 1.64; runs test

p < 0.001

) because of drift in specific fuel consumption that

R^{2}

cannot detect, and its out-of-sample validation over 37 rolling origins shows that an aggregated bias of

+ 0.31 %

can mask an origin-to-origin drift from

- 1.7 %

to

+ 2.1 %

. The contribution is not a new indicator or a new statistic, but the integration of indicator selection and multistage statistical validation into a single auditable decision procedure whose operating characteristics are quantified. Full article

(This article belongs to the Section Energy Systems)

26 pages, 2111 KB

Open AccessArticle

Pareto-Active-Region-Guided Sequential Surrogate Modeling for CFD-Based Multi-Objective Optimization of Liquid-Cooled Battery Thermal Management Systems

by Zhanming Luo, Lei Wang and Deyong Song

Processes 2026, 14(16), 2675; https://doi.org/10.3390/pr14162675 - 21 Aug 2026

Abstract

Computational fluid dynamics (CFD)-driven optimization of engineering systems is often constrained by high computational cost, particularly when surrogate models must be constructed from limited simulation samples. Although surrogate-assisted multi-objective optimization can substantially reduce CFD evaluations, local prediction errors in decision-sensitive Pareto regions may [...] Read more.

Computational fluid dynamics (CFD)-driven optimization of engineering systems is often constrained by high computational cost, particularly when surrogate models must be constructed from limited simulation samples. Although surrogate-assisted multi-objective optimization can substantially reduce CFD evaluations, local prediction errors in decision-sensitive Pareto regions may alter feasibility classification and engineering recommendations near active constraints. To address this issue, this study proposes a Pareto-active-region-guided sequential surrogate modeling framework (PAR-SSM) for multi-objective optimization of liquid-cooled battery thermal management systems. Starting from 15 face-centered central composite design (FCCD) samples, the framework selectively introduces additional high-fidelity CFD evaluations into Pareto-active and constraint-sensitive regions, yielding a 21-sample refined surrogate model. Rather than uniformly improving global prediction accuracy, PAR-SSM directs the limited CFD budget toward regions where surrogate errors can directly influence engineering decisions. After model freezing, three independent Fluent cases were used exclusively for validation, yielding mean absolute deviations of 0.098 °C for maximum temperature and 0.341 °C for temperature difference, while also revealing residual feasibility risk near active constraint boundaries. Application to an autonomous underwater vehicle (AUV) battery module showed that the N = 3 configuration dominated the nominally constrained Pareto set and provided a favorable thermal–hydraulic trade-off under low auxiliary energy consumption. Overall, PAR-SSM provides a decision-oriented strategy for balancing computational cost and optimization credibility in CFD-intensive, constrained multi-objective design. Full article

(This article belongs to the Section Energy Systems)

14 pages, 17786 KB

Open AccessArticle

Development Characteristics of Mining-Induced Fractures and Surface Air Leakage Dynamics in Shallow Coalfields

by Jianglong Wang, Yixuan Yang, Tingfeng Zhu, Fucheng Zhang and Huogen Luo

Processes 2026, 14(16), 2674; https://doi.org/10.3390/pr14162674 - 21 Aug 2026

Abstract

Surface fissures induced by shallow coal seam mining create interconnected pathways for ambient air leakage, significantly aggravating coal spontaneous combustion (CSC) risks in goafs. However, the spatiotemporal evolution of these fractures and the quantitative dynamics of air leakage under repeated mining conditions remain [...] Read more.

Surface fissures induced by shallow coal seam mining create interconnected pathways for ambient air leakage, significantly aggravating coal spontaneous combustion (CSC) risks in goafs. However, the spatiotemporal evolution of these fractures and the quantitative dynamics of air leakage under repeated mining conditions remain poorly understood. This study investigates the evolutionary laws of mining-induced cracks and air leakage behaviors through laboratory physical similarity simulations and field tracer gas testing. The results demonstrate that during repeated extraction, vertical fractures in the goaf boundaries undergo an expansion-to-stabilization process with significantly increased widths, whereas fractures in the central region experience a process from expansion to closure and stabilization. Crucially, the fracturing of the inter-seam key stratum marks a vital milestone where the upper and lower goafs merge into a complex goaf, precipitating a sudden, sharp surge in air leakage volume. Field observations categorize surface cracks into graben type, collapse type, and tensile type. Graben-type and collapse-type cracks act as the principal pathways for surface air infiltration, collectively forming a rectangular distribution network across the goaf. These findings provide a critical theoretical framework and practical guidance for predicting and controlling surface air leakage disasters in close-distance shallow seam mining. Full article

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

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15 pages, 3277 KB

Open AccessArticle

Effects of Roasting on Bioactive Components and Volatile Compounds of Prunus tangutica Kernels

by Jianjun Chen, Chaozhen Zeng, Jiulong Huang and Yuwen Mu

Processes 2026, 14(16), 2673; https://doi.org/10.3390/pr14162673 - 21 Aug 2026

Abstract

Prunus tangutica is an underused wild nut of the Chinese highlands. Its kernels are rich in polyphenols and flavonoids but also contain amygdalin, so debittering must precede roasting, and how the two steps act together is not known. This study determined the effects [...] Read more.

Prunus tangutica is an underused wild nut of the Chinese highlands. Its kernels are rich in polyphenols and flavonoids but also contain amygdalin, so debittering must precede roasting, and how the two steps act together is not known. This study determined the effects of debittering and of roasting temperature and time on the bioactive components, antioxidant capacity and volatile profile of P. tangutica kernels from Diebu, Gansu Province, roasted at 100–180 °C for 10–30 min. Debittering markedly reduced polyphenols (from 0.21–0.36 to 0.09–0.27 mg GAE/g) and flavonoids (from 0.57–1.87 to 0.10–0.63 mg RE/g). Both declined as temperature and time increased, whereas antioxidant capacity rose under intense roasting. FRAP peaked at 180 °C/20 min in non-debittered samples and DPPH radical-scavenging activity at 180 °C/30 min in debittered samples, suggesting that Maillard reaction products may partially offset the loss of native antioxidants. Roasting strongly promoted pyrazine formation (2,5-dimethylpyrazine rose from 28.77 to 3909.28 µg/kg) but also increased benzaldehyde and benzyl cyanide, the thermal degradation products of amygdalin, at 180 °C/30 min. Of the conditions tested, 160 °C/30 min was the most suitable for debittered kernels, and 120 °C/30 min was the most suitable for non-debittered kernels; no condition is proposed for the direct consumption of non-debittered kernels, because residual cyanogenic compounds were not quantified. Full article

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

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38 pages, 49140 KB

Open AccessArticle

Experimental and Numerical Investigation of Heat Transfer and Fluid Flow in Triply Periodic Minimal Surface Structures: Influence of Base Integration

by Esa Dube Kerme, Mohammed Yahya and M. Ziad Saghir

Processes 2026, 14(16), 2672; https://doi.org/10.3390/pr14162672 - 21 Aug 2026

Abstract

This study investigates the heat transfer and fluid flow characteristics of six triply periodic minimal surface (TPMS) structures, specifically Gyroid (G3P6, G3P7, G3P8, G1P7) and Diamond (D1P7 and D3P7) configurations, using both experimental and numerical methods. Comparative analysis was conducted to evaluate the [...] Read more.

This study investigates the heat transfer and fluid flow characteristics of six triply periodic minimal surface (TPMS) structures, specifically Gyroid (G3P6, G3P7, G3P8, G1P7) and Diamond (D1P7 and D3P7) configurations, using both experimental and numerical methods. Comparative analysis was conducted to evaluate the impact of adding a base to these structures on their thermal and hydraulic performance. The TPMS structures were assessed in terms of measured surface temperature, convection heat transfer coefficient, Nusselt number, overall thermal resistance, pressure drop, friction factor, and overall thermal–hydraulic performance. Results indicate that base-free structures exhibit better heat dissipation, with surface temperatures increasing by 1.2 °C (G3P6) to 5.5 °C (D3P7) when the base is added. The addition of the base reduces the convection heat transfer coefficient on average by 3.9% (G3P6) to 23% (D1P7) and increases overall thermal resistance by 3.1% (G3P6) to 28.7% (D1P7). The friction factor also rises by 6.1% (D1P7) to 47.3% (G3P6) due to the addition of the base. When the base is added, the overall thermal–hydraulic performance declines by 8.5% (G3P7) to 33.6% (D3P7), with Diamond structures experiencing a more significant reduction compared to Gyroid structures. Among the Gyroid structures, G3P6 (lower cell size and 60% porosity) demonstrated the lowest surface temperature and the highest heat dissipation capacity, while G3P8 (80% porosity) exhibited the lowest thermal performance. The Gyroid structure with larger cell size (G1P7) achieved the highest overall thermal–hydraulic performance, effectively balancing heat dissipation and fluid resistance. In contrast, when the base is integrated, the Gyroid structure with a smaller cell size and lower porosity (G3P6) showed the lowest overall thermal–hydraulic performance. Full article

(This article belongs to the Special Issue Multi-Phase Flow and Heat Transfer Processes in Thermal Engineering and Technology)

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19 pages, 4519 KB

Open AccessArticle

A Study on Geochemical Characteristics and Genesis Mechanisms of Coalbed Methane in the Dafosi Well Field, Huang-Long Jurassic Coalfield

by Kaide Liu, Yu Xia, Kaiwen Yao, Songxin Zhao, Wenping Yue, Chaowei Sun, Qiyu Wang and Xinping Wang

Processes 2026, 14(16), 2671; https://doi.org/10.3390/pr14162671 - 21 Aug 2026

Abstract

The Dafosi well field is a typical Huang-Long Jurassic low-rank coalbed methane (CBM) field. Clarifying its CBM geochemical characteristics and the mechanisms of its formation is of significant importance for deepening the understanding of the formation mechanisms of low-rank CBM in China and [...] Read more.

The Dafosi well field is a typical Huang-Long Jurassic low-rank coalbed methane (CBM) field. Clarifying its CBM geochemical characteristics and the mechanisms of its formation is of significant importance for deepening the understanding of the formation mechanisms of low-rank CBM in China and for the scientific assessment of its resource potential. A total of eight gas emission samples from six coalbed methane wells in the Dafosi coalfield were collected, along with 22 coal samples from the 4^# coal seam. Detailed analyses of microscopic coal petrographic components, gas chemical compositions, and carbon isotopes were performed. By integrating data from the 20 relevant literature sources on coalbed gas composition and isotopic characteristics within the study area, a comprehensive dataset comprising 28 sets was utilized to examine the carbon isotope characteristics and genesis types of both CH₄ and CO₂ in the coalbeds, as well as elucidate the mechanism behind CH₄ carbon isotope depletion. The findings indicate that in the primary 4^# coal seam’s microscopic petrographic composition, the organic matter content is considerably higher, averaging 93.2%. Among these, the inertinite group is dominant, averaging 68.2%; the vitrinite group is the next most abundant, averaging 22.8%. The CBM composition is predominantly CH₄, with concentrations varying from 68.753% to 98.006%, averaging 80.276%. N₂ concentrations range from 1.259% to 29.926%, averaging 17.476%. CO₂ concentrations vary from 0.04% to 2.380%, averaging 1.032%. The average concentration of heavier hydrocarbons C₂ and above is less than 0.078%, indicative of typical dry gas characteristics, C₁/C_1~n > 0.999. The concentration of CH₄ and N₂ was negatively correlated. δ¹³C₁ ranges from −87.200‰ to −62.400‰, averaging −75.802‰. CH₄ is composed of secondary biogenic gas with dominant content and a small amount of thermogenic gas. δ¹³C_CO2 ranges from −41.693‰ to −7.065‰, averaging −20.016‰. CO₂ is an organic gas, mainly derived from thermal degradation and microbial degradation of organic matter. The mechanism responsible for the light carbon isotopic composition of δ¹³C₁ lies in the fact that most of CH₄ is produced by CO₂ reduction, and a small amount is produced by acetic acid fermentation. In the gas generation process of these two pathways, biogenic methane will eventually enrich light carbon isotopes, resulting in light δ¹³C₁. Full article

(This article belongs to the Special Issue Environmental Governance and Sustainable Development: Multipollutant Control and Resource-Energy Transition)

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10 pages, 4142 KB

Open AccessArticle

NMR Characterization of Plastic Pyrolysis Oils Obtained over Clay Catalysts

by Sergei Golovin, Lyubov Furda, Evgeniy Seliverstov and Olga Lebedeva

Processes 2026, 14(16), 2670; https://doi.org/10.3390/pr14162670 - 21 Aug 2026

Abstract

The accumulation of plastic waste has become a significant environmental challenge, stimulating the development of efficient recycling technologies capable of converting polymers into valuable products. In this study, polypropylene wastes were thermocatalytically converted into liquid hydrocarbons using three naturally occurring types of clay [...] Read more.

The accumulation of plastic waste has become a significant environmental challenge, stimulating the development of efficient recycling technologies capable of converting polymers into valuable products. In this study, polypropylene wastes were thermocatalytically converted into liquid hydrocarbons using three naturally occurring types of clay as catalysts, namely, kaolin, illite, and bentonite. The obtained liquid products were investigated using one- and two-dimensional NMR spectroscopy, including 1H, 13C, and COSY techniques. Quantitative evaluation of hydrocarbon group composition was performed using established NMR correlations to determine the content of paraffins, olefins and aromatic compounds as well as fuel-related parameters. The results demonstrated that paraffins were the predominant constituents in all pyrolysis oils, accounting for more than 70 vol.%, while olefins and aromatics were present in smaller amounts. Although all catalysts promoted the formation of liquid mixtures of hydrocarbon, noticeable differences in product composition were observed. Oil obtained over illite exhibited increased aromaticity and lower olefin content, whereas kaolin produced a product characterized by the highest isoparaffin index and estimated research octane number. The findings indicate that variations in catalysts influence the characteristics of polypropylene-derived oils and may be used to tailor products’ properties for their utilization as fuel additives or petrochemical feedstocks. Full article

(This article belongs to the Section Catalysis Enhanced Processes)

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21 pages, 8152 KB

Open AccessArticle

The Hydrochemical Characteristics and Formation Mechanism of High TDS Groundwater in Arid and Semi-Arid Coal Mining Area

by Ning Yang, Yashuai Cui, Zhihong Kang, Shuheng Tang, Xin Wu, Yidi Zhang, Aoshuang Mei and Yifan Zeng

Processes 2026, 14(16), 2669; https://doi.org/10.3390/pr14162669 - 21 Aug 2026

Abstract

Understanding the formation of high-total-dissolved-solids (TDS) groundwater is essential for mine-water source identification, treatment, and resource utilization in arid and semi-arid coal mining areas. However, previous studies have commonly focused on individual aquifers and have not adequately explained the hydrochemical differentiation and evolutionary [...] Read more.

Understanding the formation of high-total-dissolved-solids (TDS) groundwater is essential for mine-water source identification, treatment, and resource utilization in arid and semi-arid coal mining areas. However, previous studies have commonly focused on individual aquifers and have not adequately explained the hydrochemical differentiation and evolutionary relationships within shallow-to-deep multi-aquifer systems. Taking the Xiaojihan Coal Mine in northern Shaanxi as a case study, 90 surface-water and groundwater samples were analyzed using self-organizing maps (SOM), hydrochemical diagrams, major-ion ratios, chlor-alkali indices, mineral saturation indices, X-ray diffraction data, and permeability-TDS relationships. SOM identified three hydrochemical units broadly corresponding to shallow surface water and groundwater from the Quaternary and Luohe formations, groundwater from the Anding Formation, and deep groundwater dominated by the Zhiluo and Yan’an formations. Their mean TDS concentrations increased from 348.69 to 1341.80 and 2510.00 mg/L, respectively. Groundwater evolved from low-TDS, HCO₃-Ca-dominated shallow water to high-TDS, SO₄-Ca/Na-rich deep water. Shallow groundwater was mainly controlled by carbonate and silicate weathering, whereas deep groundwater was increasingly affected by prolonged water-rock interaction, gypsum and anhydrite dissolution, pyrite oxidation, and reverse cation exchange. The increase in deep-groundwater TDS was primarily associated with the enrichment of SO₄²⁻, Na⁺ + K⁺, and Ca²⁺. Lower permeability with depth slowed groundwater circulation, prolonged residence time, and enhanced mineralization. XRD data confirmed the occurrence of exchange-active clay minerals, while saturation indices showed that carbonate minerals were generally near saturation to supersaturated, whereas gypsum, anhydrite, and halite remained undersaturated and retained dissolution potential. These findings clarify the shallow-to-deep evolution mechanism of high-TDS groundwater and provide a scientific basis for mine-water source identification and targeted management in arid and semi-arid coal mining areas. Full article

(This article belongs to the Special Issue Progress in Analysis of Elements in Water Environment and Pollution Process Control)

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21 pages, 4383 KB

Open AccessArticle

Reduced-Order Small-Signal Modeling of PV Storage Systems Considering Dynamic Interactions

by Xiaodi Zang, Fangzhou Yu, Penghui Qiao, Jingyu Liu, Chengzhong Fan and Li Guo

Processes 2026, 14(16), 2668; https://doi.org/10.3390/pr14162668 - 20 Aug 2026

Abstract

The complexity of circuit structures and control loops in three-level interleaved parallel DC-DC converters (TIPDCs) presents significant challenges to the small-signal reduced-order modeling of multi-converter PV storage systems. To address this issue, a research framework featuring “loop/level reduction first, followed by multi-converter equivalence” [...] Read more.

The complexity of circuit structures and control loops in three-level interleaved parallel DC-DC converters (TIPDCs) presents significant challenges to the small-signal reduced-order modeling of multi-converter PV storage systems. To address this issue, a research framework featuring “loop/level reduction first, followed by multi-converter equivalence” is proposed. Based on this framework, a reduced-order modeling method considering dynamic interactions is developed. First, the dual-loop three-level DC/DC converter is equivalently reduced to a two-level DC/DC converter model. Moreover, the equivalent analytical equations between the control parameters and filter parameters of the two converters are established. Then, further order reduction is performed on multiple parallel-connected DC/DC converters, and a small-signal reduced-order model of the multi-converter PV storage system is established. Finally, a switching model of the multi-converter PV storage system is implemented on the RT-Box hardware-in-the-loop platform, and the effectiveness of the equivalent reduced-order model is validated by multiple sets of experimental results. Full article

(This article belongs to the Special Issue Design, Control, Modeling and Simulation of Energy Converters)

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42 pages, 7523 KB

Open AccessArticle

A Robust Model Evaluation Process for Early-Stage Cooling Load Prediction of Buildings

by Yaren Aydın, Ümit Işıkdağ, Sinan Melih Nigdeli, Gebrail Bekdaş, Wook-Won Kim and Zong Woo Geem

Processes 2026, 14(16), 2667; https://doi.org/10.3390/pr14162667 - 20 Aug 2026

Abstract

In the construction industry, a large portion of energy is spent on heating and cooling, which both increases costs and contributes to resource depletion. The aim of the study was to provide and evaluate a robust ML model evaluation process for early design [...] Read more.

In the construction industry, a large portion of energy is spent on heating and cooling, which both increases costs and contributes to resource depletion. The aim of the study was to provide and evaluate a robust ML model evaluation process for early design stage cooling load prediction of buildings. For this purpose, 18 different machine learning models were evaluated using a Nested Cross-Validation approach consisting of 50 outer fold and 50 inner Optuna trials, along with hyperparameter optimization. To avoid model selection being dependent on small decimal differences, paired model comparisons, effect sizes, Holm-corrected statistical tests, and the 1-SE economy rule were applied over the same outer folds. As a result of the analysis, Categorical Boosting (CatBoost) was selected as the final model, and within the Nested-CV framework, R² = 0.8275 ± 0.0072, RMSE = 1.6792 ± 0.0210 kWh, MAE = 1.4356 ± 0.0233 kWh, and MAPE = 0.0521 ± 0.0009 were obtained. Model interpretability analyses showed that the variables Ambient Temperature, Solar Radiation, and Heat Reflective Treatment had the highest permutation importance values. Residual analyses revealed that the model exhibited low systematic bias, but the residual variance was dependent on the estimate value, and the residuals deviated from a normal distribution. This study provides a framework that evaluates not only the prediction performance but also model selection, generalization stability, interpretability, and residual behavior together. The findings demonstrate that CatBoost is a strong option for cooling load prediction in this simulation-based dataset. However, validation of the obtained results with real building data and different climatic conditions is considered an important requirement for future studies in terms of evaluating the external validity of the model. Full article

(This article belongs to the Special Issue Toward Net-Zero Industry: Sustainable Processes, Renewable Energy Solutions, and Innovative Thermal Management)

25 pages, 6889 KB

Open AccessArticle

Study on the Coupling Characteristics Between Unsteady Flow and Hydrodynamic Loads in the Guide Vane Region of a Pump–Turbine Under Runaway Condition

by Ling Li, Qifei Li and Xiangyu Chen

Processes 2026, 14(16), 2666; https://doi.org/10.3390/pr14162666 - 20 Aug 2026

Abstract

To elucidate the coupling characteristics between unsteady flow and hydrodynamic loads in the guide vane region of a pump–turbine under runaway conditions, a model pump–turbine of a high-head pumped storage power station was selected as the research object. A combined approach of model [...] Read more.

To elucidate the coupling characteristics between unsteady flow and hydrodynamic loads in the guide vane region of a pump–turbine under runaway conditions, a model pump–turbine of a high-head pumped storage power station was selected as the research object. A combined approach of model experiments and three-dimensional unsteady numerical simulations was employed to investigate the guide vane hydraulic torque, flow field structures, pressure distribution, and pressure fluctuation characteristics under different pre-opening guide vane conditions. In the experiments, the hydraulic torque of guide vanes was measured using a guide vane shaft strain testing method at five guide vane openings of 19 mm, 25 mm, 33 mm, 41 mm, and 45 mm. In the numerical simulations, a full-passage unsteady computational model was established based on the SST k-ω turbulence model, and the reliability of the numerical model was validated against experimental results. The results indicate that the guide vane hydraulic torque under runaway conditions exhibits pronounced periodic fluctuations, and the dominant period in the time domain is consistent with the blade passing frequency, demonstrating that rotor–stator interaction between the runner wake and guide vanes is the primary mechanism inducing unsteady hydraulic loads. As the guide vane opening decreases, the flow passage area in the guide vane region is reduced, and the high-speed swirling flow at the runner outlet generates significant jet impingement and local shear layers near the guide vane inlet, resulting in enhanced circumferential non-uniformity of the flow field and a substantial increase in the pressure difference across the guide vane surfaces. Among all operating conditions, the hydraulic torque fluctuation at a₀ = 19 mm is the most severe. Under small-opening conditions, flow separation, wake accumulation, and local backflow structures are prone to occur in the vicinity of the guide vanes, accompanied by pronounced high-frequency pressure disturbances and local impulsive pressure peaks. With increasing guide vane opening, the flow attachment behavior and flow field continuity are gradually improved, and the pressure fluctuations evolve from random oscillations to regular periodic pulsations, indicating a significant enhancement in flow stability. The study demonstrates that small guide vane opening conditions produce hydrodynamic load characteristics—specifically, higher-amplitude and more intermittent torque fluctuations, as well as lower minimum pressures—that are indicative of conditions conducive to increased vibration, fatigue accumulation, and cavitation risk; however, direct structural or two-phase cavitation analyses are required to confirm these implications. The present results can provide a theoretical basis for the optimal design of guide vane mechanisms and the safe operation of pump–turbines under runaway conditions, and quantitative coupling analysis reveals that the cross-correlation between inlet pressure and torque decreases from R = 0.87 at a₀ = 19 mm to R = 0.72 at a₀ = 45 mm, confirming that the flow–load coupling weakens substantially with increasing opening. Full article

(This article belongs to the Section Energy Systems)

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21 pages, 399 KB

Open AccessArticle

The Effect of Hydration Levels on the Rheological and Thermomechanical Properties of Different Gluten-Free Flours

by Maria-Andriana Mastropanagiotou, Athanasios Alexopoulos, Stavros Plessas and Theodoros Varzakas

Processes 2026, 14(16), 2665; https://doi.org/10.3390/pr14162665 - 20 Aug 2026

Abstract

The growing demand for gluten-free products has increased the need for a better understanding of the rheological behavior of alternative flours and their suitability for bakery applications. This study aimed to evaluate the effect of different hydration levels on the rheological properties of [...] Read more.

The growing demand for gluten-free products has increased the need for a better understanding of the rheological behavior of alternative flours and their suitability for bakery applications. This study aimed to evaluate the effect of different hydration levels on the rheological properties of gluten-free flours and compare their behavior with that of wheat flour. Rice flour, corn flour, chickpea flour, buckwheat flour, and wheat flour were analyzed using Mixolab 2 at hydration levels of 55%, 58%, and 60%. The resulting torque curves were examined to assess dough development, stability, and behavior during mixing and heating. Differences among flour types were observed throughout dough development and protein weakening. One-way ANOVA identified significant flour-type effects for all 19 Mixolab variables at 55% and 60% hydration and for 17 of 19 variables at 58%, where T(C4) and γ-slope were not significant. Across the three common hydration levels, two-way ANOVA showed significant main effects of flour type and hydration for every variable and significant flour × hydration interactions for all variables (p ≤ 0.035), confirming flour-specific hydration responses. Among the gluten-free flours, buckwheat maintained the most stable and comparatively robust torque profile, rice was particularly sensitive at 60% hydration, and corn and chickpea showed pronounced structural weakening during heating, most notably chickpea. A focused principal component analysis (PCA) of the five directly measured torque points (C1–C5), using the hydration levels common to all flour types, identified a dominant first component that explained 76.9% of the total variance. The first two axes together accounted for 94.3% and provided a concise two-dimensional representation of flour-specific and hydration-dependent differences. These findings highlight the importance of hydration management in gluten-free formulations and provide useful information for optimizing bakery processes involving alternative flours. Full article

(This article belongs to the Special Issue Food Processing and Ingredient Analysis)

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17 pages, 17380 KB

Open AccessArticle

Experimental and Numerical Investigation of Ultrasonic Welding of Steel/Aluminum/Steel Three-Layer Sheets and Its Application in the Engineering Finite Element and Numerical Computation Course

by Dewang Zhao, Yufan Xu, Zhongbo Peng, Xiaolong Wu, Kunmin Zhao and Emre Altas

Processes 2026, 14(16), 2664; https://doi.org/10.3390/pr14162664 - 20 Aug 2026

Abstract

The aluminum/steel hybrid body structure represents one of the key breakthrough directions for automotive lightweighting. However, aluminum and steel differ significantly in their thermophysical properties, making it difficult to achieve high-quality joining between them using conventional fusion welding methods. To address this challenge, [...] Read more.

The aluminum/steel hybrid body structure represents one of the key breakthrough directions for automotive lightweighting. However, aluminum and steel differ significantly in their thermophysical properties, making it difficult to achieve high-quality joining between them using conventional fusion welding methods. To address this challenge, the present study employs ultrasonic welding technology to achieve spot welding in a steel/aluminum/steel three-layer plate configuration. The experimental welding of the three-layer sheets and interfacial phase identification were first carried out, followed by the development of an ultrasonic vibration–thermal–mechanical coupled numerical simulation model, the accuracy of which was verified through experiments. On this basis, the dynamic evolution of the temperature and stress fields during the ultrasonic welding process was systematically revealed. Furthermore, this novel engineering simulation case was introduced into the teaching of the course Engineering Finite Element and Numerical Computation yielding favorable educational outcomes. Full article

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

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