The aim of this study was to analyse the bite forces of seven species from three carnivore families: Canidae, Felidae, and Ursidae. The material consisted of complete, dry crania and mandibles. A total of 33 measurements were taken on each skull, mandible, temporomandibular joint, and teeth. The area of the temporalis and masseter muscles was calculated, as was the length of the arms of the forces acting on them. Based on the results, the bite force was calculated using a mathematical lever model. This study compared the estimated areas of the masticatory muscles and the bending strength of the upper canines among seven species. A strong correlation was found between cranial size and bite force. The results confirmed the hypothesis that the weight of the animal and the size of the skull have a significant effect on the bite force. Full article

In bridge reinforcement projects, damaged T-beams are the most common objects for reinforcement, yet the interface bonding and bending performance of UHPC reinforcement on T-beams have hardly been studied. To ensure the reliability and stability of UHPC-strengthened T-beams in practical applications, this study introduced a post-installed rebar bonding technique to efficiently connect T-beams with UHPC layers. Initially, using ABAQUS software [2020 version] for finite element simulation, this study investigated the effects of various post-installed rebar parameters (horizontal spacing, yield strength, diameter, and matrix concrete strength) on the shear performance of the UHPC and RC interface, obtaining the optimal connection parameters. Subsequently, by comparing shear formulas in domestic and international standards, a new UHPC-RC steel bar interface shear strength theoretical formula with 93.6% accuracy was derived. Finally, finite element simulations analyzed the impact of different post-installed reinforcing bar layout forms and longitudinal spacing, as well as UHPC-strengthened location and layer thickness, on the bending performance of damaged T-beams. The results showed a good match between simulation outcomes and experimental results, applicable for further reinforcement analysis of T-beams. When the horizontal spacing of post-installed rebars is 12d, with diameters ranging from 10 mm to 14 mm, their anchoring capability is efficiently utilized. A square form of a post-installed rebar with a longitudinal spacing of 300 mm effectively improves the ultimate bending load capacity of the strengthened beam. The simulation analysis and theoretical results help in the design and application of post-installed steel connections and UHPC-strengthened structures in UHPC-strengthened reinforced concrete T-beam structures. Full article

In recent years, research on the preservation of historical architecture has gained significant attention, where the effectiveness of semantic segmentation is particularly crucial for subsequent repair, protection, and 3D reconstruction. Given the sparse and uneven nature of large-scale historical building point cloud scenes, most semantic segmentation methods opt to sample representative subsets of points, often leading to the loss of key features and insufficient segmentation accuracy of architectural components. Moreover, the geometric feature information at the junctions of components is cluttered and dense, resulting in poor edge segmentation. Based on this, this paper proposes a unique semantic segmentation network design called MSFA-Net. To obtain multiscale features and suppress irrelevant information, a double attention aggregation module is first introduced. Then, to enhance the model’s robustness and generalization capabilities, a contextual feature enhancement and edge interactive classifier module are proposed to train edge features and fuse the context data. Finally, to evaluate the performance of the proposed model, experiments were conducted on a self-curated ancient building dataset and the S3DIS dataset, achieving OA values of 95.2% and 88.7%, as well as mIoU values of 86.2% and 71.6%, respectively, further confirming the effectiveness and superiority of the proposed method. Full article

The evaluation of the structural behaviour of a masonry Venetian church with a pointed barrel vault is presented in this paper through an analysis following the necessary steps of a monument study. With a detailed geometric model and material estimation, the finite-element method is used to investigate the influence of specific structural parts of the structure, like masonry buttresses and wall connections, on the structural behaviour. The operational modal analysis is used to identify the structure dynamically. The comparison of the eigenfrequencies, which are estimated by in situ measurements and finite-element modal analysis, is used to perform a model identification. The response spectrum analysis, the static analysis after the subsistence of some parts following strengthening proposals, and the transient analysis of specific seismic excitations are used for the evaluation of the structural behaviour. The purpose of the work is to highlight the need for an interdisciplinary approach to the study of a monumental complex structure, regardless of its scale. The coexistence of structural elements of different stiffnesses, such as vaults, elongated walls, buttresses, transverse walls with pediment and belfry, as well as the concha, affects the mechanical behaviour and the pathology of the structure, which is difficult to study with simplifying models. From the analysis, it is concluded that subsidence problems, combined with seismic actions, lead to the cracking of the masonry, while the existence of buttresses limits the extension of the damage and contributes to the stabilization of the structure. Full article

The construction industry records higher accident rates than other industries, and thus, risk estimation is necessary to manage accident rates. Risk levels differ based on facility type and construction project size. In this sense, this study aims to calculate the quantitative accident risk level according to the construction project size per infrastructure facility type. To this end, the following five-step risk estimation was performed: (1) data collection and classification; (2) calculation of fatality rate based on construction cost; (3) calculation of fatal construction probability by construction cost classification; (4) reclassification of construction cost considering fatal construction probability; and (5) calculation of risk level by facility type and construction cost classification. As a result, the fatality rate per facility type was the highest in ‘Dam’ at 0.01024 (person/USD million). Additionally, the risk level according to the construction project size per facility type was the highest for ‘Dam’ (0.00403 person/USD million) for a construction of less than USD 0.77 million. The risk level presented in this study can be utilized as basic data in the design stage for safety management. Our results also indicate the necessity of preparing a separate construction cost classification for safety management. Full article

Major projects are the important platform for enhancing a country’s comprehensive national power and strengthening its capacity for independent innovation. Although major projects in China have made remarkable achievements, willingness to cooperate and innovate has not achieved the desired target. In this paper, the evolutionary game model of cooperative innovation behavior of general contractors and subcontractors is constructed by considering reputational factors. Through theoretical derivation, the influence of the distribution ratio of collaborative innovation benefit, spillover technology absorption capacity, and reputation discounting coefficient on innovation behavior is analyzed. Finally, MATLAB software is used to simulate the dynamic evolution process of strategy selection. The results show that (1) a reasonable benefit distribution coefficient can promote the evolution of innovation behavior in a positive direction; (2) both the reduction of innovation cost and the increase of spillover technology absorption capacity can make the innovation subject more inclined to choose the active collaborative innovation strategy; and (3) it is the higher-than-threshold reputation loss that can effectively inhibit the “free-rider” behavior. The research conclusions and managerial implications can provide reference for improving the willingness to cooperate in major projects’ technology innovation. Full article

The trend of using conventional devices like mobile phones, tablets, and the other devices is gaining traction in improving customer service practices. This coincides with the growing popularity of building information modeling (BIM), which has led to increased exploration of various 3D object capture methods. Additionally, the technological boom has resulted in a surge of applications working with different 3D model formats including mesh models, point cloud, and TIN models. Among these, the usage of mesh models is experiencing particularly rapid growth. The main objective advantages of mesh models are their efficiency, scalability, flexibility, sense of detail, user-friendliness, and compatibility. The idea of this paper is to use a conventional device, specifically an iPad Pro equipped with light detection and ranging (LiDAR) technology, for creating mesh models. The different data capture methods employed by various applications will be compared to evaluate the final models´ precision. The accuracy of the 3D models generated by each application will be assessed by comparing the spatial coordinates of identical points distributed irregularly across the entire surface of the chosen object. Various available currently most-used applications were utilized in the process of data collection. In general, 3D representations of the object/area, etc., may be visualized, analyzed, and further processed in more formats such as TIN models, point cloud, or mesh models. Mesh models provide a visualization of the object mirroring the solid design of the real object, thus approximating reality in the closest way. This fact, along with automatized postprocessing after data acquisition, the ability to capture and visualize both convex and concave objects, and the possibility to use this type of 3D visualization for 3D printing, contribute to the decision to test and analyze mesh models. Consequently, the mesh models were created via the automatic post-processing, i.e., without external intervention. This fact leads to the problems of random coordinate systems being automatically pre-defined by every application. This research must deal with the resulting obstacles in order to provide a valid and credible comparative analysis. Various criteria may be applied to the mesh models’ comparisons, including objective qualitative and quantitative parameters and also the subjective ones. The idea of this research is not to analyze the data acquisition process in detail, but instead to assess the possibilities of the applications for the basic users. Full article

Paving blocks are widely used in engineering construction for durable pavement surfaces characterized by their interlocking capability to enhance structural integrity. This study explores the potential use of char as a byproduct from coal pyrolysis and an alternative raw material to natural aggregates in developing paving blocks, aiming to reduce the associated environmental issues associated with the uncontrolled and excessive mining of natural resources. This study finds the paving blocks made from char to have the required engineering properties as mentioned by ASTM standard C936. Trass and trass-lime are added as supplementary cementitious materials (SCMs) to enhance the performance of char-based paving blocks. The incorporation of SCMs as a cement replacement also aims to reduce the carbon footprint arising from increased cement use. The compressive strength increased from 55.7 MPa to 65.71 MPa at 12.5% cement replacement with trass-lime. The water absorption is reduced to 4.63% from 4.95%. Beneficial effects towards freeze–thaw durability and abrasion resistance are also observed on trass-lime-incorporated paving blocks. This study signifies the remarkable potential use of coal-derived char and SCMs in developing light, high-strength, and durable paving blocks, showcasing their competitive engineering performance. These new char-based paving blocks will contribute towards a more sustainable construction environment and advance the current construction and engineering practices. Full article

Objectives: Orthopedics and dentistry have widely utilized titanium alloys as biomaterials for dental implants, but limited research has been conducted on the fabrication of ceramic particle-reinforced Ti composites for further weight reductions. The current study compared titanium–titanium diboride metal composites (Ti-TiB₂) with pure titanium (processed by powder metallurgy) in terms of toxicity, corrosion resistance, and wettability. Methods: First, cell lines of a primary dermal fibroblast normal human adult (HDFa) were used to test the cytocompatibility (in vitro) of the composite and pure Ti using an indirect contact approach. Corrosion testing was performed for the materials using electrochemical techniques such as potentiodynamic polarization in a simulated bodily fluid (SBF) in conjunction with a three-electrode electrochemical cell. The entire set of experimental tests was conducted according to the ASTM F746-04 protocol. The contact angles were measured during wettability testing in accordance with ASTM D7334-08. An X-ray diffractometer (XRD) was used to catalog every phase that was visible in the microstructure. A scanning electron microscope (SEM) and energy-dispersive X-ray spectroscopy (EDS) were used to determine the chemical composition. Results: The cytotoxicity tests revealed that there was no detectable level of toxicity, and there was no significant difference in the impact of either of the two materials on the viability of human fibroblasts. An increase in the corrosion resistance of the composite (0.036 ± 0.0001 mpy (millimeters per year)) demonstrated the development of a passive oxide coating. According to the findings, the composites showed a greater degree of hydrophilicity (contact angle 44.29° ± 0.28) than did the pure titanium (56.31° ± 0.47). Conclusions/Significance: The Ti-TiB₂ composite showed no toxicity and better corrosion resistance and wettability than did pure Ti. The composite could be a suitable alternative to Ti for applications involving dental implants. Full article

A precise evaluation of the risk of establishing insect pests is essential for national plant protection organizations. This accuracy is crucial in negotiating international trade agreements for forestry-related commodities, which have the potential to carry pests and lead to unintended introductions in the importing countries. In our study, we employed both mechanistic and correlative niche models to assess and map the global patterns of potential establishment for Aeolesthes sarta under current and future climates. This insect is a significant pest affecting tree species of the genus Populus, Salix, Acer, Malus, Juglans, and other hardwood trees. Notably, it is also categorized as a quarantine pest in countries where it is not currently present. The mechanistic model, CLIMEX, was calibrated using species-specific physiological tolerance thresholds, providing a detailed understanding of the environmental factors influencing the species. In contrast, the correlative model, maximum entropy (MaxEnt), utilized species occurrences and spatial climatic data, offering insights into the species’ distribution based on observed data and environmental conditions. The projected potential distribution from CLIMEX and MaxEnt models aligns well with the currently known distribution of A. sarta. CLIMEX predicts a broader global distribution than MaxEnt, indicating that most central and southern hemispheres are suitable for its distribution, excluding the extreme northern hemisphere, central African countries, and the northern part of Australia. Both models accurately predict the known distribution of A. sarta in the Asian continent, and their projections suggest a slight overall increase in the global distribution range of A. sarta with future changes in climate temperature, majorly concentrating in the central and northern hemispheres. Furthermore, the models anticipate suitable conditions in Europe and North America, where A. sarta currently does not occur but where its preferred host species, Populus alba, is present. The main environmental variables associated with the distribution of A. sarta at a global level were the average annual temperature and precipitation rate. The predictive models developed in this study offer insights into the global risk of A. sarta establishment and can be valuable for monitoring potential pest introductions in different countries. Additionally, policymakers and trade negotiators can utilize these models to make science-based decisions regarding pest management and international trade agreements. Full article

The effects of soluble silicon fertilization on monocots and dicots have been widely studied. However, little is known regarding its effects on protecting epiphytes against insect and fungal pests. The efficacy of silicon fertilizer to reduce damage by thrips pest complexes, namely: Thrips palmi Karny, Frankliniella occidentalis Pergande, Chaetanaphothrips orchidii Moulton, and Chaetanaphothrips signipennis Bagnall (Thysanoptera: Thripidae), and the fungal pathogens: Botrytis cinerea Persoon (Helotiales: Sclerotiniaceae) and Fusarium spp. Link (Hypocreales: Nectriaceae) was examined during a nine-month greenhouse trial in Hawaii. The trial assessed yield, quality, and pest damage across three common varieties of dendrobiums. All replicates received additional soluble silicon fertilizer applications alternating weekly between soil drench and foliar (50 mg Si/plant) applications. Yield, quality, and spray length, pest damage, plant vigor, SPAD, and leaf temperature were measured. Data were analyzed using a generalized linear model (glm) with repeated measures followed by post-hoc pair-wise comparisons in R, version 4.3.1. Treatment effects were significant at p < 0.001 for the majority of the explanatory variables including: marketable yield, spray length, thrips damage, and fungal damage. Overall, the lavender variety (‘Uniwai Supreme’) benefited the most from silicon applications with a 73.0% increase in marketable yield, compared to the white variety (‘Uniwai Mist’), which had an increase of 50.6% marketable sprays in contrast to its untreated control. Si benefits conferred to the purple variety (‘Uniwai Royale’) were intermediate to the lavender and white varieties. Although the magnitude of Si benefits varied among the varieties, all dendrobium varieties significantly benefited from silicon fertilization. Full article

Welding stands as a critical focus for the intelligent and digital transformation of the machinery industry, with automated laser welding playing a pivotal role in the sector’s technological advancement. The management of welding deformation in such operations is fundamental, relying on advanced analysis and prediction methods. The endeavor to accurately analyze welding deformation in practical applications is compounded by the interplay of numerous variables, a pronounced coupling effect among these factors, and a reliance on expert intuition. Thus, effective deformation control in automated laser welding operations necessitates the gathering of pre-test laser welding data to develop a predictive approach that accurately reflects real-world conditions and is characterized by improved reliability and stability. To address the technological evolution in automated laser welding, a predictive model based on neural network technology is proposed to map the intricate relationship between process variables and the resulting deformation. At the heart of this approach is the formulation of a predictive model utilizing a back-propagation neural network (BP), with an emphasis on four essential welding parameters: speed, peak power, duty cycle, and defocusing amount. The model’s predictive accuracy is then honed through the application of the whale optimization algorithm (WOA) and the differential evolutionary (DE) algorithm. Finally, extensive testing in an automated laser welding experimental setup is conducted to validate the accuracy and reliability of the proposed prediction model. It is demonstrated through these experiments that the deformation prediction model, enhanced by the DEWOA-BP neural network, accurately forecasts the relationship between laser welding parameters and the induced deformation, maintaining a prediction error margin of ±0.1mm. The model is employed to fulfill the requirements for a pre-welding quality evaluation, thereby facilitating a more calculated and informed approach to welding operations. This method of intelligent prediction is not only crucial for the intelligent transformation of laser welding but also holds significant implications for traditional machining technologies such as milling, grinding, and spraying. It offers innovative ideas and methods that are pivotal for the industrial revolution and technological advancement of the traditional machining industry. Full article

Since tool wear accumulates in the cutting process, the condition of the cutting tool shows a degradation trend, which ultimately affects the surface quality. Tool wear monitoring and prediction are of significant importance in intelligent manufacturing. The cutting signal shows short-term randomness due to non-uniform materials in the workpiece, making it difficult to accurately monitor tool condition by relying on instantaneous signals. To reduce the impact of transient fluctuations, this paper proposes a novel network based on deep learning to monitor and predict tool wear. Firstly, a CNN model based on residual connection was designed to extract deep features from multi-sensor signals. After that, a temporal model based on an encoder and decoder was built for short-term monitoring and long-term prediction. It captured the instantaneous features and long-term trend features by mining the temporal dependence of the signals. In addition, an encoder and decoder-based temporal model is proposed for smoothing correction to improve the estimation accuracy of the temporal model. To validate the performance of the proposed model, the PHM dataset was used for wear monitoring and prediction and compared with other deep learning models. In addition, CFRP milling experiments were conducted to verify the stability and generalization of the model under different machining conditions. The experimental results show that the model outperformed other deep learning models in terms of MAE, MAPE, and RMSE. Full article

In this paper, the tempered $\mathsf{\Psi }$–Riemann–Liouville fractional derivative and the tempered $\mathsf{\Psi }$–Caputo fractional derivative of order $n-1<\alpha <n\in \mathbb{N}$ are introduced for $C^{n-1}$–functions. A nonlinear version of the second Henry–Gronwall inequality for integral inequalities with the tempered $\mathsf{\Psi }$–Hilfer fractional integral is derived. By using this inequality, an existence and uniqueness result and a sufficient condition for the non-existence of blow-up solutions of nonlinear tempered $\mathsf{\Psi }$–Caputo fractional differential equations are proved. Illustrative examples are given. Full article

To solve the problem of fault diagnosis for the key components of the CNC machine feed system under the condition of variable speed conditions, an intelligent fault diagnosis method based on multi-domain feature extraction and an ensemble learning model is proposed in this study. First, various monitoring signals including vibration signals, noise signals, and current signals are collected. Then, the monitoring signals are preprocessed and the time domain, frequency domain, and time–frequency domain feature indices are extracted to construct a multi-dimensional mixed-domain feature set. Finally, the feature set is entered into the constructed DoubleEnsemble–LightGBM model to realize the fault diagnosis of the key components of the feed system. The experimental results show that the model can achieve good diagnosis results under different working conditions for both the widely used dataset and the feed system test bench dataset, and the average overall accuracy is 91.07% and 98.06%, respectively. Compared with XGBoost and other advanced ensemble learning models, this method demonstrates better accuracy. Therefore, the proposed method provides technical support for the stable operation and intelligence of CNC machines. Full article

We present a two-country model (North and South) that describes the phenomenon of offshoring and reshoring. The model is a continuous time-controlled Markov chain with binary states. The main trade-off involves production costs and transaction costs between one country and another. In the first part of this paper, we identify the key parameters of the model: the difference in unit production costs between the two countries considered, the marginal cost of transitioning between countries, and the incentive paid by the North country to all companies that have not relocated at the end of the planning interval. The final goal of our paper is to understand how national tax incentives can influence this process. Full article

Coal mining activity contributes to energy security and employment occupation, but is associated with environmental deterioration. Coal combustion leads to GHG emissions, while coal mining results in the generation of saline effluents. These effluents are discharged in inland surface waters, applying significant pressure on their quality, with a negative impact on aquatic life and the economy of a region. This study includes water samples that were analyzed in order to investigate the organic compounds, heavy metals, and other physicochemical parameters. Biological monitoring was done according to the Water Framework Directive methodology. The results from an aquatic area in Southern Poland, which indirectly receives coal mine effluents, indicate elevated salinity with excessive chlorides, sulfates, and sodium ions. The water quality of another non-polluted aquatic area was also assessed to examine the impact of indirect coal mine wastewater discharge on this area. The high salinity levels hinder the use of river water for drinking, agricultural, or industrial purposes. The results obtained show high pressure on the ecological status of streams and rivers that receive mine effluents, and on the density and diversity of aquatic invertebrates. This pressure is clearly visible in the structure of benthic communities and in invertebrate diversity. It also contributes to the appearance of invasive species and increasing water salinity. Limiting discharges of mine water transporting large loads of saline substances would reduce the negative impact on the quality of river waters and biological life. Full article

Dams are regarded as crucial pieces of structure that store water for irrigation and municipal uses. Given their vital role, the dam’s water quality assessment is considered to be an important criterion and requires constant monitoring. In this research, we attempted to use two water quality indices (WQIs) methods to assess the water quality of the Keddara Dam, which is located on the Boudouaou River, Algeria, using eleven water quality parameters (temperature, pH, conductivity, turbidity, total suspended solids (TSS), full alkalimetric title (TAC), hydrometric title (TH), nitrite ions (NO²⁻), nitrate ions (NO³⁻), ammonium ions (NH⁴⁺), and phosphate ions (PO₄³⁻)) for data recorded from 29 December 2018 to 3 June 2021. Application of The Canadian Council of Ministers of the Environment (CCME) WQIs and the Weighted Arithmetic Method (WAM) indicated that the Keddara Dam’s water quality parameters were within the WHO’s permissible level, except for the conductivity and turbidity values. The results of the CCME WQI ranged from acceptable (81.92) to excellent (95.08) quality, whereas the WAM WQI ranged from 9.52 to 17.77, indicating excellent quality. This demonstrates that the Keddara Dam is appropriate for agriculture and municipal use. The water quality indices (WQIs) methods are recommended as valuable tools that allow both the public and decision-makers to comprehend and manage the water quality of any aquatic environment by providing flexibility in choosing variables. Full article

The improper disposal of plastics is a growing concern due to increasing global environmental problems such as the rise of CO₂ emissions, diminishing petroleum sources, and pollution, which necessitates the research and development of biodegradable materials as an alternative to conventional packaging materials. The purpose of this research was to analyse the properties of biodegradable polymer blends of thermoplastic potato starch (TPS) and polylactide, (PLA) without and with the addition of citric acid (CA) as a potential compatibilizer and plasticizer. The prepared blends were subjected to a comprehensive physicochemical characterization, which included: FTIR-ATR spectroscopy, morphological analysis by scanning electron microscopy (SEM), determination of thermal and mechanical properties by differential scanning calorimetry (DSC), water vapour permeability (WVP), as well as biodegradation testing in soil. The obtained results indicate an improvement in adhesion between the TPS and PLA phases due to the addition of citric acid, better homogeneity of the structure, and greater compatibility of the polymer blends, leading to better thermal, mechanical and barrier properties of the studied biodegradable TPS/PLA polymer blends. After conducting the comprehensive research outlined in this paper, it has been determined that the addition of 5 wt.% of citric acid serves as an effective compatibilizer and plasticizer. This supplementation achieves an optimal equilibrium across thermal, mechanical, morphological, and barrier properties, while also promoting material sustainability through biodegradation. In conclusion, it can be stated that the use of thermoplastic starch in TPS/PLA blends accelerates the biodegradation of PLA as a slowly biodegradable polymer. While the addition of citric acid offers significant advantages for TPS/PLA blends, further research is needed to optimize the formulation and processing parameters to achieve the desired balance between mechanical strength, thermal and barrier properties and biodegradability. Full article

Block copolymer (BCP) surfaces permit an exquisite level of nanoscale control in biomolecular assemblies solely based on self-assembly. Owing to this, BCP-based biomolecular assembly represents a much-needed, new paradigm for creating nanobiosensors and nanobiomaterials without the need for costly and time-consuming fabrication steps. Research endeavors in the BCP nanobiotechnology field have led to stimulating results that can promote our current understanding of biomolecular interactions at a solid interface to the never-explored size regimes comparable to individual biomolecules. Encouraging research outcomes have also been reported for the stability and activity of biomolecules bound on BCP thin film surfaces. A wide range of single and multicomponent biomolecules and BCP systems has been assessed to substantiate the potential utility in practical applications as next-generation nanobiosensors, nanobiodevices, and biomaterials. To this end, this Review highlights pioneering research efforts made in the BCP nanobiotechnology area. The discussions will be focused on those works particularly pertaining to nanoscale surface assembly of functional biomolecules, biomolecular interaction properties unique to nanoscale polymer interfaces, functionality of nanoscale surface-bound biomolecules, and specific examples in biosensing. Systems involving the incorporation of biomolecules as one of the blocks in BCPs, i.e., DNA–BCP hybrids, protein–BCP conjugates, and isolated BCP micelles of bioligand carriers used in drug delivery, are outside of the scope of this Review. Looking ahead, there awaits plenty of exciting research opportunities to advance the research field of BCP nanobiotechnology by capitalizing on the fundamental groundwork laid so far for the biomolecular interactions on BCP surfaces. In order to better guide the path forward, key fundamental questions yet to be addressed by the field are identified. In addition, future research directions of BCP nanobiotechnology are contemplated in the concluding section of this Review. Full article

Large-tow carbon fiber (LCF) meets the low-cost requirements of modern industry. However, due to the large and dense number of monofilaments, there are problems with uneven and insufficient infiltration during material preparation. The permeability of large-tow carbon fibers can be used as a two-scale expression of resin flow during infiltration, making it an important factor to consider. This paper provides support for the study of pore formation. A two-dimensional model of randomly bundled large-filament carbon fibers is generated based on scanning electron microscope (SEM) maps. Microstructure size parameters are obtained, and a semi-analytical model of the transverse permeability of large-filament-bundled carbon fibers is established. Permeability values are then obtained. The analysis shows that the monofilaments in the tow are arranged randomly, and their periodic arrangement cannot be used to calculate permeability. Additionally, the number of monofilaments in a carbon fiber tow of the same volume fraction affects the permeability of the tow. Therefore, the permeability model of large-tow carbon fibers is reliable. Full article