3D Model Research Articles

3D and 2D-QSAR Studies on Natural Flavonoids for Nitric Oxide Production Inhibitory Activity

Background: Nitric oxide (NO), an important second messenger molecule, regulates numerous physiological responses, while excessive NO generates negative effects on the circulatory, nervous and immune systems. Recently, some natural flavonoids were reported to possess the capability of inhibiting LPS-induced NO production. To fully understand the nature of their own NO inhibitory activity, it is necessary to address the structural requirements of flavonoids as NO inhibitors. Objective: The objective of this work was to develop efficient QSAR models for predicting the NOinhibitory activity of new flavonoids and improving insights into the critical properties of the chemical structures that were required for the ideal NO production inhibitory activities. Methods: To provide insights into the structural basis of flavonoids as NO inhibitors, 3D quantitative structure-activity relationship (3D-QSAR) and 2D-QSAR models were developed on a dataset of 55 flavonoids using comparative molecular field analysis (CoMFA), comparative molecular similarity indices analysis (CoMSIA) and hologram quantitative structure-activity relationship (HQSAR) approaches. Results: The statistically significant models for CoMFA, CoMSIA and HQSAR resulted in crossvalidated coefficient (q2) values of 0.523, 0.572 and 0.639, non-cross-validated coefficient (r2) values of 0.793, 0.828 and 0.852, respectively. The robustness of these models was further affirmed using a test set of 18 compounds, which resulted in predictive correlation coefficients (r2 pred) of 0.968, 0.954 and 0.906. Furthermore, the models-derived contour maps were appraised for activity trends for the molecules analyzed. Conclusion: The 3D and 2D-QSAR models constructed in this paper were efficient in estimating the NO inhibitory activities of flavonoids and facilitating the design of flavonoid-derived NO production inhibitors.

Advancing osteosarcoma 3D modeling in vitro for novel tumor microenvironment-targeted therapies development

Osteosarcoma (OS) represents one of the most common primary bone cancers affecting children and young adults. The available treatments have remained unimproved for the past decades, hampered by the poor knowledge of OS etiology/pathophysiology and the lack of innovative, predictive and biologically relevant in vitro models, that can recapitulate the 3D OS tumor microenvironment (TME). Here, we report the development and characterization of an innovative 3D model of OS, composed of OS tumor cells, immune cells (macrophages) and mesenchymal stem cells (MSCs), that formed a multicellular tissue spheroid (MCTS). This fully humanized 3D model was shown to accurately mimic the native histological features of OS, while innately leading to the polarization of macrophages towards an M2-like phenotype, highly aggressive and pro-tumor profile. Upon the exposure to immunomodulatory molecules, the MCTS were shown to be responsive by shifting macrophages polarization, and dramatically altering the TME secretome. In agreement, when treated with immunomodulatory/stimulatory nanoparticles (NPSs), we were able to revert the TME secretome towards an anti-inflammatory profile. This study establishes an advanced 3D OS model capable of shedding light on macrophages and MSCs contributions to disease progression, paving the way for the development of innovative therapeutic approaches targeting the OS TME, while providing a biologically relevant in vitro tool for the efficacy screening of novel OS therapeutic approaches.

3D human model guided pose transfer via progressive flow prediction network

Human pose transfer is to transfer a conditional person image to a new target pose. The difficulty lies in modeling the large-scale spatial deformation from the conditional pose to the target one. However, the commonly used 2D data representations and one-step flow prediction scheme lead to unreliable deformation prediction because of the lack of 3D information guidance and the great changes in the pose transfer. Therefore, to bring the original 3D motion information into human pose transfer, we propose to simulate the generation process of real person image. We drive the 3D human model reconstructed from the conditional person image with the target pose and project it to the 2D plane. The 2D projection thereby inherits the 3D information of the poses which can guide the flow prediction. Furthermore, we propose a progressive flow prediction network consisting of two streams. One stream is to predict the flow by decomposing the complex pose transformation into multiple sub-transformations. The other is to generate the features of the target image according to the predicted flow. Besides, to enhance the reliability of the generated invisible regions, we use the target pose information which contains structural information from the flow prediction stream as the supplementary information to the feature generation. The synthesized images with accurate depth information and sharp details demonstrate the effectiveness of the proposed method.

Cranial Fluctuating Asymmetry and Schizophrenia in a contemporary Danish population

Post-mortem Computed Tomography (PMCT) scans in forensic medicine not only assists with case work but is also a useful data source for other imaging-based research, e.g. morphological studies on bones. PMCT 3D data can be combined with diagnostic information and help to elucidate how disease manifests in the body. For example, the skeleton can be influenced by developmental instability, which may result in a morphological change called fluctuating asymmetry (FA). Developmental instability also influences the risk of developing schizophrenia, which means that individuals with higher levels of developmental instability, and by extension FA, might have a higher risk of developing the disorder. This connection has been investigated in soft tissues but has not yet been investigated in bones. We used PMCT 3D models from a forensic cohort to compare levels of cranial FA between a group of individuals with diagnosed schizophrenia and a control group. Our sample included 48 individuals with diagnosed schizophrenia and 58 controls. We collected 27 landmarks from our 3D models. Levels of fluctuating asymmetry were analyzed using Procrustes ANOVA, and the two groups were compared using t-test and Wilcoxon rank sum test. Age and sex were tested as factors using Pearson correlation and two-way ANOVA. We found that there was no statistically significant difference in levels of cranial FA between the schizophrenic group and the control group, and that neither age nor sex was a factor. Our results confirm earlier studies that suggest that the multifactorial aetiology of FA and schizophrenia is difficult to capture comprehensively.

Seismic design coefficients verification of regular and vertically irregular high-rise shear wall buildings using bidirectional horizontal ground motions and 3D modeling

Seismic design coefficients verification of regular and vertically irregular high-rise shear wall buildings using bidirectional horizontal ground motions and 3D modeling

Microplastics and Cancer Progression: A Comparative Study of 2D and 3D Gastric Cancer Models Using ISO-Compliant Protocols

Microplastics have emerged as a significant global environmental concern, yet the absence of standardized protocols for assessing their toxicity remains a challenge. To address this gap, we applied the ISO 10993-5:2009 and ISO 10993-12:2012 standards for the first time to evaluate the effects of microplastics on cancer progression. Our study utilized both two-dimensional and three-dimensional models of gastric cancer to investigate the potential role of microplastics in promoting cancer growth. The MTT assay results revealed that the highest concentrations of polyethylene microplastics (PE-MPs) and polypropylene microplastics (PP-MPs) enhanced the proliferation of gastric cancer cells at both 24 and 72 hours. After 24 hours, AGS cells treated with PE-MPs and PP-MPs exhibited increased viability, reaching 116.08% ± 15.55 and 118.78% ± 13.96, respectively; however, this increase was not statistically significant. In contrast, after 72 hours, AGS cells showed significantly enhanced growth, with viability reaching 122.37% ± 9.28 for PE-MPs and 131.51% ± 3.05 for PP-MPs (p < 0.001). In the three-dimensional model, live/dead staining results after seven days indicated that spheroids exposed to microplastics demonstrated greater cell survival compared to the control group. The percentage area growth of spheroids was 7.93% ± 1.5 for the control, 13.93% ± 4.85 for PE-MPs, and 19.59% ± 1.61 for PP-MPs, with the increase in PP-MPs being statistically significant (p < 0.05). Additionally, microplastics did not penetrate the three-dimensional gastric cancer within seven days. This research highlights the potential impact of microplastics on cancer development and introduces a novel methodological approach.

3D visualization diagnostics for lung cancer detection

&lt;span&gt;Lung cancer is a leading cause of cancer deaths worldwide with an estimated 2 million new cases and 1·76 million deaths yearly. Early detection can improve survival, and CT scans are a precise imaging technique to diagnose lung cancer. However, analyzing hundreds of 2D CT slices is challenging and can cause false alarms. 3D visualization of lung nodules can aid clinicians in detection and diagnosis. The MobileNet model integrates multi-view and multi-scale nodule features using depthwise separable convolutional layers. These layers split standard convolutions into depthwise and pointwise convolutions to reduce computational cost. Finally, the 3D pulmonary nodular models were created using a ray-casting volume rendering approach. Compared to other state-of-the-art deep neural networks, this factorization enables MobileNet to achieve a much lower computational cost while maintaining a decent degree of accuracy. The proposed approach was tested on an LIDC dataset of 986 nodules. Experiment findings reveal that MobileNet provides exceptional segmentation performance on the LIDC dataset, with an accuracy of 93.3%. The study demonstrates that the MobileNet detects and segments lung nodules somewhat better than other older technologies. As a result, the proposed system proposes an automated 3D lung cancer tumor visualization.&lt;/span&gt;

Impact resistance of polyvinyl alcohol-polypropylene fiber toughened foamed concrete under low-velocity impact: experiments and 3D meso-scale modelling

Foamed concrete exhibits good energy absorption and shock absorption properties due to its microporous structure. Compared with conventional concrete, foamed concrete can more readily enter the plastic stage and more effectively reflect and absorb impact energy. However, a scientific deficit of knowledge about the impact resistance of foamed concrete with various hardeners and there is a lack of accurate verified models of such a process. In this study, the impact resistance of polyvinyl alcohol-polypropylene fiber toughened foamed concrete under different impact speeds and different amounts of polyvinyl alcohol has been investigated using the cube drop weight impact test. The toughening mechanism of polyvinyl alcohol is revealed through XRD analysis. In addition, 3D meso-scale modelling of a composite material composed of foam, mortar, an interface transition zone and fiber was conducted using the Python-based secondary development of Abaqus to simulate impact resistance. The results have demonstrated that the impact resistance (ultimate bearing capacity, total absorbed energy and dynamic increase factor) of the toughened foamed concrete samples initially increased and subsequently decreased with the addition of polypropylene fiber and polyvinyl alcohol. At the impact speed of 1.6m/s, compared with ordinary foamed concrete, the ultimate bearing capacity of polyvinyl alcohol polypropylene fiber toughened foamed concrete is increased by 107.8%, the total absorbed energy is increased by 119.7%, and the dynamic increase coefficient is increased by 31.6%; At the impact speed of 2.0m/s, compared with ordinary foamed concrete, the ultimate bearing capacity of polyvinyl alcohol polypropylene fiber toughened foamed concrete is increased by 134.2%, the total absorbed energy is increased by 87.9%, and the dynamic increase coefficient is increased by 50%. The simulation results are in good agreement with the test results, establishing that 3D meso-scale modelling modeling can accurately describe the impact resistance test of foamed concrete. It is further confirmed that 3D meso-scale modelling is reliable for predicting the impact resistance of polymer-fiber toughened foamed concrete.

CPPF++: Uncertainty-Aware Sim2Real Object Pose Estimation by Vote Aggregation.

Object pose estimation constitutes a critical area within the domain of 3D vision. While contemporary state-of-the-art methods that leverage real-world pose annotations have demonstrated commendable performance, the procurement of such real training data incurs substantial costs. This paper focuses on a specific setting wherein only 3D CAD models are utilized as a priori knowledge, devoid of any background or clutter information. We introduce a novel method, CPPF++, designed for sim-to-real category-level pose estimation. This method builds upon the foundational point-pair voting scheme of CPPF, reformulating it through a probabilistic view. To address the challenge posed by vote collision, we propose a novel approach that involves modeling the voting uncertainty by estimating the probabilistic distribution of each point pair within the canonical space. Furthermore, we augment the contextual information provided by each voting unit through the introduction of N-point tuples. To enhance the robustness and accuracy of the model, we incorporate several innovative modules, including noisy pair filtering, online alignment optimization, and a tuple feature ensemble. Alongside these methodological advancements, we introduce a new category-level pose estimation dataset, named DiversePose 300. Empirical evidence demonstrates that our method significantly surpasses previous sim-to-real approaches and achieves comparable or superior performance on novel datasets.

Extracellular vesicles powered cancer immunotherapy: Targeted delivery of adenovirus-based cancer vaccine in humanized melanoma model.

Malignant melanoma, a rapidly spreading form of skin cancer, is becoming more prevalent worldwide. While surgery is successful in treating early-stage melanoma, patients with advanced disease have only a 20% chance of surviving beyond five years. Melanomas with mutations in the NRAS gene are characterized for a more aggressive tumor biology, poorer prognosis and shorter survival. Hence, new therapeutic strategies are needed, especially for this specific group of patients. Novel approaches, such as cancer vaccines, offer promising solutions by stimulating the anti-tumor immune response. Nevertheless, their clinical efficacy is still modest and more effective approaches are required. Herein, we propose the systemic administration of the adenovirus-based cancer vaccine complexed in extracellular vesicles (EVs) with the aim of achieving a targeted therapeutic effect. The vaccine was based on previously tested oncolytic adenovirus Ad5/3-D24-ICOSL-CD40L in combination with melanoma-specific antigens targeting NRAS mutations to enhance the anticancer effect. The antineoplastic properties of the oncolytic vaccine were evaluated in xenograft MUG Mel-2 melanoma BALB/c nude mice. Moreover, to mimic the tumor microenvironment, while investigating at the same time immune cell infiltration and drug penetration, we established a 3D co-culture model based on human NRAS mutated MUG Mel-2 spheroids and PBMCs (HLA matched), which displayed a synergistic effect when treated with the cancer vaccine compared to relative controls. Subsequently, we investigated the systemic delivery of the vaccine in EV formulations in a humanized NSG MUG Mel-2 melanoma mouse model. Our study provides a promising strategy for a tumor-targeted vaccine delivery by EVs, resulting in improved anticancer efficacy and increased infiltration of tumor-infiltrating lymphocytes. This study explores the potential of EVs for the selective delivery of cancer vaccines against malignancies, such as NRAS melanoma. Overall, this research could pave the way for applying autologous EVs as a safe and efficacious tool for targeted cancer therapy.

A voxel-based 3D indoor model to support 3D pedestrian evacuation simulations

Three-dimensional (3D) indoor models enable realistic simulation of pedestrian evacuations in 3D space. However, existing indoor models do not fully identify navigable spaces located above/below physical components (e.g., chairs, stairs, desks), and the connections between these spaces and their navigable surfaces remain underexplored. These limitations hinder the accurate modelling of 3D pedestrian motions during evacuations. To address the shortcomings, we present novel automatic approaches to create a voxel-based 3D indoor model. First, based on different types of 3D motions, indoor spaces are automatically identified as freely navigable spaces, navigable spaces under conditions and non-navigable spaces. Then, navigable surfaces are identified to simulate moving above/below in 3D space. Vertical links are identified to connect the spaces and surfaces at different heights. A 3D pathfinding approach is subsequently developed to validate the model’s effectiveness. Finally, we evaluate the created model’s accuracy, robustness and efficiency across different voxel sizes. The primary findings are: 1) as voxel size increases, accuracy decreases, robustness changes and efficiency improves; 2) with very small voxel sizes, identification becomes challenging, while larger voxel sizes prevent some spaces and vertical links from being identified; and 3) indoor spaces with complex geometries require more time for identification. Our key contributions are: 1) an approach for automatically identifying indoor spaces for 3D motions; 2) two approaches for automatically identifying navigable surfaces and vertical links; and 3) a 3D pathfinding approach considering distinct 3D motion costs. This work advances 3D modelling to facilitate more realistic evacuation simulations.

Assembling a physical model helps students grasp human somatosensory pathways.

Mastering the complexity of the nervous system is essential for education programs in physiology, anatomy, and neuroscience. Students often struggle when learning somatosensory pathways, which convey information from sensory neurons to the somatosensory cortex in the brain. Active learning activities incorporating physical models have been shown to increase content comprehension as well as enjoyment of the learning process. Here, we present a three-dimensional physical model of somatosensory pathways constructed of durable, affordable, and widely available materials. In an upper level human physiology lab, students assembled the model and then used it to complete case study questions connecting damage to the spinal cord to resulting sensory deficits. This model-based activity was highly effective as indicated by significant increases in content knowledge and positive responses to survey questions on the effectiveness of the activity. This activity incorporates many evidence-based teaching practices that have been shown to increase engagement, inclusion, and mastery of content and provides an effective and fun way for students to learn a challenging topic.NEW & NOTEWORTHY This model-building activity for learning somatosensory neural pathways increases students' content knowledge and is an enjoyable way to learn a complex system. This activity adds to an ever-growing collection of evidence-based learning activities for human physiology courses.

Identification and characteristic analysis of internal defects in rock-filled concrete based on deep learning method

The distribution characteristics and geometric morphology characteristics of defects within RFC are important factors affecting the strength properties and rupture morphology of RFC. However, the excessive size of commonly used aggregates for RFC leads to difficulties in conducting in-depth experimental studies indoors. Based on the improved U-Net and image processing technology, this research establishes an integrated model for the identification, classification, and extraction of defects inside the RFC, quantitatively counts and analyzes the acquired defect distribution characteristics and geometrical morphology characteristics, and establishes a defect characteristic distribution function that can be used for the numerical reconstruction of defects. In order to realize the acceleration of U-Net training using training weights, use VGG-16 with the fully connected layer removed instead of the Encoder part of the U-Net. The integrated model in this research can realize automatic identification, classification, and extraction of multiple types of defects at the same time, and the established distribution function of defect characteristics provides a data basis and new ideas for the establishment of RFC three-dimensional numerical models containing real defects.

Modelling of the trade-off between the deep soil moisture and vegetation restoration in the hilly area of the Loess Plateau, China

Excessive depletion of soil moisture by artificial forests in the vegetation restoration areas of the Loess Plateau has attracted widespread attention. To assess potential risks of soil moisture deficit, we needed on-site vegetation and soil sampling data, as well as UAV images from the Chaigou Watershed for three-dimensional analysis, combining both sampling and raster data. Three-dimensional surfaces for assessment of trade-off were established innovatively by the local regression and interpolation methods. The results indicated that soil moisture benefits at 20–40 cm depth are lower than at 0–20 cm due to infiltration and surface disturbance. In some areas of the Chaigou Watershed, grass and shrub-grass vegetation are facing risks of soil moisture deficit based on trade-off values (RSMD) and multiparameter evaluations. Analysis of deep soil water content variability revealed the moisture decreases significantly with the deepening of the soil layer in some plots. R (Richness), H (Shannon’s Diversity), Margalef, COHESION, and CONTAG were applicable in interpolation and fitted with the local regression model (R2 > 0.6) corresponding to the trade-off, but SPLIT was proven to be inapplicable in this study area. The zero trade-off inflection points were 6 %–8 %, while the trend inflection points were 7.5 %–9 % for soil moisture and vegetation indices of vegetation and landscape in typical sampling sites of the Chaigou Watershed. Three-dimensional fitting model is more comprehensive and effective in assessing deep soil moisture conditions and grass plots on shady slopes generally had the best trade-off status in this region.

Numerical investigation on the effect of ignition timing on a low-temperature hydrogen-fueled Wankel rotary engine with passive pre-chamber ignition

Adopting the low-temperature hydrogen evaporated from the liquid hydrogen is capable of improving volumetric efficiency for the Wankel rotary engine (WRE). Considering the difficulty in ignition and slow flame propagation of low-temperature hydrogen-air mixtures, the passive pre-chamber is used to improve ignition and combustion. A three-dimensional computational fluid dynamics model for a turbulent jet ignition (TJI) WRE fueled by low-temperature hydrogen was established. The effects of low temperature and TJI on the in-cylinder flow field, combustion, emissions and leakage in the TJI-WRE fueled by low-temperature hydrogen were studied under different ignition timings. The results indicated that low-temperature tends to suppress the flame propagation, whereas TJI can accelerate the flame speed and promote flame propagation to the unburned zone in the combustion chamber. Combining low-temperature hydrogen with the passive pre-chamber can achieve high engine thermal efficiency and power while significantly reducing leakage. With the ignition timing set at 18 °CA before the top dead center, the indicated thermal efficiency reached 39.49% and the indicated mean effective pressure peaked at 0.77 MPa. Compared to the original engine, fresh mixture leakage through spark plug cavities and adjacent chambers was reduced by 72.13% and 78.79%, respectively.

A study of geothermal hydraulic fracture surface morphology and heat transfer characteristics

This study analyzed the morphological characteristics of heat-treated granite fracture surfaces subjected to cyclic hydraulic fracturing (CHF) and traditional hydraulic fracturing (THF). The differences in heat transfer characteristics between THF and CHF fracture surfaces were compared using a three-dimensional numerical heat transfer model. The heat transfer properties of CHF fracture surfaces were investigated under varying injection parameters, and corresponding mathematical models were constructed. It was found that the roughness of CHF fracture surfaces was greater than that of THF, and the heat transfer performance was superior. Specifically, the overall heat transfer coefficient (OHTC) for the C1-C3 fracture surfaces increased by 55.71, 63.40, and 75.91 W/m2/K, respectively, compared to the T1-T3 fracture surfaces. The average outlet temperature (Tout) of the CHF fracture surfaces increases with higher injection flow rates and decreases with higher injection temperatures. The OHTC and local heat transfer coefficient (LHTC) exhibit opposite trends. Specifically, injection flow rates have a quadratic polynomial relationship with the Tout and a logarithmic relationship with OHTC. Additionally, the Tout of the CHF fracture surface shows a linear positive correlation with injection temperature, while OHTC has a linear negative correlation.

High-resolution 3D hydrodynamic modeling and comprehensive assessment of tidal current energy resources

As a clean and renewable resource, tidal current holds significant development potential. However, accurately assessing tidal current energy resources has been a persistent challenge. This study proposes a comprehensive assessment method using a small-scale, high-precision, multi-criteria three-dimensional hydrodynamic model to assess resource reserves applied to the Zhairuoshan Waterway. The hydrodynamic model was employed to simulate critical parameters such as tidal level, flow velocity, and flow direction. Multiple statistical indicators were used to evaluate the model's accuracy, showing consistency. The study analysed the flow speed distribution over a complete cycle, revealing an average flow speed of 1.51 m/s, with a maximum speed reaching 3.83 m/s. The generally high flow speeds within the waterway, coupled with the stability of the tidal current, indicate the significant resource potential of the study area. A quantitative analysis of the spatial distribution of tidal current energy was conducted using energy flux density, and the results showed that high energy density areas are widely distributed. Furthermore, the theoretical tidal energy resources of the waterway were calculated, showing that the maximum resource reserves could reach 9.98 MW at the selected cross-sections. Coupled with the analysis of unit-width energy flux, the high-potential areas within the waterway were further identified.

Three-dimensional peridynamic modeling of damage and penetration in composite plates exposed to localized explosive blasts

Localized failures in composites can lead to catastrophic consequences in some vehicles and systems, such as airplanes and submarines. The paper presents a new three-dimensional (3D) peridynamic model to explore the localized explosive effects on composite plates. The study utilizes the peridynamic method to simulate fractures and deformations in composite plates when exposed to localized explosive blasts. Accurate prediction of composites' performance during explosive blast events is crucial in the design process to avoid the deadly effects of their failures. This study highlights the following novelties: (1) We present, for the first time, a novel 3D mesh-free model to simulate the fracture and damage behavior of composite plates when exposed to explosive blasts; (2) The adopted numerical modeling technique enables highly efficient simulations of fractures and failures in composites when compared with other mesh-based numerical models; (3) We introduce a new mathematical framework to reflect the explosive pressure loads through different composite layers; (4) The study provides an accessible and efficient tool for engineers and researchers to enhance the design of composites in several industries instead relying on limited-access commercial software packages. In addition to the previous novelties, the paper presents a new parametric study that investigates the performance of several composite plates, such as titanium-aramid and aluminum-aramid composites, in explosive blast scenarios. Moreover, the roles of explosive mass and plate thickness in the failure mechanisms of composites are examined.

3D package thermal analysis and thermal optimization

3D packaging mainly uses TSVs (Through Silicon via) to vertically interconnect multiple chips, achieving the purpose of signal transmission and electrical connection. As a popular advanced packaging method, its research is of great significance. Although stacked chips can achieve stronger performance in smaller spaces, they can also cause a series of reliability issues, among which thermal stress and warping due to differences in the thermal expansion coefficients of materials can even lead to chip failure. Therefore, it is highly valuable to simulate and analyze the entire 3D packaging model.In this study, the thermal stress and deformation of the whole three-dimensional package model were simulated by finite element analysis. The results showed that there were significant stress and deformation effects at the joint of the TSV structure at normal temperature, and the stress and deformation reached 209.99MPa and 0.0018519mm, respectively. After that, the temperature of the double-sided package system containing 3D package under electrothermal coupling conditions was optimized by heat dissipation design, which verified the ‘quantity first’ scheme of heat dissipation fins and reduced the temperature by 40%.

Experimental and numerical investigation on the failure behaviors of laminates with various shaped cutouts under tensile loading

Composite structures in aircraft often contain many cutouts, and failure of these structures is prone to occur near the edge of cutouts. Therefore, the failure behaviors of laminates with various shaped cutouts should be carefully investigated. To this end, experiments and numerical simulations are employed to investigate this issue. The tensile tests of composite laminates with circular, elliptical, square, and rectangular cutouts were carried out. Digital image correlation was utilized to capture the strain fields around the cutout. Combining the strain failure criterion and the modified exponential damage variables a three-dimensional progressive damage model was established, which can accurately predict the peak loads of composite laminates with diverse cutouts. All errors between the experimental and numerical results are less than 10 %. The experimental and numerical results indicate that the shape of the cutout has a great influence on the peak loads. As the ratio of major axis to minor axis (a/b) is increased from 1 to 5, peak loads obviously increase for the laminates with elliptical cutouts. Experimental results show that the average peak load of the laminates with elliptical cutout (a/b = 4) is 20.0 % higher than that of the laminates with circular cutout (a/b = 1). The dispersed distribution of high strains near the edge of the cutout results in an improvement of bearing capacity. As the ratio of length to width (l/w) in rectangular cutouts is increased from 0.5 to 3, peak loads are also improved obviously, because experimental results show that the average peak load of the laminates with rectangular cutout (l/w = 0.5) is 12.3 % lower than that of the laminates with square cutout (l/w = 1). Therefore, to improve the peak loads, it is very necessary to select the proper ratios of a/b and l/w. The above conclusions can serve as a reference for the design of composite structures.