Irregular Geometry Research Articles

Modeling of partially oriented spring-exchange magnetic composites

PurposeThe presentation refers to simulations of magnetization processes of the spring-exchange magnetic composites containing magnetically soft and ultra-high coercive phases. In particular, the aim of this study is to investigate the possibility of reducing expensive rare earth (RE) in the so-called neodymium magnets and improving their efficiency.Design/methodology/approachIn order to model hysteresis loops, a special disorder-based Monte Carlo procedure, suitable for irregular geometry of the composites, was applied. The chosen system parameters were defined in order to model Nd2Fe14B/Fe composites.FindingsThe results suggest potential for optimizing hard magnetic composites. Magnetization curve parameters are sensitive to grain coupling and easy magnetization axis ordering. Strong coupling for a single-phase hysteresis loop is unachievable for grains above a certain size, i.e. found to be a few hundred nanometers. Considering these factors and their interdependencies, it’s possible to enhance the |BH|max parameter or reduce the RE content.Research limitations/implicationsThe research was carried out using computer simulations, which by their nature are only approximations of physical processes. The next stage of research is to produce the described composites and test their actual properties.Practical implicationsThe research enhances permanent magnets, boosting efficiency in technologies like wind turbines and electric motors, indirectly benefiting the environment. It also reduces RE elements in magnets for environmental, economic and political gains.Originality/valueThe unique approach is to consider the random orientation of the magnetic anisotropy of the hard magnetic grains, which is close to real powder composites. The results provide valuable guidance for the production process of permanent magnets.

Upside-down Rayleigh-Marchenko: A practical redatuming scheme for seabed seismic acquisitions

Ocean-bottom seismic plays a crucial role in resource exploration and monitoring. However, despite their undoubted potential, the use of coarse receiver geometries poses challenges to accurate wavefield redatuming. This in turn affects the quality of subsequent imaging and reservoir characterization products. We develop a reciprocal version of the Rayleigh-Marchenko (RM) method, called the upside-down RM method, in which all spatial integrals are performed over the (usually much better-sampled) source carpet; this results in a redatuming scheme that naturally accommodates irregular and sparse receiver geometries. Our method requires the availability of multicomponent receivers and either dual sources or a preprocessing step of model-based source deghosting and uses only the down-going component of the receiver-side wavefield; as such, it can be interpreted as a full-wavefield extension of the mirror migration method commonly used in seabed settings. Two synthetic examples are used to showcase the effectiveness of our method, starting from the ideal scenario of finely and regularly sampled source and receiver arrays and subsequently considering different levels of decimation for the receiver geometry. Migrated images as well as common-angle gathers reveal that our method can be used to produce structural and amplitude-friendly imaging outputs with minimal data preprocessing.

Solar Species: Energy Optimization of Urban Form Through an Evolutionary Design Process

This paper proposes design guidelines to enhance energy efficiency and energy generation potential in active solar buildings. Additionally, it presents a variety of optimized urban forms characterized by attributes such as shape, layout, and number of buildings on the plot. These urban configurations are classified into solar species, each associated with a distinct range of high passive and active solar potential. These results were achieved by developing and applying a simulation-driven, multi-objective optimization technique for the early-stage design of a residential building cluster in a temperate climate. This method leverages both passive and active energy indicators, employing a genetic algorithm to identify optimal forms that maximize active solar potential while also minimizing operational energy demand. The approach utilizes a parametric modelling routine that relies on vertical cores and horizontal connections to produce design iterations featuring irregular geometry, while ensuring structural continuity and means of egress. The findings reveal a significant variability in onsite energy generation, with optimized solutions differing by a factor of 2.5 solely based on shape, underscoring the critical role of active solar potential. Taken together, these results hint at the descriptive and predictive capabilities of these solar species, making them a promising heuristic model for characterizing urban form in relation to energy performance.

LUOJIA Explorer: An Auto-UAV for Unexposed Space Exploration

Abstract. With the advancement of technology, unexposed spaces have emerged as a new type of strategic area, attracting significant attention from researchers. These spaces often present complex environments, such as extreme lighting variations, irregular geometries, and the lack of external positioning signals, making human entry hazardous. Fortunately, advancements in robotics and artificial intelligence have enabled unmanned systems to mitigate these challenges, allowing for safer exploration of unexposed spaces. UAVs, as vital unmanned system platforms, are extensively used across various industrial scenarios and are particularly effective for detecting unexposed spaces. To facilitate automated exploration of these areas, we propose the autonomous UAV system, LUOJIA Explorer. Equipped with a LiDAR sensor, data transmission module, and external anti-collision devices to protect the aircraft, LUOJIA Explorer is designed for effective unexposed space detection. We have integrated a laser point cloud positioning and mapping subsystem, along with a planning and control subsystem, into the LUOJIA Explorer. Through both simulation and actual experiments, the Luojia Explorer has demonstrated the capability to achieve stable flight based on self-positioning in unexposed spaces, with an exploration efficiency of 88.83 m3/s.

A New Method for Determining the Safety Distance Between Irregular Karst Cave and Circumferential Shield Tunnel

ABSTRACTWhen a shield tunnel passes through a karst area, the water‐filled cave can easily make the surrounding rock metamorphic, resulting in water inrush, ground collapse, and shield machine failure and other engineering hazards. Natural cavities have a significant degree of geometric irregularity due to groundwater alteration and soluble rock erosion. Considering the difficulties in describing the shape of a natural irregular cavity, circular, rectangular, and elliptical geometries have been simplified in most related studies. Based on the upper bound theorem of limit analysis, we established a three‐dimensional failure model including the karst caves located directly above and below the circumferential side of the tunnel. Then, we deduced the corresponding analytical solution of the critical safety distance (CSD). Furthermore, the effects of rock mass parameters, cave parameters, and geometric parameters on the CSD were analyzed. Then we designed the numerical simulation considering the irregular geometry shape at the circumferential side of tunnel using the Fourier descriptors. In addition, we estimated the CSDs for two failure models using the revised dichotomy and failure criterion. The findings demonstrated a quantifiable association between CSD and Fourier descriptors of irregular cave shape, resulting in the development of a CSD prediction model. These test results can provide a theoretical foundation and direction for predicting water inrush caused by the constrained irregular cave.

A Review of the Homogenized Lattice Boltzmann Method for Particulate Flow Simulations: From Fundamentals to Applications

The homogenized lattice Boltzmann method (HLBM) has emerged as a flexible computational framework for studying particulate flows, providing a monolithic approach to modeling pure fluid flows and flows through porous media, including moving solid and porous particles, within a unified framework. This paper presents a thorough review of HLBM, elucidating its underlying principles and highlighting its diverse applications to particle-laden flows in various fields as reported in literature. These include studies leading to new fundamental knowledge on the settling of single arbitrarily shaped particles as well as application-oriented research on wall-flow filters, hindered settling, and evaluation of the damage potential during particle transport. Among the strengths of HLBM are its monolithic approach, which allows seamless simulation of different fluid-solid interactions, and its ability to handle arbitrary particle shapes, including irregular and concave geometries, while resolving surface interactions to capture local forces. In addition, its parallel scheme based on the lattice Boltzmann method (LBM) results in high computational efficiency, making it suitable for large-scale simulations, even though LBM requires small time steps. Important future development needs are identified, including the addition of a lubrication force correction model, performance enhancements, such as support for hybrid parallelization and GPU, and the extension of compatible contact models to accommodate concave shapes. These advances promise expanded capabilities for HLBM and broader applicability for solving complex real-world problems.

How Irregular Geometry and Flow Waveform Affect Pulsating Arterial Mass Transfer.

Alzheimer's disease is a progressive degenerative condition that has various levels of effect on one's memory. It is thought to be caused by a buildup of protein in small fluid-filled spaces in the brain called perivascular spaces (PVS). The PVS often takes on the form of an annular region around arteries and is used as a protein-clearing system for the brain. To analyze the modes of mass transfer in the PVS, a digitized scan of a mouse brain PVS segment was meshed and used for computational fluid dynamics (CFD) studies. Tandem analyses were then carried out and compared between the mouse PVS section and a cylinder with commensurate dimensionless parameters and hydraulic resistance. The geometry pair was used to first validate the CFD model and then assess mass transfer in various advection states: no-flow, constant flow, sinusoidal flow, sinusoidal flow with zero net solvent flux, and an anatomically correct asymmetrical periodic flow. Two mass transfer situations were considered, one being a protein build-up and the other being a protein blend-down using a multitude of metrics. Bulk arterial solute transport was found to be advection-controlled. The consideration of temporal evolution and trajectories of contiguous protein bolus volumes revealed that flow pulsation was beneficial at bolus break-up and that additional local wall curvature-based geometry irregularities also were. Using certain measures, local solute peak concentration blend-down appeared to be diffusion-dominated even for high Peclet numbers; however, bolus size evolution analyses showed definite advection support.

System modeling and fuzzy adaptive PI sliding-mode control of a novel ship-mounted cable-based bulkhead cleaning robot

Ship cleaning poses significant risks and consumes considerable time, primarily due to the irregular hull surface geometry and the unpredictable ship motion induced by wave excitation. To address this challenge and achieve efficient, autonomous cleaning, a spatial variable structure cable-based bulkhead cleaning robot (SC-R) is proposed. Unlike traditional cable-driven parallel mechanisms (CDPMs), SC-R operates in a non-inertial frame, whereby its motion is subject to continuous and unpredictable ship motion. Consequently, SC-R exhibits intricate dynamic characteristics, posing a significant hurdle for controller design. To solve this problem, a sliding-mode controller is proposed for SC-R. Specifically, the dynamic model of SC-R, which includes ship motion and various disturbing forces, is systematically established using the Newton-Euler method. Furthermore, a fuzzy adaptive PI sliding-mode controller (FAPI-SMC) is specifically proposed to enhance the convergence speed and robustness of SC-R. The stability of the closed-loop system is analyzed using Lyapunov theory, and the tracking error is proved to be eventually bounded. Finally, the availability of this theory is confirmed by simulation and experiment. It is shown that FAPI-SMC can achieve a satisfactory control effect in practice.

Comparative analysis between continuous and discontinuous methods for the assessment of a cultural heritage structure

AbstractIn an era marked by the urgent need to ensure the safety of existing buildings according to current standards, evaluating the stability of masonry structures against hazard events has become a significant challenge. Despite the versatility and durability of masonry, structural assessments are hampered by factors such as limited information on material properties, irregular geometries, and ageing. To address this issue, numerous modelling techniques have been developed, supported by extensive scientific literature. However, significant factors related to the case study replication, such as the geometric complexity, the mechanical behaviour of masonry, the loading applications, contribute to the challenges associated with modelling procedures, including computational time, discretization procedures, and step incrementation. This paper critically discusses the most innovative modelling approaches. Specifically, it aims to compare the efficiency of the Distinct Element (discontinuous) Methods and the Finite Element (continuous) Method, both applied to the numerical simulation of a case study structure severely damaged by the 2016 Central Italy earthquake under lateral loading conditions. The continuous method is analysed using Midas FEA NX©, while the discontinuous methods are studied using 3DEC© and LMGC90© software, each with different contact conditions. Finally, the investigation highlights the main advantages and disadvantages of each method. In particular, the discontinuous method demonstrates reliability in accurately replicating failure patterns, whereas the continuous method allows for a faster model setup, making it suitable for preliminary studies on structural dynamics.

Graph-based diffusion model for fast shower generation in calorimeters with irregular geometry

Denoising diffusion models have gained prominence in various generative tasks, prompting their exploration for the generation of calorimeter responses. Given the computational challenges posed by detector simulations in high-energy physics experiments, the necessity to explore new machine-learning-based approaches is evident. This study introduces a novel graph-based diffusion model designed specifically for rapid calorimeter simulations. The methodology is particularly well-suited for low-granularity detectors featuring irregular geometries. We apply this model to the ATLAS dataset published in the context of the Fast Calorimeter Simulation Challenge 2022, marking the first application of a graph diffusion model in the field of particle physics. Published by the American Physical Society 2024

Fractal dimension and lacunarity measures of glioma subcomponents are discriminative of the grade of gliomas and IDH status.

Since the overall glioma mass and its subcomponents-enhancing region (malignant part of the tumor), non-enhancing (less aggressive tumor cells), necrotic core (dead cells), and edema (water deposition)-are complex and irregular structures, non-Euclidean geometric measures such as fractal dimension (FD or "fractality") and lacunarity are needed to quantify their structural complexity. Fractality measures the extent of structural irregularity, while lacunarity measures the spatial distribution or gaps. The complex geometric patterns of the glioma subcomponents may be closely associated with the grade and molecular landscape. Therefore, we measured FD and lacunarity in the glioma subcomponents and developed machine learning models to discriminate between tumor grades and isocitrate dehydrogenase (IDH) gene status. 3D fractal dimension (FD3D) and lacunarity (Lac3D) were measured for the enhancing, non-enhancing plus necrotic core, and edema-subcomponents using preoperative structural-MRI obtained from the The Cancer Genome Atlas (TCGA) and University of California San Francisco Preoperative Diffuse Glioma MRI (UCSF-PDGM) glioma cohorts. The FD3D and Lac3D measures of the tumor-subcomponents were then compared across glioma grades (HGGs: high-grade gliomas vs. LGGs: low-grade gliomas) and IDH status (mutant vs. wild type). Using these measures, machine learning platforms discriminative of glioma grade and IDH status were developed. Kaplan-Meier survival analysis was used to assess the prognostic significance of FD3D and Lac3D measurements. HGG exhibited significantly higher fractality and lower lacunarity in the enhancing subcomponent, along with lower fractality in the non-enhancing subcomponent compared to LGG. This suggests that a highly irregular and complex geometry in the enhancing-subcomponent is a characteristic feature of HGGs. A comparison of FD3D and Lac3D between IDH-wild type and IDH-mutant gliomas revealed that mutant gliomas had ~2.5-fold lower FD3D in the enhancing-subcomponent and higher FD3D with lower Lac3D in the non-enhancing subcomponent, indicating a less complex and smooth enhancing subcomponent, and a more continuous non-enhancing subcomponent as features of IDH-mutant gliomas. Supervised ML models using FD3D from both the enhancing and non-enhancing subcomponents together demonstrated high-sensitivity in discriminating glioma grades (~97.9%) and IDH status (~94.4%). A combined fractal estimation of the enhancing and non-enhancing subcomponents using MR images could serve as a non-invasive, precise, and quantitative measure for discriminating glioma grade and IDH status. The combination of 2-hydroxyglutarate-magnetic resonance spectroscopy (2HG-MRS) with FD3D and Lac3D quantification may be established as a robust imaging signature for glioma subtyping.

A High-Precision Inverse Finite Element Method for Shape Sensing and Structural Health Monitoring

In the contemporary era, the further exploitation of deep-sea resources has led to a significant expansion of the role of ships in numerous domains, such as in oil and gas extraction. However, the harsh marine environments to which ships are frequently subjected can result in structural failures. In order to ensure the safety of the crew and the ship, and to reduce the costs associated with such failures, it is imperative to utilise a structural health monitoring (SHM) system to monitor the ship in real time. Displacement reconstruction is one of the main objectives of SHM, and the inverse finite element method (iFEM) is a powerful SHM method for the full-field displacement reconstruction of plate and shell structures. However, existing inverse shell elements applied to curved shell structures with irregular geometry or large curvature may result in element distortion. This paper proposes a high-precision iFEM for curved shell structures that does not alter the displacement mode of the element or increase the mesh and node quantities. In reality, it just modifies the methods of calculation. This method is based on the establishment of a local coordinate system on the Gaussian integration point and the subsequent alteration of the stiffness integration. The results of numerical examples demonstrate that the high-precision iFEM is capable of effectively reducing the displacement difference resulting from inverse finite element method reconstruction. Furthermore, it performs well in practical engineering applications.

Effective prediction of drug transport in a partially liquefied vitreous humor: Physics-informed neural network modeling for irregular liquefaction geometry

As the medium for intravitreal drug delivery, the vitreous body can significantly influence drug delivery because of various possible liquefaction geometries. This work innovatively proposes a varying-porosity approach that is capable of solving the pressure and velocity fields in the heterogeneous vitreous with randomly-shaped liquefaction geometry, validated with a finite difference model. Doing so enables patient-specific treatment for intravitreal drug delivery and can significantly improve treatment efficacy. A physics-informed neural network (PINN) model is also established for the simulation, and three cases are used for validation. Despite limited information, the PINN model, together with the varying-porosity approach, captured fluid and drug transport in the partially liquefied vitreous. This opens the possibility for optimizing intravitreal drug delivery based on ultrasonography in clinical practice.

Application of Mg-MOF-loaded gelatin microspheres with osteogenic, angiogenic, and ROS scavenging capabilities in bone defect repair

The management of bone defects, particularly those with irregular geometries resulting from osteoporotic fractures, remains fraught with challenges. Microspheres have emerged as a promising vehicle for tissue engineering, distinguished by their controlled release, safety, and ease of application. Various bioactive components are integrated into microspheres to improve their performance. Metal-organic frameworks, formed from metal ions interconnected by organic ligands, are increasingly utilized in tissue engineering. Specifically, magnesium-based MOFs are notable for their broad applicability; Mg2+ ions are instrumental in bone reconstruction and repair, facilitating osteogenesis, angiogenesis, antibacterial effects, and anti-inflammatory properties. Mg-MOF was synthesized using magnesium chloride and gallic acid, and it was incorporated into gelatin microspheres to create Gel@Mg-MOF composite microspheres. Leveraging gelatin's biocompatibility, controlled release, and biodegradability, the composites' biocompatibility was evaluated through toxicity and adhesion assays. Moreover, the osteogenic and angiogenic potentials of the Gel@Mg-MOF microspheres were assessed, alongside their capacity for ROS scavenging. Results suggest that controlled Mg2+ release from Gel@Mg-MOF microspheres promotes osteogenic activity in RBMSCs and enhances angiogenic potential in HUVECs. Additionally, the gallic acid-containing composite microspheres exhibited antioxidative properties. Collectively, the findings suggest that Gel@Mg-MOF microspheres could provide effective support for bone defect repair, with potential for clinical deployment.

Numerical model of asphaltene deposition in vertical wellbores: Considerations of particle shape and drag force

Asphaltene deposition and plugging are common phenomena during crude oil production, significantly reducing production efficiency. Understanding the deposition behavior of asphaltene particles in vertical wellbores, particularly in relation to drag force interactions and settlement velocity, is imperative to mitigate these issues. Existing empirical models often fail due to their inherent inaccuracies and neglect of asphaltene particles' irregular shapes. This work established a quantitative method to describe irregular geometries of asphaltene particles. Shape coefficient, ∅, and shape coefficient influence factor, θ, are used to assess the impact of particle shape on the drag force coefficient and settling velocity. Experimental results from sedimentation experiments reveal particles with smaller shape coefficients encounter greater flow resistance and higher drag force coefficients. Moreover, the impact of shape coefficient on the drag coefficient gradually decreases as the Reynolds number increases. Based on these experimental findings, distinct models for the drag force coefficient and settling velocity of asphaltene particles are established, achieving a reduction in average error ranging between 2 % ∼ 25 % compared to existing models.

Compensating Acquisition Footprint for Amplitude-Preserving Angle Domain Common Image Gathers Based on 3D Reverse Time Migration

Angle domain common image gathers (ADCIGs) play a crucial role in seismic exploration, offering prestack underground illumination information that aids in validating migration velocity and conducting prestack amplitude versus angle (AVA) analysis for reservoir characterization. This paper introduces an innovative approach for compensating amplitude errors caused by irregular seismic acquisition geometries in ADCIGs. By incorporating an angle domain illumination compensation factor, the proposed method effectively modifies these errors, preserving the amplitude of seismic reflectivity in the prestack angle domain. The effectiveness of the proposed approach is validated through comprehensive tests conducted on synthetic and field data examples. The results demonstrate the capability of the method to enhance the quality of ADCIGs derived from 3D reverse time migration (RTM), yielding accurate and reliable amplitude preservation. While the illumination compensation factor assumes a vertically linear velocity model, the method holds promise for extension to more complex media and diverse migration techniques. This suggests its applicability and adaptability beyond the specific assumptions considered in this study. In conclusion, this paper presents an innovative angle domain illumination compensation factor that significantly improves the quality of ADCIGs by addressing amplitude errors arising from irregular seismic acquisition geometries. The experimental validation using synthetic and field data confirms the effectiveness of the proposed method within the context of 3D RTM. Furthermore, the technique holds potential for broader application in more complex subsurface scenarios and various migration methodologies.

Isogeometric modeling and vibro-acoustic analysis of flow-excited irregular cavity-plate-exterior space coupled system

The flow-induced noise has become an important noise source in marine sonar self-noise, which can adversely affect the normal operation of sonar. The marine sonar cabin is simplified as a cavity-plate-exterior space coupled system whose flow-induced vibro-acoustic characteristics are investigated in this paper. An isogeometric vibro-acoustic formulation is proposed in which the cavity with an irregular geometry is precisely described by adjusting the control points and corresponding weights. The flow-induced vibro-acoustic response is obtained by transferring the turbulent pressure data from computational fluid dynamics into the isogeometric vibro-acoustic model. Imposing turbulent pressure into the isogeometric control points is proposed to achieve this objective using a node-based interpolation method. The vibro-acoustic modeling is validated and compared with previous experimental results. These comparisons demonstrate that the developed formulation accurately predicts the vibro-acoustic characteristics of the fluid-excited coupled system. The influences of flow speed, acoustic medium, and cavity shape on flow-excited vibration and sound radiation are discussed. Results show a decrease in radiated acoustic power and radiation efficiency in the exterior space, and a shift in the plate-exterior space coupling modal frequency to lower frequencies when the cavity changes from convex to concave.

A novel meshless radial basis reproducing kernel particle approach for 3D thermo-mechanical analysis of mushy zone phase-change problems

This paper presents a three-dimensional thermo-elastoplastic computational model for the analysis of phase change problems involving the mushy zone. The model utilizes a novel meshless radial basis reproducing kernel particle approach, incorporating a high-order kernel that integrates Gaussian and cosine functions. An energy balance equation for the entire domain is formulated using the effective heat capacity method, based on the enthalpy formulation. The governing equations are discretized using the Galerkin weak form to compute thermal residual stresses, with essential boundary conditions enforced through the penalty method. Plastic deformation is characterized using the von Mises criterion with isotropic hardening, and the strain term resulting from temperature-dependent material properties is incorporated into the incremental solution process. Determination of the plastic strain increment is based on the Prandtl–Reuss flow rule. The accuracy and efficiency of the proposed meshless approach were rigorously evaluated through numerical examples encompassing two- and three-dimensional problems. The computational results were compared against available analytical and validated numerical solutions. This comprehensive assessment substantiated the robustness and precision of the developed technique. The case studies presented elucidate the capacity of the novel meshless model to effectively predict temperature distributions and residual stress fields within mushy zone phase change phenomena, accommodating both regular and irregular geometries under various boundary conditions. Notably, the model demonstrated consistent stability and high accuracy across the spectrum of simulated scenarios, thus underscoring its potential as a valuable tool for investigating complex phase change processes.

Subset simulation based simplified approach for pipeline with multiple irregular corrosion defects in time-dependent reliability analysis

Pipeline system plays an important role in the natural gas and petroleum transportation, and it is widely employed in the engineering application. However, the pipeline system is subjected to corrosion given the industry environment condition, or soil condition when it is buried. In this case, it is important to assess the remaining life of corroded pipeline. Consequently, it is important to predict the failure probability considering the corrosion growth over time and operating pressure. Nevertheless, the prediction of failure probability in corroded pipeline in not an easy task, due to the fact that a realistic corrosion usually has an irregular geometry, especially, when multiple irregular corrosion is involved in the analysis. To simplify the problem, this work presents a simplified procedure for time-dependent reliability analysis to predict the failure probability in pipeline with multiple irregular corrosion defects, considering two failure modes, the burst and leak mode. The approach is based on Subset Simulation and Weighted Depth Difference method, where the multiple irregular corrosion is treated by a discretization procedure and a weighting coefficient is evaluated in every discretization points. Then, this weighting coefficient is introduced into burst pressure assessment, which is employed by burst failure mode limit state function. In this work, the corrosion growth is modelled by power function corrosion model, and initial corrosion depth is generated randomly. The Subset Simulation is employed to evaluate the failure probability, where the Markov Chain Monte Carlo is adopted to evaluate the conditional probability and Metropolis-Hasting algorithm is employed to solve the problem. Finally, several scenarios with single and multiple irregular corrosion defects are analyzed to demonstrate the effectiveness of presented procedure.

Out-of-plane cross-angle bending stiffness of cross-laminated timber

The increasing use of cross-laminated timber (CLT) in construction worldwide can be attributed to its combination of sustainability, structural efficiency, biaxial strength and stiffness, short construction times, and architectural flexibility. However, when applied in free-form structures, CLT panels may exhibit irregular element geometries, resulting in deviations from their major or minor strength axes. The required out-of-plane cross-angle bending stiffness is not addressed by commonly used design methods. This study addresses this gap by examining the cross-angle bending stiffness of CLT panel segments using experimental, analytical, and numerical methods. Three different lay-ups (3-ply, 4-ply, and 5-ply) and five cross-angles (ranging from 0° to 90°) were tested under 3-point bending, demonstrating the nonlinear relation between cross-angle and out-of-plane bending stiffness. The lowest stiffness was observed for intermediate cross-angles and not when loaded along the minor strength direction. A proposed analytical model that combines the shear analogy with Hankinson's equation yielded adequate approximations. The model was verified by numerical simulations and then applied to predict the out-of-plane cross-angle bending stiffness of a wide range of CLT layups. This research provides valuable insights for working with CLT in complex geometrical designs, enhancing preliminary design.