Proposed Modeling Approach Research Articles

Matching decision support modeling frameworks to disease emergence stages and associated management objectives

AbstractWildlife disease management decisions often require rapid responses to situations that are fraught with uncertainty. By recognizing that management is implemented to achieve specific objectives, resource managers and science partners can identify an analysis technique and develop a monitoring plan to evaluate management effectiveness. For emerging infectious diseases, objectives may take several distinct forms, dependent on the perceived stage of disease emergence (i.e., pre‐epidemic, early outbreak, mid‐epidemic, and endemic), the expected rate of spread, and the anticipated effect of the disease on host populations. Identifying modeling techniques and metrics that are linked to management objectives will require early and consistent communication between managers and science partners. We link modeling approaches that can be used to forecast and evaluate the performance of intervention strategies with a range of disease management objectives. Our aim is to help scientists recognize alternative modeling approaches which may better align with different forms of disease management objectives, and to help managers evaluate the relevance of proposed modeling approaches to their specified objectives for disease management. Recognizing that disease management objectives can take different forms, and thus require different modeling approaches, can help wildlife disease response teams (i.e., natural resource managers, scientists, and stakeholders working collaboratively) better prepare and respond to disease threats.

Predicting the mechanical properties of semi-flexible pavement material with micromechanical modeling

Semi-flexible pavement (SFP) material is a composite comprising cement, coarse aggregates and asphalt mortar, which has complex mechanical properties. Traditional experimental methods struggle to accurately quantify the effect of each phase and their interfaces on the SFP's mechanical properties. Micromechanical modelling based on finite element method offers a promising solution. In this study, a new micromechanical model for SFP is proposed, idealizing the material by representative volume elements. SFP mesostructure is represented as a simplified five element composite consisting of cement, asphalt mortar, aggregate, pore and cement-asphalt mortar interface. Periodic boundary conditions are used to simulate an infinite repetitive structure within a finite computational domain. The resulting model allows evaluating the stiffness and damage resistance of SFP in a computationally efficient manner. This model is utilized to explore the mechanical properties of SFPs and the results are compared with the experimental findings. The results show that the model captures the uniaxial compressive strength and stiffness for all materials examined. The model is further used to evaluate the effect of properties of individual elements of SFP on its stiffness and strength. The feasibility of using the proposed modelling approach to optimize the material design of SFP is discussed.

Influence of corrosion on ultra-low cycle fatigue performance of steel butt-welded joints with various welding methods

Preferential corrosion of welded joints in steel structures has been observed in a wide range of scenarios and should receive enough attention. The current work focuses on the corrosion and ultra-low cycle fatigue (ULCF) behavior of low-alloy steel weld joints. Firstly, 1600 h neutral salt spray (NSS) tests were conducted on welded joints made by different welding methods, and then topography scanning of corrosion pits was carried out. It was found that the welded region is more susceptible to corrosion. Dynamic polarization curves of the welded joints were measured, and the results show that the self-corrosion potential of the welded region is lower than that of the base metal (BM) region, while the corrosion current density is higher than that of the BM region. Subsequently, cyclic tests were carried out on the corroded weld joints. The results show that corrosion can cause a maximum reduction of 11.79% in yield load and 20.87% in ultimate load of the welded joints. Corrosion has slight influence on the energy dissipation capacity of welded joints, but the maximum reductions in ULCF life could reach 77.31% due to corrosion. Fractography analysis further shows that secondary cracks, map cracks, and intergranular brittle fracture, apart from more common fatigue fracture, ductile fracture, and quasi-cleavage fracture, appear on the fracture surfaces. Supplementary numerical simulation was conducted to enable a better understanding of the failure processes. In the simulation, a geometric modeling method using topography scanning data of corrosion surface was proposed. By using the proposed modeling approach, together with Chaboche cyclic plasticity constitutive model and cyclic void growth model (CVGM) for capturing fracture behavior, the predicted results show an acceptable agreement with the experimental ones.

Methodology for International Transport Corridor Macro-Modeling Using Petri Nets at the Early Stages of Corridor Development with Limited Input Data

International transport corridors (ITCs) are intricate logistical networks essential for global trade flows. The effective modeling of these corridors provides invaluable insights into optimizing the transport system. However, existing approaches have significant limitations in dynamically representing the complexities and uncertainties inherent in ITC operations and at the early stages of ITC development when data are limited. This gap is addressed through the application of Evaluation Petri Nets (E-Nets), which facilitate the detailed, flexible, and responsive macro-modeling of international transport corridors. This paper proposes a novel methodology for developing E-Net-based macro-models of corridors by incorporating key parameters like transportation time, costs, and logistics performance. The model is scalable, enabling analysis from an international perspective down to specific country segments. E-Nets overcome limitations of conventional transport models by capturing the interactive, stochastic nature of ITCs. The proposed modeling approach and scalability provide strategic insights into optimizing corridor efficiency. This research delivers a streamlined yet comprehensive methodology for ITC modeling using E-Nets. The presented framework has substantial potential for enhancing logistics system analysis and planning.

Modeling the Geometry of Tree Trunks Using LiDAR Data

The effective development of digital twins of real-world objects requires sophisticated data collection techniques and algorithms for the automated modeling of individual objects. In City Information Modeling (CIM) systems, individual buildings can be modeled automatically at the second Level of Detail or LOD2. Similarly, for Tree Information Modeling (TIM) and building Forest Digital Twins (FDT), automated solutions for the 3D modeling of individual trees at different levels of detail are required. The existing algorithms support the automated modeling of trees by generating models of the canopy and the lower part of the trunk. Our argument for this work is that the structure of tree trunk and branches is as important as canopy shape. As such, the aim of the research is to develop an algorithm for automatically modeling tree trunks based on data from point clouds obtained through laser scanning. Aiming to generate 3D models of tree trunks, the suggested approach starts with extracting the trunk point cloud, which is then segmented into single stems. Subsets of point clouds, representing individual branches, are measured using Airborne Laser Scanning (ALS) and Terrestrial Laser Scanning (TLS). Trunks and branches are generated by fitting cylinders to the layered subsets of the point cloud. The individual stems are modeled by a structure of slices. The accuracy of the model is calculated by determining the fitness of cylinders to the point cloud. Despite the huge variation in trunk geometric forms, the proposed modeling approach can gain an accuracy of better than 4 cm in the constructed tree trunk models. As the developed tree models are represented in a matrix format, the solution enables automatic comparisons of tree elements over time, which is necessary for monitoring changes in forest stands. Due to the existence of large variations in tree trunk geometry, the performance of the proposed modeling approach deserves further investigation on its generality to other types of trees in multiple areas.

Simulating staff activities in healthcare environments: An empirical multi-agent modeling approach

The layout of the healthcare environment profoundly impacts healthcare efficiency, safety, employee satisfaction, and the sustainability of operations, mainly based on occupant behavior analysis. However, due to the increase in professionalism and interprofessional collaboration among healthcare practitioners and the complexity of the physical environment, existing research tools face challenges in describing and analyzing diverse occupant behaviors. This study aims to offer an empirically grounded multi-agent modeling approach as a research tool to simulate and reproduce occupant behavior within healthcare settings. Employing a design science research method, the proposed approach encompasses four stages: empirical data collection, development of behavioral rules, agent-based modeling, and validation. A continuous 24-h observational study involving doctors, nurses, and auxiliary staff within a trauma intensive care unit is conducted to demonstrate the development and application process. Results show that the proposed modeling approach achieves a simulation deviation of 8.31 % in individual walking distances and a 16.26 % deviation in overall staff spatial visitation frequency compared to real-world observations. We believe that using simple if-then rules to represent events and probability rules to describe other basic activities can simulate complex staff activities in a healthcare environment. Interdisciplinary expert evaluation acknowledged the utility of this approach. This study offers a comprehensive dataset of behaviors and contributes methodologically to evaluating the efficiency of built environment layouts. The innovation in this study lies in its scalability, extending from events and individuals to encompass the all staff in levels of modeling and validation, ensuring a consistent alignment with empirical data at each stage.

System identification and closed-loop control of laser hot-wire directed energy deposition using the parameter-signature-quality modeling scheme

Hot-wire directed energy deposition using a laser beam (DED-LB/w) is a method of metal additive manufacturing (AM) that has benefits of high material utilization and deposition rate, but parts manufactured by DED-LB/w suffer from a substantial heat input and undesired surface finish. Hence, regulating the process parameters and monitoring the process signatures to control the final quality during the deposition is crucial to ensure the quality of the final part. This paper explores the dynamic modeling of the DED-LB/w process and introduces a parameter-signature-quality modeling and control approach to enhance the quality of modeling and control of part qualities that cannot be measured in situ. The study investigates different process parameters that influence the melt pool width (signature) and bead width (quality) in single and multi-layer beads. The proposed modeling approach utilizes a parameter-signature model as F1 and a signature-quality model as F2. Linear and nonlinear modeling approaches are compared to describe a dynamic relationship between process parameters and a process signature, the melt pool width (F1). A fully connected artificial neural network is employed to model and predict the final part quality, i.e., bead width, based on melt pool signatures (F2). Finally, the effectiveness and usefulness of the proposed parameter-signature-quality modeling is tested and verified by integrating the parameter-signature (F1) and signature-quality (F2) models in the closed-loop control of the width of the part. Compared with the control loop with only F1, the proposed method shows clear advantages and bears potential to be applied to control other part qualities that cannot be directly measured or monitored in situ.

Practical stability criteria for discrete fractional neural networks in product form design analysis

In this paper, a neural network approach is suggested to the product design analysis. Namely, fractional-order neural network models are proposed as more flexible mechanism to study product form design. Since control and stability methods are fundamental in the construction and practical significance of a neural network model, appropriate controllers are designed and practical stability criteria are proposed for the fractional-order model under consideration. The stability and control analysis are based on the Lyapunov function method. Examples are elaborated to demonstrate the established results. The proposed modeling approach and the stability results are also applicable to numerous industrial design tasks.

Determining Digital Representation and Representative Elementary Volume Size of Broken Rock Mass Using the Discrete Fracture Network–Discrete Element Method Coupling Technique

Obtaining the digital characterization and representative elementary volume (REV) of broken rock masses is an important foundation for simulating their mechanical properties and behavior. In this study, utilizing the broken surrounding rock of the main powerhouse at the Liyang pumped storage power station as an engineering background, a three-dimensional fracture network generation program is first developed based on the theories of discrete fracture network (DFN) and discrete element method (DEM). The program is then integrated with a distinct element modelling platform to generate equivalent rock mass models for broken rock masses based on the DFN–DEM coupling technique. Numerical compression tests are conducted on cylindrical rock specimens produced using the proposed modelling approach, aiming to determining the REV size of the target rock masses at the Liyang power station. A comparative validation is also performed to examine the REV result obtained from the proposed approach, which adopted a REV measuring scale index (RMSI) to determine the REV size. Results indicate that the organic integration of DFN simulation techniques and DEM platforms can effectively construct numerical models for actual broken rock masses, with structural surface distributions statistically similar to the real ones. The results also show that the REV size of the investigated rock masses determined by the cylindrical rock models is 5 m × 10 m, which aligns with the size determined by the cubic rock models, as the target cubes show the same height as the cylindrical specimens. This study provides a model and parameter basis for the numerical calculation of the mechanical behavior of broken rock mass.

Evaluating the Field Emission Properties of N-Type Black Silicon Cold Cathodes Based on a Three-Dimensional Model.

Black silicon (BS), a nanostructured silicon surface containing highly roughened surface morphology, has recently emerged as a promising candidate for field emission (FE) cathodes in novel electron sources due to its huge number of sharp tips with ease of large-scale fabrication and controllable geometrical shapes. However, evaluating the FE performance of BS-based nanostructures with high accuracy is still a challenge due to the increasing complexity in the surface morphology. Here, we demonstrate a 3D modeling methodology to fully characterize highly disordered BS-based field emitters randomly distributed on a roughened nonflat surface. We fabricated BS cathode samples with different morphological features to demonstrate the validity of this method. We utilize parametrized scanning electron microscopy images that provide high-precision morphology details, successfully describing the electric field distribution in field emitters and linking the theoretical analysis with the measured FE property of the complex nanostructures with high precision. The 3D model developed here reveals a relationship between the field emission performance and the density of the cones, successfully reproducing the classical relationship between current density J and electric field E (J-E curve). The proposed modeling approach is expected to offer a powerful tool to accurately describe the field emission properties of large-scale, disordered nano cold cathodes, thus serving as a guide for the design and application of BS as a field electron emission material.

A modeling approach for the absorber of absorption heat pump systems

The study on the data-and-knowledge-driven modeling methods is very important for the digital twinning and the optimal control of absorption heat pump systems. For the purpose of obtaining an absorber model with high accuracy, low computational effort and less time-consuming for the absorption heat pump systems, a modeling method is proposed by combining the Simple Particle Swarm Optimization (SPSO) and the Wavelet Neural Network (WNN). The input-output structure of the model is presented by analyzing the operational principles of the absorber. In view of the complexity of the heat transfer and mass transfer processes inside the absorber, a single hidden layer WNN is employed as the internal structure of the model. The number of hidden layer nodes in the network model is determined by the trial-and-error method using the root mean square error and coefficient of determination. To overcome the drawback of WNN which can easily fall into the local optima during the error backpropagation process and improve the prediction accuracy of the model, the Morlet wavelet basis function and a SPSO algorithm are exploited respectively to replace the S-function of Neural Network and determine the optimal parameter values of the neural network (e.g. the weight, scaling factor, and translation factor, etc.). Experimental simulation results show the root mean square errors of the proposed model are 1.59 % and 2.21 % for the two outputs, respectively, which are smaller than the conventional WNN model. The proposed modeling approach effectively solves the problems of the BP neural network on easy falling into the local optimum and the slow convergence, which will be widely used in the process of the optimized operation control for heat pump systems.

FINITE ELEMENT MODELLING AND ANALYSIS OF FREE VIBRATIONS OF AXIALLY FUNCTIONALY GRADED BEAMS WITH NON-UNIFORM CROSS-SECTIONS

The finite element package Abaqus is used for modeling and analysis of free vibrations of axially functional graded beams with non-uniform cross-sections. Considerable attention has been paid to this aspect of the geometry, as it has a significant effect on the behavior of the beam as a structural component. User-defined material model subroutines (UMAT) were developed in a unified way for one- and three-dimensional models of the specified beams to provide numerical implementation of functional material gradients within each finite element. UMAT procedures were programmed in FORTRAN in the MS Visual Studio environment and compiled with the main program package using the Intel Fortran Compiler. In the procedures, material heterogeneity was assigned to each material integration point of appropriate standard one- and three-dimensional finite elements, eliminating the need to design graded finite elements via user-defined element subroutine. Frequencies and mode shapes of free vibrations of one- and three-dimensional axially functional graded beams with non-uniform cross-sections were found using the Lanczos method in Abaqus. An analysis of the accuracy and effectiveness of the proposed modeling approach was carried out, comparing the obtained results with data known in the literature. The presented modeling technique based on user-defined material subroutines provides valuable opportunities for scientists and engineers engaged in the dynamic analysis of structural components made of functionally gradient materials and having variable geometry along the axial direction. Keywords: axially functionally graded beams; non-uniform cross-section beams; free vibrations; graded finite element; Abaqus user defined subroutines

Integrating glass breakage models into CFD simulation to investigate realistic compartment fire behaviour

Glass failure affects the ventilation conditions in compartments, which particularly varies the fire development history in large compartments as the initial ventilation may become insufficient due to the existence of window glass. This paper proposes a ‘criterion-controlled’ model to simulate the interaction between glass failure and fire behaviour in CFD fire models. The proposed modelling approach has shown good performance in simulating the Shield Test, where the predicted cracking points and timeline of glass failure are almost identical to the test records. By implementing the glass failure model in the large compartment fire models adapted from the Kirby Test and the Malveira Test models, the influence of glass failure on the large compartment fires has been revealed. In the adapted Kirby Test model with glass panes, the case with window glass exhibits a much faster fire growth compared to the case with initially opened windows of no glass. When considering the window glass failure in Malveira Test model, the slow ‘travelling fire’ behaviour found in the full-scale test is changed to a fast spread fire and the window glass panels fail to provide the desired ventilation, which suggests the inadequacy of assuming complete openings at windows and it is necessary to consider the effect of window glass to large open-plan compartment fires in real modern buildings.

Insights into the nonlinear dynamic characteristics of a water turbine generator set considering the coupled effects of a fractional-order broadband foundation

The analysis of the coupled shaft-foundation system (CSFS) of a water turbine generator set is an extremely complicated task owing to its structural complexity and inherent nonlinear broadband dynamic characteristics. Thus, the coupling relationships of the CSFS remain unclear. The broadband vibration of the foundation subsystem has an evident influence on the vibration of the shaft subsystem of the unit; however, for the analysis of the dynamic characteristics of the water turbine generator, an overly complicated foundation can be reasonably simplified. To this end, this paper reports the development of novel energy-equivalent broadband modeling approaches to investigate the nonlinear vibration characteristics of CSFS. First, a relatively traditional integer-order lumped parameter model of the foundation subsystem was constructed, and its parameters were determined by fitting the response spectra obtained from an accurate hydropower house model. To improve the narrow-frequency limitation of the integer-order model and account for random disturbances, a novel fractional-order broadband modeling method is proposed. The advantage of the proposed fractional-order equivalent foundation model is that it can simultaneously reveal the broadband characteristics of complex structures at low frequencies of less than 1 Hz to high frequencies of hundreds of Hz with a single degree of freedom. Finally, coupled dynamic equations for the fractional-order CSFS model were derived and solved by considering the actions of various nonlinear factors and hydraulic pulsation excitation. A comparison of the dynamic responses of the CSFS with field test data demonstrated the effectiveness and practicability of the proposed modeling approaches. The results of the integer- and fractional-order CSFS models provide insights into the abundant dynamic laws and inner mechanisms of the nonlinear coupled dynamic system. Furthermore, they provided a reliable theory for the design and stability analysis of a hydropower unit, considering the varied vibrations of the coupled foundation.

Assessing human internal exposure to chemicals at different physical activity levels: A physiologically based kinetic (PBK) model incorporating metabolic equivalent of task (MET)

Physical activity levels have the potential to impact human internal exposure to environmental chemicals. However, the current lack of simple modeling approaches hinders the high-throughput screening of chemical exposure at different physical activity levels. To address this gap, this study proposes a straightforward model for assessing human internal exposure to chemicals. Our approach is based on the physiologically based kinetic (PBK) model and utilizes the metabolic equivalent of task (MET) to characterize internal exposure to chemicals at varying activity levels. To facilitate the application of this model, we have developed an Excel-based operation tool, allowing users to easily modify the MET value and generate simulation results for different physical activity levels. The simulation results demonstrate that as physical activity levels increase, the biotransfer factors (BTFs) of chemicals decrease, suggesting that higher physical activity levels reduce the bioaccumulation potential of chemicals. The intensified physical activity enhances the overall elimination kinetics of chemicals from the human body. However, the simulated concentrations of chemicals in the human body increase with higher physical activity levels, due to the significantly increased external exposure to chemicals, such as through inhalation. Our proposed modeling approach, along with the operational tool, enables high-throughput simulation of human chronic internal exposure to chemicals at different physical activity levels, where the findings can assist in screening chemicals for further health risk assessment. To accomplish this, the model incorporates certain assumptions and utilizes generic model input values. However, due to the intricate nature of the interaction between external and internal exposures at different physical activity levels, validating the simulation through experimental studies becomes challenging and is not performed in this study. For future studies, we recommend incorporating more MET-related physiological input variables, improving energy balance estimates, comprehending external exposure estimates, and conducting cohort studies to enhance and validate the proposed modeling approach.

A method to quantify the advantages of a variable valve train for CI engines

Today’s CI engines are subject to strict regulations of pollutant emissions and ambitious fuel consumption targets. Therefore, the interaction between the engine and the exhaust aftertreatment system (ATS) has become increasingly important. Numerous studies have shown that a variable valve train (VVT) improves the interaction between engine and ATS. However, most of these studies either quantify the advantage on a specific engine or only present complex CFD models, such that the results are not easily transferable to different engines. Thus, engine manufacturers cannot directly use these results to assess the advantage of various VVT strategies for their engines. In this paper, we propose a cycle-discrete cylinder model based on first principles which allows to simulate various VVT strategies. In contrast to present methods based on CFD, the proposed cylinder model can be realized with the equations presented. Furthermore, the model is identified with measurement data of an engine without a VVT. A separate engine, which is retrofitted with a fully VVT, is used to validate the proposed modeling approach. Using the identified model in combination with a mean-value model of the air path, we are able to simulate the effects of early intake valve closing, early exhaust valve opening, and cylinder deactivation for a complete CI engine that has no VVT installed. The model is then used to highlight the advantage of a VVT for two scenarios at part-load operation. At cold start, where the temperature of the ATS must be increased quickly, variable valve timing achieves higher enthalpy flows to the ATS while also lowering engine-out NOx emissions when compared to a standard engine strategy. If the ATS is at the operating temperature, cylinder deactivation achieves significantly higher enthalpy flows which prevents the ATS from cooling down. In addition, cylinder deactivation also lowers fuel consumption and engine-out NOx emissions.

Crashworthiness and dimensional stability analysis of zero Poisson's ratio Fish Cells lattice structures

The present article introduces Zero Poisson's Ratio (ZPR) Fish Cells metamaterial and investigates the effects of Poisson's ratio on the crashworthiness of Positive (PPR), Negative (NPR), and Zero Poisson's ratio lattice structures. High-fidelity Finite Element (FE) models of the proposed sandwich structures are built, based on identical domains for unit cells. Impact performances of lattice structures are addressed for low (2 m/s) and high (5 m/s) impact velocities in three orthogonal directions. The parameters investigated for crashworthiness include impactor's penetration depth, von Mises stress distribution, edges deformation and dimensional stability. Numerical results demonstrate that, unlike PPR and NPR models, the Fish Cells ZPR model possesses greater lateral stability and structural integrity with minimal edge deformations in all three directions. This leads to reduced lateral impact transfer to adjacent components and localised damaged zones, increasing the life span of structural components while reducing maintenance and repair downtime. Experimental analyses are conducted on the Fish Cells metamaterial through a drop tower test for demonstrating agreement with simulations and validation of the proposed modelling approach.

A Grey-Box Model of Laser Powder Directed Energy Deposition for Complex Scanning Strategy

Directed Energy Deposition using a laser based system (DED-LB) is a technology that enables the repair of components, cutting costs and saving resources when it comes to valuable and expensive components. Furthermore, this method can be used in the production of multi-material components. Despite its benefits, DED-LB process has limitations as well, particularly in terms of resolution, surface quality, and dimensional accuracy. Optimisation of scanning parameters and strategies, as well as the use of new materials, appears to be advantageous in this regard. Simultaneously, the use of methods such as numerical simulation expedites the process of becoming familiar with the technology, thereby improving optimization tasks. DED-LB process starts with one track; the research and optimisation of its properties are crucial, as they affect the outcome of the DED-LB component. In this research article, a novel grey-box model that exhibits the ability to precisely predict the temperature distribution and track dimensions was introduced. The proposed model adopts a numerical–analytical methodology, yielding outcomes at a comparatively reduced computational expense while upholding precision in the obtained results. The proposed modelling approach is based on the solution of the heat equation coupled with an iterative feedback loop to quantify the power losses and ensure energy and mass balance at the melt pool. The model is used to forecast the temperature field and track characteristics for a collection of linear tracks while varying the main process parameters in order to study their effect on track characteristics. In addition, this model can be used to predict the course of more complex trajectories; to illustrate this, an application in which both circular and square tracks are made was presented.

Perspectives of 3D Probabilistic Subsoil Modeling for BIM

Building information modeling (BIM) in the planning and construction of infrastructure projects, such as roads, tunnels, and excavations, requires the generation of comprehensive 3D subsoil models that encompass relevant geological and geotechnical information. Presently, this process relies on the deterministic interpolation of discrete data points obtained from exploratory boreholes and soundings, resulting in a single deterministic prediction. Commonly employed interpolation methods for this purpose include radial basis function and kriging. This contribution introduces probabilistic methods for quantifying prediction uncertainty. The proposed modeling approach is illustrated using simple examples, demonstrating how to use sequential Gaussian and Indicator Simulation techniques to model sedimentary processes such as erosion and lenticular bedding. Subsequently, a site in Munich serves as a case study. The widely used industry foundation classes (IFC) schema allows the integration of the model into the BIM environment. A mapping procedure allows transferring voxel models to the IFC schema. This article discusses the significance of incorporating uncertainty quantification into subsoil modeling and shows its integration into the BIM framework. The proposed approach and its efficient integration with evolving BIM standards and methodologies provides valuable insights for the planning and construction of infrastructure projects.

Modular Dynamic Modeling for On-Orbit Assembly of Large-Scale Space Structures

The large-scale space structure during on-orbit assembly is a time-varying system. The dynamic modeling problem of such incrementally increasing space structure is investigated, and a modular dynamic modeling approach is proposed in this paper. The dynamic model of each substructure is first established, and then, a database is designed to store substructure models, which is used for subsequent dynamic modeling in the assembly process. The fixed connection relationship between adjacent substructures is described by constraint conditions, which lead to the coefficient matrices of adjacent substructures being decoupled. The substructures are assembled in a given sequence, and then, the dynamic modeling, to describe the large-scale space structure on-orbit assembly, is gradually completed via using the proposed modeling approach. The numerical simulation is finally presented. The results demonstrate that the extra calculation resulting from the coefficient matrices coupling of adjacent substructures is avoided. Moreover, the proposed dynamic model can accurately describe the dynamic characteristics of the large-scale space structure during on-orbit assembly.