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Multibody Dynamics Using Quasi Energy and Momentum Conservative Algorithm Implemented with a Novel Four-Node Co-Rotational Quadrilateral Shell Element
1 Department of Civil Engineering, Zhejiang University, Hangzhou, China
2 Simulation & Design Development, Altair Engineering Inc., Shanghai, China
3 Aerospace Engineering, University of Illinois at Urbana-Champaign, Urbana, IL, USA
4 Department of Civil and Environmental Engineering, Imperial College London, London, UK
* Corresponding Author: Zhongxue Li. Email:
(This article belongs to the Special Issue: Advances in Modeling and Analysis of Complex Dynamics in Nonlinear Systems)
Computer Modeling in Engineering & Sciences 2026, 148(1), 7 https://doi.org/10.32604/cmes.2026.081240
Received 26 February 2026; Accepted 30 June 2026; Issue published 27 July 2026
Abstract
This paper proposes a computational theory for multibody dynamics based on a novel co-rotational formulation of a four-node quadrilateral shell element, designed to address nonlinear dynamic problems in flexible multibody systems undergoing arbitrarily large displacements and rotations. To circumvent the numerical inefficiency caused by the asymmetric tangent stiffness matrix in conventional co-rotational approaches, an incrementally additive vectorial rotational variable is introduced, which ensures the symmetry of the element’s tangent stiffness matrix in both global and local coordinate systems. The adoption of this vectorial rotational variable substantially improves computational efficiency and numerical stability. Hamilton’s principle is employed to derive the system’s dynamic equilibrium differential equation. For time integration, a generalized midpoint scheme coupled with a quasi energy–momentum conservative algorithm is used. This scheme ensures nearly exact conservation of the system’s total energy, linear momentum, and angular momentum in long-term simulations. The accuracy and stability of the proposed methodology are verified through four benchmark cases: an L-shaped plate, a ruler-shaped plate, a hemispherical shell with an 18° top opening, and a non-smooth shell-three intersecting plates. The results indicate that after the external loads are removed, the system’s total energy, total linear momentum, and total angular momentum are conserved with near-exact precision. The numerical results show excellent agreement with reference solutions from prior publications, and the computational process remains robustly stable.Keywords
The co-rotational framework, first introduced in [1–3], is widely recognized as an efficient strategy for geometrically nonlinear analysis, particularly for problems involving large displacements and rotations [4–9]. A significant advancement in this field was the Element-Independent Co-rotational (EICR) method [10,11], which facilitates the formulation of new co-rotational elements while preserving the vector transformation matrix. This advancement broadens the applicability of the approach to various element types. Crisfield and Moita [12] incorporated the concept of enhanced strain into the traditional co-rotational quadrilateral element, applying it to the analysis of two-dimensional solid beams, and subsequently extended the approach to three-dimensional solid elements [13–15]. Masud et al. [16,17] introduced an eight-node hexahedral element based on the EICR method, with the objective of modeling the bending-dominated geometrically nonlinear behavior of multilayer shells. Utilizing the natural mode method, Argyris et al. [18] developed a triangular shell element, in which the geometric stiffness matrix is derived by introducing disturbances into the equilibrium equations. Kan et al. [19] employed a streamlined two-step methodology: it first simplifies internal force calculations by omitting projector matrix terms, and then enforces element equilibrium via a global-frame correction, thereby eliminating complex local-global rotation coupling while providing a unified, simplified framework for diverse element types.
Despite its demonstrated element generality and high accuracy [20–24], the practical application of the co-rotational formulation is hindered by prohibitive computational costs, particularly in nonlinear transient analysis. This limitation primarily stems from the asymmetric tangent stiffness matrix inherent to most co-rotational formulations. Since conventional rotational degrees of freedom (DOF) are non-additive and non-commutative, the tangent stiffness matrix cannot be derived directly from the second-order partial derivatives of the strain energy functional with respect to nodal variables. This asymmetry not only increases the complexity of numerical computation but also consumes more computer resources, significantly reducing solution efficiency and thus limiting its engineering application to large-scale or complex dynamic problems.
To address the aforementioned issues, Li and Izzuddin [25,26] introduced vectorial rotational variables as nodal rotational DOFs, developing a series of novel co-rotational beam elements [27] and curved shell elements [28–32]. In computing the second-order partial derivatives of the strain energy functional, the differentiation order with respect to any nodal variables is commutative. This commutativity ensures that the derived element’s tangent stiffness matrix exhibits symmetry under both local and global coordinate systems, thereby improving computational performance and reducing storage needs. Furthermore, during the incremental solution procedure, the increments of the vectorial rotational variables can be updated by simple addition, eliminating the need to construct rotation matrices for vector updates and leading to more efficient computation. With the introduction of vectorial rotational variables, the potential of the co-rotational method for high-fidelity simulations and advanced engineering applications is further unlocked, promising broader adoption in the future.
Traditional time integration algorithms, particularly the Newmark family of methods [33–35], while unconditionally stable for linear problems, often exhibit energy drift and numerical instability in nonlinear regimes [36,37]. This is primarily due to significant geometric nonlinearities and strong coupling between rigid body motion and elastic deformation in such systems. These two difficulties challenge the linear assumptions within time steps and lead to instability and/or inaccuracies in long-duration simulations [38,39].
To address convergence issues in nonlinear dynamic analysis, Belytschko and Schoeberle [40] proposed using energy conservation as a stability criterion for time integration algorithms. Hughes et al. [41] introduced a constrained energy method, incorporating Lagrange multipliers into the trapezoidal integration scheme. Building on this work, Kuhl and Ramm [42] added momentum conservation as an additional constraint. However, this approach of enforcing energy conservation via Lagrange multipliers still suffers from convergence difficulties during computation. In contrast, the Energy–Momentum Conservation (EMC) algorithm proposed by Simo [36,43–45] exhibits unconditional stability for both linear and nonlinear dynamic problems. This method was later extended to beams [46–48], shells [49–52], and multibody systems [53–55], demonstrating remarkable stability even in long-duration simulations.
Nonlinear time integration methods that preserve energy conservation continue to evolve. Magisano et al. [49] improved upon Simo and Tarnow’s approach by redefining the midpoint internal force vector using (1) averaged endpoint stresses and (2) a time-averaged strain-displacement tangent operator. By retaining the Hamiltonian structure present in linear elastodynamic equations, Sánchez et al. [56] developed a symplectic Hamiltonian finite element method capable of conserving both energy and momentum. Schiebl and Romero [57] addressed the discretization of energy and momentum conserving time integration algorithms in atomic particle dynamics, with a specific focus on three key aspects: handling periodic boundary conditions, approximating three-body interactions, and extending the framework to functional potentials. Zhang et al. [58–60] enforced energy conservation as a constraint and enhanced the accuracy of the formulation by selecting three or more interpolation points for computing internal forces. To address the fundamental challenge of defining a reference frame in the deformed configuration for 3D Euler–Bernoulli beam theory, Santana et al. [61] proposed two innovative approaches based on Gram–Schmidt orthogonalization and displacement derivatives. These approaches were subsequently extended by Chhang et al. [62] to dynamic problems, yielding a stable time integration algorithm which strictly preserves both energy and momentum.
The solution scheme combining the co-rotational framework with the energy conserving algorithm can stably solve dynamic problems involving large displacements and rotations. Crisfield and Shi [20], by modifying the equations of motion and introducing correction coefficients, developed an approximately energy-conserving co-rotational algorithm for beam and rod structures, which significantly improves computational efficiency. Zhong and Crisfield [63] extended this algorithm to shell elements. Based on the co-rotational formulation, Almeida and Awruch [64] proposed an implicit time integration algorithm, which approximately conserves system energy and was successfully applied to analyze the nonlinear dynamic behavior of laminated composite shells undergoing large rotations. Yang and Xia [65,66] innovatively adopted a predictor-corrector iterative strategy combined with the generalized energy-momentum method, achieving efficient and stable solutions for co-rotational shell elements.
This paper proposes a new computational theory for multibody dynamics by employing a novel co-rotational formulation of the four-node quadrilateral shell element [29,31] and introducing a quasi-energy–momentum conserving algorithm [67]. In the proposed co-rotational formulation, the rotational variables at each node are represented by vector components. Because the sequence of differentiation is commutative when computing the second-order partial derivatives of the energy functional with respect to the nodal variables, the tangent stiffness matrix of the element exhibits symmetry. Assumed membrane and shear strains [29,68–70] are employed to mitigate the computational inaccuracies and inefficiencies arising from membrane and shear locking. Different from the exact energy–momentum conserving (EMC) algorithm [44], which constructs the strain energy functional using both strain and stress quantities, and replaces the mid-step strain values with the arithmetic mean of the endpoint strains while evaluates the stresses at the midpoint, our quasi-energy–momentum conserving algorithm directly evaluates the strain energy functional using the strain vectors. In our approach, all strain vectors, as well as their first and second partial derivatives with respect to the nodal variables, are computed via the arithmetic mean of the corresponding endpoint values. Furthermore, after discretizing the dynamic equilibrium differential equations, the term containing the first-order time derivatives of the rotational variables is incorporated into the equivalent load vector. This yields a symmetric mass matrix, consequently improving computational speed and reducing storage requirements. The proposed methodology ensures the nearly exact conservation of total energy, linear momentum, and angular momentum, while demonstrating excellent numerical stability throughout the computation.
The structure of this paper is organized as follows: Section 2 presents the co-rotational framework of the four-node quadrilateral shell element, where the element formulation is derived under local coordinate system. Section 3 establishes the dynamic equilibrium differential equations and employs a generalized midpoint interpolation method for incremental iterative solution. Section 4 validates the accuracy and stability of the developed multibody dynamics approach through four classic shell-structure examples. Section 5 provides the conclusions.
In Fig. 1,

Figure 1: Co-rotational framework of the element.
For the element in its initial configuration, the local coordinate system’s directional vectors are defined by the following equations:
where the vectors
where
Similarly, for the deformed configuration, these directional vectors of the local coordinate system can be obtained from the normalized vectors
where
In the global coordinate system, this four-node quadrilateral shell element has five or six DOFs per node—three for translation and two or three for rotation. The element’s nodal variable vector is:
where
In the local coordinate system, the four-node quadrilateral shell element has five DOFs per node, resulting in a total of 20 nodal variables:
where
In the initial configuration, the nodal coordinates
where
The nodal translational DOFs in the local coordinate system are obtained from the global-coordinate ones as:
where
For nodes of a smooth shell, or nodes of a non-smooth shell located away from the intersection, the relationship between the local and global components of the shell’s mid-surface normal vector is expressed as:
where
For nodes on the intersection line of non-smooth shells, three global rotational DOFs are employed per node. The relationship between the local and global components of the shell’s mid-surface normal vector is then given by:
where,
At a node on the intersection line of a non-smooth shell, the triad of orientational vectors
In the global coordinate system, the initial value of the nodal mid-surface normal vector is calculated from the cross product of the tangent vectors along the natural coordinate ξ-axis and η-axis at the node:
where “×” is the symbol of cross product,
For a node shared by adjacent elements in a smooth shell, or by elements in the same patch of a non-smooth shell, the mid-surface normal is the average of the element normals at that node:
where
In the local coordinate system, the quadrilateral element employs the Green-Lagrange strain measure suitable for shallow shells, which is split into the membrane strain
where
Taking the stationarity of the potential energy, the element’s internal force vector in the local coordinate system is obtained:
The element’s tangent stiffness matrix is obtained by computing the partial derivative of the internal force vector with respect to the nodal variables
where
It can be seen from Eqs. (15)–(17) that the element tangent stiffness matrix
3 Computational Theory of Multibody Dynamics for Four-Node Quadrilateral Shell Element
For a conservative system, the Hamiltonian H, which represents the total mechanical energy, is defined as the summation of the kinetic energy K and the total potential energy V, and the total potential energy V comprises the internal strain energy
Differentiating the Hamiltonian H with respect to time gives:
In the global coordinate system, the coordinates of any point within the element can be calculated by:
where,
The velocity is computed by taking the time derivative of the coordinates:
where
Integrating the nodal kinetic energy over the element volume yields the kinetic energy functional of the four-node quadrilateral shell element:
The time derivative of the element kinetic energy functional is calculated as:
For Node i away from intersections of shells, the first derivative of the normal vector
where
The second derivative of the normal vector
where:
Define the matrix
where:
Therefore,
For Node i located on an intersection line of non-smooth shells,
Write Eqs. (31) and (32) in the form of Eq. (30a,b); then we have:
where:
The expressions for the first-order partial derivatives in Eqs. (35) and (36) are given by Eqs. (B20a–k) and (B21a–c) on Pages 596–597 of the reference [32], while those for the second-order partial derivatives are given by Eq. (B47a–r) on Page 600 of the reference [32].
Substitute the time derivatives of the shell’s mid-surface normal vector at Node i into Eq. (23) and define the term
where
After rearrangement, the following expression is obtained:
where:
The definition of the element mass matrix
Thus, the first-order time derivative of the element kinetic energy is given by:
The mass matrices
The time derivative of the element strain energy functional is calculated as:
where
The total linear momentum
where
The total linear momentum and total angular momentum of the system are respectively expressed as:
The time derivative of the system’s total strain energy is obtained by assembling the time derivatives of the individual elemental strain energies:
where n represents all elements in the system;
The system’s external work accumulated from
The first-order time derivative of the system’s external work is:
Substituting the time derivatives of the system’s kinetic energy functional
The term
For
where
Based on the Newmark-β method, the nodal velocities
where
At the generalized midpoints
Considering Eq. (57), the first term of Eq. (58) can be rewritten as:
All variables at time
then, Eq. (58) can be rewritten as:
Eq. (61) can be solved using an incremental iterative method. The incremental equation is written as:
where, the iteration step is indicated by the superscripts
In Eq. (62),
where, the calculation of
As can be seen from Eqs. (15) and (16), (45a,b), and (63), the elemental tangent stiffness matrix
In Eq. (62), the terms
since both
Substituting Eq. (64) into Eq. (62) yields:
solving this equation obtains the incremental displacement
After each iteration step, update the equivalent stiffness and load terms using the newly obtained nodal variables.
An energy-based convergence criterion is employed. The ratio between the work done by the residual load at the
Convergence is attained once this ratio meets
To overcome membrane and shear locking problems, assumed membrane strain, assumed shear strain, and their first- and second-order partial derivatives with respect to the local nodal variables
In Eqs. (68) and (69), the values of
where,
To evaluate the computational accuracy and stability of the proposed theory, multi-body dynamics analyses are conducted on four benchmark problems: an L-shaped plate, a ruler-shaped plate, a hemispherical shell with an 18° opening at the top, and a non-smooth shell formed by three intersecting plates. The numerical results are subsequently compared with reference data from [66,72–77]. All parameters are reported in SI units.
The geometric description, mesh discretization and load configuration for the L-shaped plate are presented in Fig. 2. The plate has thickness

Figure 2: Mesh discretization and load configuration of the L-shaped plate.
The L-shaped plate is unconstrained along all boundaries and exhibits low stress levels, indicating that strength-related issues are negligible. Fig. 3a,b presents the time histories of the system’s total energy and linear momentum, respectively, for the 480-element model. After the external load is removed at t = 1 s, the results demonstrate excellent conservation properties. The total energy curve is compared with that reported by Lavrenčič and Brank [73], who employed a quadrilateral shell element based on a mixed variational formulation along with an energy–momentum conservation algorithm. The close agreement between the two sets of results validates the accuracy of the present numerical method.

Figure 3: Time-history curves for the L-shaped plate.
Fig. 3c presents the time history curves of the system’s angular momentum, which remain constant after the removal of the external load, thereby demonstrating the conservation properties of the proposed algorithm with respect to momentum. Fig. 3d compares the time history curves of the system’s total energy obtained respectively with three different element mesh densities (Ne = 21, 22, 23), demonstrating good convergence of the proposed algorithm.
Fig. 4a–c presents the time history curves of displacements at point S on the L-shaped plate along the X, Y, and Z axes, respectively, obtained using three different meshes. It is shown that even with a coarse mesh, very accurate results can be achieved.

Figure 4: Time-history curves of displacements at Point S for different element meshes.
Table 1 reports the values of the system’s total energy after load removal for five different element mesh densities (Ne = 21, 22, 23, 24, 25).

Defining the relative error as |EN−Eref|/Eref, where EN is the value obtained respectively from five different element meshes, Eref is the value obtained from the finest mesh of 7680 elements (Ne = 25). The convergence behavior is also evaluated on a log-log scale (Fig. 5). Linear regression yields a slope of −1.27, with a coefficient of determination R2 = 0.998, confirming a convergence rate of approximately 1.27 in the energy norm.

Figure 5: Convergence analysis in log-log scale.
After time

Figure 6: L-shaped plate’s motion trajectory.
Table 2 compares the CPU times for solving the discretized structural dynamic equations using two approaches for the assembled equivalent tangent stiffness matrix. The first approach exploits symmetry and sparsity via one-dimensional storage and LDLT decomposition; the second uses full-matrix storage and Gaussian elimination, ignoring these properties (as required for asymmetric matrices). The former requires substantially less CPU time than the latter, demonstrating that our proposed multibody dynamics formulation—which yields symmetric equivalent mass and global tangent stiffness matrices—is computationally far more efficient than conventional co-rotational formulations with asymmetric element-level tangent stiffness matrices.

The geometric description, mesh discretization and load configuration of the ruler-shaped plate are presented in Fig. 7. The plate has thickness

Figure 7: Mesh discretization and load configuration of the ruler-shaped plate.
A medium mesh density featuring an 8 × 60 element configuration (480 elements and 549 nodes) is employed in the simulation. The time-history curves of the system’s strain energy, kinetic energy, total energy, linear momentum, and angular momentum are presented in Fig. 8a–c, respectively. As illustrated, these quantities remain nearly exactly conserved throughout the simulation and show excellent agreement with the reference solutions reported by Kuhl and Ramm [72] and Yang and Xia [66].

Figure 8: Time-history curves for the ruler-shaped plate.
Table 3 presents the system’s total energy after load removal, computed using different mesh densities. From the coarse mesh to the medium and fine meshes, the maximum variation in the system’s total energy is only 0.03 J, corresponding to a relative error of approximately 0.012%. As the mesh density increases, the system’s total energy changes marginally and approaches a stable value, indicating that the numerical solution has essentially converged.

Fig. 9 presents the motion trajectory of the ruler-shaped plate within the time duration [0, 0.4 s], with consecutive frames interval of 0.01 s.

Figure 9: Ruler-shaped plate’s motion trajectory.
Table 4 compares the CPU times for solving the discretized structural dynamic equations of the ruler-shaped plate using two approaches for the assembled equivalent tangent stiffness matrix. The first approach exploits symmetry and sparsity via one-dimensional storage and LDLT decomposition; the second uses full-matrix storage and Gaussian elimination, ignoring these properties (as required for asymmetric matrices).

4.3 Hemispherical Shell with an 18° Opening at the Top
Fig. 10 illustrates the geometry, mesh discretization, and loading configuration of a hemispherical shell featuring an 18° opening at the apex. The shell is characterized by radius

Figure 10: Mesh discretization and load configuration of the hemispherical shell with an 18° opening at the top.
Fig. 11 presents the time-history curves of the system’s strain energy, kinetic energy, and total energy over the time interval [0, 2.5 s], along with a detailed view of the energy response within [0, 0.1 s]. As shown, following the removal of the external load at t = 0.03 s, the structure enters a state of free vibration. During this phase, kinetic energy and strain energy are continuously exchanged, while the total energy remains constant, thereby satisfying the conservation condition of the system.

Figure 11: Time-history curves of energy for the hemispherical shell with an opening: (a) [0, 2.5 s]; (b) [0, 0.1 s].
Fig. 12 illustrates the time-history curves of the displacements at Point A (X-direction) and Point B (Y-direction) over the interval [0, 2.5 s]. The maximum and minimum displacement magnitudes at both nodes are identical, and both displacement responses exhibit periodic variations. Furthermore, the simulation remains numerically stable throughout the entire time domain.

Figure 12: Time-history curves of the displacements at Point A and B of the hemispherical shell with an opening: (a) in X-direction at point A; (b) in Y-direction at point B.
Table 5 presents the system’s total energy after load removal with different mesh densities. As the discretization is refined, the total system energy asymptotically approaches a stable value.

Fig. 13 depicts the vibration sequence of the hemispherical shell within [0, 0.11 s], with snapshots taken at 0.01 s intervals.

Figure 13: Vibration sequence of the hemispherical shell with an opening.
Table 6 compares the CPU times for solving the discretized structural dynamic equations of the hemispherical shell with an opening using two approaches for the assembled equivalent tangent stiffness matrix. The first approach exploits symmetry and sparsity via one-dimensional storage and LDLT decomposition; the second uses full-matrix storage and Gaussian elimination, ignoring these properties (as required for asymmetric matrices).

The configuration of the three intersecting plates is shown in Fig. 14. The plate has thickness
where

Figure 14: Mesh discretization of three intersecting plates.
Fig. 15 presents the time-history curves of the system energy for the three intersecting plates. It is observed that the total energy of the system remains conservative after the removal of the external load. Zhang et al. [76] and Chróścielewski and Witkowski [77] also analyzed this model using a geometrically exact shell element formulation, implemented with an energy–momentum conserving algorithm. The total energy obtained in the present study is compared with that reported by Chróścielewski and Witkowski [77], thereby validating the accuracy of the current results.

Figure 15: Time-history curves of the system energy for the three intersecting plates.
The time-history curves of the linear and angular momenta for the three intersecting plates are presented in Fig. 16a,b, respectively. The total linear momentum exhibits near-exact conservation following load removal. The total angular momentum, however, while approximately conserved, exhibits small oscillations throughout its time history.

Figure 16: Time-history curves for the three intersecting plates: (a) Linear momentum; (b) Angular momentum.
Table 7 presents the total energy of the three intersecting plates upon load removal for different mesh densities.

Fig. 17 shows the motion trajectories of the three intersecting plates over a period of 14 s, with a time interval of 1 s between adjacent frames. The three intersecting plates undergo large displacements and large rotations in space.

Figure 17: Motion trajectories of the three intersecting plates.
Table 8 compares the CPU times for solving the discretized structural dynamic equations of the three intersecting plates using respectively two approaches for the assembled equivalent tangent stiffness matrix. The first approach exploits symmetry and sparsity via one-dimensional storage and LDLT decomposition; the second uses full-matrix storage and Gaussian elimination, ignoring these properties (as required for asymmetric matrices).

This paper has proposed a novel computational framework for multibody dynamics capable of analyzing the nonlinear dynamic behavior of flexible multibody systems undergoing large displacements and large rotations. The core contribution lies in integrating a co-rotational four-node quadrilateral shell element—formulated using incrementally additive vectorial rotational variables—with a quasi-energy–momentum conserving algorithm. This integration effectively resolves the issue of asymmetric tangent stiffness matrices inherent in conventional co-rotational formulations. Specifically, during the discretization of the dynamic equilibrium differential equations, the term in the inertial forces containing the first-order time derivatives of the rotational variables is incorporated into the equivalent load vector. This treatment yields a symmetric mass matrix and a symmetric equivalent tangent stiffness matrix, thereby enhancing computational performance and reducing storage requirements.
The accuracy and robustness of the proposed method have been validated through numerical simulations of four benchmark problems: an L-shaped plate, a ruler-shaped plate, a hemispherical shell with an 18° opening at the top, and a non-smooth shell-three intersecting plates. The numerical results show excellent agreement with data reported in the literature, demonstrating the method’s superior performance in computational accuracy, efficiency, and numerical stability.
In this work, the term “multibody systems” is not intended in its literal sense to refer exclusively to systems composed of multiple distinct bodies. Instead, it is adopted in a broader context to denote systems that are free of boundary constraints and capable of undergoing large translational motions as well as arbitrarily large rotations under dynamic loading. Such systems may comprise either a single body or multiple bodies. The present study specifically addresses smooth and non-smooth shell structures considered as single-body systems. In this regard, numerous related studies on multibody dynamics cited in the references below also primarily employ single-body systems as numerical examples. The extension of the proposed formulation to multibody dynamics problems involving non-conservative loads, or to multibody systems consisting of multiple bodies interconnected by joints, is left as a direction for future research.
Acknowledgement: None.
Funding Statement: This research was funded by National Natural Science Foundation of China (No. 11672266) and and the Fundamental Research Funds for the Central Universities, China (No. 343593).
Author Contributions: Zhongxue Li: Conceptualization (lead); Methodology (lead); Software (lead); Writing—original draft (supporting); Writing—review & editing (equal). Yu Peng: Investigation (supporting)—numerical examples; Writing—original draft (supporting). Jin Xu: Investigation (supporting)—numerical examples; Writing—original draft (supporting). Loc Vu-Quoc: Methodology (supporting); Validation (supporting); Writing—review & editing (equal). Bassam A. Izzuddin: Methodology (supporting); Validation (supporting); Writing—review & editing (equal). All authors: Engaged in critical discussions regarding the theoretical development and contributed to the final manuscript. All authors reviewed and approved the final version of the manuscript.
Availability of Data and Materials: The data that support the findings of this study are available from the corresponding author, upon reasonable request.
Ethics Approval: Not applicable.
Conflicts of Interest: The authors declare no conflicts of interest.
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Copyright © 2026 The Author(s). Published by Tech Science Press.This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


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