Truss-like Structures Research Articles

(Invited) Scalable Manufacturing and Application of Piezoelectric Biomaterials

Piezoelectric materials are a group of important functional building blocks that interfacing the human body by coupling biomechanical energy and electricity. So far, many technology innovations have advanced piezoelectric materials and composites toward a broad range of biomedical applications, which possess unique biocompatibility and flexibility. Fundamentally, materials design and engineering draw the boundary where this technology may advance. In this talk, I introduce our most recent development of piezoelectric materials and composites that are particularly designed for implantable nanogenerator applications. First, I present our wafer-scale approach to creating piezoelectric biomaterial thin films based on amino acids. The self-assembled sandwich film and truss-like structures enabled both strong piezoelectricity and largely improved flexibility. Then, new ferroelectric composites are presented as a new material used in 3D printing for directly manufacturing of piezoelectric architectures with tunable piezoelectric and mechanical properties. Toward the end, novel applications of implantable piezoelectric materials are introduced, which enable the closed-loop electrostimulations for many biomedical therapeutics.

Vibration-based methods for local damage identification of breathing cracks in truss-like structures

A vibration-based local damage identification method is proposed for truss-like structures with breathing cracks. Firstly, a bilinear model is established to represent the characteristics of breathing cracks, and the features of such cracks are detected through reciprocity and homogeneity tests on structural input-output signals. Since the crack is influenced by tensional and compressive forces on truss members, only one damage factor is required to quantify the stiffness reduction of each member. Subsequently, a dynamic equilibrium equation concerning the damage factor is constructed to identify the new load term. The integral equation method, which relies on the virtual work principle, is employed to obtain the displacement responses and loads under all tensile conditions. Finally, the mean value of cumulative damage coefficients for each truss member can be derived as their corresponding damage factor. Numerical examples involving a plane truss structure and a truss offshore platform are utilised to illustrate the effectiveness of this damage identification method. The results demonstrate exceptional precision and efficiency in accurately identifying various damages in truss structures under different excitations and signal-to-noise ratios. A actual space truss structure confirm that this damage identification method exhibits high-level precision in identifying single-member damages as well as multi-member damages with breathing cracks locally.

Size and topology optimization of truss-like structures under seismic excitations incorporating probabilistic aspects

Size and topology optimization of truss-like structures under seismic excitations incorporating probabilistic aspects

Application of Re-Entrant Auxetic Tubular Truss-Like Structure in Force Measurements

Application of Re-Entrant Auxetic Tubular Truss-Like Structure in Force Measurements

A computational framework for nanotrusses: Input convex neural networks approach

The present research aims to provide a practical numerical tool for the mechanical analysis of nanoscale trusses with similar accuracy to molecular dynamics (MD). As a first step, MD simulations of uniaxial tensile and compression tests of all possible chiralities of single-walled carbon nanotubes up to 4 nm in diameter were performed using the AIREBO potential. The results represent a dataset consisting of stress/strain curves that were then used to develop a neural network that serves as a surrogate for a constitutive model for all nanotubes considered. The cornerstone of the new framework is a partially input convex integrable neural network. It turns out that convexity enables favorable convergence properties required for implementation in the classical nonlinear truss finite element available in Abaqus. This completes a molecular dynamics-machine learning-finite element framework suitable for the static analysis of large, nanoscale, truss-like structures. The performance is verified through a comprehensive set of examples that demonstrate ease of use, accuracy, and robustness.

Research on a hierarchical feature-based contour extraction method for spatial complex truss-like structures in aerial images

Spatial truss-like structures are three-dimensional frame structures consisting of a series of linear members and nodes, which are widely used in the power engineering. UAVs and various land-air robots are widely used in power inspection to reduce the reliance on manual labor. Extracting the contours of such objects (represented in the form of points and line segments) in aerial images will further improve the efficiency of power inspections. Because existing methods struggle to deal with the complex background interference in aerial images, an innovative contour extraction method based on hierarchical features is proposed in this paper, which uses two artificial neural networks to extract image-wise features and patch-wise features respectively and link them with patch division. The IoU of the method can reach 83.4%, which is improved by 5.4% and 50.8% compared to the lightweight semantic segmentation network and HED-based method, respectively. Meanwhile the Polygons and line segments measurement (PoLis) outperforms the other four types of methods compared with it by at least 39.1%, which overcomes the drawbacks of the other methods that have poor contour extraction ability in complex backgrounds and aerial images with numerous feature. Meanwhile, the running time of this method is 85 ms. The proposed method overcomes the shortcomings of existing contour extraction methods, improves the effect of contour extraction in complex backgrounds in power inspection scenarios, facilitating the improvement of the intelligence level of inspection robots, which in turn promotes the automation level in power engineering.

Topology optimization of truss-like structures with bidirectional non-orthogonal materials based on mathematical programming

Topology optimization of truss-like structures with bidirectional non-orthogonal materials based on mathematical programming

Lightweight panels with high delamination resistance made of integrally woven truss-like fabric structures

Lightweight panels are of high relevance for various applications, such as automotive, aerospace, civil engineering, and achieve high stiffnesses and strengths at low self-weight. The sandwich principle is commonly used to manufacture the panels, although conventional materials and reinforcement structures often limit the design and application of the panels in a wide range of possible applications. The reason for this is that lightweight panels fail either under combined compressive/shear loading or as a result of delamination of the individual layers. In this article, novel fabric structures are presented as a basis for the fabrication of lightweight panels that effectively overcome these deficiencies. These fabrics have a spatial truss-like structure, with the core and top layer being connected by continuously running reinforcing fibers. This results in high panel stability and high delamination resistance, which are evaluated in this article using mechanical tests in compression, flexure and combined tension-shear. The results are related to sample panels with conventional honeycomb core as reference. The high potential and excellent delamination resistance of the new fabric-based lightweight panels is shown in the result of the tests.

The integration of morphological design and topology optimization to enhance the visual quality of electricity pylons

Purpose: This paper aims to enhance the visual quality of artificial above-ground structures, like pylons, masts, and towers of infrastructures and facilities, through a systematic design method for their morphological and structural optimization.Design/methodology/approach: The method achieves the functional and aesthetic goals based on the application of computer-aided tools. In particular, this is achieved according to three key steps:• Morphological development of landscape-related symbolism, environment, or culture and social needs.• Topology optimization of the design concept to reduce the structural weight and its visual impact.• Engineering of the resulting optimized structure.Practical implications: As a case study, the method is used for designing electricity pylons for the coastal territory of a Mediterranean European country, such as Italy. Citizens were involved during the identification phase of a symbolic shape for the concept development and during the final assessment phase.Research limitations/implications: The engineering phase has been performed by assembling standard lattice components with welded connections. Even if the use of this truss-like structure should lead to a minimum cost, the developed structure employs an additional 15%–20% of trusses and sheet metal covers the final cost is higher than a standard lattice pylon.Findings: The result is a structure with enhanced visual quality according to the international guidelines and fully complying with mandatory and functional requirements, such as regulatory and industrial feasibility, as well as those arising from social components.Originality/value: The method shows its potential in defining a custom design for lightweight structures with enhanced visual quality regarding the critical situation discussed here. The method considers both the subjective perception of citizens and their priorities and the landscape where the structures will be installed.

A new metaheuristic algorithm: Shrimp and Goby association search algorithm and its application for damage identification in large-scale and complex structures

This paper presents the application of a new Shrimp and Goby Association Search algorithm (SGA) to solve large-scale global optimization problems. The performance of SGA is assessed using 13 benchmark high-dimensional functions, 10 classical benchmark functions, and several real-world engineering applications. For the first time, an efficient optimization approach for structural health monitoring (SHM) in truss-like structures is presented. The proposed approach is applied for damage identification of complex structures. A real structure, namely Canton Tower in Guangzhou, China, is served as an example for damage detection. Interestingly, this tower was the tallest structure in the world in 2009 with a height of 610 m. The great merit of this example is that it provides a real complex structure with a high-dimensional problem to assess the performance of SGA in the real world. The results show that SGA can deal with this problem effectively, at the same time, it operates better to escape from local optima with faster convergence rate than population-based algorithms.

Digital Manufacture of a Continuous Fiber Reinforced Thermoplastic Matrix Truss Core Structural Panel Using Off-the-Tool Consolidation

Sandwich panels are commonly used as structure, based on fiber reinforced composites, with the goal of high flexural stiffness and low mass. It is most common to separate two high performance composite facesheets with a low-density core, generally in the form of a foam or honeycomb. A recent concept has been to replace these traditional core materials with fiber reinforced truss-like structures, with the goal of further reducing mass. A system is described that can radically reduce the amount of tooling required for truss core sandwich panel manufacture. This system, which is a digital manufacturing platform for the extrusion of continuous fiber reinforced commingled glass fiber/PET tow, was developed to demonstrate the rigidization of composites both on, and off, a tool surface. Navtruss core panels were successfully manufactured using this digital manufacturing platform, without conventional tooling, and the resulting through thickness compression moduli and panel shear moduli were within 14.6% and 23% of the values baseline compression molded specimens. Thus, the results suggest that, with further development, complex truss core structures with performance approaching that of compression molded panels can be manufactured with radically reduced tooling requirements from high volume fraction, continuous fiber reinforced thermoplastic matrix composites.

The topological ligament in shape optimization: a connection with thin tubular inhomogeneities

In this article, we propose a formal method for evaluating the asymptotic behavior of a shape functional when a thin tubular is added between two distant regions of the boundary of a domain. In the contexts of the conductivity equation and the linear elasticity system, we relate this issue to a perhaps more classical problem of thin tubular inhomogeneities: we analyze the solutions to versions of the physical partial differential equations which are posed inside a fixed background medium, and whose material coefficients are altered inside a tube with vanishing thickness. Our main contribution from the theoretical point of view is to propose a heuristic energy argument to calculate the limiting behavior of these solutions with a minimum amount of effort. We retrieve known formulas when they are available, and we manage to treat situations which are, to the best of our knowledge, not reported in the literature (including the setting of the 3d linear elasticity system). From the numerical point of view, we propose three different applications of the formal ligament approach derived from these expansions. At first, it is an original way to account for variations of a domain, and it thereby provides a new type of sensitivity for a shape functional, to be used concurrently with more classical shape and topological derivatives in optimal design frameworks. Besides, it suggests new, interesting algorithms for the design of the scaffold structure sustaining a shape during its fabrication by a 3d printing technique, and for the design of truss-like structures. Several numerical examples are presented in two and three space dimensions to appraise the efficiency of these methods.

Topology optimization of load-bearing capacity

The present work addresses the problem of maximizing a structure load-bearing capacity subject to given material strength properties and a material volume constraint. This problem can be viewed as an extension to limit analysis problems which consist in finding the maximum load capacity for a fixed geometry. We show that it is also closely linked to the problem of minimizing the total volume under the constraint of carrying a fixed loading. Formulating these topology optimization problems using a continuous field representing a fictitious material density yields convex optimization problems which can be solved efficiently using state-of-the-art solvers used for limit analysis problems. We further analyze these problems by discussing the choice of the material strength criterion, especially when considering materials with asymmetric tensile/compressive strengths. In particular, we advocate the use of a L1-Rankine criterion which tends to promote uniaxial stress fields as in truss-like structures. We show that the considered problem is equivalent to a constrained Michell truss problem. Finally, following the idea of the SIMP method, the obtained continuous topology is post-processed by an iterative procedure penalizing intermediate densities. Benchmark examples are first considered to illustrate the method overall efficiency while final examples focus more particularly on no-tension materials, illustrating how the method is able to reproduce known structural patterns of masonry-like structures. This paper is accompanied by a Python package based on the FEniCS finite-element software library.

A probabilistic risk-based decision framework for structural health monitoring

Obtaining the ability to make informed decisions regarding the operation and maintenance of structures, provides a major incentive for the implementation of structural health monitoring (SHM) systems. Probabilistic risk assessment (PRA) is an established methodology that allows engineers to make risk-informed decisions regarding the design and operation of safety-critical and high-value assets in industries such as nuclear and aerospace. The current paper aims to formulate a risk-based decision framework for structural health monitoring that combines elements of PRA with the existing SHM paradigm. As an apt tool for reasoning and decision-making under uncertainty, probabilistic graphical models serve as the foundation of the framework. The framework involves modelling failure modes of structures as Bayesian network representations of fault trees and then assigning costs or utilities to the failure events. The fault trees allow for information to pass from probabilistic classifiers to influence diagram representations of decision processes whilst also providing nodes within the graphical model that may be queried to obtain marginal probability distributions over local damage states within a structure. Optimal courses of action for structures are selected by determining the strategies that maximise expected utility. The risk-based framework is demonstrated on a realistic truss-like structure and supported by experimental data. Finally, a discussion of the risk-based approach is made and further challenges pertaining to decision-making processes in the context of SHM are identified.

Discrete topology optimization in augmented space: integrated element removal for minimum size and mesh sensitivity control

A computational strategy is proposed to circumvent some of the major issues that arise in the classical threshold-based approach to discrete topology optimization. These include the lack of an integrated element removal strategy to prevent the emergence of hair-like elements, the inability to effectively enforce a minimum member size of arbitrary magnitude, and high sensitivity of the final solution to the choice of ground structure. The proposed strategy draws upon the ideas used to arrive at mesh-independent solutions in continuum topology optimization and enables efficient imposition of a minimum size constraint onto the set of non vanishing elements. This is achieved via augmenting the design variables by a set of auxiliary variables, called existence variables, that not only prove very effective in addressing the aforementioned issues but also bring in a set of added benefits such as better convergence and complexity control. 2D and 3D examples from truss-like structures are presented to demonstrate the superiority of the proposed approach over the classical approach to discrete topology optimization.

Designing stress for optimizing and toughening truss-like structures

Optimization of materials and structures is a crucial step in the design of man-made mechanical components for a wide field of engineering applications. It also plays a key role in mechanobiology of living systems, being involved by nature across the scales, from single-cell to tissues and organs, as a strategy to minimize metabolic cost and maximize biomechanical performances. The synergy between the continuously increasing development of high-resolution 3D printing technologies and the possibility to predict chemical and physical properties through molecular dynamics-based numerical analyses has recently contributed to boost the use of both design and topology optimization procedures. They are employed in ab initio simulations as key strategies for deciding microstructures to improve mechanical performances and, concretely, to achieve prototypes of new material components. With this in mind, we here propose to abandon the classical approach of using a single scalar objective function employed in the classical design and topology optimization strategies, to introduce multiple quantities to be minimized, identified as the differences between material yield stress and the maximum von Mises stress. After mathematically justifying the well-posedness of this unconventional choice for the case at hand, it is highlighted that the proposed strategy is based on the concept of "equalizing" a proper stress measure at any point of the body and, for this reason, it is baptized as Galilei’s optimization, in honor of the Italian scholar who somehow first wondered about the possibility of changing sizes of beams to have uniform internal forces and, in turn, minimum weight. By exploiting analytical solutions and ad hoc implementing a parametric finite element algorithm to be applied to a wide variety of solids with arbitrary complex structural geometries, including nested or hierarchically organized architectures, it is first demonstrated that the proposed optimization strategy roughly retraces principles invoked by nature to guide growth, remodeling and shaping of biomaterials. More importantly, by means of several benchmark examples, we finally show the proposed procedure might be also helpfully employed to conceive a new class of micro-structured, eventually 3D-printed materials exhibiting surprising post-elastic properties, such as high overall resilience and toughness, in particular obtaining a decrease of stress concentration and a slowing down of crack propagation as direct effects of the optimization, which de facto minimizes stress gradients wherever in the solid domain.

A Novel Hybrid Harmony Search Approach for the Analysis of Plane Stress Systems via Total Potential Optimization

By finding the minimum total potential energy of a structural system with a defined degree of freedoms assigned as design variables, it is possible to find the equilibrium condition of the deformed system. This method, called total potential optimization using metaheuristic algorithms (TPO/MA), has been verified on truss and truss-like structures, such as cable systems and tensegric structures. Harmony Search (HS) algorithm methods perfectly found the analysis results of the previous structure types. In this study, TPO/MA is presented for analysis of plates for plane stress members to solve general types of problems. Due to the complex nature of the system, a novel hybrid Harmony Search (HHS) approach was proposed. HHS is the hybridization of local search phases of HS and the global search phase of the Flower Pollination Algorithm (FPA). The results found via HHS were verified with the finite element method (FEM). When compared with classical HS, HHS provides smaller total potential energy values, and needs less iterations than other new generation metaheuristic algorithms.

Three-dimensional printing of truss-like structure for use in scaffold: Experimental, numerical, and analytical analyses

Rapid prototyping is a promising technique for the fabrication of tissue engineering scaffolds. It has an inherent capacity to make predetermined forms and structures and also distinct pore architecture as well. The objective of this study is to investigate the effect of gradient pore geometries on the elastic behavior of the poly (methyl methacrylate) scaffold under compressive loading. Two kinds of models comprise simple and gradient architecture fabricated by three-dimensional printing. The mechanical properties of scaffolds were investigated experimentally, numerically, and analytically. Moreover, the cell adhesion and proliferation of scaffold were studied under two conditions: chitosan-coated and noncoated. Results indicated that although simple architecture renders higher amounts of mechanical properties, gradient architecture can make elastic regions after each plastic deformation improving the elastic behavior of scaffold at the higher strain value. Additionally, the excellent correspondence between the results of experimental compressive tests, finite element analysis, and analytical method display that the proposed models can predict precisely the mechanical properties of the scaffold. Furthermore, chitosan coating improves remarkably the number of cell proliferation of the scaffold.

Mechanical behaviors of 3D printed lightweight concrete structure with hollow section

A practical revolution in construction could be realized by combining the potential of 3D concrete printing with lightweight cementitious materials to fabricate adeptly hollow structures. In this study, five concrete mixtures with different replacement rates of lightweight ceramsite sand to silica sand are prepared for extrusion-based 3D printability evaluation. To reduce the water absorption induced shrinkage and micro-cracks, the ceramsite sands were coated with polyvinyl alcohol. An optimized cementitious material was identified by harmonizing the fresh properties to the continuous printing process. Cubic and beam elements with four different types of interior hollow structures were designed and 3D printed based on the optimized lightweight mixture. The interior structures include cellular-shaped structure, truss-like structure, lattice-shaped structure with a square topology, as well as gridding shaped structure with triangle topology. The mechanical capacities of the printed samples were measured and evaluated by compressive tests for the cubic samples and four-points flexural bending tests for the beam specimens. Basing on the results, the rectangular lattice hollow structure demonstrates the best mechanical resistance to compression and the truss-shaped prism structure ensues the highest flexural properties. The stress distribution and failure process were also explored through discrete element method.

Investigation of an adaptive, hinge-less, and highly shear stiff structure for morphing skins

In this article, a novel shear stiff, hinge-less, and truss-like structure for morphing skins is presented and investigated. Adaptive skins are an essential component of morphing wings, which enable perimeter length changes with low deformation energy requirements and increase the efficiency of the morphing system. Based on fundamental considerations for morphing skins, a high shear to morphing stiffness ratio is targeted. The underlying deformation energies for compliant structures are evaluated and provide the basis for the developed geometry of the novel structure. The sizing parameters of the structure are optimized for shear stiffness and morphing stiffness by an evolutionary multi-objective optimization algorithm. A representative geometry is manufactured and tested to verify the nonlinear simulations for shear and morphing stiffness. Furthermore, various cover options forming the aerodynamic surface were investigated and compared in terms of out-of-plane deformations and for their interaction with the underlying structure. The chosen concept, comprising of the novel substructure and sliding covers, exhibits superior performance, reaching a shear to morphing stiffness ratio up to 300, while forming a closed aerodynamic surface.