518 research outputs found
Repeatability of Joint-Dominated Deployable Masts
No full textDeployable masts are a class of structure that can be stowed in a small volume and expanded into long, slender, and stable booms. Their greatest benefit as space structures is their packing ratio: masts can typically be packed to a fraction of their deployed length at a diameter only modestly wider than their deployed width. This thesis is concerned with precision deployable masts, which can be stowed and deployed with repeatability of the tip position of better than 1 mm over 60 m. The methods of investigation are experimental measurements of a sample mast and numerical modeling of the mast with specially attention to hysteretic joints.
A test article of an ADAM mast was used for the experimental work. Two categories of experi- ment were pursued: measurements of mast components as inputs to the model, and measurements of full bays as validation cases for the model. Measurements of the longeron ball end joint friction, cable preload, and latch behavior are of particular note, and were evaluated for their variability. Further measurements were made of a bay in torsion and a short two-bay mast in shear, showing that there is residual displacement in this mast after shear loading is applied and released.
The modeling approach is described in detail, with attention to the treatment of the mast latches, which lock the structure in its deployed configuration. A user element subroutine was used within the framework of the Abaqus finite element analysis solver to model the behavior of the latches with high fidelity.
Validation cases for the model are presented in comparison with experimental observations of a two-bay mast. These cases show that the model captures a number of important and complex nonlinear effects of the hysteretic mast components. Parametric studies of the impacts of component behaviors and modeling practices are explored, emphasizing the impacts of part variability and the idealization of the mast latching mechanisms.</p
The glass truss bridge
No full textA Glass Truss Bridge has been constructed on the Green Village on the campus of Delft University of Technology (TU Delft) by the Glass & Transparency Research group (faculties of Architecture and CiTG). The bridge has been fitted with as many glass components as was structurally feasible, showcasing the group’s research into the structural application of glass in the built environment. The diagonals in the truss are glass bundle struts and the nodes of the truss are cast glass components. The lenticular truss will serve as a temporary bridge. Because of the experimental nature of the truss, with its unusual and novel applications of structural glass, a number of demonstrative proof loadings were performed to ease concerns about the safety of the structure. The glass bundles have been proof-loaded to twice their maximum expected load just prior to their installation in the structure. The whole bridge, once installed, has then been proof-loaded for several critical load combinations (static and dynamic) just after installation. During the proof-loading the strains in the glass diagonals have been measured. These lie well within the acceptable limits. In the paper the structural design of the bridge, in particular the glass node connector and the glass bundle diagonals will be explained. Then the proof-loading of the bridge will be described and the results of the proof-loading are presented and discussed.OLD Structural DesignApplied Mechanic
Preventing failure propagation in steel truss bridges
No full text[EN] Metal and steel truss bridges are essential for transportation networks worldwide but are vulnerable to collapse due to deterioration and increasing traffic loads, par-ticularly for ageing structures. Several bridge collapses, such as the Seongsu bridge (South Korea, 1994), I-35 bridge (USA, 2007), and Chauras bridge (India, 2012), have highlighted the need to develop accurate robustness assessment strategies and efficient mitigation of collapse risks. This paper summarizes results of experi-mental and computational studies for a steel riveted bridge with a truss-type struc-ture. The experimental component presented involves unique tests to be performed on a 21 m full-scale bridge span subjected to the failure of different elements under laboratory conditions. The paper then presents a first approach to explore different damage and failure scenarios for steel truss bridges, which will assist in defining data collection strategies for optimised monitoring and developing data analysis methods for real-time diagnosis of ageing bridges. With this, the paper contributes to avoiding progressive collapses and presents a framework, developed as part of an ongoing project, to identify vulnerable zones for prioritising monitoring systems that anticipate failure propagation and prevent collapse. The framework is based on a systematic analysis of past bridge failures and simulations of carefully designed generic cases.Sánchez-Rodríguez, A.; López, S.; Makoond, NC.; Buitrago, M.; Riveiro, B.; Adam, JM. (2023). Preventing failure propagation in steel truss bridges. Ernst & Sohn, Wiley Online Library. 2206-2213. https://doi.org/10.1002/cepa.2377S2206221
Thermal post-buckling behavior of simply supported sandwich panels with truss cores
No full textThis article presents a thermal post-buckling solution for sandwich panels with truss cores under simply supported conditions, when subjected to uniform temperature rise. The Reissner assumptions are adopted and truss cores are assumed to be continuous and homogeneous. Differential governing equations are developed based on the variational principle. The perturbation technique is employed to determine the thermal post-buckling path of sandwich panels with truss cores. Based on the present method, influences of truss core configuration, relative density, aspect ratio, and initial imperfection on the thermal post buckling behavior are discussed
Failure maps and optimal design of metallic sandwich panels with truss cores subjected to thermal loading
No full textSandwich panels with truss cores have been widely investigated due to their superior mechanical performances. When being used in the thermal protection system of a high-speed aircraft, sandwich panels are usually subjected to intense thermal loading and may fail due to various mechanisms. This paper presents a theoretical and numerical analysis on the failure mechanisms and optimal design of metallic sandwich panels with truss cores subjected to uniform thermal loading. Five failure modes are considered: global buckling, face sheet buckling, face sheet yielding, core member buckling and core member yielding. Failure maps of sandwich panels with several truss core topologies are developed based on these failure modes. Taking the five failure modes as constraint conditions, sandwich panels with truss cores are optimally designed for the minimum weight at given thermal loadings. It is found from the optimal analysis that sandwich panels with Kagome and X-type truss cores are more efficient than those with tetrahedral and pyramidal truss cores. Sandwich panels with fully-clamped boundary conditions have superior thermal loading resistance than those with simply-supported boundary conditions. (C) 2016 Elsevier Ltd. All rights reserved
Analytical fault tree and diagnostic aids for the preservation of historical steel truss bridges
No full text[EN] Historical steel bridges represent an important construction typology integrating the constructive heritage of the past century that needs to be preserved. Exposure to fatigue phenomenon, aging, improper design or execution, extreme events, and other aggressive environmental agents can seriously compromise the conservation and performance of these structures as some recent catastrophic collapses have shown (Mississippi River bridge, Minneapolis, Minnesota 2007; Kinzua Bridge State Park, Pennsylvania 2003). In this context, the diagnostic of historical steel bridges becomes of basic importance to identify and implement maintenance, monitoring and conservation strategies. Fault Trees are useful tools for practitioners that provide a complete overview of possible failures. In the related literature, this instrument is mainly applied with approaches that are based on previous experience or failures detected in similar structures, and so the Fault Tree can only provide qualitative support. This paper proposes a new method to achieve an "Analytical" Bridge Fault Tree linking the technician's experience and the numerical simulations of different fault scenarios. The latter are achieved by a numerical model able to consider fatigue failure and different concurring causes in the analysis (e.g., and aggressive phenomena, corrosion, defects, lack of maintenance). The proposed approach was applied to a historical railway steel truss bridge located in the East of Spain (Valencia Region) in order to show its applicability and potential.The research project described here was partially funded by the Generalitat Valenciana "Conselleria de Innovacion, Universidades, Ciencia y Sociedad Digital" through the European Social Fund (FSE) for Regional Development. The second author was financially supported by an Industrial PhD research program (PON-RI 2014-2020) sponsored by the Italian Ministry of Universities and Research (DOT130UZWT) . We would like to express our gratitude to FGV (Ferrocarrils de la Generalitat Valenciana) and CALSENS S.L. for providing data on a real bridge, also to Juan Antonio Garcia Cerezo, of FGV, for his invaluable cooperation and recommendations.Sangiorgio, V.; Nettis, A.; Uva, G.; Pellegrino, F.; Varum, H.; Adam, JM. (2022). Analytical fault tree and diagnostic aids for the preservation of historical steel truss bridges. Engineering Failure Analysis. 133:1-15. https://doi.org/10.1016/j.engfailanal.2021.105996S11513
Building and Testing Lenticular Truss Bridge with Glass-Bundle Diagonals and Cast Glass Connections
No full textOn the campus of Delft University the Glass and Transparency Research Group is preparing to build a pedestrian bridge as a low arch consisting of dry-stacked glass blocks. As temporary support for the arch, a lens-shaped truss has been constructed and placed on location. This truss has been fitted with as many glass components as was structurally feasible. The diagonals in the truss are glass bundle struts and the nodes of the truss are cast glass components. The lenticular truss will serve as a temporary bridge during the time the team needs to prepare for construction of the eventual Glass Arch Bridge. Due to the experimental nature of the truss, with its unusual and novel applications of structural glass, a number of demonstrative proof loadings were performed to ease concerns about the safety of the structure. The glass bundles have been proof-loaded to twice their maximum expected load just prior to their installation in the structure. The whole system has then been proof-loaded for several critical load combinations (static and dynamic) just after installation. During the proof-loading the strains in the glass diagonals have been measured. These lie easily within the acceptable limits. In the paper the structural design of the bridge, in particular the glass node connector and the glass bundle diagonals will be explained. Then the proof-loading of the bridge will be described. Then the results of the proof-loading are presented and discussed.OLD Structural DesignApplied Mechanic
Automated location of steel truss bridge damage using machine learning and raw strain sensor data
No full text[EN] Strategic major infrastructure ageing requires structural health monitoring usage to avoid critical safety issues and disasters. Machine Learning can be a valuable tool to automate the process of analysing raw monitoring data. Usually, frequency domain damage-sensitive features are extracted with data pre-processing procedures; thus these features are used as input for classification or regression problems. This paper describes a method of locating damage in steel truss railway bridges through machine learning classification tools, enabling automatic analysis of raw strain sensors signals without any pre-processing or preliminary feature extraction. Data were generated by simulating different damage scenarios with a finite element software, and then were processed by two machine learning classification tools: (a) the K-nearest Neighbours was adopted with the Dynamic Time Warping algorithm metric to select the most informative features; (b) a model suitable for high-dimensional data analysis, known as the Convolutional Neural Network, was then trained to classify strain sensors time series. The results indicate that the method applied can detect damages with an accuracy of 93% and is suitable for structural health monitoring.Parisi, F.; Mangini, AM.; Fanti, MP.; Adam, JM. (2022). Automated location of steel truss bridge damage using machine learning and raw strain sensor data. Automation in Construction. 138:1-13. https://doi.org/10.1016/j.autcon.2022.104249S11313
Inverting the structure–property map of truss metamaterials by deep learning
No full textInspired by crystallography, the periodic assembly of trusses into architected materials has enjoyed popularity for more than a decade and produced countless cellular structures with beneficial mechanical properties. Despite the successful and steady enrichment of the truss design space, the inverse design has remained a challenge: While predicting effective truss properties is now commonplace, efficiently identifying architectures that have homogeneous or spatially varying target properties has remained a roadblock to applications from lightweight structures to biomimetic implants. To overcome this gap, we propose a deep-learning framework, which combines neural networks with enforced physical constraints, to predict truss architectures with fully tailored anisotropic stiffness. Trained on millions of unit cells, it covers an enormous design space of topologically distinct truss lattices and accurately identifies architectures matching previously unseen stiffness responses. We demonstrate the application to patient-specific bone implants matching clinical stiffness data, and we discuss the extension to spatially graded cellular structures with locally optimal properties.Team Sid Kuma
Static analysis of a lattice prestressed truss
No full textThe aim of this bachelor thesis is to calculate the pre-stressed truss for the given layout and possible design of reinforcement. The calculation of the load effects has been carried out by means of manual calculation using the contact method, scia engineering software and using type treasures. Subsequently, the effects were compared. The assessment of the ultimate limit state and serviceability was carried out manually according to the applicable standards
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