Compliance, Stress-Based and Multi-physics Topology Optimization for 3D-Printed Concrete Structures

Vantyghem, Gieljan; Boel, Veerle; Corte, Wouter De; Steeman, Marijke

doi:10.1007/978-3-319-99519-9_30

Cited by 23 publications

(16 citation statements)

References 29 publications

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“…The structural design of printed structures can take advantages of the shape freedom brought by the printing process, target "full compression" mode [17] and use topological optimization principles [18][19][20][21]. Topological optimization consists in a mathematical design step that optimizes material shape within a given design space, for a given set of loads and boundary conditions.…”

Section: Introductionmentioning

confidence: 99%

Nailing of Layers: A Promising Way to Reinforce Concrete 3D Printing Structures

et al. 2020

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Today, the extrusion-based 3D printing of concrete is a potential breakthrough technology for the construction industry. It is expected that 3D printing will reduce the cost of construction of civil engineering structures (removal of formwork) and lead to a significant reduction in time and improve working environment conditions. Following the use of this additive manufacturing layer-wise process, it is required to change the way concrete structures are designed and reinforced, especially for the parts of the structure under tension loads. Indeed, the extrusion-based concrete 3D printing process does not allow for the production of conventional reinforced concrete, and there is a need to develop other ways of compensating for the low mechanical performances of concrete, particularly in tension. In this study, the reinforcement of printed structures by using steel nails through the deposited layers of fresh concrete was investigated. Additionally, three-layer and 10-layer samples were reinforced with nails with varying inclination and spacing. The results show that inclined nails can be used to provide a flexural strengthening of the printing material in different directions.

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Section: Introductionmentioning

confidence: 99%

Nailing of Layers: A Promising Way to Reinforce Concrete 3D Printing Structures

et al. 2020

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“…With the growing interest in AM processes, design for additive manufacturing (DfAM) has emerged as an important paradigm to include AM constraints in early stages of design. These constraints pertain to minimum feature size [15], efficient use of support structure [16][17][18], anisotropic material properties [19,20], and post-processing [13,21].…”

Section: Related Workmentioning

confidence: 99%

“…where 0 ≤ w acc < 1 is the filtering weight for accessibility, and can be either a constant or adaptively updated based on the secluded volume V Γ(O) .S ϕ is the normalized sensitivity field with respect to the objective function, i.e., only the second term [λ 2 ] T [K Ω ][u Ω ] on the right hand side of (24), noting that the volume constraint is satisfied with the optimality criteria iteration [49].S IMF is the normalized accessibility filter defined in terms of the normalized IMF as:S The expressions in (20) through (26) are general and representation-agnostic, and can be used in both densitybased and levelset TO. To generate the results of this paper, we use the method of solid isotropic material with penalization (SIMP).…”

Section: Machining-constrained Topology Optimizationmentioning

confidence: 99%

Topology optimization with accessibility constraint for multi-axis machining

Mirzendehdel

Behandish

Nelaturi

2020

Computer-Aided Design

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In this paper, we present a topology optimization (TO) framework to enable automated design of mechanical components while ensuring the result can be manufactured using multi-axis machining. Although TO improves the part's performance, the as-designed model is often geometrically too complex to be machined and the as-manufactured model can significantly vary due to machining constraints that are not accounted for during TO. In other words, many of the optimized design features cannot be accessed by a machine tool without colliding with the part (or fixtures). The subsequent post-processing to make the part machinable with the given setup requires trial-and-error without guarantees on preserving the optimized performance. Our proposed approach is based on the well-established accessibility analysis formulation using convolutions in configuration space that is extensively used in spatial planning and robotics. We define an inaccessibility measure field (IMF) over the design domain to identify non-manufacturable features and quantify their contribution to non-manufacturability. The IMF is used to penalize the sensitivity field of performance objectives and constraints to prevent formation of inaccessible regions. Unlike existing discrete formulations, our IMF provides a continuous spatial field that is desirable for TO convergence. Our approach applies to arbitrary geometric complexity of the part, tools, and fixtures, and is highly parallelizable on multi-core architecture. We demonstrate the effectiveness of our framework on benchmark and realistic examples in 2D and 3D. We also show that it is possible to directly construct manufacturing plans for the optimized designs based on the accessibility information.

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“…Besides a higher degree of customisation, the positive performance of a digitally fabricated system can be evaluated by monitoring four main factors: time, cost, quality, and flexibility [10]. In other words, removing the formworks in favour of modularisation and prefabrication or part of the concrete/reinforcement due to material [11,12] and shape efficiency [13] results in cost and CO2 emission reduction [2]14], while providing additional functions [15,16]; the resulting features represent, in practice, the key decision-making factors for the overall construction management of the project [6,17]. However, this scenario has to deal with the slow innovation uptake of the construction industry even if estimates for future investments in infrastructure [18] have stimulated this sector toward the transformation of the way in which numerous engineering and construction firms operate [19].…”

Section: Introductionmentioning

confidence: 99%

“…Result of a topology optimisation study of a rectangular design domain subjected to a concentrated load[15].…”

mentioning

confidence: 99%