scholarly journals State of the Art Review of Reinforcement Strategies and Technologies for 3D Printing of Concrete

Energies ◽  
2022 ◽  
Vol 15 (1) ◽  
pp. 360
Author(s):  
Zhengyu Wu ◽  
Ali M. Memari ◽  
Jose P. Duarte

This state of the art review paper aims to discuss the results of a literature survey on possible ways to reinforce printed concrete based on existing reinforcement strategies. Just as conventional concrete, for 3D printed concrete to be suitable for large-scale construction, reinforcement is needed to increase the tensile capacity of concrete members and reduce temperature and shrinkage cracking. Despite efforts that are currently underway, the development of proper reinforcement suitable for printed concrete is still very active on the research agenda. As an initial step for designing suitable reinforcement for printed concrete, the existing reinforcement methods for printed concrete as well as conventional cast concrete from the literature are reviewed and summarized. Through the preliminary evaluation of the suitability and effectiveness of various reinforcement methods, guidelines are proposed to better understand possible solutions to reinforce printed concrete and inspire new practical ideas to fill the current technology void. The conclusions also include the possible improvements of the existing reinforcement methods to be considered in future applications.

2008 ◽  
Vol 400-402 ◽  
pp. 27-36
Author(s):  
Christopher K.Y. Leung

Recent advancements in concrete science and technology have made possible the development of high performance fiber reinforced cementitious composites (HPFRCC) with excellent mechanical properties and long-term durability. However, the costs of these materials are many times that of conventional concrete and the construction of complete structures with them is hard to justify. The strategic application of high performance materials, in selected parts of concrete structures, can bring along higher performance/cost and wider acceptance of the material in practice. This paper will investigate several examples of selective HPFRCC application, including the fabrication of permanent formwork for durability enhancement, the replacement of steel reinforcements at the anchorage zone of post-tensioned members to relieve the steel congestion problem as well as the development of simple and narrow joints for pre-cast concrete members. Based on the experimental results obtained so far, the selected use of HPFRCC in concrete structures appears to have good potential for practical applications.


2018 ◽  
Vol 14 (12) ◽  
pp. 1915-1960 ◽  
Author(s):  
Rudolf Brázdil ◽  
Andrea Kiss ◽  
Jürg Luterbacher ◽  
David J. Nash ◽  
Ladislava Řezníčková

Abstract. The use of documentary evidence to investigate past climatic trends and events has become a recognised approach in recent decades. This contribution presents the state of the art in its application to droughts. The range of documentary evidence is very wide, including general annals, chronicles, memoirs and diaries kept by missionaries, travellers and those specifically interested in the weather; records kept by administrators tasked with keeping accounts and other financial and economic records; legal-administrative evidence; religious sources; letters; songs; newspapers and journals; pictographic evidence; chronograms; epigraphic evidence; early instrumental observations; society commentaries; and compilations and books. These are available from many parts of the world. This variety of documentary information is evaluated with respect to the reconstruction of hydroclimatic conditions (precipitation, drought frequency and drought indices). Documentary-based drought reconstructions are then addressed in terms of long-term spatio-temporal fluctuations, major drought events, relationships with external forcing and large-scale climate drivers, socio-economic impacts and human responses. Documentary-based drought series are also considered from the viewpoint of spatio-temporal variability for certain continents, and their employment together with hydroclimate reconstructions from other proxies (in particular tree rings) is discussed. Finally, conclusions are drawn, and challenges for the future use of documentary evidence in the study of droughts are presented.


Materials ◽  
2021 ◽  
Vol 14 (4) ◽  
pp. 1021
Author(s):  
Bernhard Dorweiler ◽  
Pia Elisabeth Baqué ◽  
Rayan Chaban ◽  
Ahmed Ghazy ◽  
Oroa Salem

As comparative data on the precision of 3D-printed anatomical models are sparse, the aim of this study was to evaluate the accuracy of 3D-printed models of vascular anatomy generated by two commonly used printing technologies. Thirty-five 3D models of large (aortic, wall thickness of 2 mm, n = 30) and small (coronary, wall thickness of 1.25 mm, n = 5) vessels printed with fused deposition modeling (FDM) (rigid, n = 20) and PolyJet (flexible, n = 15) technology were subjected to high-resolution CT scans. From the resulting DICOM (Digital Imaging and Communications in Medicine) dataset, an STL file was generated and wall thickness as well as surface congruency were compared with the original STL file using dedicated 3D engineering software. The mean wall thickness for the large-scale aortic models was 2.11 µm (+5%), and 1.26 µm (+0.8%) for the coronary models, resulting in an overall mean wall thickness of +5% for all 35 3D models when compared to the original STL file. The mean surface deviation was found to be +120 µm for all models, with +100 µm for the aortic and +180 µm for the coronary 3D models, respectively. Both printing technologies were found to conform with the currently set standards of accuracy (<1 mm), demonstrating that accurate 3D models of large and small vessel anatomy can be generated by both FDM and PolyJet printing technology using rigid and flexible polymers.


Sensors ◽  
2021 ◽  
Vol 21 (6) ◽  
pp. 1977
Author(s):  
Ricardo Oliveira ◽  
Liliana M. Sousa ◽  
Ana M. Rocha ◽  
Rogério Nogueira ◽  
Lúcia Bilro

In this work, we demonstrate for the first time the capability to inscribe long-period gratings (LPGs) with UV radiation using simple and low cost amplitude masks fabricated with a consumer grade 3D printer. The spectrum obtained for a grating with 690 µm period and 38 mm length presented good quality, showing sharp resonances (i.e., 3 dB bandwidth < 3 nm), low out-of-band loss (~0.2 dB), and dip losses up to 18 dB. Furthermore, the capability to select the resonance wavelength has been demonstrated using different amplitude mask periods. The customization of the masks makes it possible to fabricate gratings with complex structures. Additionally, the simplicity in 3D printing an amplitude mask solves the problem of the lack of amplitude masks on the market and avoids the use of high resolution motorized stages, as is the case of the point-by-point technique. Finally, the 3D printed masks were also used to induce LPGs using the mechanical pressing method. Due to the better resolution of these masks compared to ones described on the state of the art, we were able to induce gratings with higher quality, such as low out-of-band loss (0.6 dB), reduced spectral ripples, and narrow bandwidths (~3 nm).


2021 ◽  
Vol 7 (3) ◽  
pp. 50
Author(s):  
Anselmo Ferreira ◽  
Ehsan Nowroozi ◽  
Mauro Barni

The possibility of carrying out a meaningful forensic analysis on printed and scanned images plays a major role in many applications. First of all, printed documents are often associated with criminal activities, such as terrorist plans, child pornography, and even fake packages. Additionally, printing and scanning can be used to hide the traces of image manipulation or the synthetic nature of images, since the artifacts commonly found in manipulated and synthetic images are gone after the images are printed and scanned. A problem hindering research in this area is the lack of large scale reference datasets to be used for algorithm development and benchmarking. Motivated by this issue, we present a new dataset composed of a large number of synthetic and natural printed face images. To highlight the difficulties associated with the analysis of the images of the dataset, we carried out an extensive set of experiments comparing several printer attribution methods. We also verified that state-of-the-art methods to distinguish natural and synthetic face images fail when applied to print and scanned images. We envision that the availability of the new dataset and the preliminary experiments we carried out will motivate and facilitate further research in this area.


2021 ◽  
Vol 40 (3) ◽  
pp. 1-13
Author(s):  
Lumin Yang ◽  
Jiajie Zhuang ◽  
Hongbo Fu ◽  
Xiangzhi Wei ◽  
Kun Zhou ◽  
...  

We introduce SketchGNN , a convolutional graph neural network for semantic segmentation and labeling of freehand vector sketches. We treat an input stroke-based sketch as a graph with nodes representing the sampled points along input strokes and edges encoding the stroke structure information. To predict the per-node labels, our SketchGNN uses graph convolution and a static-dynamic branching network architecture to extract the features at three levels, i.e., point-level, stroke-level, and sketch-level. SketchGNN significantly improves the accuracy of the state-of-the-art methods for semantic sketch segmentation (by 11.2% in the pixel-based metric and 18.2% in the component-based metric over a large-scale challenging SPG dataset) and has magnitudes fewer parameters than both image-based and sequence-based methods.


Author(s):  
Anil S. Baslamisli ◽  
Partha Das ◽  
Hoang-An Le ◽  
Sezer Karaoglu ◽  
Theo Gevers

AbstractIn general, intrinsic image decomposition algorithms interpret shading as one unified component including all photometric effects. As shading transitions are generally smoother than reflectance (albedo) changes, these methods may fail in distinguishing strong photometric effects from reflectance variations. Therefore, in this paper, we propose to decompose the shading component into direct (illumination) and indirect shading (ambient light and shadows) subcomponents. The aim is to distinguish strong photometric effects from reflectance variations. An end-to-end deep convolutional neural network (ShadingNet) is proposed that operates in a fine-to-coarse manner with a specialized fusion and refinement unit exploiting the fine-grained shading model. It is designed to learn specific reflectance cues separated from specific photometric effects to analyze the disentanglement capability. A large-scale dataset of scene-level synthetic images of outdoor natural environments is provided with fine-grained intrinsic image ground-truths. Large scale experiments show that our approach using fine-grained shading decompositions outperforms state-of-the-art algorithms utilizing unified shading on NED, MPI Sintel, GTA V, IIW, MIT Intrinsic Images, 3DRMS and SRD datasets.


2020 ◽  
Vol 499 (2) ◽  
pp. 2934-2958
Author(s):  
A Richard-Laferrière ◽  
J Hlavacek-Larrondo ◽  
R S Nemmen ◽  
C L Rhea ◽  
G B Taylor ◽  
...  

ABSTRACT A variety of large-scale diffuse radio structures have been identified in many clusters with the advent of new state-of-the-art facilities in radio astronomy. Among these diffuse radio structures, radio mini-halos are found in the central regions of cool core clusters. Their origin is still unknown and they are challenging to discover; less than 30 have been published to date. Based on new VLA observations, we confirmed the mini-halo in the massive strong cool core cluster PKS 0745−191 (z = 0.1028) and discovered one in the massive cool core cluster MACS J1447.4+0827 (z = 0.3755). Furthermore, using a detailed analysis of all known mini-halos, we explore the relation between mini-halos and active galactic nucleus (AGN) feedback processes from the central galaxy. We find evidence of strong, previously unknown correlations between mini-halo radio power and X-ray cavity power, and between mini-halo and the central galaxy radio power related to the relativistic jets when spectrally decomposing the AGN radio emission into a component for past outbursts and one for ongoing accretion. Overall, our study indicates that mini-halos are directly connected to the central AGN in clusters, following previous suppositions. We hypothesize that AGN feedback may be one of the dominant mechanisms giving rise to mini-halos by injecting energy into the intra-cluster medium and reaccelerating an old population of particles, while sloshing motion may drive the overall shape of mini-halos inside cold fronts. AGN feedback may therefore not only play a vital role in offsetting cooling in cool core clusters, but may also play a fundamental role in re-energizing non-thermal particles in clusters.


Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1091
Author(s):  
Izaak Van Crombrugge ◽  
Rudi Penne ◽  
Steve Vanlanduit

Knowledge of precise camera poses is vital for multi-camera setups. Camera intrinsics can be obtained for each camera separately in lab conditions. For fixed multi-camera setups, the extrinsic calibration can only be done in situ. Usually, some markers are used, like checkerboards, requiring some level of overlap between cameras. In this work, we propose a method for cases with little or no overlap. Laser lines are projected on a plane (e.g., floor or wall) using a laser line projector. The pose of the plane and cameras is then optimized using bundle adjustment to match the lines seen by the cameras. To find the extrinsic calibration, only a partial overlap between the laser lines and the field of view of the cameras is needed. Real-world experiments were conducted both with and without overlapping fields of view, resulting in rotation errors below 0.5°. We show that the accuracy is comparable to other state-of-the-art methods while offering a more practical procedure. The method can also be used in large-scale applications and can be fully automated.


Algorithms ◽  
2021 ◽  
Vol 14 (5) ◽  
pp. 146
Author(s):  
Aleksei Vakhnin ◽  
Evgenii Sopov

Modern real-valued optimization problems are complex and high-dimensional, and they are known as “large-scale global optimization (LSGO)” problems. Classic evolutionary algorithms (EAs) perform poorly on this class of problems because of the curse of dimensionality. Cooperative Coevolution (CC) is a high-performed framework for performing the decomposition of large-scale problems into smaller and easier subproblems by grouping objective variables. The efficiency of CC strongly depends on the size of groups and the grouping approach. In this study, an improved CC (iCC) approach for solving LSGO problems has been proposed and investigated. iCC changes the number of variables in subcomponents dynamically during the optimization process. The SHADE algorithm is used as a subcomponent optimizer. We have investigated the performance of iCC-SHADE and CC-SHADE on fifteen problems from the LSGO CEC’13 benchmark set provided by the IEEE Congress of Evolutionary Computation. The results of numerical experiments have shown that iCC-SHADE outperforms, on average, CC-SHADE with a fixed number of subcomponents. Also, we have compared iCC-SHADE with some state-of-the-art LSGO metaheuristics. The experimental results have shown that the proposed algorithm is competitive with other efficient metaheuristics.


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