scholarly journals Solar‐thermal driven drying technologies for large‐scale industrial applications: State of the art, gaps, and opportunities

2020 ◽  
Vol 44 (13) ◽  
pp. 9864-9888
Author(s):  
In'am Kamfa ◽  
Jürgen Fluch ◽  
Ruben Bartali ◽  
Derek Baker
2020 ◽  
Vol 11 (2) ◽  
Author(s):  
Debrayan Bravo Hidalgo ◽  
Alexander Báez Hernández

The objective of this contribution is to provide a state-of-the-art on research in solar thermal electricity systems. This objective is achieved using Scopus, and the softwears “Publish or Perish” and “VOSviewer”. The results of the research show the behavior of scientific productivity in this area. As well as the most productive thematic areas. Nations that lead the research in the generation of electric power on a large scale, using solar thermal energy. Network of scientific collaboration among nations, referring to the research of electricity generation through solar thermal energy. Correlation network among the most productive authors, in this subject within the Scopus directory. Most cited articles by each of the main journals that disseminate this theme. Conceptual bases of the generation of electricity with solar thermal energy. Properties of thermal energy storage technologies (TES) in power plants with parabolic solar concentrators or solar concentration towers. Current technologies and trends. Technological trends. Trends in the global energy market.


Metals ◽  
2020 ◽  
Vol 10 (2) ◽  
pp. 244 ◽  
Author(s):  
Vladimir Segal

This paper presents a state-of-the-art and a retrospective view of the critical stages in the evolution of equal-channel angular extrusion (ECAE) from the original idea to a cost-effective industrial technology. These stages include optimization of the structure modification and material processing, development of the special tools, process commercialization, and a large-scale validation of the semi-continuous ECAE at the industrial floor. All aspects are extensively summarized, based on the author’s experience in the field, which spans almost half of a century. Special attention is paid to the processing of large batch billets. Practical examples illustrate industrial applications of ECAE. The scope for future development is also discussed.


2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Yanpei Tian ◽  
Xiaojie Liu ◽  
Alok Ghanekar ◽  
Fangqi Chen ◽  
Andrew Caratenuto ◽  
...  

AbstractSpectrally selective solar absorbers (SSAs), which harvest heat from sunlight, are the key to concentrated solar thermal systems. An ideal SSA must have an absorptivity of unity in the solar irradiance wavelength region (0.3–2.5 $$\upmu $$ μ m), and its infrared thermal emissivity must be zero to depress spontaneous blackbody irradiation (2.5–25 $$\upmu $$ μ m). Current SSA designs which utilize photonic crystals, metamaterials, or cermets are either cost-inefficient due to the complexity of the required nanofabrication methods, or have limited applicability due to poor thermal stability at high temperatures. We conceptually present blackbody-cavity solar absorber designs with nearly ideal spectrally selective properties, capable of being manufactured at scale. The theoretical analyses show that the unity solar absorptivity of the blackbody cavity and nearly zero infrared emissivity of the SSA’s outer surface allow for a stagnation temperature of 880 $$^\circ $$ ∘ C under 10 suns. The performance surpasses state-of-the-art SSAs manufactured using nanofabrication methods. This design relies only on traditional fabrication methods, such as machining, casting, and polishing. This makes it suitable for large-scale industrial applications, and the “blackbody cavity” feature enables easy integration with existing concentrated solar thermal systems using the parabolic reflector and Fresnel lens as optical concentrators.


2022 ◽  
Vol 54 (9) ◽  
pp. 1-38
Author(s):  
Frank Siqueira ◽  
Joseph G. Davis

Recent advances in the large-scale adoption of information and communication technologies in manufacturing processes, known as Industry 4.0 or Smart Manufacturing, provide us a window into how the manufacturing sector will evolve in the coming decades. As a result of these initiatives, manufacturing firms have started to integrate a series of emerging technologies into their processes that will change the way products are designed, manufactured, and consumed. This article provides a comprehensive review of how service-oriented computing is being employed to develop the required software infrastructure for Industry 4.0 and identifies the major challenges and research opportunities that ensue. Particular attention is paid to the microservices architecture, which is increasingly recognized as offering a promising approach for developing innovative industrial applications. This literature review is based on the current state of the art on service computing for Industry 4.0 as described in a large corpus of recently published research papers, which helped us to identify and explore a series of challenges and opportunities for the development of this emerging technology frontier, with the goal of facilitating its widespread adoption.


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.


Author(s):  
Florian Kuisat ◽  
Fernando Lasagni ◽  
Andrés Fabián Lasagni

AbstractIt is well known that the surface topography of a part can affect its mechanical performance, which is typical in additive manufacturing. In this context, we report about the surface modification of additive manufactured components made of Titanium 64 (Ti64) and Scalmalloy®, using a pulsed laser, with the aim of reducing their surface roughness. In our experiments, a nanosecond-pulsed infrared laser source with variable pulse durations between 8 and 200 ns was applied. The impact of varying a large number of parameters on the surface quality of the smoothed areas was investigated. The results demonstrated a reduction of surface roughness Sa by more than 80% for Titanium 64 and by 65% for Scalmalloy® samples. This allows to extend the applicability of additive manufactured components beyond the current state of the art and break new ground for the application in various industrial applications such as in aerospace.


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.


2021 ◽  
Vol 141 ◽  
pp. 110757 ◽  
Author(s):  
Falk Cudok ◽  
Niccolò Giannetti ◽  
José L. Corrales Ciganda ◽  
Jun Aoyama ◽  
P. Babu ◽  
...  

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