scholarly journals Manufacturing Processes of Integral Blade Rotors for Turbomachinery, Processes and New Approaches

2020 ◽  
Vol 10 (9) ◽  
pp. 3063 ◽  
Author(s):  
Haizea González-Barrio ◽  
Amaia Calleja-Ochoa ◽  
A. Lamikiz ◽  
L. N. López de Lacalle
Keyword(s):  
Working Conditions ◽  
Manufacturing Processes ◽  
Complex Geometries ◽  
Grinding Processes ◽  
New Approaches ◽  
Present Complex ◽  
Useful Life ◽  
Manufacturing Techniques

Manufacturing techniques applied to turbomachinery components represent a challenge in the aeronautical sector. These components are commonly composed of high resistant super-alloys; in order to satisfy the extreme working conditions, they have to support during their useful life. Besides, in the particular case of Integrally Bladed Rotors (IBR), they usually present complex geometries that need to be roughed and finished by milling and grinding processes, respectively. Thermoresistant superalloys present many challenges in terms of machinability what leads to find new alternatives to conventional manufacturing processes. In order to face this issue, this work presents a review of the last advances for IBR manufacturing and repairing processes.

scholarly journals Remaining Useful Life Estimation of Aircraft Engines Using a Joint Deep Learning Model Based on TCNN and Transformer

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Hai-Kun Wang ◽  
Yi Cheng ◽  
Ke Song
Keyword(s):  
Deep Learning ◽  
Working Conditions ◽  
Health Management ◽  
Remaining Useful Life ◽  
Aircraft Engines ◽  
Key Technology ◽  
Life Estimation ◽  
Useful Life ◽  
New Generation ◽  
Deep Learning Model

The remaining useful life estimation is a key technology in prognostics and health management (PHM) systems for a new generation of aircraft engines. With the increase in massive monitoring data, it brings new opportunities to improve the prediction from the perspective of deep learning. Therefore, we propose a novel joint deep learning architecture that is composed of two main parts: the transformer encoder, which uses scaled dot-product attention to extract dependencies across distances in time series, and the temporal convolution neural network (TCNN), which is constructed to fix the insensitivity of the self-attention mechanism to local features. Both parts are jointly trained within a regression module, which implies that the proposed approach differs from traditional ensemble learning models. It is applied on the Commercial Modular Aero-Propulsion System Simulation (C-MAPSS) dataset from the Prognostics Center of Excellence at NASA Ames, and satisfactory results are obtained, especially under complex working conditions.

Physico-Chemical Challenges in 3D Printing of Polymeric Nanocomposites and Hydrogels for Biomedical Applications

2021 ◽  
Vol 21 (5) ◽  
pp. 2778-2792
Author(s):  
Massimo Bonini
Keyword(s):  
Additive Manufacturing ◽  
3D Printing ◽  
Biomedical Applications ◽  
Nanocomposite Materials ◽  
Manufacturing Processes ◽  
Polymeric Nanocomposites ◽  
Physico Chemical ◽  
Polymeric Hydrogels ◽  
Manufacturing Techniques

Additive manufacturing techniques (i.e., 3D printing) are rapidly becoming one of the most popular methods for the preparation of materials to be employed in many different fields, including biomedical applications. The main reason is the unique flexibility resulting from both the method itself and the variety of starting materials, requiring the combination of multidisciplinary competencies for the optimization of the process. In particular, this is the case of additive manufacturing processes based on the extrusion or jetting of nanocomposite materials, where the unique properties of nanomaterials are combined with those of a flowing matrix. This contribution focuses on the physico-chemical challenges typically faced in the 3D printing of polymeric nanocomposites and polymeric hydrogels intended for biomedical applications. The strategies to overcome those challenges are outlined, together with the characterization approaches that could help the advance of the field.

Variance Quantification of Different Additive Manufacturing Processes for Acoustic Meta Materials

2021 ◽  
Vol 263 (4) ◽  
pp. 2708-2723
Author(s):  
Manuel Bopp ◽  
Arn Joerger ◽  
Matthias Behrendt ◽  
Albert Albers
Keyword(s):  
Mechanical Properties ◽  
Additive Manufacturing ◽  
Production Process ◽  
Laser Scanning ◽  
Mode Shapes ◽  
Manufacturing Processes ◽  
3D Laser Scanning ◽  
Fused Filament Fabrication ◽  
Manufacturing Techniques ◽  
Different Levels

Many concepts for acoustic meta materials rely on additive manufacturing techniques. Depending on the production process and material of choice, different levels of precision and repeatability can be achieved. In addition, different materials have different mechanical properties, many of which are frequency dependent and cannot easily be measured directly. In this contribution the authors have designed different resonator elements, which have been manufactured utilizing Fused Filament Fabrication with ABSplus and PLA, as well as PolyJet Fabrication with VeroWhitePlus. All structures are computed in FEA to obtain the calculated Eigenfrequencies and mode shapes, with the respective literature values for each material. Furthermore, the dynamic behavior of multiple instances of each structure is measured utilizing a 3D-Laser-Scanning Vibrometer under shaker excitation, to obtain the actual Eigenfrequencies and mode shapes. The results are then analyzed in regards to variance between different print instances, and in regards to accordance between measured and calculated results. Based on previous work and this analysis the parameters of the FEA models are updated to improve the result quality.

Hybride Fertigung mittels Laser-Strahlschmelzen/Hybrid manufacturing by laser-based powder bed fusion

2021 ◽  
Vol 111 (06) ◽  
pp. 363-367
Author(s):  
Lukas Langer ◽  
Matthias Schmitt ◽  
Georg Schlick ◽  
Johannes Schilp
Keyword(s):  
Additive Manufacturing ◽  
Manufacturing Processes ◽  
Complex Geometries ◽  
Hybrid Manufacturing ◽  
Powder Bed Fusion ◽  
Process Chain ◽  
Manufacturing Costs ◽  
Additive Fertigung ◽  
Powder Bed

Die additive Fertigung ermöglicht komplexe Geometrien und individualisierte Bauteile. Die hohen Material- und Fertigungskosten können ein Hindernis für einen wirtschaftlichen Einsatz sein. In der hybriden additiven Fertigung werden die Vorteile konventioneller sowie additiver Fertigungsverfahren kombiniert. Für eine weitere Steigerung der Wirtschaftlichkeit und Effizienz werden nichtwertschöpfende Schritte der Prozesskette identifiziert und Automatisierungsansätze entwickelt.   Additive manufacturing enables complex geometries and individualized components. However, high material and manufacturing costs can be a hindrance for economical use. Hybrid additive manufacturing combines the advantages of conventional with additive manufacturing processes. For a further increase in profitability and efficiency, non-value-adding steps in the process chain are identified and automation approaches developed.

Current Issues of Developing Methodology and Software Solutions Used in Different Phases of Modelling Additive Production Processes

2018 ◽  
Vol 771 ◽  
pp. 97-102 ◽  
Author(s):  
Andrey Ripetskiy ◽  
Stanislav Vassilyev ◽  
Sergey Zelenov ◽  
Ekaterina Kuznetsova
Keyword(s):  
Additive Manufacturing ◽  
Structured Data ◽  
Manufacturing Processes ◽  
Mathematical Methods ◽  
New Techniques ◽  
Additive Production ◽  
Production Processes ◽  
Manufacturing Techniques ◽  
Technological Limitations ◽  
New Criteria

The mathematical methods and examples considered in the article allow efficient modeling of additive manufacturing processes by formulating a number of new criteria for geometry evaluation for compliance with the technological limitations of the additive manufacturing techniques. The aim of the research is the development of the new techniques, methods, algorithms and structured data aimed to validate the entire chain of additive manufacturing process.

scholarly journals Design of Additively Manufactured Structures for Biomedical Applications: A Review of the Additive Manufacturing Processes Applied to the Biomedical Sector

2019 ◽  
Vol 2019 ◽  
pp. 1-6 ◽  
Author(s):  
Flaviana Calignano ◽  
Manuela Galati ◽  
Luca Iuliano ◽  
Paolo Minetola
Keyword(s):  
Additive Manufacturing ◽  
Biomedical Applications ◽  
Point Of View ◽  
Disruptive Technology ◽  
Manufacturing Processes ◽  
Medical Field ◽  
Successful Case ◽  
Design Perspective ◽  
Manufacturing Techniques ◽  
Am Processes

Additive manufacturing (AM) is a disruptive technology as it pushes the frontier of manufacturing towards a new design perspective, such as the ability to shape geometries that cannot be formed with any other traditional technique. AM has today shown successful applications in several fields such as the biomedical sector in which it provides a relatively fast and effective way to solve even complex medical cases. From this point of view, the purpose of this paper is to illustrate AM technologies currently used in the medical field and their benefits along with contemporary. The review highlights differences in processes, materials, and design of additive manufacturing techniques used in biomedical applications. Successful case studies are presented to emphasise the potentiality of AM processes. The presented review supports improvements in materials and design for future researches in biomedical surgeries using instruments and implants made by AM.

Incorporating Manufacturing Constraints in Topology Optimization Methods: A Survey

2017 ◽  
Author(s):  
Alok Sutradhar ◽  
Jaejong Park ◽  
Payam Haghighi ◽  
Jacob Kresslein ◽  
Duane Detwiler ◽  
...  
Keyword(s):  
Topology Optimization ◽  
Additive Manufacturing ◽  
Optimization Methods ◽  
Manufacturing Processes ◽  
Complex Geometries ◽  
Manufacturing Constraints ◽  
Post Processing ◽  
Optimization Framework ◽  
Manufacturing Methods ◽  
Traditional Manufacturing

Topology optimization provides optimized solutions with complex geometries which are often not suitable for direct manufacturing without further steps or post-processing by the designer. There has been a recent progression towards linking topology optimization with additive manufacturing, which is less restrictive than traditional manufacturing methods, but the technology is still in its infancy being costly, time-consuming, and energy inefficient. For applications in automotive or aerospace industries, the traditional manufacturing processes are still preferred and utilized to a far greater extent. Adding manufacturing constraints within the topology optimization framework eliminates the additional design steps of interpreting the topology optimization result and converting it to viable manufacturable parts. Furthermore, unintended but inevitable deviations that occur during manual conversion from the topology optimized result can be avoided. In this paper, we review recent advances to integrate (traditional) manufacturing constraints in the topology optimization process. The focus is on the methods that can create manufacturable and well-defined geometries. The survey will discuss the advantages, limitations, and related challenges of manufacturability in topology optimization.

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