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Eng
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Stylistic Design Engineering (SDE)
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Stylistic Design Engineering (SDE)

A special issue of Eng (ISSN 2673-4117).

Deadline for manuscript submissions: closed (31 December 2021) | Viewed by 11084

Special Issue Editors

Dr. Leonardo Frizziero

E-Mail Website
Guest Editor
Department of Industrial Engineering, University of Bologna, 40126 Bologna, Italy
Interests: industrial and car design; computer aided design; design methods; augmented reality; 3D printing
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Giampiero Donnici

E-Mail Website
Guest Editor
Faculty of Mechanical Engineering, University of Bologna, 40126 Bologna, Italy
Interests: stylistic design engineering (SDE); design engineering; QFD; benchmarking; TopFlop analysis; design for Six Sigma (DFSS); digital prototyping with augmented reality; design for additive manufacturing

Special Issue Information

Dear Colleagues,

The Special Issue entitled "Stylistic Design Engineering (SDE)" aims to deepen the following topics, aimed at improving design technologies and methodologies such as the Ramacciotti method, the quality function deployment method (QFD), benchmarking (BM) and top flop analysis (TPA), towards new innovative products, both from a technological and stylistic point of view.

The problem of innovative design is absolutely a priority, both in advanced economies and in developing countries. If correctly implemented, the application of innovative design principles allows the creation of innovative products, following procedures that not only lead to new product concepts on the market, but also guarantee their high quality and reliability.

This Special Issue is dedicated to the deepening of research and case studies, related to the issue of innovative design, not only from a technical and engineering point of view, by tackling innovative solutions, but also aesthetically. In particular, the SDE (or the Ramacciotti method) is able to systematize the design process of innovative products and reduce their costs. The industrial challenges of innovation, in form and functionality, can be overcome precisely through the use of the SDE methodology, ensuring that beautiful aesthetic projects are carried out systematically, and with low costs.

Many tools help designers to achieve the above mentioned goals: digital sketches, 2D and 3D CAD, augmented reality, additive manufacturing, QFD, TRIZ, etc. All these tools are well integrated in the SDE, also from the perspective of Industry 4.0. To give an example, just think of the advantages that can be derived from a realization of the style of a car through 3D printing or augmented reality.

Possible points of interest and development:

  • SDE—Stylistic design engineering (or the Ramacciotti method) applied to the design of innovative products;
  • QFD applied to the design of innovative products;
  • TRIZ applied to the design of innovative products;
  • Benchmarking applied to the design of innovative products;
  • Top-flop analysis for the design of innovative products;
  • Design for disassembly for maintenance;
  • 4.0 Digital prototyping (augmented reality);
  • 4.0 Physical prototyping (additive manufacturing).

Prof. Dr. Leonardo Frizziero
Prof. Dr. Giampiero Donnici
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Eng is an international peer-reviewed open access quarterly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1200 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

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Published Papers (2 papers)

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18 pages, 4329 KiB  
Article
Neural Network Optimization Algorithms to Predict Wind Turbine Blade Fatigue Life under Variable Hygrothermal Conditions
by Khaled Ziane, Adrian Ilinca, Sasan Sattarpanah Karganroudi and Mariya Dimitrova
Eng 2021, 2(3), 278-295; https://doi.org/10.3390/eng2030018 - 5 Jul 2021
Cited by 13 | Viewed by 4123
Abstract
Moisture and temperature are the most important environmental factors that affect the degradation of wind turbine blades, and their influence must be considered in the design process. They will first affect the resin matrix and then, possibly, the interface with the fibers. This [...] Read more.
Moisture and temperature are the most important environmental factors that affect the degradation of wind turbine blades, and their influence must be considered in the design process. They will first affect the resin matrix and then, possibly, the interface with the fibers. This work is the first to use a series of metaheuristic approaches to analyze the most recent experimental results database and to identify which resins are the most robust to moisture/temperature in terms of fatigue life. Four types of resin are compared, representing the most common types used for wind turbine blades manufacturing. Thermoset polymer resins, including polyesters and vinyl esters, were machined as coupons and tested for the fatigue in air temperatures of 20 °C and 50 °C under “dry” and “wet” conditions. The experimental fatigue data available from Sandia National Laboratories (SNL) for wind turbine-related materials have been used to build, train, and validate an artificial neural network (ANN) to predict fatigue life under different environmental conditions. The performances of three algorithms (Backpropagation BP, Particle Swarm Optimization PSO, and Cuckoo Search CS) are compared for adjusting the synaptic weights of the ANN and evaluating the efficiency in predicting the fatigue life of the materials studied, under the conditions mentioned above. For accuracy evaluation, the mean square error (MSE) is used as an objective function to be optimized by the three algorithms. Full article
(This article belongs to the Special Issue Stylistic Design Engineering (SDE))
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Review

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30 pages, 5966 KiB  
Review
Piezoresistive Sensing Approaches for Structural Health Monitoring of Polymer Composites—A Review
by Saad Nauman
Eng 2021, 2(2), 197-226; https://doi.org/10.3390/eng2020013 - 22 May 2021
Cited by 47 | Viewed by 5732
Abstract
Structural health monitoring (SHM) is an emerging paradigm of real-time in situ structural evaluation for the detection of damage and structural degradation. This is achieved while the structure is kept in-service as against traditional non-destructive evaluation (NDE) techniques which require scheduled interventions while [...] Read more.
Structural health monitoring (SHM) is an emerging paradigm of real-time in situ structural evaluation for the detection of damage and structural degradation. This is achieved while the structure is kept in-service as against traditional non-destructive evaluation (NDE) techniques which require scheduled interventions while the structure is kept offline. SHM offers great advantages over traditional regimens of condition monitoring (CM) by improving structural reliability and safety through timely detection of structural defects also known as “diagnosis”. Polymeric composite materials offer the unique opportunity of integrating different phases for designing self-sensing smart systems capable of self-diagnosis. Polymers are unique in the sense that they can be designed in various configurations as they generally have facile manufacturing procedures. Among other properties, piezoresistance is the one that can be detected in composites in real-time as a function of strain. Conductive polymers including intrinsic and extrinsic conductive polymers can be used to induce piezoresistivity in composites. Careful design procedures can be adopted to maximize the sensitivity of these piezoresistive composites in order to fully exploit the potential of this property for SHM. Various manufacturing/integration strategies can be employed to effectively use piezoresistance in composites for structural health monitoring. These include self-sensing in carbon fiber-reinforced composites, use of surface deposited/mounted sensing films and patterns, integration of filaments and yarns during reinforcement manufacturing or lay-up and impregnation of reinforcements with piezoresistive matrices. A comprehensive review of these techniques is presented with the view of their utility in the SHM of composites. A selection criterion for these techniques is also presented based on sensitivity, manufacturing method and detection capability. Full article
(This article belongs to the Special Issue Stylistic Design Engineering (SDE))
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