Abstract: Metasurfaces provide unprecedented routes to manipulations on electromagnetic waves, which can realize many exotic functionalities. Despite the rapid development of metasurfaces in recent years, the design process of metasurface is still time-consuming and computational resource-consuming. Moreover, it is quite complicated for layman users to design metasurfaces as plenty of specialized knowledge is required. In this work, a metasurface design method named REACTIVE is proposed on the basis of deep learning, as deep learning method has shown its natural advantages and superiorities in mining undefined rules automatically in many fields. REACTIVE is capable of calculating metasurface structure directly through a given design target; meanwhile, it also shows the advantage in making the design process automatic, more efficient, less time-consuming, and less computational resource-consuming. Besides, it asks for less professional knowledge, so that engineers are required only to pay attention to the design target. Herein, a triple-band absorber is designed using the REACTIVE method, where a deep learning model computes the metasurface structure automatically through inputting the desired absorption rate. The whole design process is achieved 200 times faster than the conventional one, which convincingly demonstrates the superiority of this design method. REACTIVE is an effective design tool for designers, especially for laymen users and engineers.

Abstract: The need of a neutron source for the qualification of materials to be used in future fusion power reactors have been recognized in the European (EU) fusion programme for many years. The construction and exploitation of this facility is presently considered to be in the critical path of DEMO. This issue prompted the EU to launch activities for the design and engineering of the IFMIF-DONES (International Fusion Materials Irradiation Facility-DEMO Oriented Neutron Source) facility based on and taking profit of the results obtained in the IFMIF/EVEDA (Engineering Validation and Engineering Design Activities) project, presently conducted in the framework of the EU-Japan Bilateral Agreement on the Broader Approach to Fusion. These activities and R&D work for the IFMIF-DONES Plant are presently taking place in the framework of a work package of the EUROfusion Consortium, in direct collaboration with the Fusion for Energy Organization. The main objective of these activities is to consolidate the design and the underlying technology basis in order to be ready for IFMIF-DONES construction as early as possible. The paper presents the main engineering results for a generic site obtained during the first years of design work, as indicated in the recently released IFMIF-DONES Preliminary Engineering Design Report, making emphasis on the design evolution from previous phases and on the critical issues to be further developed in the near future. The proposed European site to host the facility (Granada, Spain) is briefly introduced as well.

Abstract: We review progress in designing and transforming multi-functional yield-stress fluids and give a perspective on the current state of knowledge that supports each step in the design process. We focus mainly on the rheological properties that make yield-stress fluids so useful and the trade-offs which need to be considered when working with these materials. Thinking in terms of “design with” and “design of” yield-stress fluids motivates how we can organize our scientific understanding of this field. “Design with” involves identification of rheological property requirements independent of the chemical formulation, e.g. for 3D direct-write printing which needs to accommodate a wide range of chemistry and material structures. “Design of” includes microstructural considerations: conceptual models relating formulation to properties, quantitative models of formulation-structure-property relations, and chemical transformation strategies for converting effective yield-stress fluids to be more useful solid engineering materials. Future research directions are suggested at the intersection of chemistry, soft-matter physics, and material science in the context of our desire to design useful rheologically-complex functional materials.

Abstract: The Construction Industry is a complex and fragmented industry worldwide with regards to its supply chain, products, and processes, and is faced with a similar dilemma as faced by manufacturers during its time in past decades. Scope, time, and cost are the triple constraints of project management and leading factors in defining the project performance. Productivity and efficiency of each construction project is measured through its triple constraints, therefore the factors that affect project success are significantly important. Despite the importance of understanding project performance indicators, few empirical studies have been conducted over the last decade in terms of analyzing the factors that determine the performance of high-rise buildings in Engineering, Procurement, and Construction (EPC) projects. Hence, the aim of this paper is to analyze and rank EPC critical activities across large-scale residential construction projects in Iran, by using the TOPSIS method as a multi-attribute group decision-making technique. Results indicate that engineering design, project planning and controls are significant factors contributing to the project performance. In addition, engineering has a pivotal role in project performance and this significance is followed by the construction phase. On the contrary, all believe procurement is more important than Construction phase.

Abstract: Additive manufacturing (AM) continues to rise in popularity due to its various advantages over traditional manufacturing processes. AM interests industry, but achieving repeatable production quality remains problematic for many AM technologies. Thus, modeling different process variables in AM using machine learning can be highly beneficial in creating useful knowledge of the process. Such developed artificial neural network (ANN) models would aid designers and manufacturers to make informed decisions about their products and processes. However, it is challenging to define an appropriate ANN topology that captures the AM system behavior. Toward that goal, an approach combining dimensional analysis conceptual modeling (DACM) and classical ANNs is proposed to create a new type of knowledge-based ANN (KB-ANN). This approach integrates existing literature and expert knowledge of the AM process to define a topology for the KB-ANN model. The proposed KB-ANN is a hybrid learning network that encompasses topological zones derived from knowledge of the process and other zones where missing knowledge is modeled using classical ANNs. The usefulness of the method is demonstrated using a case study to model wall thickness, part height, and total part mass in a fused deposition modeling (FDM) process. The KB-ANN-based model for FDM has the same performance with better generalization capabilities using fewer weights trained, when compared to a classical ANN.

Abstract: The use of Building Information Modeling (BIM) for building energy modeling (BEM) is a recent evolution in design practice. The success of BIM-BEM execution relies on considering two important aspects: process and technology. In this paper, a review of the literature using a systematic approach is proposed to highlight that these two aspects are rarely addressed concurrently. This review includes an overview of the BIM-BEM process and recent technological developments, while elaborating on the main research gap. In order to address the identified research gap, the creation of a framework is proposed that would embed the technological approaches within the whole design process by using a proper Level Of Development (LOD) and information requirements via Model View Definition (MVD).

Abstract: Engineering design optimization in real life is a challenging global optimization problem, and many meta-heuristic algorithms have been proposed to obtain the global best solutions. An excellent meta-heuristic algorithm has two symmetric search capabilities: local search and global search. In this paper, an improved Butterfly Optimization Algorithm (BOA) is developed by embedding the cross-entropy (CE) method into the original BOA. Based on a co-evolution technique, this new method achieves a proper balance between exploration and exploitation to enhance its global search capability, and effectively avoid it falling into a local optimum. The performance of the proposed approach was evaluated on 19 well-known benchmark test functions and three classical engineering design problems. The results of the test functions show that the proposed algorithm can provide very competitive results in terms of improved exploration, local optima avoidance, exploitation, and convergence rate. The results of the engineering problems prove that the new approach is applicable to challenging problems with constrained and unknown search spaces.

Abstract: . The wind energy industry relies heavily on computational fluid dynamics (CFD) to analyze new turbine designs. To utilize CFD earlier in the design process, where lower-fidelity methods such as blade element momentum (BEM) are more common, requires the development of new tools. Tools that utilize numerical optimization are particularly valuable because they reduce the reliance on design by trial and error. We present the first comprehensive 3-D CFD adjoint-based shape optimization of a modern 10 MW offshore wind turbine. The optimization problem is aligned with a case study from International Energy Agency (IEA) Wind Task 37, making it possible to compare our findings with the BEM results from this case study and therefore allowing us to determine the value of design optimization based on high-fidelity models. The comparison shows that the overall design trends suggested by the two models do agree, and that it is particularly valuable to consult the high-fidelity model in areas such as root and tip where BEM is inaccurate. In addition, we compare two different CFD solvers to quantify the effect of modeling compressibility and to estimate the accuracy of the chosen grid resolution and order of convergence of the solver. Meshes up to 14×106 cells are used in the optimization whereby flow details are resolved. The present work shows that it is now possible to successfully optimize modern wind turbines aerodynamically under normal operating conditions using Reynolds-averaged Navier–Stokes (RANS) models. The key benefit of a 3-D RANS approach is that it is possible to optimize the blade planform and cross-sectional shape simultaneously, thus tailoring the shape to the actual 3-D flow over the rotor. This work does not address evaluation of extreme loads used for structural sizing, where BEM-based methods have proven very accurate, and therefore will likely remain the method of choice.

Abstract: There has been an increased emphasis on designing integrated STEM learning environments for K-12 students that facilitate seamless learning of disciplinary concepts infused with science inquiry, engineering design, mathematical reasoning, and technological skills. However, there is limited prior research investigating how to facilitate such integrated STEM learning in formal classrooms that go beyond a simple combination of the different subject areas and instead enable teaching and learning of disciplinary concepts infused with scientific inquiry, engineering design, mathematical reasoning, and 21st century technological skills. In this paper, we investigate the affordances of using an educational Computer Aided Design tool, Energy 3D, and corresponding curricular materials to support such integrated STEM learning anchored in the engineering design process. We present an exploratory case study that was conducted in a middle school in the US, where a project-based learning approach was followed and students were asked to design a low-cost energy-efficient home within a given budget using the Energy3D CAD tool. Findings indicate that students learned to engage in the design process and demonstrated practices of idea fluency and systematic experimentation; practices usually representative of informed designers. During the design process while analyzing the problem space, generating ideas, and evaluating solutions, they developed better understanding of the relationships between variables and underlying science concepts, used various mathematical analysis tools and graphical representations embedded in the available technology to inform their engineering design decisions. The learning environment using Energy3D afforded formative feedback to help students understand relationship between variables, provided converging evidences using multiple analytical tools, and enabled visual problem decomposition using suboptimal model to engage students in integrated STEM learning. This study provides a platform for future research investigating the effectiveness of educational CAD tools and curricular scaffolds designed specifically for K-12 students for supporting integrated STEM learning anchored in the design process.

Abstract: Building design review is the procedure of checking a design against codes and standard provisions to satisfy the accuracy of the design and identify non-compliances before construction begins. The current approaches for conducting the design review process in an automatic or semi-automatic manner are either based on proprietary, domain-specific or hard-coded rule-based mechanisms. These methods may be effective in their specific applications, but they have the downsides of being costly to maintain, inflexible to modify, and lack a generalized framework of rules and regulations modeling that can adapt to various engineering design realms, and thus don’t support a neutral data standard. They are often referred to as ‘Black Box’ or ‘Gray Box’ approaches. This research offers a new comprehensive framework that reduces the limitations of the cited methods. Building regulations, for instance, are legal documents transcribed and approved by professionals to be interpreted and applied by people. They are hardly as precise as formal logic. Engineers, architects, and contractors can read those technical documents and transform them into scientific notations and software applications. They can extract any data they need, reason about it, and apply it at various phases of the project. How these extraction and use are carried out is a critical component of automating the design review process. The chief goal is to address this issue by developing a Generalized Adaptive Framework (GAF) for a neutral data standard (Industry Foundation Classes (IFC)) that enables automating the code compliance checking processes to achieve design efficiency and cost-effectiveness. The objectives of this study comprise i) to develop a theoretical background to an adaptive framework that supports a neutral data standard for transforming the written code regulations and rules into a computable model, and ii) to define the various modules required for computerizing of the code compliance verification process.

Abstract: Approximate computing is an emerging paradigm for developing highly energy-efficient computing systems such as various accelerators. In the literature, many libraries of elementary approximate circuits have already been proposed to simplify the design process of approximate accelerators. Because these libraries contain from tens to thousands of approximate implementations for a single arithmetic operation it is intractable to find an optimal combination of approximate circuits in the library even for an application consisting of a few operations. An open problem is "how to effectively combine circuits from these libraries to construct complex approximate accelerators". This paper proposes a novel methodology for searching, selecting and combining the most suitable approximate circuits from a set of available libraries to generate an approximate accelerator for a given application. To enable fast design space generation and exploration, the methodology utilizes machine learning techniques to create computational models estimating the overall quality of processing and hardware cost without performing full synthesis at the accelerator level. Using the methodology, we construct hundreds of approximate accelerators (for a Sobel edge detector) showing different but relevant tradeoffs between the quality of processing and hardware cost and identify a corresponding Pareto-frontier. Furthermore, when searching for approximate implementations of a generic Gaussian filter consisting of 17 arithmetic operations, the proposed approach allows us to identify approximately 103 highly relevant implementations from 1023 possible solutions in a few hours, while the exhaustive search would take four months on a high-end processor.

Abstract: The requirements of Human Factors and Ergonomics (HF/E) in engineering design must be satisfied, including usability, safety, reliability, and operability in the workplace and work environment. Thi...

Abstract: To date, topology optimization has proven to be the most beneficial, yet most complex, structural optimization technique available to engineers and scientists. However, particularly in the aerospace industry, there exists little application to real-world design problems, including all the complexities required to ensure that the resulting design complies with the regulations. In this paper, a topology optimization algorithm is developed to solve aerospace design problems. Two problems are considered in this work. The first is the design of an aircraft landing gear. The final topology is compared to a design found using standard engineering practices to show the benefits of topology optimization. The second problem uses the topology optimization methodology to design an aircraft engine mount. The main goal of this paper is to demonstrate that topology optimization can be used to find minimum weight structures to aerospace design problems, using Federal Aviation Regulations to ensure that the resulting designs meet the airworthiness standards of the aviation industry.

Abstract: Virtual reality (VR) technology has become ever mature today with affordable and yet powerful hardware. In the manufacturing industry, there is a growing interest of adopting VR to improve existing work procedures. Factory layout planning (FLP) is a long standing area in production engineering that sees great potentials of VR integration. Virtual reality supported layout planning (VLP) is gaining wider attention in research and practice as the virtual environment allows designers to test out “what if” scenarios in relative ease. However, previous research of VLP mostly focus on general layout planning but not the detailed level planning. Also, it is reported that the virtual modeling process is time-consuming and costly. In this study, we propose a point cloud based virtual factory modelling approach for the VLP tasks. It incorporates point cloud representation of physical environment with CAD data to model the virtual factory with the aims of simplifying the modelling process and improving decision-making for the VLP tasks. The proposed approach is exemplified and refined through three industrial cases. The implementations and results of the cases are highlighted and discussed in details. At the end, a general guidance for VLP is extracted and presented for future point cloud based VR support in FLP tasks.

Abstract: Isolation of design phase from construction has made the design changes inevitable in construction projects. Extensive literature appraisal has acknowledged the detrimental effect of design changes on project performances. However, the impact and causes of design changes have been divided up, either separately or project specific. As a result, the relationship between impact and causes of design changes could not be established for general construction. The primary objective of this paper is to examine the impact of design changes on project cost and identifying actions responsible for these changes. The objectives of the study were achieved through a systematic review of past literature published in well-established journals, and contents analyzed. From the extensive literature review, it was established that the design change is one of the predominant factors to cost overrun, and in some cases, may upshot into cost overrun between 5 and 40% of the project cost. Also, many causes of design changes resulting in cost overrun within the perspective of the owner, consultant, and contractors are explored. Some projects experienced closure as a result of owner induced design changes, although these changes may not be significant in number. Design changes as a result of consultants and contractors in some cases might have reduced impact but are frequent. For each consideration, most events leading to design changes can be eliminated by improving on communication and coordination between stakeholders. The main contribution of this research is to bring together the impact and causes of design changes on cost under one platform for effectively managing the design process.