Combining structural performance and designer preferences in evolutionary design space exploration

This paper addresses the need to consider both quantitative performance goals and qualitative requirements in conceptual design. A new computational approach for design space exploration is proposed that extends existing interactive evolutionary algorithms for increased inclusion of designer preferences, overcoming the weaknesses of traditional optimization that have limited its use in practice. This approach allows designers to set the evolutionary parameters of mutation rate and generation size, in addition to parent selection, in order to steer design space exploration. This paper demonstrates the potential of this approach through a numerical parametric study, a software implementation, and series of case studies

Office of Exploration: Exploration studies technical report. Volume 2: Studies approach and results

The NASA Office of Exploration has been tasked with defining and recommending alternatives for an early 1990's national decision on a focused program of human exploration of the solar system. The Mission Analysis and System Engineering (MASE) group, which is managed by the Exploration Studies Office at the Johnson Space Center, is responsible for coordinating the technical studies necessary for accomplishing such a task. This technical report describes the process that has been developed in a case study approach. The four case studies that were developed in FY88 include: (1) human expedition to Phobos; (2) human expeditions to Mars; (3) lunar observatory; and (4) lunar outpost to early Mars evolution. The final outcome of this effort is a set of programmatic and technical conclusions and recommendations for the following year's work. Volume 2 describes the case study process, the technical results of each of the case studies, and opportunities for additional study. Included in the discussion of each case study is a description of the mission key features and profile. Mission definition and manifesting are detailed, followed by a description of the mission architecture and infrastructure. Systems concepts for the required orbital nodes, transportation systems, and planetary surface systems are discussed. Prerequisite implementation plans resulting from the synthesized case studies are described and in-depth assessments are presented

Evolutionary Multiobjective Design in Automotive Development

This paper describes the use of evolutionary algorithms to solve multiobjective optimization problems arising at different stages in the automotive design process. The problems considered are black box optimization scenarios: definitions of the decision space and the design objectives are given, together with a procedure to evaluate any decision alternative with regard to the design objectives, e.g., a simulation model. However, no further information about the objective function is available. In order to provide a practical introduction to the use of multiobjective evolutionary algorithms, this article explores the three following case studies: design space exploration of road trains, parameter optimization of adaptive cruise controllers, and multiobjective system identification. In addition, selected research topics in evolutionary multiobjective optimization will be illustrated along with each case study, highlighting the practical relevance of the theoretical results through real-world application examples. The algorithms used in these studies were implemented based on the PISA (Platform and Programming Language Independent Interface for Search Algorithm) framework. Besides helping to structure the presentation of different algorithms in a coherent way, PISA also reduces the implementation effort considerabl

Impact of Mixed Reality implementation on early-stage interactive-product design process

This article proposes a novel approach towards quick concept generation and validation of interactive-product behaviours. When designing for user-product interactions, designers have to consider spatial and behavioural elements besides form/tangible aspects and perform quick-validation of the generated concepts often done through functional prototyping at later design stages. As a result, the designed-outcomes often depend on parameters like designer’s familiarity with the design tools used, the level of fidelity achieved while prototyping and the frequency of design-iterations, limiting a thorough-exploration of concept-space and outcomes’ creativity at the early design stages. This research targets such dependencies and non-creative hindrances at concept generation stage through a Mixed Reality implementation. This work establishes requirements for creating a suitable design-tool and presents a proof-of-concept use-case. A design task to ideate, create and revise concepts of playful product-behaviours swiftly was performed to assess the impact of the implemented method. In an empirical study, a broader exploration of solution-space and an overall improvement in creative output-flow was observed when compared to the design-outcomes in the traditional storyboard design approach. Though the implemented design-tool’s unfamiliarity and capability presented a challenge, a significant increase in usage of iterative concept-design behaviour was observed throughout the study

Exploring the fit between CSR and innovation

An exploration of the fit or space between CSR and innovation is presented, based on the RESPONSE project, a 15-month study involving 60 SMEs throughout Europe. The main practical output of the project was the Social Innovation model, yet a conceptual understanding of CSR and innovation is best advanced through the three hypotheses that constitute the conclusions of the project: H1) The diffusion of CSR should be modelled on the diffusion of innovation; H2) CSR implementation and innovation can be configured to form a virtuous circle; and H3) There is a maturity path toward true integration of CSR and innovation. These three hypotheses inform, respectively, on the background, results and development of the project. H1 is framed within the context of the original European Commission call and proposal; H2 ties in with the Social Innovation model; and H3 is discussed in the light of a short case involving a high-performing SME. Since the hypotheses were the result of the project, we do not attempt to prove them here, but discuss their significance, with the idea that further research and community development will fully evaluate their accuracy.Corporate social responsibility; innovation; small and medium-size enterprises;

Is Big Data for everyone? The challenges of Big Data adoption in SMEs

The aim of this paper is to present an investigative study on the concept of Big Data and its challenges towards implementation in manufacturing SMEs. Big Data aims to facilitate the collaborative approach in SMEs through the creation of real time data visualization to address key challenges to many of the market variations for every sector SMEs. Although, earlier research studies have highlighted the importance of Big Data from technological perspectives, this study focuses towards SMEs due to its feasibility and flexibility within the market space. This research aims to investigate the use of case study approach for the re-use, adoption and understanding of strategic future direction from the findings. The findings and early analysis from this paper could be referred by researchers when addressing the use of big data analytics within manufacturing SMEs. Finally, the paper provides a key strategic point towards the exploration of Big Data within SMEs

Robust building scheme design optimization for uncertain performance prediction

Design exploration is a vital part of the building design process that aims at identifying the best-performing design with regard to the requirements of the client and building regulations. Building performance simulation can support this “explorative” process, its potential however being restricted by the fact that all design parameters are subject to uncertainty. In addition, while the need for an efficient exploration of the design space has resulted in the integration of optimization into the design process, the majority of existing research treats uncertainty quantification and optimization as separate processes. Finally, candidate designs are commonly evaluated with respect to only one or two design criteria, while the multi-dimensionality of real-world problems calls for integrated design solutions that meet several – often-conflicting – objectives. A new approach is thus developed that aims to help designers identify robust Pareto-optimal solutions that satisfy several design criteria, while remaining optimal regardless of the uncertainty in boundary conditions. Through its implementation to a real-world case-study building, the novel approach is found to be able to identify optimum solutions that preserve their optimality over the entire range of uncertain performance scenarios

Optimization of patch antennas via multithreaded simulated annealing based design exploration

In this paper, we present a new software framework for the optimization of the design of microstrip patch antennas. The proposed simulation and optimization framework implements a simulated annealing algorithm to perform design space exploration in order to identify the optimal patch antenna design. During each iteration of the optimization loop, we employ the popular MEEP simulation tool to evaluate explored design solutions. To speed up the design space exploration, the software framework is developed to run multiple MEEP simulations concurrently. This is achieved using multithreading to implement a manager-workers execution strategy. The number of worker threads is the same as the number of cores of the computer that is utilized. Thus, the computational runtime of the proposed software framework enables effective design space exploration. Simulations demonstrate the effectiveness of the proposed software framework

Fog computing, applications , security and challenges, review

The internet of things originates a world where on daily basis objects can join the internet and interchange information and in addition process, store, gather them from the nearby environment, and effectively mediate on it. A remarkable number of services might be imagined by abusing the internet of things. Fog computing which is otherwise called edge computing was introduced in 2012 as a considered is a prioritized choice for the internet of things applications. As fog computing extend services of cloud near to the edge of the network and make possible computations, communications, and storage services in proximity to the end user. Fog computing cannot only provide low latency, location awareness but also enhance real-time applications, quality of services, mobility, security and privacy in the internet of things applications scenarios. In this paper, we will summarize and overview fog computing model architecture, characteristic, similar paradigm and various applications in real-time scenarios such as smart grid, traffic control system and augmented reality. Finally, security challenges are presented