scholarly journals TRACING THE EMERGENCE OF DESIGN PROBLEMS AND THEIR IMPACTS ON THE COMPLEXITY OF ENGINEERING SOLUTIONS

2021 ◽  
Vol 1 ◽  
pp. 3229-3238
Author(s):  
Torben Beernaert ◽  
Pascal Etman ◽  
Maarten De Bock ◽  
Ivo Classen ◽  
Marco De Baar
Keyword(s):  
Large Scale ◽  
Fusion Reactor ◽  
Design Stage ◽  
Engineering Model ◽  
Design Problems ◽  
Nuclear Fusion Reactor ◽  
Early Design Stage ◽  
Iterative Design ◽  
Problems And Solutions ◽  
Emergent Design

AbstractThe design of ITER, a large-scale nuclear fusion reactor, is intertwined with profound research and development efforts. Tough problems call for novel solutions, but the low maturity of those solutions can lead to unexpected problems. If designers keep solving such emergent problems in iterative design cycles, the complexity of the resulting design is bound to increase. Instead, we want to show designers the sources of emergent design problems, so they may be dealt with more effectively. We propose to model the interplay between multiple problems and solutions in a problem network. Each problem and solution is then connected to a dynamically changing engineering model, a graph of physical components. By analysing the problem network and the engineering model, we can (1) derive which problem has emerged from which solution and (2) compute the contribution of each design effort to the complexity of the evolving engineering model. The method is demonstrated for a sequence of problems and solutions that characterized the early design stage of an optical subsystem of ITER.

Efficient Possibilistic Uncertainty Analysis of a Car Crash Scenario Using a Multifidelity Approach

2019 ◽  
Vol 5 (4) ◽  
Author(s):  
Markus Mäck ◽  
Michael Hanss
Keyword(s):  
Uncertainty Analysis ◽  
Large Scale ◽  
Uncertainty Propagation ◽  
Possibility Theory ◽  
Design Stage ◽  
High Fidelity ◽  
Zone Structure ◽  
Early Design Stage ◽  
Car Crash ◽  
Fidelity Model

Abstract The early design stage of mechanical structures is often characterized by unknown or only partially known boundary conditions and environmental influences. Particularly, in the case of safety-relevant components, such as the crumple zone structure of a car, those uncertainties must be appropriately quantified and accounted for in the design process. For this purpose, possibility theory provides a suitable tool for the modeling of incomplete information and uncertainty propagation. However, the numerical propagation of uncertainty described by possibility theory is accompanied by high computational costs. The necessarily repeated model evaluations render the uncertainty analysis challenging to be realized if a model is complex and of large scale. Oftentimes, simplified and idealized models are used for the uncertainty analysis to speed up the simulation while accepting a loss of accuracy. The proposed multifidelity scheme for possibilistic uncertainty analysis, instead, takes advantage of the low costs of an inaccurate low-fidelity model and the accuracy of an expensive high-fidelity model. For this purpose, the functional dependency between the high- and low-fidelity model is exploited and captured in a possibilistic way. This results in a significant speedup for the uncertainty analysis while ensuring accuracy by using only a low number of expensive high-fidelity model evaluations. The proposed approach is applied to an automotive car crash scenario in order to emphasize its versatility and applicability.

scholarly journals Parallel Implementation of Non-slicing Floorplans with MPI and OpenMP

2021 ◽  
Author(s):  
Oluvaseun Owojaiye
Keyword(s):  
Message Passing ◽  
Large Scale ◽  
Message Passing Interface ◽  
Parallel Implementation ◽  
Computation Time ◽  
Sequential Algorithm ◽  
Design Stage ◽  
Single Chip ◽  
Solution Quality ◽  
Early Design Stage

Advancement in technology has brought considerable improvement to processor design and now manufacturers design multiple processors on a single chip. Supercomputers today consists of cluster of interconnected nodes that collaborate together to solve complex and advanced computation problems. Message Passing Interface and Open Multiprocessing are the popularly used programming models to optimize sequential codes by parallelizing them on the different multiprocessor architecture that exist today. In this thesis, we parallelize the non-slicing floorplan algorithm based on Multilevel Floorplanning/placement of large scale modules using B*tree (MB*tree) with MPI and OpenMP on distributed and shared memory architectures respectively. In VLSI (Very Large Scale Integration) design automation, floorplanning is an initial and vital task performed in the early design stage. Experimental results using MCNC benchmark circuits show that our parallel algorithm produced better results than the corresponding sequential algorithm; we were able to speed up the algorithm up to 4 times, hence reducing computation time and maintaining floorplan solution quality. On the other hand, we compared both parallel versions; and the OpenMP results gave slightly better than the corresponding MPI results.

Continuous Preference Trend Mining for Optimal Product Design With Multiple Profit Cycles

2013 ◽  
Author(s):  
Jungmok Ma ◽  
Harrison M. Kim
Keyword(s):  
Product Design ◽  
Large Scale ◽  
Life Cycles ◽  
Design Stage ◽  
Early Design Stage ◽  
Data Mining Algorithms ◽  
Optimal Product Design ◽  
Predictive Design ◽  
Purchase Patterns ◽  
Trend Mining

Product and design analytics is emerging as a promising area for the analysis of large-scale data and reflection of the extracted knowledge for the design of optimal system. The Continuous Preference Trend Mining (CPTM) algorithm and a framework that are proposed in this study address some fundamental challenges in the context of product and design analytics. The first contribution is the development of a new predictive trend mining technique that captures a hidden trend of customer purchase patterns from large accumulated transactional data. Different from traditional, static data mining algorithms, the CPTM does not assume the stationarity, and dynamically extract valuable knowledge of customers over time. By generating trend embedded future data, the CPTM algorithm not only shows higher prediction accuracy in comparison with static models, but also provide essential properties that could not be achieved with a previous proposed model: avoiding an over-fitting problem, identifying performance information of constructed model, and allowing a numeric prediction. The second contribution is a predictive design methodology in the early design stage. The framework enables engineering designers to optimize product design over multiple life cycles while reflecting customer preferences and technological obsolescence using the CPTM algorithm. For illustration, the developed framework is applied to an example of tablet PC design in leasing market and the result shows that the selection of optimal design is achieved over multiple life cycles.

scholarly journals Parallel Implementation of Non-slicing Floorplans with MPI and OpenMP

2021 ◽  
Author(s):  
Oluvaseun Owojaiye
Keyword(s):  
Message Passing ◽  
Large Scale ◽  
Message Passing Interface ◽  
Parallel Implementation ◽  
Computation Time ◽  
Sequential Algorithm ◽  
Design Stage ◽  
Single Chip ◽  
Solution Quality ◽  
Early Design Stage

Advancement in technology has brought considerable improvement to processor design and now manufacturers design multiple processors on a single chip. Supercomputers today consists of cluster of interconnected nodes that collaborate together to solve complex and advanced computation problems. Message Passing Interface and Open Multiprocessing are the popularly used programming models to optimize sequential codes by parallelizing them on the different multiprocessor architecture that exist today. In this thesis, we parallelize the non-slicing floorplan algorithm based on Multilevel Floorplanning/placement of large scale modules using B*tree (MB*tree) with MPI and OpenMP on distributed and shared memory architectures respectively. In VLSI (Very Large Scale Integration) design automation, floorplanning is an initial and vital task performed in the early design stage. Experimental results using MCNC benchmark circuits show that our parallel algorithm produced better results than the corresponding sequential algorithm; we were able to speed up the algorithm up to 4 times, hence reducing computation time and maintaining floorplan solution quality. On the other hand, we compared both parallel versions; and the OpenMP results gave slightly better than the corresponding MPI results.

Using Automated Use Case Generation for Early Design Stage Functional Failure and Human Error Analysis

2019 ◽  
Author(s):  
Lukman Irshad ◽  
H. Onan Demirel ◽  
Irem Y. Tumer
Keyword(s):  
Human Error ◽  
Large Scale ◽  
Design Stage ◽  
Test Case ◽  
Use Case ◽  
Human Errors ◽  
Functional Failure ◽  
Early Design ◽  
Early Design Stage ◽  
Complex Engineered Systems

Abstract Human errors and poor ergonomics are attributed to a majority of large-scale accidents and malfunctions in complex engineered systems. Human Error and Functional Failure Reasoning (HEFFR) is a framework developed to assess potential functional failures, human errors, and their propagation paths during early design stages so that more reliable systems with improved performance and safety can be designed. In order to perform a comprehensive analysis using this framework, a wide array of potential failure scenarios need to be tested. Coming up with such use cases that can cover a majority of faults can be challenging or even impossible for a single engineer or a team of engineers. In the field of software engineering, automated test case generation techniques have been widely used for software testing. This research explores these methods to create a use case generation technique that covers both component-related and human-related fault scenarios. The proposed technique is a time based simulation that employs a modified Depth First Search (DFS) algorithm to simulate events as the event propagation is analyzed using HEFFR at each timestep. This approach is applied to a hold-up tank design problem and the results are analyzed to explore the capabilities and limitations.

Multi-Objective Design Problem of Tire Wear and Visualization of Its Pareto Solutions2

2006 ◽  
Vol 34 (3) ◽  
pp. 170-194 ◽  
Author(s):  
M. Koishi ◽  
Z. Shida
Keyword(s):  
Inverse Problems ◽  
Conceptual Design ◽  
Dimensional Space ◽  
Design Stage ◽  
Objective Functions ◽  
Pareto Solutions ◽  
Design Problems ◽  
Multi Objective ◽  
Design Engineers ◽  
Design Variables

Abstract Since tires carry out many functions and many of them have tradeoffs, it is important to find the combination of design variables that satisfy well-balanced performance in conceptual design stage. To find a good design of tires is to solve the multi-objective design problems, i.e., inverse problems. However, due to the lack of suitable solution techniques, such problems are converted into a single-objective optimization problem before being solved. Therefore, it is difficult to find the Pareto solutions of multi-objective design problems of tires. Recently, multi-objective evolutionary algorithms have become popular in many fields to find the Pareto solutions. In this paper, we propose a design procedure to solve multi-objective design problems as the comprehensive solver of inverse problems. At first, a multi-objective genetic algorithm (MOGA) is employed to find the Pareto solutions of tire performance, which are in multi-dimensional space of objective functions. Response surface method is also used to evaluate objective functions in the optimization process and can reduce CPU time dramatically. In addition, a self-organizing map (SOM) proposed by Kohonen is used to map Pareto solutions from high-dimensional objective space onto two-dimensional space. Using SOM, design engineers see easily the Pareto solutions of tire performance and can find suitable design plans. The SOM can be considered as an inverse function that defines the relation between Pareto solutions and design variables. To demonstrate the procedure, tire tread design is conducted. The objective of design is to improve uneven wear and wear life for both the front tire and the rear tire of a passenger car. Wear performance is evaluated by finite element analysis (FEA). Response surface is obtained by the design of experiments and FEA. Using both MOGA and SOM, we obtain a map of Pareto solutions. We can find suitable design plans that satisfy well-balanced performance on the map called “multi-performance map.” It helps tire design engineers to make their decision in conceptual design stage.

scholarly journals A Novel Methodology for Adaptive Coordination of Multiple Controllers in Electrical Grids

Mathematics ◽  
2021 ◽  
Vol 9 (13) ◽  
pp. 1474
Author(s):  
Ruben Tapia-Olvera ◽  
Francisco Beltran-Carbajal ◽  
Antonio Valderrabano-Gonzalez ◽  
Omar Aguilar-Mejia
Keyword(s):  
Power Systems ◽  
Power System ◽  
Electric Power ◽  
Large Scale ◽  
Short Circuit ◽  
Dynamic Performance ◽  
Low Frequency ◽  
Electric Power System ◽  
Design Stage ◽  
Positive Interaction

This proposal is aimed to overcome the problem that arises when diverse regulation devices and controlling strategies are involved in electric power systems regulation design. When new devices are included in electric power system after the topology and regulation goals were defined, a new design stage is generally needed to obtain the desired outputs. Moreover, if the initial design is based on a linearized model around an equilibrium point, the new conditions might degrade the whole performance of the system. Our proposal demonstrates that the power system performance can be guaranteed with one design stage when an adequate adaptive scheme is updating some critic controllers’ gains. For large-scale power systems, this feature is illustrated with the use of time domain simulations, showing the dynamic behavior of the significant variables. The transient response is enhanced in terms of maximum overshoot and settling time. This is demonstrated using the deviation between the behavior of some important variables with StatCom, but without or with PSS. A B-Spline neural networks algorithm is used to define the best controllers’ gains to efficiently attenuate low frequency oscillations when a short circuit event is presented. This strategy avoids the parameters and power system model dependency; only a dataset of typical variable measurements is required to achieve the expected behavior. The inclusion of PSS and StatCom with positive interaction, enhances the dynamic performance of the system while illustrating the ability of the strategy in adding different controllers in only one design stage.

scholarly journals Hospital Construction Cost Affecting Their Lifecycle: An Italian Overview

Healthcare ◽  
2021 ◽  
Vol 9 (7) ◽  
pp. 888
Author(s):  
Leopoldo Sdino ◽  
Andrea Brambilla ◽  
Marta Dell’Ovo ◽  
Benedetta Sdino ◽  
Stefano Capolongo
Keyword(s):  
Healthcare Services ◽  
Construction Cost ◽  
Design Stage ◽  
Quality Healthcare ◽  
Healthcare Facilities ◽  
Early Design Stage ◽  
Hospital Facility ◽  
Italian Context ◽  
The Cost ◽  
Cost Components

The need for 24/7 operation, and the increasing requests of high-quality healthcare services contribute to framing healthcare facilities as a complex topic, also due to the changing and challenging environment and huge impact on the community. Due to its complexity, it is difficult to properly estimate the construction cost in a preliminary phase where easy-to-use parameters are often necessary. Therefore, this paper aims to provide an overview of the issue with reference to the Italian context and proposes an estimation framework for analyzing hospital facilities’ construction cost. First, contributions from literature reviews and 14 case studies were analyzed to identify specific cost components. Then, a questionnaire was administered to construction companies and experts in the field to obtain data coming from practical and real cases. The results obtained from all of the contributions are an overview of the construction cost components. Starting from the data collected and analyzed, a preliminary estimation tool is proposed to identify the minimum and maximum variation in the cost when programming the construction of a hospital, starting from the feasibility phase or the early design stage. The framework involves different factors, such as the number of beds, complexity, typology, localization, technology degree and the type of maintenance and management techniques. This study explores the several elements that compose the cost of a hospital facility and highlights future developments including maintenance and management costs during hospital facilities’ lifecycle.

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