Deep Component-Based Neural Network Energy Modelling for Early Design Stage Prediction

2019 ◽  
pp. 21-36
Author(s):  
Sundaravelpandian Singaravel ◽  
Philipp Geyer
Keyword(s):  
Neural Network ◽  
Design Stage ◽  
Early Design ◽  
Early Design Stage ◽  
Energy Modelling

Prediction of tire pattern noise in early design stage based on convolutional neural network

2021 ◽  
Vol 172 ◽  
pp. 107617
Author(s):  
Sang-Kwon Lee ◽  
Hwajin Lee ◽  
Jiseon Back ◽  
Kanghyun An ◽  
Youngsam Yoon ◽  
...  
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Design Stage ◽  
Early Design ◽  
Early Design Stage ◽  
Pattern Noise

A hybrid metamodel-based method for quick energy prediction in the early design stage

2021 ◽  
pp. 128825
Author(s):  
Shuyan Zhu ◽  
Yufeng Zhang ◽  
Ke Xiang ◽  
Chenlong Ma
Keyword(s):  
Design Stage ◽  
Early Design ◽  
Energy Prediction ◽  
Early Design Stage

Identification of Human Errors During Early Design Stage Functional Failure Analysis

2018 ◽  
Author(s):  
Lukman Irshad ◽  
Salman Ahmed ◽  
Onan Demirel ◽  
Irem Y. Tumer
Keyword(s):  
Failure Analysis ◽  
Human Error ◽  
System Level ◽  
Design Stage ◽  
Human Factors Engineering ◽  
Human Errors ◽  
Functional Failure ◽  
Early Design ◽  
Early Design Stage ◽  
Early Design Stages

Detection of potential failures and human error and their propagation over time at an early design stage will help prevent system failures and adverse accidents. Hence, there is a need for a failure analysis technique that will assess potential functional/component failures, human errors, and how they propagate to affect the system overall. Prior work has introduced FFIP (Functional Failure Identification and Propagation), which considers both human error and mechanical failures and their propagation at a system level at early design stages. However, it fails to consider the specific human actions (expected or unexpected) that contributed towards the human error. In this paper, we propose a method to expand FFIP to include human action/error propagation during failure analysis so a designer can address the human errors using human factors engineering principals at early design stages. To explore the capabilities of the proposed method, it is applied to a hold-up tank example and the results are coupled with Digital Human Modeling to demonstrate how designers can use these tools to make better design decisions before any design commitments are made.

A review of the Sustainability and Parametric Design Approach of Complex Tall Buildings at an Early Design Stage

2021 ◽  
Author(s):  
Aiman H. H. Al-Masoodi ◽  
F. H. Alkhatib ◽  
Nasir Shafiq ◽  
Al-Hussein M. H. Al-Aidrous
Keyword(s):  
Parametric Design ◽  
Tall Buildings ◽  
Design Approach ◽  
Design Stage ◽  
Early Design ◽  
Early Design Stage
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