scholarly journals Multi-Objective Optimization Method for the Shape of Large-Space Buildings Dominated by Solar Energy Gain in the Early Design Stage

2021 ◽  
Vol 9 ◽  
Author(s):  
Longwei Zhang ◽  
Chao Wang ◽  
Yu Chen ◽  
Lingling Zhang
Keyword(s):  
Energy Efficiency ◽  
Solar Radiation ◽  
Solar Energy ◽  
Optimization Method ◽  
Design Stage ◽  
Large Space ◽  
Early Design ◽  
Early Design Stage ◽  
Building Shape ◽  
Key Indicators

Large-space buildings feature a sizable interface for receiving solar radiation, and optimizing their shape in the early design stage can effectively increase their solar energy harvest while considering both energy efficiency and space utilization. A large-space building shape optimization method was developed based on the “modeling-calculation-optimization” process to transform the “black box” mode in traditional design into a “white box” mode. First, a two-level node control system containing core space variables and envelope variables is employed to construct a parametric model of the shape of a large-space building. Second, three key indicators, i.e., annual solar radiation, surface coefficient, and space efficiency, are used to representatively quantify the performance in terms of sunlight capture, energy efficiency, and space utilization. Finally, a multi-objective genetic algorithm is applied to iteratively optimize the building shape, and the Pareto Frontier formed by the optimization results provides the designer with sufficient alternatives and can be used to assess the performance of different shapes. Further comparative analysis of the optimization results can reveal the typical shape characteristics of the optimized solutions and potentially determine the key variables affecting building performance. In a case study of six large-space buildings with typical shapes, the solar radiation of the optimized building shape solutions was 13.58–39.74% higher than that of reference buildings 1 and 3; compared with reference buildings 2 and 4, the optimized solutions also achieved an optimal balance of the three key indicators. The results show that the optimization method can effectively improve the comprehensive performance of buildings.

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.

scholarly journals A Comprehensive Method of Apportioning Reliability Goals for New Product of Hydraulic Excavator

2019 ◽  
Vol 2019 ◽  
pp. 1-11 ◽  
Author(s):  
Wenting Liu ◽  
Qingliang Zeng ◽  
Lirong Wan ◽  
Chenglong Wang
Keyword(s):  
Real Life ◽  
Chemical System ◽  
Design Stage ◽  
Hydraulic Excavator ◽  
Effect Analysis ◽  
Reliability Allocation ◽  
Early Design ◽  
Construction Machinery ◽  
Early Design Stage ◽  
Fmea Method

It is important to allocate a reliability goal for the hydraulic excavator in the early design stage of the new system. There are some effective methods for setting reliability target and allocating its constituent subsystems in the field of aerospace, electric, vehicles, railways, or chemical system, but until now there is no effective method for the hydraulic excavator or engineering machinery. In this paper, an approach is proposed which combines with the conventional reliability allocation methods for setting reliability goals and allocating the subsystem and parts useful in the early design stage of the hydraulic excavator newly developed. It includes Weibull analysis method, modified Aeronautical Radio Inc. (ARINC) method, and modified systematic failure mode and effect analysis (FMEA) method. After completing reliability allocation, it is necessary to organize the designers and experts to evaluate the rationality of the reliability target through FEMA analysis considering feasibility of the improvement technically for the part which was new developed or had fault in its predecessor. The proposed approach provides an easy methodology for allocate a practical reliability goal for the hydraulic excavator capturing the real life behavior of the product. It proposes a simple and unique way to capture the improvement of the subsystems or components of the hydraulic excavator. The proposed approach could be extended to consider other construction machinery equipment and have practicality value to research excellent mechanical product.

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