Seismic structural design methodology for inelastic shear buildings that regulates floor accelerations

2019 ◽  
Vol 187 ◽  
pp. 428-443 ◽  
Author(s):  
Assaf Shmerling ◽  
Robert Levy
Keyword(s):  
Structural Design ◽  
Design Methodology ◽  
Inelastic Shear ◽  
Shear Buildings

Reconnecting governance configuration variables to enterprises contingency factors for optimizing productivity at the start-up level

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Walter Amedzro St-Hilaire
Keyword(s):  
Structural Design ◽  
Design Methodology ◽  
System Analysis ◽  
System Control ◽  
Ceteris Paribus ◽  
New Approach ◽  
Content Type ◽  
Start Up ◽  
The Future

PurposeThe article broaches the important topic of the relationships between governance operationalizations and productivity at the start-up level. It proposes a new approach to reconnect the contingency factors to the optimization of productivity. This helps us to identify the changing characteristics that influence the determinants of decisions, actions and management of the technological projects of the mainly innovative enterprises.Design/methodology/approachThe study uses techniques that effectively solve unobserved endogeneity and heterogeneity problems in enterprises: an empirical–structural design. With this method, this study enables rich empirical conceptualization and helps with extending theory. However, there is a need to further the research by taking into account the system analysis and the complexity of the research object: one of the options might be to explore a possible follow-up of the research through drawing on ethnostatistics and qualimetrics.FindingsThe analysis reveals that the phenomenon of technological project productivity in operational governance context is thus manifested by the coexistence of the applied governance configuration variables, the contingency factors operationalization, the optimizing productivity mechanisms and this with the secular innovation and stagnation and stagnation. Ceteris paribus, the governance operationalizations have an important role in the productivity of technological projects of the innovative enterprises.Originality/valueThis research is the first to mobilize as major determinants of the operationalization of governance, the oversight of the capital, the dividend strategy and the system control, the managerial follow-up, the detection of opportunistic behaviours and the application of governing incentives (among others) as governance configuration variables in order to highlight their interactions with productivity in the innovative firm technological projects. For this reason alone, the paper will be referenced by other authors in the future.

scholarly journals Facility Design Variations using a Strong Component based Methodology

2018 ◽  
pp. 1-5
Keyword(s):  
Structural Design ◽  
Design Methodology ◽  
Facility Layout ◽  
Strong Component ◽  
Facility Design ◽  
Layout Problem ◽  
Qualitative And Quantitative ◽  
Product And Process ◽  
And Storage ◽  
Relevant Factors

In this presentation is shown how a strong component-based facility layout design methodology addresses the design problem when some design relevant factors are adapted. The strong-component-based methodology proposes a unique structural design, a non-dedicated facility, capable of producing a family of products that require similar operations and workstations, which can be shared. Simultaneously, the methodology suggests that this structure can take advantage of both, known classical layout designs, product and process, in a single or multiple machine environments. In addition, adding or reducing a number of stations, adding feeding and storage facilities, considering qualitative and quantitative coefficients are some of the factors variations that can be addressed when using this methodology. In consequence, organisational impacts of the facility layout problem are addressed and solutions that can be obtained using the strong component-based methodology are suggested when the interrelations diagram are crated, an essential diagram which eases the facility design goals.

Earthquake response of inelastic shear buildings

1966 ◽  
Vol 56 (2) ◽  
pp. 393-408
Author(s):  
S. L. Lee ◽  
D. S. Perelman ◽  
J. F. Fleming
Keyword(s):  
Plastic Deformation ◽  
Structural Material ◽  
Strain Hardening ◽  
Building Codes ◽  
Earthquake Response ◽  
Seismic Shear ◽  
Inelastic Shear ◽  
Shear Building ◽  
Hardening Coefficient ◽  
Shear Buildings

abstract A typical multi-story bilinear inelastic shear building is subjected to idealized earthquake motions. The dependence of the deflection of the structure, the maximum shear in each story, and the extent of the plastic deformation upon the period and amplitude of the earthquake, and the strain hardening coefficient of the structural material is shown. It is noted that, at least within the scope of this study, the maximum shears in the stories of the building are larger than the minimum seismic shear requirements of most of the building codes.

Integrated structural design methodology for agricultural protecting structures covered with nets

2010 ◽  
Vol 105 (2) ◽  
pp. 205-220 ◽  
Author(s):  
D. Briassoulis ◽  
A. Mistriotis
Keyword(s):  
Structural Design ◽  
Design Methodology

Economically optimal structural design methodology for flexible pavements

2016 ◽  
pp. 69-78
Author(s):  
Anastasios Tsiknas ◽  
Adamantia Athanasopoulou
Keyword(s):  
Structural Design ◽  
Design Methodology ◽  
Flexible Pavements ◽  
Optimal Structural Design

Multi-level Pareto supported design methodology- application to RO-PAX structural design

2019 ◽  
Vol 67 ◽  
pp. 102638
Author(s):  
Jerolim Andric ◽  
Pero Prebeg ◽  
Vedran Zanic
Keyword(s):  
Structural Design ◽  
Design Methodology ◽  
Multi Level

scholarly journals Data-driven topology design using a deep generative model

2021 ◽  
Author(s):  
Shintaro Yamasaki ◽  
Kentaro Yaji ◽  
Kikuo Fujita
Keyword(s):  
Structural Design ◽  
High Performance ◽  
Design Methodology ◽  
Generative Model ◽  
Topology Design ◽  
Training Data ◽  
Data Driven ◽  
Design Domain ◽  
Numerical Examples ◽  
New Material

AbstractIn this paper, we propose a sensitivity-free and multi-objective structural design methodology called data-driven topology design. It is schemed to obtain high-performance material distributions from initially given material distributions in a given design domain. Its basic idea is to iterate the following processes: (i) selecting material distributions from a dataset of material distributions according to eliteness, (ii) generating new material distributions using a deep generative model trained with the selected elite material distributions, and (iii) merging the generated material distributions with the dataset. Because of the nature of a deep generative model, the generated material distributions are diverse and inherit features of the training data, that is, the elite material distributions. Therefore, it is expected that some of the generated material distributions are superior to the current elite material distributions, and by merging the generated material distributions with the dataset, the performances of the newly selected elite material distributions are improved. The performances are further improved by iterating the above processes. The usefulness of data-driven topology design is demonstrated through numerical examples.

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