Changing and repurposing existing buildings for their continued use was quite common in the past and structurally safe buildings were adapted to meet new functions and needs. In modern conservation theory, Adaptive Reuse is an important means of preserving cultural heritage. The main question is what are the priorities and shortcomings of adaptive reuse theoretical references within interior architecture based on comparative study with Nara Document parameters. The research method of this study is qualitative, with logical argument as a strategy. The priorities were studied and then the most important weaknesses and drawbacks of these approaches to Adaptive Reuse were analyzed in a comparative study with the Nara Grid by 32 semi-structured interviews with experts in the fields of Architecture, Interior architecture and conservation. The results show four main Adaptive Reuse priorities extracted from the reviewed literature: Host Space Function, Programmatic Approach to New Use, Technical Requirements and Design-oriented strategies and solutions. These theoretical priorities do not negate each other; in fact, they are rather complementary. However, if one of them gains more importance in the process it can lead to many losses. of their most important disadvantages, the following are worth mentioning: A physical outlook and a lack of attention to intangible and soft values, a lack of attention to the meaning and characteristics of functions of the building in the past, ignoring the human presence and its needs, ignoring architectural details and interior architecture, lack of interdisciplinary research, and lack of adequate strategies in line with building values. It seems like the issues mentioned above could be avoided and redeemed through an emphasis in conservation policy on fixed feature spaces, semi-fixed feature spaces, and informal spaces in interior spaces, as well as considering human needs and social sciences in the redesign process, and following each priority and approach in the redesign process accordingly.
In this article, an Advanced Charged System Search (ACSS) algorithm is applied for the optimum design of steel structures. ACSS uses the idea of Opposition-based Learning and Levy flight to enhance the optimization abilities of the standard CSS. It also utilizes the information of the position of each charged particle in the subsequent search process to increase the convergence speed. The objective function is to find a minimum weight by choosing suitable sections subjected to strength and displacement requirements specified by the American Institute of Steel Construction (AISC) standard subject to the loads defined by Load Resistance Factor Design (LRFD). To show the performance of the ACSS, four steel structures with different number of elements are optimized. The results, efficiency, and accuracy of the ACSS algorithm are compared to other meta-heuristic algorithms. The results show the superiority of the ACSS compared to the other considered algorithms.
The primary objective of the current study is to optimize and evaluate the seismic performance of steel moment -resisting frame (MRF) structures considering soil-structure interaction (SSI) effects. The structural optimization is implemented in the context of performance-based design in accordance with FEMA-350 at different confidence levels from 50% to 90% by taking into account fixed-and flexible-base conditions using an efficient metaheuristic algorithm. Nonlinear response-history analysis (NRHA) is conducted to evaluate the seismic response of structures, and the beam-on-nonlinear Winkler foundation (BNWF) model is used to simulate the soil-foundation interaction under the MRFs. The seismic performance of optimally designed fixed-and flexible-base steel MRFs are compared in terms of overall damage index, seismic collapse safety, and inter -story drift ratios at different performance levels. Two illustrative examples of 6-and 12-story steel MRFs are presented. The results show that the consideration of SSI in the optimization process of 6-and 12-story steel MRFs results in an increase of 1.0 to 9.0 % and 0.5 to 5.0 % in structural weight and a slight decrease in structural seismic safety at different confidence levels.
The arithmetic optimization algorithm (AOA) is a recently developed metaheuristic optimization algorithm that simulates the distribution characteristics of the four basic arithmetic operations (i.e., addition, subtraction, multiplication, and division) and has been successfully applied to solve some optimization problems. However, the AOA suffers from poor exploration and prematurely converges to non-optimal solutions, especially when dealing with multi-dimensional optimization problems. More recently, in order to overcome the shortcomings of the original AOA, an improved version of AOA, named IAOA, has been proposed and successfully applied to discrete structural optimization problems. Compared to the original AOA, two major improvements have been made in IAOA: (1) The original formulation of the AOA is modified to enhance the exploration and exploitation capabilities; (2) The IAOA requires fewer algorithm-specific parameters compared with the original AOA, which makes it easy to be implemented. In this paper, IAOA is applied to the optimal design of large-scale dome-like truss structures with multiple frequency constraints. To the best of our knowledge, this is the first time that IAOA is applied to structural optimization problems with frequency constraints. Three benchmark dome-shaped truss optimization problems with frequency constraints are investigated to demonstrate the efficiency and robustness of the IAOA. Experimental results indicate that IAOA significantly outperforms the original AOA and achieves results comparable or superior to other state-of-the-art algorithms.
In recent decades, steel was used more than other materials in structural engineering. However, the safety of high-heat steel structures dramatically decreased, due to steel mechanical properties. Therefore, the design process should be done in a way that the structure has the required resistance at high temperatures and during the fire, according to the effect of heat on the performance of steel structures. In this study, the optimal design process of steel structures is considered under the fire load. In the optimal design process, the failure risk of the structure members is considered as a constraint. Therefore, the optimization process requires thermal and structural reliability analysis. A parametric model has been used to analyse the reliability of the structure in the fire limit state. The optimization process is also performed based on the Colliding Bodies Optimization (CBO) algorithm. In order to evaluate the optimal design process, 3 and 6-floors frames have been investigated. The results showed that the members' condition is effective in the structural resistance for the thermal loading. On the contrary, the structure design based on the reliability under the fire load provides a proper prediction from the behaviour of the structure and satisfies the requirements for the common state of design.
