A fuzzy adaptive metaheuristic algorithm for identifying sustainable, economical, lightweight, and earthquake-resistant reinforced concrete cantilever retaining walls

• URL: http://arxiv.org/abs/2302.00198v1
• Date: Wed, 1 Feb 2023 03:00:52 GMT
• Title: A fuzzy adaptive metaheuristic algorithm for identifying sustainable, economical, lightweight, and earthquake-resistant reinforced concrete cantilever retaining walls
• Authors: Farshid Keivanian, Raymond Chiong, Ali R. Kashani, and Amir H. Gandomi
• Abstract summary: In earthquake-prone zones, the seismic performance of reinforced concrete cantilever (RCC) retaining walls is significant. To tackle RCC weights and forces resulting from earth pressures, 26 constraints for structural strengths and geotechnical stability along with 12 geometric variables are associated with each design. A novel adaptive fuzzy-based metaheuristic algorithm is applied to conduct effective search and produce sustainable, economical, lightweight RCC designs.
• Score: 11.864109595762814
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: In earthquake-prone zones, the seismic performance of reinforced concrete cantilever (RCC) retaining walls is significant. In this study, the seismic performance was investigated using horizontal and vertical pseudo-static coefficients. To tackle RCC weights and forces resulting from these earth pressures, 26 constraints for structural strengths and geotechnical stability along with 12 geometric variables are associated with each design. These constraints and design variables form a constraint optimization problem with a twelve-dimensional solution space. To conduct effective search and produce sustainable, economical, lightweight RCC designs robust against earthquake hazards, a novel adaptive fuzzy-based metaheuristic algorithm is applied. The proposed method divides the search space to sub-regions and establishes exploration, information sharing, and exploitation search capabilities based on its novel search components. Further, fuzzy inference systems were employed to address parameterization and computational cost evaluation issues. It was found that the proposed algorithm can achieve low-cost, low-weight, and low CO2 emission RCC designs under nine seismic conditions in comparison with several classical and best-performing design optimizers.

Related papers

• Structures vibration control via tuned mass dampers using a co-evolution coral reefs optimization algorithm [0.0]
  We tackle a problem of optimal design and location of Tuned Mass Dampers (TMDs) for structures subjected to earthquake ground motions. Specifically, the Coral Reefs Optimization (CRO) with Substrate Layer (CRO-SL) is proposed as a competitive co-evolution algorithm. The proposed approach is able to solve the TMD design and location problem, by exploiting the combination of different types of searching mechanisms.
  arXiv  Detail & Related papers  (2024-02-10T16:09:56Z)
• High-Dimensional Bayesian Optimisation with Large-Scale Constraints -- An Application to Aeroelastic Tailoring [1.8004890248574648]
  Design optimisation potentially leads to lightweight aircraft structures with lower environmental impact. Due to the high number of design variables and constraints, these problems are ordinarily solved using gradient-based optimisation methods. The present study attempts to tackle the problem by using high-dimensional Bayesian optimisation in combination with a dimensionality reduction approach.
  arXiv  Detail & Related papers  (2023-12-14T12:51:29Z)
• A Real-time Faint Space Debris Detector With Learning-based LCM [4.454216126942097]
  This paper proposes a method for low-SNR streak extraction based on local contrast and maximum likelihood estimation (MLE) The algorithm in this paper is of high speed and precision, which guarantees its promising applications in the extraction of high dynamic targets.
  arXiv  Detail & Related papers  (2023-09-15T08:37:28Z)
• Adaptive search space decomposition method for pre- and post- buckling analyses of space truss structures [0.7537475180985098]
  The paper proposes a novel adaptive search space decomposition method and a gradient-free optimization-based formulation for the pre- and post-buckling analyses. We tackle three benchmark problems and evaluate a medium-sized test representing a real structural problem in this paper. The accuracy and robustness of the adopted methodology show a high potential of gradient-free algorithms in analyzing space truss structures.
  arXiv  Detail & Related papers  (2022-11-14T16:47:25Z)
• Revisiting GANs by Best-Response Constraint: Perspective, Methodology, and Application [49.66088514485446]
  Best-Response Constraint (BRC) is a general learning framework to explicitly formulate the potential dependency of the generator on the discriminator. We show that even with different motivations and formulations, a variety of existing GANs ALL can be uniformly improved by our flexible BRC methodology.
  arXiv  Detail & Related papers  (2022-05-20T12:42:41Z)
• Efficient Micro-Structured Weight Unification and Pruning for Neural Network Compression [56.83861738731913]
  Deep Neural Network (DNN) models are essential for practical applications, especially for resource limited devices. Previous unstructured or structured weight pruning methods can hardly truly accelerate inference. We propose a generalized weight unification framework at a hardware compatible micro-structured level to achieve high amount of compression and acceleration.
  arXiv  Detail & Related papers  (2021-06-15T17:22:59Z)
• Resource Planning for Hospitals Under Special Consideration of the COVID-19 Pandemic: Optimization and Sensitivity Analysis [87.31348761201716]
  Crises like the COVID-19 pandemic pose a serious challenge to health-care institutions. BaBSim.Hospital is a tool for capacity planning based on discrete event simulation. We aim to investigate and optimize these parameters to improve BaBSim.Hospital.
  arXiv  Detail & Related papers  (2021-05-16T12:38:35Z)
• Biogeography-Based Optimization of RC structures including static soil-structure interaction [0.0]
  We present a method to minimize the cost of the structural design of reinforced concrete structures using Biogeography-Based Optimization. SAP2000 is used as computational engine, taking into account modelling aspects such as static soil-structure interaction (SSSI)
  arXiv  Detail & Related papers  (2021-03-08T22:48:04Z)
• Robust Reinforcement Learning with Wasserstein Constraint [49.86490922809473]
  We show the existence of optimal robust policies, provide a sensitivity analysis for the perturbations, and then design a novel robust learning algorithm. The effectiveness of the proposed algorithm is verified in the Cart-Pole environment.
  arXiv  Detail & Related papers  (2020-06-01T13:48:59Z)
• Stabilizing Differentiable Architecture Search via Perturbation-based Regularization [99.81980366552408]
  We find that the precipitous validation loss landscape, which leads to a dramatic performance drop when distilling the final architecture, is an essential factor that causes instability. We propose a perturbation-based regularization - SmoothDARTS (SDARTS) - to smooth the loss landscape and improve the generalizability of DARTS-based methods.
  arXiv  Detail & Related papers  (2020-02-12T23:46:58Z)
• Semiparametric Bayesian Forecasting of Spatial Earthquake Occurrences [77.68028443709338]
  We propose a fully Bayesian formulation of the Epidemic Type Aftershock Sequence (ETAS) model. The occurrence of the mainshock earthquakes in a geographical region is assumed to follow an inhomogeneous spatial point process.
  arXiv  Detail & Related papers  (2020-02-05T10:11:26Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.