Reliability Allocation and Optimization for(ROSS) of a Spacecraft by using Genetic Algorithm

Abed, Saad Abbas; Sulaiman, Hatem Kareem; Hassan, Zahir Abdul Haddi

doi:10.1088/1742-6596/1294/3/032034

Cited by 28 publications

(3 citation statements)

References 2 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The geometry optimization uses shape derivatives from differential geometry, which provide sensitivity of the cost and constraints to local perturbations in the manifold [6][7][8][9]. The shape derivatives are given by: Let M be an n-dimensional differentiable manifold representing the design space.…”

Section: Optimization Modelmentioning

confidence: 99%

Structural Reliability and Optimization Using Differential Geometric Approaches

Abed,

Ghassan,

Qaes

et al. 2024

Iraqi Journal for Computer Science and Mathematics

View full text Add to dashboard Cite

This study investigates how differential geometry ideas can be used to effectively carry out structural optimization and reliability analysis. Strong mathematical representations and methods for examining intricate surfaces and forms are provided by differential geometry. The basic ideas of differential geometry, such as tensors, manifolds, and curvature, are initially introduced in the work. Then, to account for ambiguities in the geometry, the probability theory in tangent spaces is developed. As a result, structural reliability can be determined using propagating uncertainty. To enable reliability-based design optimization, differential geometry representations are linked with optimization techniques. The proposed differential geometry-based approach is applied in a number of case studies to trusses, airplane wings, car bodies, and ship hulls. The outcomes show a significant increase in productivity and scalability compared to conventional finite element methods. The article offers new tools for dealing with uncertainty.

show abstract

Section: Optimization Modelmentioning

confidence: 99%

Structural Reliability and Optimization Using Differential Geometric Approaches

Abed,

Ghassan,

Qaes

et al. 2024

Iraqi Journal for Computer Science and Mathematics

View full text Add to dashboard Cite

show abstract

“…Considering modelling or measurement uncertainties, statistics appear in various reliability analysis activities, such as sampling and DOEs. An accurate reliability estimation method considering various uncertainties from measurements to modelling can play a significant role in improving the design and performance of mechanical and structural systems [7][8][9]. An effective SRA can also help with the justification of design for different working conditions based on design and performance requirements [10,11].…”

Section: Introductionmentioning

confidence: 99%

Deep learning-based methods in structural reliability analysis: a review

Afshari

Zhao

Zhuang

et al. 2023

Meas. Sci. Technol.

View full text Add to dashboard Cite

One of the most significant and growing research fields in mechanical and civil engineering is Structural Reliability Analysis (SRA). A reliable and precise SRA usually has to deal with complicated , aand numerically expensive problems. Artificial intelligence-based (AI) nd specifically, Deep learning-based (DL) methods, have been applied to the SRA problems to reduce the computational cost and to improve the accuracy of reliability estimation as well. This article reviews the recent advances in using DL models in SRA problems. The review includes the most common categories of DL-based methods used in SRA. More specifically, the application of supervised methods, unsupervised methods, and hybrid deep learning methods in SRA are explained. In this paper, the supervised methods for SRA are categorized as Multi-Layer Perceptron (MLP), Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN ), Long short-term memory (LSTM), Bidirectional (Bi-LSTM) and Gated recurrent units (GRU). For the unsupervised methods, we have investigated methods such as Generative Adversarial Network (GAN), Autoencoders (AE), Self-Organizing Map (SOM), Restricted Boltzmann Machine (RBM), and Deep Belief Network (DBN). We have made a comprehensive survey of these methods in SRA. Aiming towards an efficient SRA, deep learning-based methods applied for approximating the limit state function (LSF) with First/Second Order Reliability Methods (FORM/SORM), Monte Carlo simulation (MCS), or MCS with importance sampling (IS). Accordingly, the current paper focuses on the structure of different DL-based models and the applications of each DL method in various SRA problems. This survey helps researchers in mechanical and civil engineering, especially those who are engaged with structural and reliability analysis or dealing with quality assurance problems.

show abstract

“…One of the first researchers to take up the reduction oxygen supply system (ROSS) study of a spacecraft system for the first time by Aggarwal [1], and due to the importance of the topic in terms of engineering and science, light was re-shed by several researchers such as Hassan et al [2]- [9] where the researchers discussed the reliability of this system and the study of mean time to failure (MTTF) using the engineering properties of many reliability limits. Also Abed et al [10] discussed the issue of optimizing the reliability of this system has solved by using a genetic algorithm.…”

Section: Introductionmentioning

confidence: 99%

Application of the Jaya algorithm to solve the optimal reliability allocation for reduction oxygen supply system of a spacecraft

Abed

Aljanabi

Ameer

et al. 2021

IJEECS

View full text Add to dashboard Cite

In this paper the reliability of reduction oxygen supply system (ROSS) of a spacecraft which was calculated as a complex system using minimal cut method. The reliability of each component of system was calculated as well as the reliability importance of the system. The cost of each component of the system was possible approaches of the allocation values of reliability based the minimization of the overall cost in this system. The advantage of this algorithm can be used to allocate the optimization of reliability for simple or complex system. This optimization is achieved using the Jaya algorithm. The proposed technique is based on the notion that a conclusion reached on a particular problem should pass near the best results and avoid the worst outcomes. The original findings of this paper are: i) the system used in this paper is a spacecraft’s reduced oxygen supply system with the logarithmic cost function; and ii) the results obtained were by using the Jaya algorithm to solve specific system reliability optimization problems.

show abstract

Reliability Allocation and Optimization for(ROSS) of a Spacecraft by using Genetic Algorithm

Cited by 28 publications

References 2 publications

Structural Reliability and Optimization Using Differential Geometric Approaches

Structural Reliability and Optimization Using Differential Geometric Approaches

Deep learning-based methods in structural reliability analysis: a review

Application of the Jaya algorithm to solve the optimal reliability allocation for reduction oxygen supply system of a spacecraft

Contact Info

Product

Resources

About