Labour Commitments in the EVFTA: Amendments and Supplements to Vietnamese Law and Recommendations

Following months of negotiations, Vietnam and the European Union (EU) signed the EU-Vietnam free trade agreement (EVFTA) on June 30, 2019 (effective from August 1, 2020). Although this agreement opens up enormous opportunities for cooperation with the EU in many trade areas, Vietnam would still ensure compliance with other non-trade provisions, particularly with the labour clauses in this agreement, in accordance with the principle pacta sunt servanda, which is a fundamental principle of international law. By using a synthesis research method, comprehensive assessment, and in-depth comparison with documents of the International Labour Organization (ILO), EVFTA regulations, and Vietnamese legal documents on labour, this study aims to review the amendments and modifications of Vietnam’s labour law to fulfil the commitments in labour in the EVFTA, as well as provide recommendations on how to enhance the Vietnamese labour law to ensure effective implementation of these international labour responsibilities. Keywords: EVFTA, EU, labour, commitment. DOI: 10.7176/JLPG/125-10 Publication date:October 31st 2022

Techniques for Reducing Redundant Unicast Traffic in HSR Networks

High-availability seamless redundancy (HSR) is a seamless redundancy protocol for Ethernet networks. HSR provides seamless communication with fault tolerance based on the duplication of every unicast frame sent in a ring topology. HSR is very useful for mission- and time-critical systems such as substation automation systems (SASs). However, the main drawback of HSR is to generate excessively redundant network traffic in HSR networks. This drawback would unnecessarily waste network bandwidth and hence could degrade network performance in HSR networks. Several traffic reduction techniques for HSR networks have been proposed to improve the network performance in the networks. These techniques can be classified into two main groups: traffic filtering-based and dual paths-based techniques. In this chapter, we provide a description and comparison of these HSR traffic reduction techniques. This chapter describes these traffic reduction techniques and compares their network performance. The operations, advantages, and disadvantages of these techniques are investigated and summarized

Influence of ground motion duration on seismic fragility of base isolated NPP structures

This study investigates the influence of earthquake duration on seismic fragility of base isolated nuclear power plant (NPP) structures. Two groups of ground motions are employed in performing time history analyses, in which short duration (SD) and long duration (LD) characteristics are considered. The advanced power reactor 1400 (APR1400) NPP structures are used for developing finite element model, which is constructed using lumped-mass stick elements. A series of 486 lead rubber bearings (LRBs) are installed under the base mat of the NPP structures to reduce the seismic damage. Seismic responses of the base isolated NPP are quantified in terms of lateral displacements and hysteretic energy distributions of LRBs. Seismic fragility curves for damage states, which are defined based on the deformation of LRB, are developed. The results reveal that the average lateral displacements of LRBs under SD and LD motions are very similar. For PGA larger than 0.4g, the mean deformation of LRB for LD motions is higher than that for SD motions. The probability of damage of base isolated NPP structures under LD motions is reduced approximately 15% compared to that asubjected to SD earthquakes. This finding emphasizes that it is crucial to use both SD and LD ground motions in seismic evaluations of base isolated NPP structure

Influence of ground motion duration on seismic fragility of base isolated NPP structures

This study investigates the influence of earthquake duration on seismic fragility of base isolated nuclear power plant (NPP) structures. Two groups of ground motions are employed in performing time history analyses, in which short duration (SD) and long duration (LD) characteristics are considered. The advanced power reactor 1400 (APR1400) NPP structures are used for developing finite element model, which is constructed using lumped-mass stick elements. A series of 486 lead rubber bearings (LRBs) are installed under the base mat of the NPP structures to reduce the seismic damage. Seismic responses of the base isolated NPP are quantified in terms of lateral displacements and hysteretic energy distributions of LRBs. Seismic fragility curves for damage states, which are defined based on the deformation of LRB, are developed. The results reveal that the average lateral displacements of LRBs under SD and LD motions are very similar. For PGA larger than 0.4g, the mean deformation of LRB for LD motions is higher than that for SD motions. The probability of damage of base isolated NPP structures under LD motions is reduced approximately 15% compared to that asubjected to SD earthquakes. This finding emphasizes that it is crucial to use both SD and LD ground motions in seismic evaluations of base isolated NPP structure

Model Updating for Large-Scale Railway Bridge Using Grey Wolf Algorithm and Genetic Alghorithms

This paper proposes a novel hybrid algorithm to deal with an inverse problem of a large-scale truss bridge. Grey Wolf Optimization (GWO) Algorithm is a well-known and widely applied metaheuristic algorithm. Nevertheless, GWO has two major drawbacks. First, this algorithm depends crucially on the positions of the leading Wolf. If the position of the leaderis far from the best solution, the obtained results are poor. On the other hand, GWO does not own capacities to improve the quality of new generations if elements are trapped into local minima. To remedy the shortcomings of GWO, we propose a hybrid algorithm combining GWO with Genetic Algorithm (GA), termed HGWO-GA. This proposed method contains two key features (1) based on crossover and mutation capacities, GA is first utilized to generate the high-quality elements (2) after that, the optimization capacity of GWO is employed to seek the optimal solutions. To assess the effectiveness of the proposed approach, a large-scale truss bridge is employed for model updating. The obtained results show that HGWO-GA not only provides a good agreement between numerical and experimental results but also outperforms traditional GWO in terms of accuracy

Damage detection for a large-scale truss bridge using Tranmissibility and ANNAOA

In this paper, we propose an efficient approach to enhance the capacity of Artificial Neural Network (ANN) to deal with Structural Health Monitoring (SHM) problems.  Over the last decades, ANN has been extensively utilized for damage detection in structures. In order to identify damages, ANN frequently utilizes input information that is based on dynamic features such as mode shapes or natural frequencies. However, this type of data may not be able to detect minor damages if the structural defects are insignificant. To transcend these limitations, in this work, we propose utilizing transmissibility to create input data for the input layer of ANN. Moreover, to deal with local minimum problems of ANN, a combination between the Arithmetic Optimization Algorithm (AOA) and ANN is proposed. The global search capacity of AOA is employed to remedy the local minima of ANN. To evaluate the effectiveness of the proposed approach, a numerical model with different damage scenarios is considered. The suggested approach detects damage location precisely and with higher severity detection precision than the conventional ANN method

Damage detection for a large-scale truss bridge using Tranmissibility and ANNAOA

In this paper, we propose an efficient approach to enhance the capacity of Artificial Neural Network (ANN) to deal with Structural Health Monitoring (SHM) problems.  Over the last decades, ANN has been extensively utilized for damage detection in structures. In order to identify damages, ANN frequently utilizes input information that is based on dynamic features such as mode shapes or natural frequencies. However, this type of data may not be able to detect minor damages if the structural defects are insignificant. To transcend these limitations, in this work, we propose utilizing transmissibility to create input data for the input layer of ANN. Moreover, to deal with local minimum problems of ANN, a combination between the Arithmetic Optimization Algorithm (AOA) and ANN is proposed. The global search capacity of AOA is employed to remedy the local minima of ANN. To evaluate the effectiveness of the proposed approach, a numerical model with different damage scenarios is considered. The suggested approach detects damage location precisely and with higher severity detection precision than the conventional ANN method