944 research outputs found
FMI Compliant Approach to Investigate the Impact of Communication to Islanded Microgrid Secondary Control
In multi-master islanded microgrids, the inverter controllers need to share
the signals and to coordinate, in either centralized or distributed way, in
order to operate properly and to assure a good functionality of the grid. The
central controller is used in centralized strategy. In distributed control,
Multi-agent system (MAS) is considered to be a suitable solution for
coordination of such system. However the latency and disturbance of the network
may disturb the communication from central controller to local controllers or
among agents or and negatively influence the grid operation. As a consequence,
communication aspects need to be properly addressed during the control design
and assessment. In this paper, we propose a holistic approach with
co-simulation using Functional Mockup Interface (FMI) standard to validate the
microgrid control system taking into account the communication network. A
use-case of islanded microgrid frequency secondary control with MAS under
consensus algorithm is implemented to demonstrate the impact of communication
and to illustrate the proposed holistic approach.Comment: Proceedings of the IEEE PES ISGT Asia 2017 conferenc
Experimental study of the long-term shortening of reinforced concrete columns under maintaining concentric axial load
This paper presents the results of an experimental study to measure the shortening of reinforced concrete (RC) columns under long-term maintaining concentric axial load. Long-term axial deformation due to shrinkage and creep of the concrete were recorded beside deformation due to mechanical load. Eight RC cylinder - columns (content of reinforcement 1.5% and 2%) with diameter of 150 mm and height of 600 mm were tested during the period of 600 days to determine their shortening. The experimental results showed that the long-term deformation of RC columns occurs primarily during the first year of loading. The deformation creep of concrete is much greater than the shrinkage deformation. The reinforcement content has a significant effect on the long-term deformation of concrete columns
Experimental study of the long-term shortening of reinforced concrete columns under maintaining concentric axial load
This paper presents the results of an experimental study to measure the shortening of reinforced concrete (RC) columns under long-term maintaining concentric axial load. Long-term axial deformation due to shrinkage and creep of the concrete were recorded beside deformation due to mechanical load. Eight RC cylinder - columns (content of reinforcement 1.5% and 2%) with diameter of 150 mm and height of 600 mm were tested during the period of 600 days to determine their shortening. The experimental results showed that the long-term deformation of RC columns occurs primarily during the first year of loading. The deformation creep of concrete is much greater than the shrinkage deformation. The reinforcement content has a significant effect on the long-term deformation of concrete columns
Mechanical response of outer frames in tuning fork gyroscope model with connecting diamond-shaped frame
In tuning fork micro-gyroscopes, two outer frames are connected by using the linking elements. The driving vibrations of the two outer frames are required to be exactly opposite to generate the opposite sensing modes perpendicular to driving direction. These opposite driving vibrations are provided by a mechanical structure named the diamond-shaped frame. This paper presents mechanical responses of two outer frames in a proposed model of tuning fork gyroscope when an external force with different types is applied to them. The results show that the presence of a diamond-shaped frame guarantees the absolute anti-phase mode for the driving vibrations of outer frames
Policy Learning for Off-Dynamics RL with Deficient Support
Reinforcement Learning (RL) can effectively learn complex policies. However,
learning these policies often demands extensive trial-and-error interactions
with the environment. In many real-world scenarios, this approach is not
practical due to the high costs of data collection and safety concerns. As a
result, a common strategy is to transfer a policy trained in a low-cost, rapid
source simulator to a real-world target environment. However, this process
poses challenges. Simulators, no matter how advanced, cannot perfectly
replicate the intricacies of the real world, leading to dynamics discrepancies
between the source and target environments. Past research posited that the
source domain must encompass all possible target transitions, a condition we
term full support. However, expecting full support is often unrealistic,
especially in scenarios where significant dynamics discrepancies arise. In this
paper, our emphasis shifts to addressing large dynamics mismatch adaptation. We
move away from the stringent full support condition of earlier research,
focusing instead on crafting an effective policy for the target domain. Our
proposed approach is simple but effective. It is anchored in the central
concepts of the skewing and extension of source support towards target support
to mitigate support deficiencies. Through comprehensive testing on a varied set
of benchmarks, our method's efficacy stands out, showcasing notable
improvements over previous techniques.Comment: Accepted by AAMAS 2024 as a full pape
CAMELLIA HOABINHENSIS (THEACEAE: SECT. CHRYSANTHA), A NEW YELLOW-FLOWERED SPECIES FROM NORTHERN VIETNAM
A new species, Camellia hoabinhensis (section Chrysantha, Theaceae), is described and illustrated based on specimens collected from a lowland forest on limestone hills in Hoa Binh Province, northern Vietnam. The species is characterized by its small habit to 4.5 m tall, large flowers 9.0–9.5 cm in diameter with 18–19 light yellow petals, and hairy filaments, ovaries, and styles. A comparison of the new species with similar species, C. euphlebia, C. impressinervis, C. phanii, and C. velutina, is provided. The IUCN conservation status of the proposed species is Data Deficient (DD)
Advancements, Challenges, and Future Directions in Rainfall-Induced Landslide Prediction: A Comprehensive Review
Rainfall-induced landslides threaten lives and properties globally. To address this, researchers have developed various methods and models that forecast the likelihood and behavior of rainfall-induced landslides. These methodologies and models can be broadly classified into three categories: empirical, physical-based, and machine-learning approaches. However, these methods have limitations in terms of data availability, accuracy, and applicability. This paper reviews the current state-of-the-art of rainfall-induced landslide prediction methods, focusing on the methods, models, and challenges involved. The novelty of this study lies in its comprehensive analysis of existing prediction techniques and the identification of their limitations. By synthesizing a vast body of research, it highlights emerging trends and advancements, providing a holistic perspective on the subject matter. The analysis points out that future research opportunities lie in interdisciplinary collaborations, advanced data integration, remote sensing, climate change impact analysis, numerical modeling, real-time monitoring, and machine learning improvements. In conclusion, the prediction of rainfall-induced landslides is a complex and multifaceted challenge, and no single approach is universally superior. Integrating different methods and leveraging emerging technologies offer the best way forward for improving accuracy and reliability in landslide prediction, ultimately enhancing our ability to manage and mitigate this geohazard
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