• Journal of Astronomy and Space Sciences
• /
• 제32권4호
• /
• pp.379-386
• /
• 2015

This work presents fuel-optimal altitude maintenance of Low-Earth-Orbit (LEO) spacecrafts experiencing non-negligible air drag and J2 perturbation. A pseudospectral (direct) method is first applied to roughly estimate an optimal fuel consumption strategy, which is employed as an initial guess to precisely determine itself. Based on the physical specifications of KOrea Multi-Purpose SATellite-2 (KOMPSAT-2), a Korean artificial satellite, numerical simulations show that a satellite ascends with full thrust at the early stage of the maneuver period and then descends with null thrust. While the thrust profile is presumably bang-off, it is difficult to precisely determine the switching time by using a pseudospectral method only. This is expected, since the optimal switching epoch does not coincide with one of the collocation points prescribed by the pseudospectral method, in general. As an attempt to precisely determine the switching time and the associated optimal thrust history, a shooting (indirect) method is then employed with the initial guess being obtained through the pseudospectral method. This hybrid process allows the determination of the optimal fuel consumption for LEO spacecrafts and their thrust profiles efficiently and precisely.

• Nuclear Engineering and Technology
• /
• 제56권4호
• /
• pp.1472-1479
• /
• 2024

Cyber-Physical Energy Systems (CPESs) integrate cyber and hardware components to ensure a reliable and safe physical power production and supply. Renewable Energy Sources (RESs) add uncertainty to energy demand that can be dealt with flexible operation (e.g., load-following) of CPES; at the same time, scenarios that could result in severe consequences due to both component stochastic failures and aging of the cyber system of CPES (commonly overlooked) must be accounted for Operation & Maintenance (O&M) planning. In this paper, we make use of Deep Reinforcement Learning (DRL) to search for the optimal O&M strategy that, not only considers the actual system hardware components health conditions and their Remaining Useful Life (RUL), but also the possible accident scenarios caused by the failures and the aging of the hardware and the cyber components, respectively. The novelty of the work lies in embedding the cyber aging model into the CPES model of production planning and failure process; this model is used to help the RL agent, trained with Proximal Policy Optimization (PPO) and Imitation Learning (IL), finding the proper rejuvenation timing for the cyber system accounting for the uncertainty of the cyber system aging process. An application is provided, with regards to the Advanced Lead-cooled Fast Reactor European Demonstrator (ALFRED).

• 한국도로학회논문집
• /
• 제14권6호
• /
• pp.13-23
• /
• 2012

PURPOSES : This study is to improve the highway management and rehabilitation efficiently by method for asset management. METHODS : Based on the literature review, The concept of this paper is to investigate the use of asset values from a Bridge management system to improvement of maintenance system more efficiently. This study is suggested for an evaluation method based on the current bridge condition by Written-down replacement cost of the assets. RESULTS : We suggests the optimization methodology of road asset valuation for budge distribution and performance measure. CONCLUSIONS : We evaluate all of national highway's bridge by the optimization methodology of road asset valuation, and suggest application methods of asset result.

• 대한전기학회논문지:전력기술부문A
• /
• 제55권9호
• /
• pp.392-398
• /
• 2006

Maintenance scheduling of generating units (MSU) has strategic dimension in an oligopolistic market. Strategic MSU of gencos can affect a market power through capacity withdrawal which is related to bidding strategy in an generation wholesale market. This paper presents a combined framework that models the interrelation between competitive bidding and strategic MSU. The combined game model is represented as some sub-optimization problems of a market operator (MO) and gencos, that should be solved through bi-level optimization scheme. The gradient method with dual variables is also adopted to calculate a Nash Equilibrium (NE) by an iterative update technique in this paper. Illustrative numerical example shows that NE of a supply function equilibrium is obtained properly by using proposed solution technique. The MSU made by MO is compared with that by each genco and that under perfect competition market.

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 1997년도 하계학술대회 논문집 D
• /
• pp.781-783
• /
• 1997

Genetic Algorithm is a kind of an evolution programming based on natural evolution principle. It applied to probabilistic searching, machine learning and optimization, and many good results were reported. Generator maintenance scheduling is an optimization Problem with constraints. This paper applied a genetic algorithm to generator maintenance scheduling problem and tested on sample systems. The results are compared with heuristic method and branch-and-bound method.

• 국제학술발표논문집
• /
• The 4th International Conference on Construction Engineering and Project Management Organized by the University of New South Wales
• /
• pp.597-602
• /
• 2011

A robust asset management methodology is essential for effective decision-making of maintenance, repair and rehabilitation of a bridge network. It can be achieved by a computer-based bridge management system (BMS). Successful BMS development requires a reliable bridge deterioration model, which is the most crucial component in a BMS, and an optimal management philosophy. The maintenance optimization methodology proposed in this paper is developed for a small bridge network with limited structural condition rating records. . The methodology is organized in three major components: (1) bridge health index (BHI); (2) maintenance and budget optimization; and (3) reliable Artificial Intelligence (AI) based bridge deterioration model. The outcomes of the paper will help to identify BMS implementation problems and to provide appropriate solutions for managing small bridge networks.

• 한국조명전기설비학회:학술대회논문집
• /
• 한국조명전기설비학회 2007년도 춘계학술대회 논문집
• /
• pp.328-333
• /
• 2007

Traditional maintenance planning is based on a constant maintenance interval for equipment life. In order to consider economic aspect for tm based preventive maintenance, preventive maintenance is desirable to be scheduled by RCM(Reliability-Centered Maintenance) evaluation. The main objective of RCM is to reduce the maintenance cost, by focusing on the most important functions of the system and avoiding or removing maintenance actions that are not strictly necessary. So, Markov state model is utilized considering stochastic state in RCM In this paper, a Markov state model much can be used for scheduling and optimization of maintenance is presented. The deterioration process of system condition is modeled by the stepwise Markov model in detail. Also, because the system is not continuously monitored, the inspection is considered. In case study, simulation results about RCM will be shown using the real historical data of combustion turbine generating unit in Korean power systems.

• 한국철도학회논문집
• /
• 제8권6호
• /
• pp.544-549
• /
• 2005

Nowadays, most of bridge networks are complete or close to completion. The biggest challenge railroad./highway agencies and departments of transportation face is the maintenance of these networks, keeping them safe and serviceable, with limited funds. To maintain the bridges effectively, there is an urgent need to predict their remaining life from a system reliability viewpoint. And, it is necessary to develop the maintenance models based on system reliability concept. In this paper, maintenance models are developed for preventive maintenance and essential maintenance by using system reliability and lifetime distributions. The proposed model is applied to an existing railroad bridge. The optimal maintenance strategy of this bridge is obtained in terms of services life extension and cumulative maintenance cost.

• 시스템엔지니어링학술지
• /
• 제12권1호
• /
• pp.41-58
• /
• 2016

Reliability Centered Maintenance (RCM) introduces a systematic method and decision logic tree for utilizing previous operating experience focused on reliability and optimization of maintenance activities. In this paper RCM methodology is applied on safety injection system for APR-1400. Functional Failure Mode Effects and Criticality Analysis (FME&CA) are applied to evaluate the failure modes and the effect on the component, system and plant. Logic Tree Analysis (LTA) is used to determine the optimum maintenance tasks. The results show that increasing the condition based maintenance will reduce component failure and improve reliability and availability of the system. Also the extension of the surveillance test interval of Safety Injection Pumps (SIPs) would lead to an improved pump's availability, eliminate the unnecessary maintenance tasks and this will optimize maintenance activities.

• 한국철도학회:학술대회논문집
• /
• 한국철도학회 2009년도 춘계학술대회 논문집
• /
• pp.1655-1660
• /
• 2009

At the Rolling-stock, most important thing is thorough maintenance for safety as a mass transit. Recently, many studies of cost down method and acquisition of high reliability have being progressed with considering of safety. Maintenance cost is closely relative to the preventive maintenance. But generally the preventive maintenance is decided in compliance with an experience. So the study of cost down method at the preventive maintenance is difficult. In this study, many results of effectiveness and optimization for the preventive maintenance are checked. Then., it is possible that efficiency preventive maintenance method will be able to suggest.