• Journal of the Korea Society for Simulation
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• v.25 no.3
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• pp.133-146
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• 2016

To engage multiple missiles in single launcher against multiple targets, launcher system has to operate for optimized launch angle to each target sequentially. If the launch angle sequence is simply defined according to the target assignment order only, overall engagement time would be increased, and even in some engagement scenarios, it could be possible to miss some moving targets being out of proper engagement area. Therefore, the study on methodology for a real-time decision of optimized launch angle sequence is necessary. In this paper, the automatic decision model of launch angle sequence was suggested to minimize total engagement time by analyzing the simulation results of all engagement sequence set for multiple moving target scenario. Performance of proposed methodology for decision of optimal launch angle sequence was verified by comparing with the optimal or suboptimal sequence obtained from simulation results.

• Journal of the Korea Institute of Military Science and Technology
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• v.22 no.1
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• pp.93-105
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• 2019

In order to establish an effective engagement plan of the missile defense system, both spatial and temporal performance analysis of the intercept system should be performed. However, research on existing missile defense systems has been mainly focused on spatial performance. In this study, time performance factors are defined through the composition and operational concept of missile defense system, and the target ballistic missile interception process is presented as integrated timeline through ballistic missile model and radar model. We also proposed an algorithm for deriving time performance. Simulation results confirm that the time performance factors can be used in the engagement planning for multi-engagement through the example of engagement planning.

• Journal of the military operations research society of Korea
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• v.2 no.1
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• pp.101-109
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• 1976

The goal of tactical war-gaming is to create an environment for two opposing teams allowing them to make tactical decisions that would correlate with the decision which they would make under the same circumstances while at sea. Therefore the real time war-gaming methodology should be developed to achieve the goal of tactical war-gaming. Surface to surface engagement models for the real time war-gaming such as maneuvering, tracking and damage assessment models were discussed in this paper. Concurrently system flow diagram to aid war-gaming effort was suggested in appendix.

• Journal of the Korea Institute of Military Science and Technology
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• v.9 no.4
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• pp.5-14
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• 2006

The correct and opportune decision of reengaging the intercepted target is required in order to enhance the engagement performance of the surface to air missile systems that has the ability to defense or attack against various targets at the same time. The engagement efficiency and success of these systems will be largely enhanced by assigning quickly its system resources to the intercepted target and minimizing the waste of system resources for the target which is not able to attack any more. The kill-assessment algorithm has to be able to evaluate automatically whether various targets intercepted by missiles are killed or not on the basis of the reasonable confidence level. The definition of kill assessment is discussed and the kill assessment algorithm is designed reliably by using Kalman filter and a probability theory. Finally its performance is evaluated and analyzed by the Monte Carlo simulation.

• Journal of the Korea Institute of Military Science and Technology
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• v.25 no.6
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• pp.637-647
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• 2022

Since the concept of Manned-UnManned Teaming(MUM-T) and Unmanned Aircraft System(UAS) can efficiently respond to rapidly changing battle space, many studies are being conducted as key components of the mosaic warfare environment. In this paper, we propose a rule-based AI engagement model based on Basic Fighter Maneuver(BFM) capable of Within-Visual-Range(WVR) air-to-air combat and a simulation environment in which human pilots can participate. In order to develop a rule-based AI engagement model that can pilot a fighter with a 6-DOF dynamics model, tactical manuals and human pilot experience were configured as knowledge specifications and modeled as a behavior tree structure. Based on this, we improved the shortcomings of existing air combat models. The proposed model not only showed a 100 % winning rate in engagement with human pilots, but also visualized decision-making processes such as tactical situations and maneuvering behaviors in real time. We expect that the results of this research will serve as a basis for development of various AI-based engagement models and simulators for human pilot training and embedded software test platform for fighter.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.50 no.4
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• pp.287-295
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• 2022

As low altitude long-range artillery threat has been strengthened, the development of anti-artillery interception system to protect assets against its attacks will be kicked off. We view the defense of long-range artillery attacks as a typical dynamic weapon target assignment (DWTA) problem. DWTA is a sequential decision process in which decision making under future uncertain attacks affects the subsequent decision processes and its results. These are typical characteristics of Markov decision process (MDP) model. We formulate the problem as a MDP model to examine the assignment policy for the defender. The proximity of the capital of South Korea to North Korea border limits the computation time for its solution to a few second. Within the allowed time interval, it is impossible to compute the exact optimal solution. We apply approximate dynamic programming (ADP) approach to check if ADP approach solve the MDP model within processing time limit. We employ Shoot-Shoot-Look policy as a baseline strategy and compare it with ADP approach for three scenarios. Simulation results show that ADP approach provide better solution than the baseline strategy.

• Journal of the Korea Society for Simulation
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• v.29 no.1
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• pp.39-46
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• 2020

The utilization of artificial intelligence (AI) in the engagement has been a key research topic in the defense field during the last decade. To pursue this utilization, it is imperative to acquire a realistic simulation to train an AI engagement agent with a synthetic, but realistic field. This paper is a case study of training an AI agent to operate with a hardware realism in the air-warfare dog-fighting. Particularly, this paper models the pursuit of an opponent in the dog-fighting setting with a gun-only engagement. In this context, the AI agent requires to make a decision on the pursuit style and intensity. We developed a realistic hardware simulator and trained the agent with a reinforcement learning. Our training shows a success resulting in a lead pursuit with a decreased engagement time and a high reward.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.47 no.12
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• pp.856-864
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• 2019

The weapon-target assignment (WTA) problem is a matter of effectively allocating weapons to a number of threats. The WTA in a rapidly changing dynamic environment of engagement must take into account both of properties of the threat and the weapon and the effect of the previous decision. We propose a method of applying the Greedy Randomized Adaptive Search Procedure (GRASP) algorithm, a kind of meta-heuristic method, to derive optimal solution for a dynamic WTA problem. Firstly, we define a dynamic WTA problem and formulate a mathematical model for applying the algorithm. For the purpose of the assignment strategy, the objective function is defined and time-varying constraints are considered. The dynamic WTA problem is then solved by applying the GRASP algorithm. The optimal solution characteristics of the formalized dynamic WTA problem are analyzed through the simulation, and the algorithm performance is verified via the Monte-Carlo simulation.

• Advances in nano research
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• v.12 no.5
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• pp.489-499
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• 2022

Nanofluids have recently triggered a substantial scientific interest as cooling media. However, their stability is challenging for successful engagement in industrial applications. Different factors, including temperature, nanoparticles and base fluids characteristics, pH, ultrasonic power and frequency, agitation time, and surfactant type and concentration, determine the nanofluid stability regime. Indeed, it is often too complicated and even impossible to accurately find the conditions resulting in a stabilized nanofluid. Furthermore, there are no empirical, semi-empirical, and even intelligent scenarios for anticipating the stability of nanofluids. Therefore, this study introduces a straightforward and reliable intelligent classifier for discriminating among the stability regimes of alumina-water nanofluids based on the Zeta potential margins. In this regard, various intelligent classifiers (i.e., deep learning and multilayer perceptron neural network, decision tree, GoogleNet, and multi-output least squares support vector regression) have been designed, and their classification accuracy was compared. This comparison approved that the multilayer perceptron neural network (MLPNN) with the SoftMax activation function trained by the Bayesian regularization algorithm is the best classifier for the considered task. This intelligent classifier accurately detects the stability regimes of more than 90% of 345 different nanofluid samples. The overall classification accuracy and misclassification percent of 90.1% and 9.9% have been achieved by this model. This research is the first try toward anticipting the stability of water-alumin nanofluids from some easily measured independent variables.

• THE INTERNATIONAL COMMERCE & LAW REVIEW
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• v.70
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• pp.1-20
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• 2016

This study is to find the accurate interpretations for the UCP600 by integrating, ISBP745, Official Opinions of ICC Banking Commission and some Case Laws suggesting the reasonable implication for the upcoming UCP. Major results analyzed by this study are as follows. First, The preclusion rule, UCP600 Article 16(c), is closely connected with the doctrine of documentary cure, so the banks requirement of Single Notice must state all the discrepancies of the documents presented. Exceptionally if the cured documents by the presenter are happened to be inconsistent the initial notice the bank can require the presenter to re-tender within the expiry date or the last day for presentation. Secondly, The Issuing Bank can utilize the right of seeking a waiver of documentary discrepancies from the applicant with the time limit of 5 banking days. If the bank wants to require an applicant to report discrepancies promptly, he may include a provision in the reimbursement engagement limiting the time limit within which the applicant must give notice of facial discrepancies. Thirdly, if a credit contains a non-documentary condition, banks will deem such condition as not states and will disregard it. According to the principle of private autonony if a credit contains a non-documentary condition to be consistent with by the parties concerned in a credit the non-documentary condition can be treated, as an effective condition itself. Fourthly, according to the Korean Supreme Court's decision, negotiation includes the method of crediting the credit amount and then transfers such funds into a special account and controls the account. Finally, UCP600 Article 33 states a bank has no obligation to accept a presentation outside of its banking hours. However, there is no rule in UCP600 in regard to a presentation after the close of business. Hopefully the upcoming UCP has to stipulates a sort of definite article to determine such ambiguous.