• Geomechanics and Engineering
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• v.28 no.6
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• pp.599-611
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• 2022

Tendon reinforced cemented soil is applied extensively in foundation stabilisation and improvement, especially in areas with soft clay. To solve the deterioration problem led by steel corrosion, the glass fiber-reinforced polymer (GFRP) tendon is introduced to substitute the traditional steel tendon. The interface bond strength between the cemented soil matrix and GFRP tendon demonstrates the outstanding mechanical property of this composite. However, the lack of research between the influence factors and bond strength hinders the application. To evaluate these factors, back propagation neural network (BPNN) is applied to predict the relationship between them and bond strength. Since adjusting BPNN parameters is time-consuming and laborious, the particle swarm optimisation (PSO) algorithm is proposed. This study evaluated the influence of water content, cement content, curing time, and slip distance on the bond performance of GFRP tendon-reinforced cemented soils (GTRCS). The results showed that the ultimate and residual bond strengths were both in positive proportion to cement content and negative to water content. The sample cured for 28 days with 30% water content and 50% cement content had the largest ultimate strength (3879.40 kPa). The PSO-BPNN model was tuned with 3 neurons in the input layer, 10 in the hidden layer, and 1 in the output layer. It showed outstanding performance on a large database comprising 405 testing results. Its higher correlation coefficient (0.908) and lower root-mean-square error (239.11 kPa) were obtained compared to multiple linear regression (MLR) and logistic regression (LR). In addition, a sensitivity analysis was applied to acquire the ranking of the input variables. The results illustrated that the cement content performed the strongest influence on bond strength, followed by the water content and slip displacement.

• Structural Engineering and Mechanics
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• v.85 no.5
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• pp.635-644
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• 2023

The design of honeycomb sandwich structures is often challenging because these structures can be tailored from a variety of possible cores and face sheets configurations, therefore, the design of sandwich structures is characterized as a time-consuming and complex task. A data-driven computational approach that integrates the analytical method and Artificial Neural Network (ANN) is developed by the authors to rapidly predict the design of sandwich structures for a targeted maximum structural deflection. The elaborated ANN reverse design approach is applied to obtain the thickness of the sandwich core, the thickness of the laminated face sheets, and safety factors for composite sandwich structure. The required data for building ANN model were obtained using the governing equations of sandwich components in conjunction with the Monte Carlo Method. Then, the functional relationship between the input and output features was created using the neural network Backpropagation (BP) algorithm. The input variables were the dimensions of the sandwich structure, the applied load, the core density, and the maximum deflection, which was the reverse input given by the designer. The outstanding performance of reverse ANN model revealed through a low value of mean square error (MSE) together with the coefficient of determination (R2) close to the unity. Furthermore, the output of the model was in good agreement with the analytical solution with a maximum error 4.7%. The combination of reverse concept and ANN may provide a potentially novel approach in designing of sandwich structures. The main added value of this study is the elaboration of a reverse ANN model, which provides a low computational technique as well as savestime in the design or redesign of sandwich structures compared to analytical and finite element approaches.

• Journal of Korea Society of Industrial Information Systems
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• v.14 no.2
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• pp.16-22
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• 2009

The most efficient method to reduce duplicated messages is a partial dominant pruning for receiving and forwarding messages by in-fly format on the mobile ad hoc network. In this paper, we propose directional partial dominant pruning method by expanding partial dominant pruning for reducing not only number of forwarding nodes but number of antenna elements on the ad hoc network with directional antennas. by simulation, we prove superiority that average number of forwarding nodes for each antenna element and the ratio of duplicated messages for each nodes rather than existing partial dominant pruning method though the number of antenna elements are increasing rather than in case of using omni antennas.

• Journal of the Korea Society of Computer and Information
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• v.14 no.3
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• pp.161-171
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• 2009

In this paper, we propose an automatic method for setting data constraints of a data cleansing service, which is for managing the quality of data exchanged between composite services based on SOA(Service-Oriented Architecture) and enables to minimize human intervention during the process. Because it is impossible to deal with all kinds of real-world data, we focus on business data (i.e. costumer order, order processing) which are frequently used in services such as CRM(Customer Relationship Management) and ERP(Enterprise Resource Planning). We first generate an extended-element vector by extending semantics of data exchanged between composite services and then build a rule-based system for setting data constraints automatically using the decision tree learning algorithm. We applied this rule-based system into the data cleansing service and showed the automation rate over 41% by learning data from multiple registered services in the field of business.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.2
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• pp.245-254
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• 2022

In this paper, a design optimization method for anti-jamming GPS antenna is presented. For this purpose, jamming performance analysis criteria and methods are presented. And based on the proposed analysis method, the antenna design elements that can realize the best performance were optimized. The anti-jamming GPS antenna for applying the presented method has a structure in which 7 radiating elements are arranged. Here, six radiating elements were circular arranged, and one element was arranged in the center of the circular arrangement. The optimized antenna design parameter(radius of the circular array) is 0.48 λ. As a result of the simulation, it was confirmed that when the steering angle(theta, phi) of the main lobe was (0°, 0°), the pattern null steering range(based on theta) was 57° to 90°.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.2
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• pp.333-342
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• 2022

Cellular Automata (CA) is a discrete and abstract computational model that is being applied in various fields. Applicable as an excellent pseudo-random sequence generator, CA has recently developed into a basic element of cryptographic systems. Several studies on CA-based stream ciphers have been conducted and it has been observed that the encryption strength increases when the radius of a CA's neighbor is increased when appropriate CA rules are used. In this paper, among CAs that can be applied as a one-dimensional pseudo-random number sequence generator (PRNG), one-dimensional 5-neighbor CAs are classified according to the connection state of their neighbors, and the ignition relationship of the characteristic polynomial is obtained. Also this paper propose a synthesis algorithm for an asymmetric 1-D linear 5-neighbor MLCA in which the radius of the neighbor is increased by 2 using the one-dimensional 3-neighbor 90/150 CA state transition matrix.

• Journal of the Korean Society of Industry Convergence
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• v.26 no.6_3
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• pp.1279-1288
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• 2023

Recently, domestic leisure boats have been actively researching eco-friendly product development to enter the global market. Since the hulls of existing leisure boats are mainly made of fiber reinforced plastic (FRP) or aluminum, design techniques for securing structural safety by applying related materials have been mainly studied. In this study, an initial structural design safety assessment of a trimaran pontoon leisure boat with a modular hull structure and eco-friendly high-density polyethylene (HDPE) material was conducted, and sensitivity evaluation and optimization analysis for lightweight design were performed. The initial structural design safety assessment was carried out by creating a finite element analysis model and applying the loading conditions specified in the ship classification regulation to check whether the specified allowable stresses are satisfied. For the sensitivity evaluation, the influence of stress and weight of each hull structural member was evaluated using the orthogonal array design of experiments method, and an approximate model based on the response surface method was generated using the results of the design of experiments. The optimization analysis set the thickness of the hull structural members as the design variable and considered the optimal design formulation to minimize the weight while satisfying the allowable stress. The algorithm of the optimization analysis applied the Gradient-population Based Optimizer (GBO) to improve the accuracy of the optimal solution convergence while reducing the numerical cost. Through this study, the optimal design of a newly developed eco-friendly trimaran pontoon leisure boat with a weight reduction of 10% was presented.

• Journal of the Society of Naval Architects of Korea
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• v.61 no.2
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• pp.115-124
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• 2024

To detect and prevent structural damage caused by various loads on marine structures and ships, structural health monitoring procedure is essential. Estimating loads acting on the structures which are measured by sensors that are mounted properly are crucial for structural health monitoring. However, attaching an excessive number of sensors to the structure without consideration can be inefficient due to the high costs involved and the potential for inducing structural instability. In this study, we introduce a method to determine the optimal number of sensors and their optimized locations for strain measurement sensors, allowing for accurate load estimation throughout the structure using model expansion method. To estimate the loads exerted on the entire structure with minimal sensors, we construct a strain-load interpolation matrix using the strain mode shapes of the finite element (FE) model and select the optimal sensor locations by applying D-Optimal Design and the row exchange algorithm. Finally, we estimate the loads exerted on the entire structure using the model expansion method. To validate the proposed method, we compare the results obtained by applying the optimal sensor placement and model expansion method to an FE model subjected to arbitrary loads with the loads exerted on the entire FE model, demonstrating efficiency and accuracy.

• Journal of Advanced Navigation Technology
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• v.28 no.1
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• pp.1-14
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• 2024

Global navigation satellite system (GNSS) providing position, navigation and timing (PNT) services consist of satellite, ground, and user systems. Monitoring stations, a key element of the ground segment, play a crucial role in continuously collecting satellite navigation signals for service provision and fault detection. These stations detect anomalies such as threats to the signal-in-space (SIS) of satellites, receiver issues, and local threats. They deliver received data and detection results to the master station. This paper introduces the main monitoring algorithms and measurement pre-processing processes for quality assessment and fault detection of received satellite signals in current satellite navigation system monitoring stations. Furthermore, it proposes a strategy for the development of components, architecture, and algorithms for the new regional navigation satellite system (RNSS) monitoring stations.

• Advances in Computational Design
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• v.8 no.4
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• pp.309-325
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• 2023

An innovative inertial reactive armor is being developed through a multi-discipline project. Unlike the well-known explosive or non-explosive reactive armour that uses high-energy explosives or bulging effect, the proposed inertial reactive armour uses active disc elements that is set to rotate rapidly upon impact to effectively deflect and disrupt shaped charges and kinetic energy penetrators. The effectiveness of the proposed armour highly depends on the tangential velocity of the impact point on the rotating disc. However,for a single layer armour with an array of high-speed rotating discs, the tangential velocity is relatively low near the center of the disc and is not available between the gap of the discs. Therefore, it is necessary to configure the armor with double layers to increase the tangential velocity at the point of impact. This paper explores a multi-objective geometry design optimization for the double-layered armor using Nelder-Mead optimization algorithm and integration tools of the python programming language. The optimization objectives include maximizing both average tangential velocity and high tangential velocity areas and minimizing low tangential velocity area. The design parameters include the relative position (translation and rotation) of the disc element between two armor layers. The optimized design results in a significant increase of the average tangential velocity (38%), increase of the high tangential velocity area (71.3%), and decrease of the low tangential velocity area (86.2%) as comparing to the single layer armor.