Earticle

Valves are one of the indispensable components in modern industry. Filling and de-pressure connectors in rocket valves used for space launch vehicles are very important parts for smooth fluid supply. For this reason, an optimized design that can improve efficiency, miniaturization, weight reduction, and safety of the valve at the same time is required. In this work, flow analysis and structural analysis were performed through 3D modeling using computational numerical analysis for open type filling and de-pressure valves. As results, the flow velocity and pressure distribution of the fluid were analyzed through the flow analysis of valve, and stress distribution was conducted in structural analysis. Through this study, it is consequently expected to provide valves of various specifications by performing production and performance test evaluation of development prototypes.

This study proposes an energy-efficient framework for non-terrestrial networks (NTNs) integrating a low Earth orbit (LEO) satellite, an unmanned aerial vehicle (UAV)-mounted reconfigurable intelligent surface (RIS), and a terrestrial user. The framework jointly optimizes the UAV’s 3D trajectory, satellite beamforming vectors, and RIS reflection coefficients to maximize energy efficiency (EE), accounting for UAV propulsion energy consumption and Quality of Service (QoS) constraints. The resulting non-convex fractional problem is solved using a low-complexity iterative algorithm combining successive convex approximation (SCA) and second-order cone programming (SOCP). Simulation results reveal up to 35% EE improvement over baseline schemes, highlighting the framework’s scalability and practicality for sustainable NTN systems.

Electric motors, as the core of modern electric propulsion platforms, face increasing demands for high power density and lightweight designs. Conventional electric motors, relying on copper windings and iron cores, encounter significant limitations in meeting these requirements, particularly in applications such as aircraft and heavy-duty vehicles. High-temperature superconducting (HTS) tapes, characterized by their superior current-carrying capacity under critical conditions, offer a promising alternative. Motors incorporating HTS tapes demonstrate exceptional power-to-weight ratios, driving extensive research into replacing conventional motors. However, for mobility applications, HTS motors require optimized support structures designed to meet weight constraints. Unlike static applications of HTS coils, the support structure for a rotating superconducting rotor must ensure torque transmission and maintain cryogenic conditions while addressing both structural and thermal factors. This study focuses on the optimized design of the support structure for a superconducting rotor equipped with HTS coils. The proposed design is evaluated through finite element method (FEM) analysis, verifying its mechanical and thermal performance under operational conditions.

There has been increasingly large demand for next generation high speed transport system to compliment air travel and for aerospace vehicle launchers for uses such as low orbit space transports. In this study, characteristics of two pulsed power accelerator designs commonly referred as Rail Gun and Gauss Gun were tested with the custom designed experimental set up. Velocity and various side effects during the operation of the accelerator, such as “suck-back” effect and rail erosion were noted and were used to achieve minimum set of controls defined as controlled acceleration, deceleration and deflection respectively. The experimental system with four sets of acceleration motors were able to achieve acceleration with measured energy efficiency peaking at 3 percent. It was concluded that the concept of transport system utilizing electromagnetic pulsed power system can be viable with relatively simple requirements while allowing unique designs without its form factor limited to conventional strictly linear path.

Taguchi's robust parameter design is an approach to reduce the performance variation of quality characteristics in products and processes. In robust design, the signal-to-noise ratio (SN ratio) was used to find the optimum condition to minimize the variation of quality characteristics as much as possible and bring the average of quality characteristics closer to the target value. In this paper, we propose a simultaneous optimization method based on a linear model of the SN ratio as a method to find the optimal condition of the control factor in case of multi-characteristics. In addition, the proposed method and the existing method were compared and studied by taking actual cases.

Taguchi has used the signal-to-noise ratio (SN) to achieve the appropriate set of operating conditions where variability around target is low in the Taguchi parameter design. Taguchi has dealt with having constraints on both the mean and variability of a characteristic (the dual response problem) by combining information on both mean and variability into an SN. Many Statisticians criticize the Taguchi techniques of analysis, particularly those based on the SN. In this paper we propose a substantially simpler optimization procedure for parameter design to solve the dual response problems without resorting to SN.

본 논문은 자율주행차량 환경에서 V2X(Vehicle-to-Everything) 통신의 성능을 최적화하고, 높은 이동성과 네트워크 불안정성이 특징인 VANET(Vehicular Ad Hoc Network) 환경에서 효과적인 지능형 교통 시스템(ITS)을 구현하기 위한 SDVN(Software-Defined Vehicular Network) 기반 설계 방법을 제안한다. 기존의 VANET은 분산형 구조로 인해 패킷 손실, 지연 증가, 네트워크 단절 등 여러 한계가 존재하며, 이를 해결하기 위해 본 연구는 SDN 아키텍처를 차량 통신망에 통합하였다. SDN의 중앙집중 제어 특성을 활용하여 네트워크 토폴로지를 실시간으로 관리하고, 트래픽 상황에 따라 최적의 경로를 동적으로 설정할 수 있도록 하였다. 시뮬레이션은 VEINS, SUMO, OMNeT++, Mininet-WiFi, Ryu 컨트롤러를 통합하여 구축되었으며, 다양한 차량 밀도와 도시 교차로 기반 시나리오에서 VANET 대비 SDVN의 성능을 정량적으로 비교하였다. 실험 결과, SDVN 기반 ITS는 평균 지연 시간에서 최대 25% 감소, 패킷 전달률(PDR) 15% 증가, 네트워크 처리량(Throughput) 약 30% 향상을 나타냈으며, 중앙제어로 인한 제어 메시지 오버헤드는 소폭 증가하였다. 본 연구는 향후 자율주행 기술의 확산과 더불어 차량 통신 인프라의 고도화를 위한 기반 기술로 활용될 수 있을 것이다.

This paper presents an in-depth optimization strategy for Vehicle-to-Everything (V2X) communication tailored for autonomous vehicle networks and proposes a robust Intelligent Transportation System (ITS) architecture built upon Software-Defined Vehicular Networking (SDVN) within highly dynamic VANET environments. While traditional Vehicular Ad Hoc Networks (VANETs) offer decentralized communication among mobile nodes, they suffer from inherent limitations such as frequent topology changes, high latency, and unreliable data delivery. The proposed architecture integrates real-time mobility simulation (SUMO), discrete event network modeling (OMNeT++), vehicular communication (VEINS), wireless emulation (Mininet-WiFi), and programmable flow control via the Ryu SDN controller. Various urban traffic scenarios with differing vehicle densities (low, medium, high) were simulated, and the performance of the SDVN-based ITS was benchmarked against a conventional VANET model. The SDVN model demonstrated a reduction of up to 25% in latency, a 15% improvement in PDR, and up to 30% higher throughput, while incurring only a moderate increase in control overhead due to SDN signaling. These findings validate the feasibility and efficiency of SDVN-enhanced ITS frameworks for next-generation smart transportation infrastructures and offer valuable insights for large-scale deployment in future autonomous mobility ecosystems.

Advances in digital tools and building structure technologies have enabled more flexible architectural design, with AI-based performance design gaining considerable attention as a new design methodology. Stadium design must consider the two primary elements of sports events: athletes and spectators. Given that the facade of a stadium directly impacts solar energy efficiency, it is essential to incorporate environmental performance considerations from the initial design phase. This study employs an AI-based Generative Design process to generate a facade form that efficiently manages solar radiation and daylight, satisfying two conflicting performance objectives: max- imizing sunlight for turf growth in the pitch zone and minimizing direct sunlight exposure in the stadium seating zone. The optimal solution derived ranks 331st for pitch zone sunlight and 408th for stadium seating sunlight out of a dataset of 1,000 models. While this solution does not represent the absolute best for either individual objective, it is evaluated as the most balanced alternative, achieving the goal of maximizing sunlight in the pitch zone and minimizing it in the seating zone

The properties of the conductor-mechanical, thermal, and electrical-are the key information in the design and optimization of superconducting coils. Particularly, in devices using second generation (2G) high temperature superconductors (HTS), whose base materials (for example, the substrate or stabilizer) and dimensions are adjustable, a design process for conductor optimization is one of the most important factors to enhance the electrical and thermal performance of the superconducting system while reducing the cost of the conductor. Recently, we developed a numerical program that can be used for 2G HTS conductor optimization. Focusing on the five major properties, viz. the electrical resistivity, heat capacity, thermal conductivity, Z-value, and enthalpy, the program includes an electronic database of the major base materials and calculates the equivalent properties of the 2G HTS conductors using the dimensions of the base materials as the input values. In this study, the developed program is introduced and its validity is verified by comparing the experimental and simulated results obtained with several 2G HTS conductors.

In this paper, recognizing the importance of the database query optimization design methods, we implemented mobile database with mobile program (J2ME) which is a useful database procedures. In doing so, we emphasize the logical query optimization which brings mobile database to performance improvement. The research implies that the suggested mobile program (J2ME) would contribute to the realization of the efficient mobile database as the related technology develops in the future.

본 연구는 루틴, 퀘르세틴, 식이섬유가 전분 소화율에 미치는 영향을 통계적 혼합물 설계방법을 이용하여 확인 하고자 하였다. 세 가지 성분들은 모두 농도가 증가함에 따라 전분소화 지연 효과가 나타났으며, 그 중에서도 퀘르세틴 과 식이섬유가 함께 섞였을 때 가장 높은 지연 효과를 보였다. 이 혼합물 설계는 simplex-centroid 실험설계법을 이 용하였고, 최적 모델은 quadratic 모델에서 나타났다. 이때 얻어진 회귀방정식을 통하여 유의한 상승효과를 확인할 수 있었다. 최적화 통계 방법을 사용하여 혼합비를 분석한 결과 퀘르세틴과 식이섬유가 72: 28 비율에서 전분 소화 지연 효과가 최대로 나타나는 것을 확인하였다. 전분소화에 대한 영향을 3차원 표면 도표로 시각화하여 나타내었으며, 이 결과로 퀘르세틴과 식이섬유의 상호작용으로 인하여 전분 소화를 15% 이상 지연시키는 것을 확인할 수 있었다.

This study was conducted to develop the efficient system for starch hydrolysis suppression using rutin, quercetin and dietary fiber through the statistical mixture design. The three components were replaced with wheat flour at the level of 10% and the mixed gel with three components was characterized by in vitro starch digestion. The mixture design was applied by simplex-centroid experimental model. The quadratic model (R2=0.86) was well fitted and the obtained regression equation indicated that the significant positive effects was observed in the quercetin and fiber mixture. Based on the statistical results, the best mixing ratio of quercetin and fiber was 72: 28 that led to the lowest predicted glycemic index (pGI). Their interactions on the pGI of starch digestibility were clearly visualized in the 3D surface plot. These results suggested that the mixture of quercetin and fiber interact strongly with wheat flour, consequently retarding starch hydrolysis by 15%.

본 연구에서는 중심합성계획법을 이용하여 티탄철광의 건식 자력선별에서 2인자 3수준의 실험설계를통해 변수의 최적화 및 수학적 모델을 구축하였다. 자계강도(x1)와 급광량(x2)을 독립변수로 선정하였으며, 종속변수인 TiO2의 품위(y1)와 회수율(y2)을 수학적 모델로 도출하였다. y1 및 y2에 가장 크게 영향을 미치는 인자는자계강도(x1) 이었으며, 급광량(x2)은 큰 영향을 미치지 않았다. 생성된 반응모델의 결정계수(R 2 , coefficient of determination)는 0.99%, prob>F는 0.0001로 매우 높은 신뢰도를 보였다. 최적의 선별조건을 찾기 위해 Minitab 17을 이용하여 최적화 시킨 결과 (x1 : 4,360 gauss, x2 : 10.85 g/min.)의 조건에서 TiO2의 품위와 회수율이 각각49.09% TiO2와 98.16%인 결과를 얻었다.

In this study, a two factor - three level Central Composite Design (CCD) combined with response surface methodology was applied for modeling and optimization of process parameters of cross belt magnetic separation on the Ha-dong ilmenite. The magnetic intensity (x1) and feed rate (x2) were determined as independent variables, but the dependant variables of y1 : grade of TiO2 and recovery were obtained by mathmatical model. It results that x1 gives great influence on the response surface model (y1, y2), but the x2 does little. And it appears that the predicted values of grade and recovery applying the model equations are highly consisted with the experimental values of grade and recovery (R 2 : 0.99, prob>F 0.0001). As a result, it was confirmed that the ilmenite could be concentrated to 49.09% with the recovery of 98.16%, at optimum condition as follow ; (x1 : 4,360 gauss, x2 : 10.85 g/min.) applying Minitab 17.

오일 및 CO2 가격을 반영한 CO2 자극공법의 최적 설계안을 검토하기 위하여 본 수치 연구를 수행하였다. 주입설계 최적화를 위하여 순현가와 연계된 목적함수를 정의하고 Computer Modeling Group의 최적화 도구인 CMOST를 이용하였다. 복수의 CO2-오일 가격 시나리오를 설정하고 순현재가치를 기준으로 자극공법의 생산성에 영향을 주는 주입량과 soaking 시간 등의 설계 인자들을 최적화하였다. 본 연구 결과에 따르면 CO2 가격이 상승하면서 주입량이 감소하였으며 이는 두 번째 단계에서 더 크게 나타났다. CO2 가격이 높을수록 주입의 효율성을 고려하여 첫 번째 단계에서 가능한 많은 양을 생산하는 것이 적절하였다. 오일 가격이 증가하면서 첫 번째 단계의 주입설계는 거의 변하지 않는다. soaking 시간의 경우 경향성이 뚜렷하지 않았으며 생산성에 미치는 영향도 매우 작았다.

This numerical study was undertaken to investigate optimal design of CO2 stimulation considering oil and CO2 prices. For injection design optimization, objective function associated with net present value (NPV) was defined. CMOST, the optimization tool of Computer Modeling Group, is used to determine optimum cases. Design parameters such as injection volume and soaking time, which are known to affect the performance of CO2 stimulation, were optimized in terms of NPV through different scenarios of oil and CO2 prices. Results from the study indicated that optimum injection volume was declined at higher cost of CO2, especially in the second cycle. For higher CO2 price, it was better to maximize production of the first cycle for improving the efficiency of injection. As oil price increases, there were no changes of injection scheme in the first cycle. Soaking time had no clear tendency related with operating condition and affected production performance very slightly.

고로슬래그(BFS) 경량기포콘크리트 제조의 최적 배합비를 도출하기 위해 반응표면분석법 중 하나인 Box-Behnken법을 이용하여연구를 수행하였다. 경량기포콘크리트는 상압증기양생법으로 제조하였으며 주요 실험변수로는 물/분체(W/P_d)비, BFS 치환률 그리고분체량(P_d) 기준 Al분말 첨가량을 설정하였다. 반응표면분석에 의해 경량기포콘크리트의 절건비중 및 압축강도에 대한 회귀 모델식이 유도되었다. 경량기포콘크리트의 절건비중과 압축강도에 대한 목표값을 각각 0.72와 4.42 MPa로 설정하고 회귀 모델식에 의해도출된 경량기포콘크리트의 최적 배합비는 W/P_d비 0.62, BFS 치환률 35.5% 그리고 분체대비 Al분말 첨가량 0.05%이었다. 이처럼도출된 배합비로 제조한 경량기포콘크리트 시험체에 대한 절건비중과 압축강도의 측정값을 통해 회귀 모델식의 신뢰성이 확인되었다.

This study was conducted to optimize a mixing design of lightweight aerated concrete with the blast furnace slag(BFS) using Box-Behnken method, one of response surface designs. The lightweight aerated concrete with the BFS was made on the conditions of steam curing method at atmospheric pressure. The experimental factors were unit Water(W)/total powder(Pd) ratio,BFS replacement percentage and Al powder addition based on the total powder (P_d*%). From the results of the response surface analysis, regression models for dried specific gravity and compressive strength of the lightweight aerated concrete were derived. When the target values for dried specific gravity and compressive strength of the lightweight aerated concrete were set at 0.72and 4.42 MPa respectively, its optimized mixing conditions driven from the regression models were 0.62 of W/P_d ratio, 35.5%of BFS replacement and 0.05% of Al powder addition. This experimental design model was found to be credible by measuring the dried specific gravity and compressive strength of the sample made from the above mixing conditions

The importance of eco-friendly architectural design has become an essential design element along with the global climate crisis. Nevertheless, eco-friendly considerations are generally made in the mid to late stages of the architectural design process, and in particular, there is a high tendency to focus on consideration of architectural facilities or facade design rather than determining the overall shape, such as the layout, height, or orientation of the building. However, as mentioned above, the decisions made in the early design process often determine the actual performance of the building, so more advanced research is needed on ways to increase the energy performance of buildings in the early design stage. An algorithm was designed so that the eco-friendly design techniques derived through this study can be universally applied not only to specific sites but also to unspecified sites. Through the two proposed stages - placement, height and orientation - it was possible to derive an optimized building shape in the early design stage, and thus it can be said to be a technique that enables a high level of energy savings throughout the entire life cycle of the building.

This study focused on the problems of generative-based optimization design, recently become increasingly popular in the field of architectural design, such as overlooking form due to performance-oriented evaluation and designers' difficulties in analyzing huge number of solutions. In response to this, the study aims to incorporate a form-based clustering technique into the existing optimization process. To achieve this, we use Wallacei, an optimization tool, to perform optimization on the set example. Afterwards, the cluster composition and process characteristics of the derived optimal solution group were analyzed using various clustering techniques. In detail, K-means clustering was applied to the optimal solution group derived for the example set as the first step to confirm the adequacy and characteristics of clustering according to the form criteria. Second, we perform comparison analysis on the changes and differences in various clustering results derived from K-means clustering and three hierarchical clustering to derive rationality and efficient utilization of its application. Through this, the application of the clustering technique to generative design simplifies the huge solutions through form-based evaluation and clustering to increase user interpretation of the solutions and its usability, thereby complementing the completeness of optimization process required in architectural design.

Multidisciplinary Design Optimization(MDO) method that considers principles in various fields affecting big scale structure and system design at the same time is used. Because most variables are connected many engineering phenomena under the classic optimized design method(all-in-one design approach), it is hard to judge the meaning of final design solution obtained, and there are cases where all variables converge before reaching the optimal design value in large-scale design problems with many variables. Collaborative Optimization (CO) method, the most advanced MDO approach, is used to efficiently solve these optimum problems, to efficiently analyze design problems involving numerous design variables and constraints and in which various engineering phenomena occur. However, the application of the MDO problem to CO introduces a number of numerical problems by destroying the numerical properties of the original optimal design problem. Therefore, this study researches one solution by listing the problems of CO after organizing various approaches of MDO.