• Smart Structures and Systems
• /
• 제17권6호
• /
• pp.957-980
• /
• 2016

Structural damage detection (SDD) is a challenging task in the field of structural health monitoring (SHM). As an exploring attempt to the SDD problem, a hybrid self-adaptive Firefly-Nelder-Mead (SA-FNM) algorithm is proposed for the SDD problem in this study. First of all, the basic principle of firefly algorithm (FA) is introduced. The Nelder-Mead (NM) algorithm is incorporated into FA for improving the local searching ability. A new strategy for exchanging the information in the firefly group is introduced into the SA-FNM for reducing the computation cost. A random walk strategy for the best firefly and a self-adaptive control strategy of three key parameters, such as light absorption, randomization parameter and critical distance, are proposed for preferably balancing the exploitation and exploration ability of the SA-FNM. The computing performance of the SA-FNM is evaluated and compared with the basic FA by three benchmark functions. Secondly, the SDD problem is mathematically converted into a constrained optimization problem, which is then hopefully solved by the SA-FNM algorithm. A multi-step method is proposed for finding the minimum fitness with a big probability. In order to assess the accuracy and the feasibility of the proposed method, a two-storey rigid frame structure without considering the finite element model (FEM) error and a steel beam with considering the model error are taken examples for numerical simulations. Finally, a series of experimental studies on damage detection of a steel beam with four damage patterns are performed in laboratory. The illustrated results show that the proposed method can accurately identify the structural damage. Some valuable conclusions are made and related issues are discussed as well.

• 한국소음진동공학회:학술대회논문집
• /
• 한국소음진동공학회 2007년도 추계학술대회논문집
• /
• pp.1318-1320
• /
• 2007

Fan noise prediction method is presented for air conditioning and/or cooling system applications where fan acts as an internal equipment having very complicated flow interaction with other various system components. The internal flow paths and distribution in the fan-applied systems such as computer or air conditioner are analyzed by using the FNM(Flow Network Modeling) with the flow resistances for flow elements of the system. Based on the fan operation point predicted from the FNM analysis results, the present fan noise model predicts overall sound power, pressure levels and spectrum. The predictions of the flow distribution, the fan operation and the noise level in electronic system by the present method are well agreed with 3-D CFD and actual noise test results.

• 한국소음진동공학회논문집
• /
• 제18권9호
• /
• pp.952-960
• /
• 2008

Fan noise prediction method is presented for air conditioning, automobile and electronic cooling system applications where fan acts as an internal equipment having very complicated flow interaction with other various system components. The internal flow paths and distribution in the fan-applied systems such as computer or air conditioner are analyzed by using the FNM(flow network modeling). Fan noise prediction method comprises two models for the discrete frequency noise due to rotating steady aerodynamic lift and blade interaction and for the broadband noise due to turbulent boundary layer and wake vortex shedding. Based on the fan operation point predicted from the FNM analysis results and fan design parameters, the present far noise model predicts overall sound pressure level and spectrum. The predictions for the flow distribution, the fan operation and the noise level in air cooling system by the present method are well agreed with 3-D CFD and actual noise test results.

• 한국유체기계학회 논문집
• /
• 제10권3호
• /
• pp.33-38
• /
• 2007

Fan selection procedure and fan noise evaluation method are presented for the system electronic cooling by combining FNM(Flow Network Model) and fan noise correlation model. Internal flow paths and distribution in electronic system we analyzed by using the FNM with the flow resistances for flow elements of the system. Based on the fan operation point predicted from the FNM analysis results, the present fan noise model predicts overall sound power, pressure levels and spectrum. The predictions of the flow distribution, the fan operation and the noise level in electronic system by the present method are well agreed with 3-D CFD and actual test results.

• Journal of the Korean Association of Oral and Maxillofacial Surgeons
• /
• 제48권4호
• /
• pp.207-218
• /
• 2022

Objectives: This study aimed to define the prevalence and characteristics of skull base anomalies and the features of sphenoid sinus pneumatization (SSP). Materials and Methods: Five hundred cone-beam computed tomography scans were evaluated retrospectively for the presence of fossa navicularis magna (FNM), canalis basilaris medianus (CBM), sphenoid emissary foramen (SEF), and/or Onodi cells (OC). Patterns of the SSP and sphenoid sinus mucosa dimensions (SSMD) were also recorded. Results: The prevalence of FNM, CBM, SEF, and OC was 26.0%, 22.4%, 47.4%, and 18.4%, respectively. Two hundred sixty-two (52.4%) sellar-type SSP were defined, followed by post-sellar 191 (38.2%), pre-sellar 31 (6.2%), and conchal 16 (3.2%) types. The frequency of SSMD less than 1 mm, 1-3 mm, and greater than 3 mm was 40.6%, 38.4%, and 21.0%, respectively. An SEF was detected more frequently in females, while SSMD greater than 3 mm was more frequent in males. An FNM was more prevalent in the 18-29 and 30-39 age groups and SEF was significantly less frequent in patients over 60 years of age compared to other age groups. A sinus mucosa larger than 3 mm was more common in the younger than 18 year group. The frequency of post-sellar-type pneumatization was lower in patients younger than 18 years. Conclusion: Skull-base anomalies are common and may be detected incidentally during imaging procedures. The sphenoid sinus, its variations, and pneumatization patterns should also be taken into consideration in imaging procedures performed for various purposes.

• 한국정보통신학회논문지
• /
• 제10권9호
• /
• pp.1648-1653
• /
• 2006

이 연구에서는 해석학적 전류-전압 모델을 이용하여 DGMOSFET(Double Gate MOSFET)의 전송특성을 분석하였다. MOSFET의 게이트길이가 100nm이하로 작아지면 산화막두께가 1.5m이하로 작아져야만하고 채널의 도핑이 매우 증가하기 때문에 소자의 문턱전압변화, 누설전류의 증가 등 다양한 문제가 발생하게 된다 이러한 문제를 조사하기 위하여 해석학적 전류-전압 모델을 이용하여 소자의 크기를 변화시키면서 전류-전압특성을 조사하였다 소자의 크기를 변화시키면서 해석학적 전류-전압 모델의 타당성을 조사하였으며 온도 변화에 대한 특성도 비교 분석하였다. 게이트 전압이 2V에서 77K의 전류-전압 특성이 실온에서 보다 우수하다는 것을 알 수 있었다.