• Proceedings of the SAREK Conference
• /
• 2008.06a
• /
• pp.919-924
• /
• 2008

Power consumption in the building thermal load could be the sum of the building fabric conduction load, building ventilation convection load and other such as radiation loss load. Dynamic Breathing Building (DBB) is the state-of-the-art to improve the wall insulation and indoor air quality(IAQ) performance as making air flow through the wall. This heat recovery type DBB contributes the power consumption saving due to the improved dynamic U-value. KIER twin test cell with static insulation(SI) and dynamic insulation(DI) at KIER was developed to test building power consumption at the real outside conditions. Then, the actual results were compared with the theory to predict the power consumption at the KIER twin test cell and introduced the building new radiation loss factor $\alpha$ to explain the difference between the both the theory and the actual case. As the results, the power consumption at the breathing DI wall building could saved 10.8% at the 2ACH(Air change per hour) compared with conventional insulation. The building radiation loss factor $\alpha$ for this test condition to calibrate the actual test was 0.55 in the test condition.

• Proceedings of the SAREK Conference
• /
• 2008.06a
• /
• pp.748-753
• /
• 2008

In modern buildings, the air-tightness and insulation for energy saving resulted in degradation of Indoor Air Quality(IAQ). It has brought out new diseases such as New Building Syndrome(NBS) and Sick Building Syndrome(SBS) to the tenants of such buildings. As a result, researches on the Dynamic Breathing Building(DBB) are being undertaken to minimize energy loss as well as to improve IAQ. DBB is a state-of-the-art technology to build channels inside the wall so that air migrates between indoor and outdoor, which improves insulation performance and IAQ. This study attempts to evaluate the improvement of DBB employed in real buildings. As analyzing tools, IAQ improvement and particle degradation while were evaluated while the required indoor ventilation rate was satisfied. DBB were installed in the twin test cells at Korea Institute of Energy Research(KIER). From the test, IAQ was compared with outdoor air base on the concentration of particle matter(PM10). As a results, the concentration of particle dust (PM10) within the breathing walls was reduced by 80% at 0.7 ACH, 67% at 2 ACH, 63% at 3 ACH respectively. As ACH is higher, Dnamic Isulation(DI) and normal wall permit more PM10 particles being infiltrated.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
• /
• v.22 no.6
• /
• pp.361-368
• /
• 2010

Due to the insulation and the air-tightness requirement in modern buildings have resulted NBS(New Building Syndrome) and SBS(Sick Building Syndrome) of IAQ problems. Therefore, energy efficient way of solving such IAQ issues are of major concern in these days and building industries. This paper introduces a method to improve thermal performance with a DI(Dynamic Insulation) concept. The characteristic of the dynamic insulation is that the lower U-value as the higher air velocity through the DI in a micro level. A thermal performance monitoring study has been conducted to show the energy impact of porous DI over the static insulation material. The results show that up to 45% could be improved in the case with DI compared to the conventional insulation.

• Smart Structures and Systems
• /
• v.20 no.6
• /
• pp.669-682
• /
• 2017

The normalised version of bispectrum, the so-called bicoherence, has often proved a reliable method of damage detection on engineering applications. Indeed, higher-order spectral analysis (HOSA) has the advantage of being able to detect non-linearity in the structural dynamic response while being insensitive to ambient vibrations. Skewness in the response may be easily spotted and related to damage conditions, as the majority of common faults and cracks shows bilinear effects. The present study tries to extend the application of HOSA to damage localisation, resorting to a neural network based classification algorithm. In order to validate the approach, a non-linear finite element model of a 4-meters-long cantilever beam has been built. This model could be seen as a first generic concept of more complex structural systems, such as aircraft wings, wind turbine blades, etc. The main aim of the study is to train a Neural Network (NN) able to classify different damage locations, when fed with bispectra. These are computed using the dynamic response of the FE nonlinear model to random noise excitation.