• Steel and Composite Structures
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• v.33 no.1
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• pp.37-66
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• 2019

In cold-formed steel structures, such as trusses, wall frames and portal frames, the use of back-to-back built-up cold-formed stainless-steel lipped channels as compression members are becoming increasingly popular. The advantages of using stainless-steel as structural members are corrosion resistance and durability, compared with carbon steel. The AISI/ASCE Standard, SEI/ASCE-8-02 and AS/NZS do not include the design of stainless-steel built-up channels and very few experimental tests or finite element analyses have been reported in the literature for such back-to back cold-formed stainless-steel channels. Current guidance by the American Iron and Steel Institute (AISI) and the Australian and New Zealand (gAS/NZS) standards for built-up carbon steel sections only describe a modified slenderness approach, to consider the spacing of the intermediate fasteners. Thus, this paper presents a numerical investigation on the behavior of back-to-back cold-formed stainless-steel built-up lipped channels. Three different grades of stainless steel i.e., duplex EN1.4462, ferritic EN1.4003 and austenitic EN1.4404 have been considered. Effect of screw spacing on the axial strength of such built-up channels was investigated. As expected, most of the short and intermediate columns failed by either local-global or local-distortional buckling interactions, whereas the long columns, failed by global buckling. All three grades of stainless-steel stub columns failed by local buckling. A comprehensive parametric study was then carried out covering a wide range of slenderness and different cross-sectional geometries to assess the performance of the current design guidelines by AISI and AS/NZS. In total, 647 finite element models were analyzed. From the results of the parametric study, it was found that the AISI & AS/NZS are conservative by around 10 to 20% for cold-formed stainless-steel built-up lipped channels failed through overall buckling, irrespective of the stainless-steel grades. However, the AISI and AS/NZS can be un-conservative by around 6% for all three grades of stainless-steel built-up channels, which failed by local buckling.

• Steel and Composite Structures
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• v.19 no.2
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• pp.485-501
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• 2015

Channels are implemented in composite beams as shear connectors in two arrangements, face to face and back to back. No relevant explanation is found in the design codes to clarify the preference of the mentioned arrangements. Besides, the designers do not have a common opinion on this subject; i.e., some recommend the face to face and others, back to back status. In this research, channel shear connectors in composite beams are studied analytically for both arrangements using ABAQUS software. For this purpose, they have been modeled in simply supported beams in the arrangements of face to face and back to back; their effects on the crack initiation load of concrete slabs were monitored. The stiffness values of composite beams were also compared in the two arrangements using force-displacement curve; the results are relatively the same in both cases. Furthermore, the effects of compressive strength of concrete, channel size, length and spacing of channels as well as steel type of channels on the performance of composite beams have been investigated. According to the results obtained in this research, the face to face status shows better performance in comparison with that of back to back, considering the load of concrete fracturing.

• Steel and Composite Structures
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• v.42 no.4
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• pp.513-538
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• 2022

This paper reports on experiments addressing the buckling and collapse behavior of an innovative built-up cold-formed steel (CFS) columns. The built-up column consists of four individual CFS lipped channels, two of them placed back-to-back at the web using two self-drilling screw fasteners at specified spacing along the column length, while the other two channels were connected flange-to-flange using one self-drilling screw fastener at specified spacing along the column length. In total, 12 experimental tests are reported, covering a wide range of column lengths from stub to slender columns. The initial geometric imperfections and material properties were determined for all test specimens. The effect of screw spacing, load-versus axial shortening behaviour and buckling modes for different lengths and screw spacing were investigated. Nonlinear finite element (FE) models were also developed, which included material nonlinearities and initial geometric imperfections. The FE models were validated against the experimental results, both in terms of axial capacity and failure modes of built-up CFS columns. Furthermore, using the validated FE models, a parametric study was conducted which comprises 324 models to investigate the effect of screw fastener spacing, thicknesses and wide range of lengths on axial capacity of back-to-back and flange-to-flange built-up CFS channel sections. Using both the experimental and FE results, it is shown that design in accordance with the American Iron and Steel Institute (AISI) and Australia/New Zealand (AS/NZS) standards is slightly conservative by 6% on average, while determining the axial capacity of back-to-back and flange-to-flange built-up CFS channel sections.

• Steel and Composite Structures
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• v.28 no.2
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• pp.233-250
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• 2018

Back-to-back built-up cold-formed steel un-lipped channel sections are used in cold-formed steel structures; such as trusses, wall frames and portal frames. In such built-up columns, intermediate fasteners resist the buckling of individual channel-sections. No experimental tests or finite element analyses have been reported in the literature for back-to-back built-up cold-formed steel un-lipped channel sections and specially investigated the effect of screw spacing on axial strength of such columns. The issue is addressed in this paper. The results of 95 finite element analyses are presented covering stub to slender columns. The finite element model is validated against the experimental tests recently conducted by authors for back-to-back built-up cold-formed steel lipped channel sections. The verified finite element model is then used for the purposes of a parametric study to investigate the effect of screw spacing on axial strength of back-to-back built-up cold-formed steel un-lipped channel sections. Results are compared against the built-up lipped channel sections and it is shown that the axial strength of un-lipped built-up sections are 31% lesser on average than the built-up lipped channel sections. It was also found that the American Iron and Steel Institute (AISI) and the Australian and New Zealand Standards were over-conservative by around 15% for built-up columns failed through overall buckling, however AISI and AS/NZS were un-conservative by around 8% for built-up columns mainly failed by local buckling.

• Korean Journal of Applied Biomechanics
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• v.34 no.1
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• pp.9-17
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• 2024

Objective: The purpose of this study is to apply 8-week velocity-based training to domestic professional athletes and the kinematic and kinetic analysis of the 1-RM improvement of back squat and power clean, which can represent strength-power ability, to verify the effectiveness of velocity-based training in Korea and to establish a basic basis. Method: The subjects who participated in this study were 10 professional athletes from K University (age: 21.40 ± 0.97 yrs., height: 179.90 ± 3.54 cm., body mass: 71.298 ± 2.98 kg). All subjects performed back squat and power clean 1-RM before and after 8-weeks of velocity-based training. A 3-dimensional motion analysis with 8 infrared cameras and 4 channels of EMG was performed in this study. A paired t-test was used for statistical verification. The significant level was set at α=.05. Results: Both Back squat and Power Clean 1-RM showed statistically significant increases (p<.05). In the case of back squat, there was no statistically significant difference in both kinematic and kinetic variables (p>.05). In the case of Power Clean, only the quadriceps of Phase 1 showed a statistically significant decrease (p<.05). Conclusion: Domestic professional athletes can improve their strength-power ability through velocity-based training, and such training for at least 8-weeks is considered a way to improve their performance.

• Nuclear Engineering and Technology
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• v.51 no.8
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• pp.1897-1904
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• 2019

Three-layer back propagation network (BPN) and genetic neural network (GNN) were developed in this study to predict the flow boiling heat transfer coefficient (HTC) in conventional and small-diameter channels. The GNN has higher precision than BPN (with root mean square errors of 17.16% and 20.50%, respectively) and other correlations. The inputs include vapor quality x, mass flux G, heat flux q, diameter D and physical parameter φ, and the predicted flow boiling HTC is set as the outputs. Influences of input parameters on the flow boiling HTC are discussed based on the trained GNN: nucleate boiling promoted by a larger saturated pressure, a larger heat flux and a smaller diameter is dominant in small channels; convective boiling improved by a larger mass flux and a larger vapor quality is more significant in conventional channels. The HTC increases with pressure both in conventional and small channels. The HTC in conventional channels rises when mass flux increases but remains almost unaffected in small channels. A larger heat flux leads to the HTC growth in small channels and an increase of HTC was observed in conventional channels at a higher vapor quality. HTC increases inversely with diameter before dry out.

• Membrane Journal
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• v.16 no.1
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• pp.31-38
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• 2006

The ceramic microfiltration system with periodic $N_2$-back-flushing was operated for treating paper wastewater discharged from a company making toilet papers by recycling milk or juice cartons. Two kinds of alumina membranes with 7 channels used here for recycling paper wastewater. The optimal filtration time interval for HC04 membrane with $0.4{\mu}m$ pore size was lower value of 4 min than 16 min for HC10 with $1.0{\mu}m$ pore size at fixed back-flushing time 40 sec, trans-membrane pressure $1.0kg_f/cm^2$ and back-flushing pressure $5.0kg_f/cm^2$. From the results of TMP effect at fixed filtration time interval and back-flushing time, the lower TMP was better on membrane fouling because high TMP could make easily membrane cake and fouling inside membrane structure. However, we could acquire the highest volume of total permeate at the highest TMP for the reason that TMP was driving force in our filtration system to treat paper wastewater. Then the permeate water of low turbidity was acquired in our microfiltration system using multi channels ceramic membranes, and the treated water could be reused in paper process.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.8 no.3
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• pp.71-82
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• 2009

As a solution to spectrum under-utilization problem, Cognitive radio (CR) introduces a dynamic spectrum access technology. In the area, one of the most important problems is how secondary users (SUs) should choose between the available channels, which means how to achieve load balancing between channels. We consider spectrum load balancing problem for CR system in frequency domain and especially in time domain. Our objective is to balance the load among the channels and balance the occupied time length of slots for a fixed channel dynamically in order to obtain a user-optimal solution. In frequency domain, we refer to Dynamic Noncooperative Scheme with Communication (DNCOOPC) used in distributed system and a distributed Dynamic Spectrum Load Balancing algorithm (DSLB) is formed based on DNCOOPC. In time domain, Spectrum Load Balancing method with QoS support is proposed based on Dynamic Feed Back theory and Hash Table (SLBDH). The performance of DSLB and SLBDH are evaluated. In frequency domain, DSLB is more efficient compared with existing Compare_And_Balance (CAB) algorithm and gets more throughput compared with Spectrum Load Balancing (SLB) algorithm. Also, DSLB is a fair scheme for all devices. In time domain, SLBDH is an efficient and precise solution compared with Spectrum Load Smoothing (SLS) method.

• Korean Journal of Applied Biomechanics
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• v.32 no.4
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• pp.134-140
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• 2022

Objective: This study aims to verify effect of 1-RM direct measurement method of back squat on beginners. Method: Total of 8 healthy adults were recruited for this study (age: 29 ± 3.81 yrs., height: 174 ± 3.83 cm., body mass: 74 ± 11.63 kg., 1RM: 96 ± 19.78 kg). All participants performed the back squat with 80%, 90% and 100% of the pre-measured 1RM. A three-dimensional motion analysis was performed with 8 infrared cameras and 3 channels of EMG were used for this study. One-way ANOVA with repeated measure was used for the statistical analysis with the significant level set to α=.05. Results: The ankle joint ROM in the transverse plane was significantly increased as the weight increased during the concentric contraction phase 2 (p < .05). In addition, the erector spinae and the gluteus maximus, which are synergist for the motion, showed a significant difference according to the increased weight (p < .05). Conclusion: Our results revealed that beginners increase potential dynamic knee valgus as weight increased. Therefore, it is thought that field coaches should pay attention to this to minimize and prevent injuries when measuring 1-RM for beginners.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1628-1630
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• 1997

The purpose of this study is to see the method of the analysis of EEG(Electroencephalography) whcih is a nonlinear system, to quantize human emotion under color stimulation using the analysis of EEG. The result of this study would be used clinical study and development fo image instruments with color. In this study, the method of the analysis of EEG is power spectrum using FFT(Fast Fourier Transform) and the modelling of EEG under color stimulation base on back propagation Neural Networks ond of AI(Artfical Intellignece) skills. First, input layer make a match to relative power which get analyzing s in 4 channels, and output layer make a match to color stimulation which is measured human emotion. Finally, weights of each neurons determine by learing back porpagation Neural Networks.