• Advances in concrete construction
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• 제9권1호
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• pp.55-70
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• 2020

In this research article, acid resistance, sulphate resistance and sorptivity of self compacted concrete (SCC) prepared from C&D waste have been discussed. To improve the above properties of self compacted recycled aggregate concrete (SCRAC) along with mechanical and durability properties, different two stage mixing approaches (TSMA and TSMAsfc) were followed. In the proposed two stage mixing approach (TSMAsfc), silica fume, a proportional amount of cement and a proportional amount of water were mixed in premix stage which fills the pores and cracks of recycled aggregate concrete (RAC). The concrete specimen prepared using above mixing approaches were immersed in 1% concentration of sulphuric acid (H2SO4) and magnesium sulphate (MgSO4) solution for 28, 90 and 180 days for evaluating the acid resistance of SCRAC. Experimental results concluded that the proposed two stage mixing approach (TSMAsfc) is most suitable for acid resistance and sulphate resistance in terms of weight loss and strength loss due to the elimination of pores and cracks in the interfacial transition zone (ITZ). In modified two stage mixing approach, the pores and cracks of recycled concrete aggregate (RCA) were filled up and make ITZs of SCRAC stronger. Microstructure analysis was carried out to justify the reason of improvement of ITZs by electron probe micro analyser (EPMA) analysis. X-ray mapping was also done to know the presence of strength contributing elements presents in the concrete sample. It was established that SCRAC with modified mixing approach have shown improved results in terms of acid resistance, sulphate resistance, sorptivity and mechanical properties.

• Smart Structures and Systems
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• 제15권1호
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• pp.57-80
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• 2015

Extended Kalman Filter (EKF) has been widely used for structural identification and damage detection. However, conventional EKF approaches require that external excitations are measured. Also, in the conventional EKF, unknown structural parameters are included as an augmented vector in forming the extended state vector. Hence the sizes of extended state vector and state equation are quite large, which suffers from not only large computational effort but also convergence problem for the identification of a large number of unknown parameters. Moreover, such approaches are not suitable for intelligent structural damage detection due to the limited computational power and storage capacities of smart sensors. In this paper, a two-stage and two-step algorithm is proposed for the identification of structural damage as well as unknown external excitations. In stage-one, structural state vector and unknown structural parameters are recursively estimated in a two-step Kalman estimator approach. Then, the unknown external excitations are estimated sequentially by least-squares estimation in stage-two. Therefore, the number of unknown variables to be estimated in each step is reduced and the identification of structural system and unknown excitation are conducted sequentially, which simplify the identification problem and reduces computational efforts significantly. Both numerical simulation examples and lab experimental tests are used to validate the proposed algorithm for the identification of structural damage as well as unknown excitations for structural health monitoring.

• Asian-Australasian Journal of Animal Sciences
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• 제17권2호
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• pp.228-236
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• 2004

Two varieties of alfalfa (Medicago sativa L cv. Pioneer and Beaver) and timothy (Phleum pratense L cv. Climax and Joliette), grown at different locations in Saskatchewan (Canada), were cut at three stages [1=one week before commercial cut (early bud for alfalfa; joint for timothy); 2=at commercial cut (late bud for alfalfa; pre-bloom head for timothy); 3=one week after commercial cut (early bloom for alfalfa; full head for timothy)]. The energy values of forages were determined using three approaches, including chemical (NRC 2001 formula) and biological approaches (standard in vitro and in situ assay). The objectives of this study were to determine the effects of forage variety and stage of maturity on energy values under the climate conditions of western Canada, and to investigate relationship between chemical (NRC 2001 formula) approach and biological approaches (in vitro and in situ assay) on prediction of energy values. The results showed that, in general, forage species (alfalfa vs. timothy) and cutting stage had profound impacts, but the varieties within each species (Pioneer vs. Beaver in alfalfa; Climax vs. Joliette in timothy) had minimal effects on energy values. As forage maturity increased, the energy contents behaved in a quadratic fashion, increasing at stage 2 and then significantly decreasing at stage 3. However, the prediction methods-chemical approach (NRC 2001 formula) and biological approaches (in vitro and in situ assay) had great influences on energy values. The highest predicted energy values were found by using the in situ approach, the lowest prediction value by using the NRC 2001 formula, and the intermediate values by the in vitro approach. The in situ results may be most accurate because it is closest to simulate animal condition. The energy values measured by biological approaches are not predictable by the chemical approach in this study, indicating that a refinement is needed in accurately predicting energy values.

• 한국경영과학회지
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• 제35권2호
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• pp.19-35
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• 2010

Many papers have used a two-stage approach of first calculating DEA efficiency scores and then seeking to correlate these scores with various environmental variables. Most of the studies have not checked whether such a two-stage approach is statistically valid for identifying significant environmental variables. Recently Simar and Wilson (2007) (SW) introduce a sensible data generating process and bootstrap procedure based on truncated regression for the two-stage approach. Banker and Natarajan (2008) (BN) provide a statistical foundation for the two-stage approach comprising a DEA followed by an ordinary least squares or maximum likelihood estimation. Researchers have to identify an approach suitable for their research circumstances in terms of properties, merits, demerits, and robustness to plausible departures from its chosen data generating process. We summarize the foundations and properties of the two-stage procedures suggested by SW and BN. And we discuss merits and demerits of those procedures. Also using Monte Carlo simulation we assess their relative performance under several misspecified settings.

• 국제학술발표논문집
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• The 6th International Conference on Construction Engineering and Project Management
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• pp.496-500
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• 2015

International construction projects are inherently more risky than domestic projects with multi-dimensional uncertainties that require complementary risk management at both the country and project levels. However, despite a growing need for systematic country evaluations, most studies have focused on project-level decisions and lack country-based approaches for firms in the construction industry. Accordingly, this study suggests data-driven approaches for evaluating countries using two quantitative models. The first is a two-stage country segmentation model that not only screens negative countries based on country attractiveness (macro-segmentation) but also identifies promising countries based on the level of past project performance in a given country (micro-segmentation). The second is a multi-criteria country segmentation model that combines a firm's business objective with the country evaluation process based on Kraljic's matrix and fuzzy preference relations (FPR). These models utilize not only secondary data from internationally reputable institutions but also performance data on Korean firms from 1990 to 2014 to evaluate 29 countries. The proposed approaches enable firms to enhance their decision-making capacity for evaluating and selecting countries at the early stage of corporate strategy development.

• 품질경영학회지
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• 제18권1호
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• pp.65-76
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• 1990

A lot-sizing model for multi-stage MRP systems is proposed, in which known demands must be satisfied. In this model, an approach with considerations of initial inventory and limited production capacity is involved. Most of the studies on the lot-sizing techniques for multi-stage material requirement planning systems have been focused upon two basic approaches. One approach is to develope an algorithm yielding an optimal solution. Due to the computational complexity and sensitivity of the optimal solution to the problem of lot sizing, heuristic approaches are often employed. In this paper, the heuristic approach is used by sequential application of a single-stage algorithm with a set of modified cost by the concept of multi-echelon costs. The proposed method is compared with an lot-sizing method(Florian-Klein Model) to prove its effectiveness by numerical examples.

• IEIE Transactions on Smart Processing and Computing
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• 제2권2호
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• pp.45-56
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• 2013

The precise identification of vehicle positions, known as the vehicle localization problem, is an important requirement for building intelligent vehicle ad-hoc networks (VANETs). To solve this problem, two categories of solutions are proposed: stand-alone and data fusion approaches. Compared to stand-alone approaches, which use single information including the global positioning system (GPS) and sensor-based navigation systems with differential corrections, data fusion approaches analyze the position information of several vehicles from GPS and sensor-based navigation systems, etc. Therefore, data fusion approaches show high accuracy. With the position information on a set of vehicles in the preprocessing stage, data fusion approaches is used to estimate the precise vehicular location in the local map building stage. This paper proposes an efficient local map building scheme, which increases the accuracy of the estimated vehicle positions via V2V communications. Even under the low ratio of vehicles with communication modules on the road, the proposed local map building scheme showed high accuracy when estimating the vehicle positions. From the experimental results based on the parameters of the practical vehicular environments, the accuracy of the proposed localization system approached the single lane-level.

• 소성∙가공
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• 제17권3호
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• pp.155-160
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• 2008

We analyzed a sequence of multi-stage automatic cold forging processes composed of four axisymmetric processes followed by a non-axisymmetric process using rigid-plastic finite element based forging simulators. The forging sequence selected for an example involves a piercing process and a heading process accompanying folding or overlapping, which all make it difficult to simulate the processes. To reduce computational time and to enhance the solution reliability, only the non-symmetric process was analyzed by the three-dimensional approach after the axisymmetric processes were analyzed by the two-dimensional approach. It has been emphsized that this capability is very helpful in simulating the multi-stage automatic forging processes which are next to axisymmetric or involve several axisymmetric processes.

• 한국소성가공학회:학술대회논문집
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• 한국소성가공학회 2007년도 추계학술대회 논문집
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• pp.195-200
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• 2007

We analyzed a sequence of multi-stage automatic cold forging processes composed of four axisymmetric processes followed by a non-axisymmetric process using rigid-plastic finite element based forging simulators. The forging sequence selected for an example involves a piercing process and a heading process accompanying folding or overlapping, which all make it difficult to simulate the processes. To reduce computational time and to enhance the solution reliability, only the non-symmetric process was analyzed by the three-dimensional approach after the axisymmetric processes were analyzed by the two-dimensional approach. It has been emphsized that this capability is very helpful in simulating the multi-stage automatic forging processes which are next to axisymmetric.

• 소성∙가공
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• 제11권2호
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• pp.171-178
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• 2002

The elastic deflections of the cold forging die influence the dimensional accuracy of forged parts. The die dimension is continuously changed during the loading, unloading, and ejecting stage. In this paper, we evaluated the elastic deflections of cold forging die during the loading, unloding and ejecting stage with experimental and FEM analysis. Uni-axial strain gages are used to measure elastic strain of die during each forging stage. Strain gages are attached un the upper surface of die. A commercial F.E.M. code, DEFORM$-2D^{TM}$ is used to predict the elastic strains of die, to be compared those by experiments. Two modelling approaches are used to define the reasonable analysis method. The first of the two modelling approaches is to regard the die as rigid body over forging cycle. And then, the die stress is analyzed by loading the die with pressure from the deformed part. The other is to regard the die as elastic body from forging cycle. The elastic strain of tool is calculated and the tool is elastically deformed at each strep. The calculated results under the elastic die assumption are well agreed wish experimental data using the strain gages.