• Title/Summary/Keyword: alternative testing methods

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Experimental and Numerical Analysis of Warm Mix Asphalt Pavement prepared using Steel Slag and RAP (제강슬래그와 폐아스팔트를 활용한 중온 아스팔트 포장의 거동 분석)

  • Lee, Hojoung;Jang, Dongbok;Kim, Hyunwook;Kim, In-TaI;Kim, Kibyung;Lee, Jaehoon
    • International Journal of Highway Engineering
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    • v.19 no.2
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    • pp.55-65
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    • 2017
  • PURPOSES : This study aimed to analyze the experimental and numerical behavior of warm mix asphalt pavement prepared using steel slag and RAP and to conduct economic analysis of pavement construction. METHODS : For developing high performance asphalt pavement, we performed three evaluations: fundamental analysis, experimental testing, and 3D finite element analysis. In particular, 3D finite element analysis was conducted on several pavement structures by adopting the results of experimental tests. RESULTS : Through the various evaluations, it was established that steel slag was effective for use as asphalt mixture aggregate. Moreover, asphalt mixture constituting steel slag and RAP demonstrated higher performance behavior compared with conventionally used asphalt mixture. Furthermore, based on the 3D FE modeling, we established that the developed asphalt pavement constituting steel slag and RAP can be utilized for thin layer pavement with comparable performance behavior. CONCLUSIONS :Warm mix asphalt pavement prepared using steel slag and RAP is more competitive and economic compared to hot-mix asphalt pavement. Moreover, it can be applied for preparing thin layer asphalt pavements with reasonable performance. The developed warm mix asphalt pavement prepared using steel slag and RAP can be an alternative pavement type with competitive performance based on the reasonable economic benefit it provides.

Study of wind tunnel test results of high-rise buildings compared to different design codes

  • Badri, Abdulmonem A.;Hussein, Manar M.;Attia, Walid A.
    • Wind and Structures
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    • v.20 no.5
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    • pp.623-642
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    • 2015
  • Several international codes have been developed for evaluating wind loads on structures; however, the wind structure interaction could not be accurately captured by these codes due to the gusty nature of wind and the dynamic behavior of structures. Therefore, the alternative wind tunnel testing was introduced. In this study, an introduction to the available approaches for wind load calculations for tall buildings was presented. Then, a comparative study between different codes: the Egyptian code, ECP 201-08, ASCE 7-05, BS 6399-2, and wind tunnel test results was conducted. An investigation has been carried out on two case studies tall buildings located within the Arabian Gulf region. Numerical models using (ETABS) software were produced to obtain the relation between codes analytical values and wind tunnel experimental test results for wind loads in the along and across wind directions. Results for the main structural responses including stories forces, shears, overturning moments, lateral displacements, and drifts were presented graphically in order to give clear comparison between the studied methods. The conclusions and recommendations for future works obtained from this research are finally presented to help improving Egyptian code provisions and show limitations for different cases.

Transmission Effect of Price Variations (가격변동의 전이효과)

  • Kim, Tae-Ho;Ann, Ji-Hee
    • Communications for Statistical Applications and Methods
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    • v.17 no.2
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    • pp.241-253
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    • 2010
  • As standard unit root tests are empirically proved to fail to reject the null hypothesis of a unit root for many economic and business time series, it is doubtful that most of those series are informative about the existence of a unit root or that those tests are powerful against relevant alternative hypotheses. This study attempts to perform tests of the null hypothesis of stationarity as well as tests of the null hypothesis of a unit root using the time series data of housing prices in the major metropolitan areas. The results of the additional analyses such as lead-lag, cross-correlation and impulse response for testing the statistical interrelationships between the prices are generally found to be consistent.

Seismic performance and design of bridge piers with rocking isolation

  • Chen, Xingchong;Xia, Xiushen;Zhang, Xiyin;Gao, Jianqiang
    • Structural Engineering and Mechanics
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    • v.73 no.4
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    • pp.447-454
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    • 2020
  • Seismic isolation technology has a wide application to protect bridges from earthquake damage, a new designed bridge pier with seismic isolation are provided for railways in seismic regions of China. The pier with rocking isolation is a self-centering system under small and moderate earthquakes, and the unbonded prestressed tendons are used to prevent overturning under strong earthquakes. A numerical model based on pseudo-static testing results is presented to evaluate the seismic performance of isolation bridge piers, and is validated by the shaking table test. It is found that the rocking response and the loss of prestressing for the bridge pier increase with the increase of earthquake intensity. Besides, the intensity and spectral characteristics of input ground motion have great influence on displacement of the top and bottom of the bridge pier, while have less influence on the bending moment of the pier bottom. Experimental and numerical results show that the rocking-isolated piers presented in this study have good seismic performance, and it provides an alternative way for the railway bridge in the regions with high occurrence of earthquakes. Therefore, we provide the detailed procedures for seismic design of the rocking-isolated bridge pier, and a case study of the seismic isolation design with rocking piers is carried out to popularize the seismic isolation methods.

Force monitoring of steel cables using vision-based sensing technology: methodology and experimental verification

  • Ye, X.W.;Dong, C.Z.;Liu, T.
    • Smart Structures and Systems
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    • v.18 no.3
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    • pp.585-599
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    • 2016
  • Steel cables serve as the key structural components in long-span bridges, and the force state of the steel cable is deemed to be one of the most important determinant factors representing the safety condition of bridge structures. The disadvantages of traditional cable force measurement methods have been envisaged and development of an effective alternative is still desired. In the last decade, the vision-based sensing technology has been rapidly developed and broadly applied in the field of structural health monitoring (SHM). With the aid of vision-based multi-point structural displacement measurement method, monitoring of the tensile force of the steel cable can be realized. In this paper, a novel cable force monitoring system integrated with a multi-point pattern matching algorithm is developed. The feasibility and accuracy of the developed vision-based force monitoring system has been validated by conducting the uniaxial tensile tests of steel bars, steel wire ropes, and parallel strand cables on a universal testing machine (UTM) as well as a series of moving loading experiments on a scale arch bridge model. The comparative study of the experimental outcomes indicates that the results obtained by the vision-based system are consistent with those measured by the traditional method for cable force measurement.

Rapid and Specific Detection of Apple stem grooving virus by Reverse Transcription-recombinase Polymerase Amplification

  • Kim, Nam-Yeon;Oh, Jonghee;Lee, Su-Heon;Kim, Hongsup;Moon, Jae Sun;Jeong, Rae-Dong
    • The Plant Pathology Journal
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    • v.34 no.6
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    • pp.575-579
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    • 2018
  • Apple stem grooving virus (ASGV) is considered to cause the most economically important viral disease in pears in Korea. The current PCR-based methods used to diagnose ASGV are time-consuming in terms of target detection. In this study, a novel assay for specific ASGV detection that is based on reverse transcription-recombinase polymerase amplification is described. This assay has been shown to be reproducible and able to detect as little as $4.7ng/{\mu}l$ of purified RNA obtained from an ASGV-infected plant. The major advantage of this assay is that the reaction for the target virus is completed in 1 min, and amplification only requires an incubation temperature of $42^{\circ}C$. This assay is a promising alternative method for pear breeding programs or virus-free certification laboratories.

Noninvasive Testing for Colorectal Cancer Screening: Where Are We Now?

  • Jaeyoung Chun;Jie-Hyun Kim;Young Hoon Youn;Hyojin Park
    • Journal of Digestive Cancer Research
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    • v.11 no.2
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    • pp.85-92
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    • 2023
  • Colorectal cancer (CRC) is one of the most prevalent cancers and is the leading cause of cancer-related mortality worldwide. Based on the current screening guidelines by the American Cancer Society and Korean multi-society expert committee, CRC screening is recommended in asymptomatic adults starting at the age of 45 years. Fecal immunochemical test-based screening programs reduce the development of CRC and related mortality in the general population. However, this most popular CRC screening strategy demonstrates a crucial limitation due to modest diagnostic accuracy. Colonoscopy may be considered as an alternative primary method for CRC screening; however, its implementation can still be challenging due to concerns regarding invasiveness, low adherence, cost-effectiveness, and quality assurance. To overcome the limitations of current screening tests, innovative noninvasive tests for CRC screening have been developed with advances in molecular biology, genetics, epigenetics, and microbiomics for detecting CRC, which may enhance the approach to CRC screening and diagnosis in clinical practice in the near future. This review explores the emerging screening methods and discusses their potential for integration into current practice.

Allosteric Probe-Based Colorimetric Assay for Direct Identification and Sensitive Analysis of Methicillin Resistance of Staphylococcus aureus

  • Juan Chu;Xiaoqin Zhao
    • Journal of Microbiology and Biotechnology
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    • v.34 no.3
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    • pp.681-688
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    • 2024
  • The accurate and rapid detection of methicillin-resistance of Staphylococcus aureus (SA) holds significant clinical importance. However, the methicillin-resistance detection strategies commonly require complicated cell lysis and gene extraction. Herein, we devised a novel colorimetric approach for the sensitive and accurate identification of methicillin-resistance of SA by combining allosteric probe-based target recognition with self-primer elongation-based target recycling. The PBP2a aptamer in the allosteric probe successfully identified the target MRSA, leading to the initiation of self-primer elongation based-cascade signal amplification. The peroxidase-like hemin/G-quadruplex undergo an isothermal autonomous process that effectively catalyzes the oxidation of ABTS2- and produces a distinct blue color, enabling the visual identification of MRSA at low concentrations. The method offers a shorter duration for bacteria cultivation compared to traditional susceptibility testing methods, as well as simplified manual procedures for gene analysis. The overall amplification time for this test is 60 min, and it has a detection limit of 3 CFU/ml. In addition, the approach has exceptional selectivity and reproducibility, demonstrating commendable performance when tested with real samples. Due to its advantages, this colorimetric assay exhibits considerable potential for integration into a sensor kit, thereby offering a viable and convenient alternative for the prompt and on-site detection of MRSA in patients with skin and soft tissue infections.

Power peaking factor prediction using ANFIS method

  • Ali, Nur Syazwani Mohd;Hamzah, Khaidzir;Idris, Faridah;Basri, Nor Afifah;Sarkawi, Muhammad Syahir;Sazali, Muhammad Arif;Rabir, Hairie;Minhat, Mohamad Sabri;Zainal, Jasman
    • Nuclear Engineering and Technology
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    • v.54 no.2
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    • pp.608-616
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    • 2022
  • Power peaking factors (PPF) is an important parameter for safe and efficient reactor operation. There are several methods to calculate the PPF at TRIGA research reactors such as MCNP and TRIGLAV codes. However, these methods are time-consuming and required high specifications of a computer system. To overcome these limitations, artificial intelligence was introduced for parameter prediction. Previous studies applied the neural network method to predict the PPF, but the publications using the ANFIS method are not well developed yet. In this paper, the prediction of PPF using the ANFIS was conducted. Two input variables, control rod position, and neutron flux were collected while the PPF was calculated using TRIGLAV code as the data output. These input-output datasets were used for ANFIS model generation, training, and testing. In this study, four ANFIS model with two types of input space partitioning methods shows good predictive performances with R2 values in the range of 96%-97%, reveals the strong relationship between the predicted and actual PPF values. The RMSE calculated also near zero. From this statistical analysis, it is proven that the ANFIS could predict the PPF accurately and can be used as an alternative method to develop a real-time monitoring system at TRIGA research reactors.

Predicting tensile strength of reinforced concrete composited with geopolymer using several machine learning algorithms

  • Ibrahim Albaijan;Hanan Samadi;Arsalan Mahmoodzadeh;Danial Fakhri;Mehdi Hosseinzadeh;Nejib Ghazouani;Khaled Mohamed Elhadi
    • Steel and Composite Structures
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    • v.52 no.3
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    • pp.293-312
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    • 2024
  • Researchers are actively investigating the potential for utilizing alternative materials in construction to tackle the environmental and economic challenges linked to traditional concrete-based materials. Nevertheless, conventional laboratory methods for testing the mechanical properties of concrete are both costly and time-consuming. The limitations of traditional models in predicting the tensile strength of concrete composited with geopolymer have created a demand for more advanced models. Fortunately, the increasing availability of data has facilitated the use of machine learning methods, which offer powerful and cost-effective models. This paper aims to explore the potential of several machine learning methods in predicting the tensile strength of geopolymer concrete under different curing conditions. The study utilizes a dataset of 221 tensile strength test results for geopolymer concrete with varying mix ratios and curing conditions. The effectiveness of the machine learning models is evaluated using additional unseen datasets. Based on the values of loss functions and evaluation metrics, the results indicate that most models have the potential to estimate the tensile strength of geopolymer concrete satisfactorily. However, the Takagi Sugeno fuzzy model (TSF) and gene expression programming (GEP) models demonstrate the highest robustness. Both the laboratory tests and machine learning outcomes indicate that geopolymer concrete composed of 50% fly ash and 40% ground granulated blast slag, mixed with 10 mol of NaOH, and cured in an oven at 190°F for 28 days has superior tensile strength.