1,721,031 research outputs found
Utilization of normal and treated cement kiln dust as cement replacement materials in concrete
No full textCement Kiln Dust (CKD) is a by-product generated throughout the production of Ordinary
Portland Cement (OPC). It is normally emitted to the atmosphere or converted into liquid
and subsequently drained out as effluents to landfills and wastage areas. It impacted human
health and the environment negatively. However, it can be utilized in concrete as raw
cement replacement materials due to its engineering properties which work as an alternative
binder of OPC in addition to that it has benefits in creating economic and environmental
advantages. This study aimed to modify CKD and investigate the chemical composition
of normal-CKD and modified -CKD accordingly. The term modified noted that CKD has
gone through a process of modification using heating process. The reactivity property of
CKD was investigated using pH analysis. Then, mix proportions of different percentage
of normal-CKD and modified -CKD were developed to study the addition effects on
the compressive and flexural strength for different curing period. The trend of strength
development over the addition of CKD was also analyzed. OPC was replaced by CKD at
0% and successively increased by 10% to 100% through binder weight (OPC). A fixed
amount of water to binder (W/B) with a ratio of 0.45 was used for all hybrids. The mixes
were formed into the specimen and tested for compressive strength and flexural strength at
7, 14 and 28 curing days. The medium particle size of CKD used was less than 10?m. The
results of compressive and flexural strength showed that modified-CKD resulted in better
properties and 10% replacement showed
the maximum values of compressive and
flexural strength as a result considered best
percentage replacement in agreement with
its noteworthy results
Machine learning in concrete technology: A review of current researches, trends, and applications
Get PDFMachine learning techniques have been used in different fields of concrete technology to characterize the materials based on image processing techniques, develop the concrete mix design based on historical data, and predict the behavior of fresh concrete, hardening, and hardened concrete properties based on laboratory data. The methods have been extended further to evaluate the durability and predict or detect the cracks in the service life of concrete, It has even been applied to predict erosion and chemical attaches. This article offers a review of current applications and trends of machine learning techniques and applications in concrete technology. The findings showed that machine learning techniques can predict the output based on historical data and are deemed to be acceptable to evaluate, model, and predict the concrete properties from its fresh state, to its hardening and hardened state to service life. The findings suggested more applications of machine learning can be extended by utilizing the historical data acquitted from scientific laboratory experiments and the data acquitted from the industry to provide a comprehensive platform to predict and evaluate concrete properties. It was found modeling with machine learning saves time and cost in obtaining concrete properties while offering acceptable accuracy
Formwork Pressure of Self-Compacting Concrete
No full textSelf-compacting concrete (SCC) is commonly known for its high flowability and resistance to segregation. Using SCC in constructing large structural members where reinforcements are congested offers several benefits, including reduced project time and a better work environment due to the lack of vibration. However, the concern is the presumably higher pressure exerted on the formwork during casting. This thesis presents the results of a study on the form pressure exerted by SCC, which included the literature review to evaluate existing theoretical design models, laboratory testing, and modelling. A laboratory setup was developed, including a 2-meter circular column instrumented with a wireless pressure system. Two types of SCC were tested: with and without ground granulated blast furnace slag (GGBFS). The pressure was recorded by novel pressure sensors attached to transmitters to send real-time data to the cloud. The system was equipped with a pressure membrane that was in direct contact with the concrete. Several material and environmental parameters were recorded before and during casting. The collected data were used to assess the accuracy of the following models, including DIN1821 (2010), Khayat et al. (2009), Gardner et al. (2012), Teixeira et al. (2017), Beitzel (2010), Ovarlez and Roussel (2006), and Proske (2010). Most models were conservative, calculating higher pressures than recorded. In the next step, machine learning methods were developed to monitor and predict the pressure during casting continuously. These models showed significantly higher accuracy and flexibility than the existing prediction models.
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Formwork Pressure of Self-Compacting Concrete
No full textSelf-compacting concrete (SCC) is commonly known for its high flowability and resistance to segregation. Using SCC in constructing large structural members where reinforcements are congested offers several benefits, including reduced project time and a better work environment due to the lack of vibration. However, the concern is the presumably higher pressure exerted on the formwork during casting. This thesis presents the results of a study on the form pressure exerted by SCC, which included the literature review to evaluate existing theoretical design models, laboratory testing, and modelling. A laboratory setup was developed, including a 2-meter circular column instrumented with a wireless pressure system. Two types of SCC were tested: with and without ground granulated blast furnace slag (GGBFS). The pressure was recorded by novel pressure sensors attached to transmitters to send real-time data to the cloud. The system was equipped with a pressure membrane that was in direct contact with the concrete. Several material and environmental parameters were recorded before and during casting. The collected data were used to assess the accuracy of the following models, including DIN1821 (2010), Khayat et al. (2009), Gardner et al. (2012), Teixeira et al. (2017), Beitzel (2010), Ovarlez and Roussel (2006), and Proske (2010). Most models were conservative, calculating higher pressures than recorded. In the next step, machine learning methods were developed to monitor and predict the pressure during casting continuously. These models showed significantly higher accuracy and flexibility than the existing prediction models.
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Get PDFWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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