scholarly journals Assessment of the Sustainability of Concrete by Ensuring Performance during Structure Service Life

2022 ◽  
Vol 14 (2) ◽  
pp. 617
Author(s):  
Dan Georgescu ◽  
Radu Vacareanu ◽  
Alexandru Aldea ◽  
Adelina Apostu ◽  
Cristian Arion ◽  
...  

The article presents an original method to assess the sustainability of concrete. The method uses three parameters, namely, performance, lifetime and environmental impact, to calculate a sustainability index. The originality and simplicity of the proposed method is shown when finding the sustainability index, where the first two factors (service life and performance) are kept constant. This approach is possible within the context of the new proposals that specify the durability of structural concrete in EN 1992 and EN 206. It allows the classification of concrete according to its performance, through environmental action resistance classes (ERC). For this purpose, specific experimental methods were used in order to determine the performance of concrete exposed to carbonation. The concretes were prepared with two cement types with additions (CEM II/A-S and CEM II/A-M (S-LL)). Based on the carbonation resistance classes (first parameter—performance) and exposure classes, the thickness of the concrete cover layer was determined to ensure a certain service lifetime (second parameter—service lifetime). Lastly, the global warming potential was calculated for each composition, allowing the users of the method to select the compositions with the lowest environmental impact.

Author(s):  
Dan Georgescu ◽  
Radu Vacareanu ◽  
Aldea Alexandru ◽  
Adelina Apostu ◽  
Cristian Arion ◽  
...  

The article presents an original method to assess the sustainability of concrete. The method uses three parameters, namely: performance, lifetime and environmental impact, to calculate a sustainability index. The originality and the simplicity of the proposed method presented in the article consists in the fact that by applying the relation to determine the sustainability index, the first two factors service life and performance are constant. This approach is possible in the context of the new proposals to specify the durability of structural concrete in EN 1992 and EN 206. That allows classification of concrete according to its performance, through Environmental action Resistance Classes (ERC). For this purpose, specific experimental methods were used in order to determine the performance of concrete exposed to carbonation. The concretes were prepared with two cement types with additions (CEM II / A-S and CEM II / A-M (S-LL)). Based on the carbonation resistance classes (the first constant - the performance) and exposure classes, the thickness of the concrete cover layer was determined to ensure a certain service lifetime (second constant - the service lifetime). Finally, the global warming potential was calculated for each composition, consequently allowing the users of the method, to select the compositions with the lowest impact on the environment.


Author(s):  
Dan Georgescu ◽  
Radu Vacareanu ◽  
Alexandru Aldea ◽  
Adelina Apostu ◽  
Cristian Arion ◽  
...  

This article presents a method to assess the sustainability of concrete based on three elements: service life, performance and environmental impact. The method proposes - to achieve similar performance and service life times, regardless of the component materials used, so that the sustainability assessment ultimately depends on the environmental impact criterion. To this end, specific experimental methods are used to determine the performance of concrete in terms of compressive strength and carbonation resistance for concrete cast with two blended cement types. The procedure needed to classify the concrete through carbonation resistance is detailed, in relationship with the performance obtained for compressive strength. The obtained results highlight the concrete formulations to be used to ensure similar performances regardless of the cement type used. In conclusion, the simplicity in the application of the method, which is closely related to the performance approach on concrete durability in the revision proposals of the European standards, is highlighted. The method is also a useful tool to encourage the widespread use in concrete formulation of blended cements with low environmental impact, without reducing the performance or service life time of the constructions.


Author(s):  
Saliha Zahoor ◽  
Ikram Ullah Lali ◽  
Muhammad Attique Khan ◽  
Kashif Javed ◽  
Waqar Mehmood

: Breast Cancer is a common dangerous disease for women. In the world, many women died due to Breast cancer. However, in the initial stage, the diagnosis of breast cancer can save women's life. To diagnose cancer in the breast tissues there are several techniques and methods. The image processing, machine learning and deep learning methods and techniques are presented in this paper to diagnose the breast cancer. This work will be helpful to adopt better choices and reliable methods to diagnose breast cancer in an initial stage to survive the women's life. To detect the breast masses, microcalcifications, malignant cells the different techniques are used in the Computer-Aided Diagnosis (CAD) systems phases like preprocessing, segmentation, feature extraction, and classification. We have been reported a detailed analysis of different techniques or methods with their usage and performance measurement. From the reported results, it is concluded that for the survival of women’s life it is essential to improve the methods or techniques to diagnose breast cancer at an initial stage by improving the results of the Computer-Aided Diagnosis systems. Furthermore, segmentation and classification phases are challenging for researchers for the diagnosis of breast cancer accurately. Therefore, more advanced tools and techniques are still essential for the accurate diagnosis and classification of breast cancer.


Sensors ◽  
2021 ◽  
Vol 21 (8) ◽  
pp. 2648
Author(s):  
Muhammad Aamir ◽  
Tariq Ali ◽  
Muhammad Irfan ◽  
Ahmad Shaf ◽  
Muhammad Zeeshan Azam ◽  
...  

Natural disasters not only disturb the human ecological system but also destroy the properties and critical infrastructures of human societies and even lead to permanent change in the ecosystem. Disaster can be caused by naturally occurring events such as earthquakes, cyclones, floods, and wildfires. Many deep learning techniques have been applied by various researchers to detect and classify natural disasters to overcome losses in ecosystems, but detection of natural disasters still faces issues due to the complex and imbalanced structures of images. To tackle this problem, we propose a multilayered deep convolutional neural network. The proposed model works in two blocks: Block-I convolutional neural network (B-I CNN), for detection and occurrence of disasters, and Block-II convolutional neural network (B-II CNN), for classification of natural disaster intensity types with different filters and parameters. The model is tested on 4428 natural images and performance is calculated and expressed as different statistical values: sensitivity (SE), 97.54%; specificity (SP), 98.22%; accuracy rate (AR), 99.92%; precision (PRE), 97.79%; and F1-score (F1), 97.97%. The overall accuracy for the whole model is 99.92%, which is competitive and comparable with state-of-the-art algorithms.


Materials ◽  
2021 ◽  
Vol 14 (6) ◽  
pp. 1440
Author(s):  
Pei-Yuan Lun ◽  
Xiao-Gang Zhang ◽  
Ce Jiang ◽  
Yi-Fei Ma ◽  
Lei Fu

The premature failure of reinforced concrete (RC) structures is significantly affected by chloride-induced corrosion of reinforcing steel. Although researchers have achieved many outstanding results in the structural capacity of RC structures in the past few decades, the topic of service life has gradually attracted researchers’ attention. In this work, based on the stress intensity, two models are developed to predict the threshold expansive pressure, corrosion rate and cover cracking time of the corrosion-induced cracking process for RC structures. Specifically, in the proposed models, both the influence of initial defects and modified corrosion current density are taken into account. The results given by these models are in a good agreement with practical experience and laboratory studies, and the influence of each parameter on cover cracking is analyzed. In addition, considering the uncertainty existing in the deterioration process of RC structures, a methodology based on the third-moment method in regard to the stochastic process is proposed, which is able to evaluate the cracking risk of RC structures quantitatively and predict their service life. This method provides a good means to solve relevant problems and can prolong the service life of concrete infrastructures subjected to corrosion by applying timely inspection and repairs.


2020 ◽  
Vol 79 (Suppl 1) ◽  
pp. 861-862
Author(s):  
Z. Izadi ◽  
T. Johansson ◽  
J. LI ◽  
G. Schmajuk ◽  
J. Yazdany

Background:The Rheumatology Informatics System for Effectiveness (RISE) Registry was developed by the ACR to help rheumatologists improve quality of care and meet federal reporting requirements. In the current quality program administered by the U.S. Centers for Medicare and Medicaid services, rheumatologists are scored on quality measures, and performance is tied to financial incentives or penalties. Rheumatoid arthritis (RA)-specific quality measures can only be submitted through RISE to federal programs.Objectives:This study used data from the RISE registry to investigate rheumatologists’ federal reporting patterns on five RA-specific quality measures in 2018 and investigated the effect of practice characteristics on federal reporting of these measures.Methods:We analyzed data on all rheumatologists who continuously participated in RISE between Jan 2017 to Dec 2018 and who had patients eligible for at least one RA-specific measure. Five measures were examined: tuberculosis screening before biologic use, disease activity assessment, functional status assessment, assessment and classification of disease prognosis, and glucocorticoid management. We assessed whether or not rheumatologists reported specific quality measures via RISE. We investigated the effect of practice characteristics (practice structure; number of providers; geographic region) on the likelihood of reporting using adjusted analyses that controlled for measure performance (performance in 2018; change in performance from 2017; and performance relative to national average performance). Analyses accounted for clustering by practice.Results:Data from 799 providers from 207 practices managing 213,757 RA patients was examined. The most common practice structure was a single-specialty group practice (53%), followed by solo (28%) and multi-specialty group practice (12%). Most providers (73%) had patients eligible for all five RA quality measures. Federal reporting of quality measures through RISE varied significantly by provider, ranging from no reporting (60%) to reporting all eligible RA measures (12.2%). Reporting through RISE also varied significantly by quality measure and was highest for functional status assessment (36%) and lowest for assessment and classification of disease prognosis (20%). Small practices (1-4 providers) were more likely to report all eligible RA quality measures compared to larger practices (21%, 6%; p<0.001). In adjusted analyses, solo practices were more likely than single-specialty group practices to report RA measures (42%, 31%; p<0.027) while multispecialty group practices were less likely (18%, 31%; p<0.001). Additionally, higher performance in 2018 and performance ≥ the national average performance was associated with federal reporting of the measures through RISE (p≤0.004).Conclusion:Forty percent of U.S. rheumatologists participating in RISE used the registry for federal quality reporting. Physicians using RISE for reporting were disproportionately in small and solo practices, suggesting that the registry is fulfilling an important role in helping these practices participate in national quality reporting programs. Supporting small practices is especially important given the workforce shortages in rheumatology. We observed that practices reporting through RISE had higher measure performance than other participating practices, which suggests that the registry is facilitating quality improvement. Studies are ongoing to further investigate the impact of federal quality reporting programs and RISE participation on the quality of rheumatologic care in the United States.Disclaimer: This data was supported by the ACR’s RISE Registry. However, the views expressed represent those of the authors, not necessarily those of the ACR.Disclosure of Interests:Zara Izadi: None declared, Tracy Johansson: None declared, Jing Li: None declared, Gabriela Schmajuk Grant/research support from: Pfizer, Jinoos Yazdany Grant/research support from: Pfizer


Author(s):  
V. Vijaya Kishore ◽  
R.V.S. Satyanarayana

A vital necessity for clinical determination and treatment is an opportunity to prepare a procedure that is universally adaptable. Computer aided diagnosis (CAD) of various medical conditions has seen a tremendous growth in recent years. The frameworks combined with expanding capacity, the coliseum of CAD is touching new spaces. The goal of proposed work is to build an easy to understand multifunctional GUI Device for CAD that performs intelligent preparing of lung CT images. Functions implemented are to achieve region of interest (ROI) segmentation for nodule detection. The nodule extraction from ROI is implemented by morphological operations, reducing the complexity and making the system suitable for real-time applications. In addition, an interactive 3D viewer and performance measure tool that quantifies and measures the nodules is integrated. The results are validated through clinical expert. This serves as a foundation to determine, the decision of treatment and the prospect of recovery.


Sign in / Sign up

Export Citation Format

Share Document