Dataset Information

Proposing a New Method Based on Image Analysis to Estimate the Segregation Index of Lightweight Aggregate Concretes.

ABSTRACT: This work presents five different methods for quantifying the segregation phenomenon in lightweight aggregate concretes (LWAC). The use of LWACs allows greater design flexibility and substantial cost savings, and has a positive impact on the energy consumption of a building. However, these materials are susceptible to aggregate segregation, which causes an irregular distribution of the lightweight aggregates in the mixture and may affect the concrete properties. To quantify this critical process, a new method based on image analysis is proposed and its results are compared to the well-established methods of density and ultrasonic pulse velocity measurement. The results show that the ultrasonic test method presents a lower accuracy than the other studied methods, although it is a nondestructive test, easy to perform, and does not need material characterization. The new methodology via image analysis has a strong correlation with the other methods, it considers information from the complete section of the samples, and it does not need the horizontal cut of the specimens or material characterization.

SUBMITTER: Solak AM

PROVIDER: S-EPMC6862299 | biostudies-literature | 2019 Nov

REPOSITORIES: biostudies-literature

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Proposing a New Method Based on Image Analysis to Estimate the Segregation Index of Lightweight Aggregate Concretes.

Solak Afonso Miguel AM Tenza-Abril Antonio José AJ Baeza-Brotons Francisco F Benavente David D

Materials (Basel, Switzerland) 20191105 21

This work presents five different methods for quantifying the segregation phenomenon in lightweight aggregate concretes (LWAC). The use of LWACs allows greater design flexibility and substantial cost savings, and has a positive impact on the energy consumption of a building. However, these materials are susceptible to aggregate segregation, which causes an irregular distribution of the lightweight aggregates in the mixture and may affect the concrete properties. To quantify this critical process ...[more]

PMID: 31694271

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Project description:As irradiated brain volume at 12 Gy (V12) is a predictor for radionecrosis, the purpose of the study was to develop a model for Cyberknife (CK) plans that is able to predict the lowest achievable V12 at a given tumor size and prescription dose (PD), and to suggest a new quality index regarding V12 for optimizing the treatment planning of brain metastases.In our model V12 was approximated as a spherical shell around the tumor volume. The radial distance between tumor surface and the 12 Gy isodose line was calculated using an approximation of the mean dose gradient in that area. Assuming a radially symmetrical irradiation from the upper half space, the dose distribution is given by the superposition of single fields. The dose profiles of a single field were derived by the measured off-center ratios (OCR) of the CK system. Using the calculated gradients of the sum dose profiles, minimal-V12 was estimated for different tumor sizes. The model calculation was tested using a phantom dataset and retrospectively applied on clinical cases.Our model allows the prediction of a best-case scenario for V12 at a given tumor size and PD which was confirmed by the results of the isocentric phantom plans. The results of the non-isocentric phantom plans showed that an optimization of coverage caused an increase in V12. This was in accordance with the results of the retrospective analysis. V12 s of the clinical cases were on average twice that of the predicted model calculation. A good agreement was achieved for plans with an optimal conformity index (nCI). Re-planning of cases with high V12 showed that lower values could be reached by selecting smaller collimators and by allowing a larger number of total MU and more MU per beam.V12 is a main parameter for assessing plan quality in terms of radiotoxicity. The index f12 defined as the ratio of V12 from the actual plan with the evaluated V12 from our model describes the conformity of an optimally possible V12 and thus can be used as a new quality index for optimizing treatment plans.

Dataset Information

Proposing a New Method Based on Image Analysis to Estimate the Segregation Index of Lightweight Aggregate Concretes.

Publications

Proposing a New Method Based on Image Analysis to Estimate the Segregation Index of Lightweight Aggregate Concretes.

Similar Datasets

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