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Experiment of the monitoring prestress loss of prestressed concrete beams with damages under static loading

Wang Jinbo, Li Guodong, Lan Chunguang, Guo Nan

Archives of Civil Engineering

2023

Vol. 69, nr 1

437--451

In this paper, based on the feasible method and sensors for the full-scale prestressed monitor, the novel optical fiber sensors and the traditional monitoring sensors will be set up into two prestressed concrete beams with the same geometrical dimensions, material properties, and construction conditions, etc. to investigate the working state of the novel sensors and obtain the evolution law of prestress loss of the prestressed feature component under the static load. The results show that the evolution law of prestress loss of the loaded beam under the condition of no damage state and initial crack is the same as the non-loaded one; however, the prestress loss increases with the increase of time under the situation with the limit crack. The total loss of the prestressed beam with the limit crack is 36.4% without damage. The prestress loss of the prestressed beam under the static load increase with the development of the crack (injury).

The hydrological impact of tropical cyclones on soil moisture using a sensor based hybrid deep learning model

Srivastava Gautam, Kavitha V., Vimaladevi M., Parthiban N.

Acta Geophysica

2022

Vol. 70, no 6

2933--2951

Tropical cyclones that originate from the Indian Ocean affect the Indian Sub-Continent. Heavy rainfall and flooding occur because of these cyclones. South Odisha was affected by Cyclonic Storm Daye in September 2018 and Cyclonic Storm Titli was occurred in August affecting Andhra Pradesh and Odisha as well. The Eastern portion of India was affected by the Cyclonic Storm Fani in April 2019. In May 2020, West Bengal was affected by the Amphan which is a Super Cyclonic Storm and in the same year Tamil Nadu was affected by the very severe Cyclonic Storm Nivar in November 2020. These are just a few of the notable cyclonic events in the Indian Sub-Continent. These cyclonic events cause a dramatic change in a very short time from dry soil to exceptional flooding. In this proposed work, we are attempting to create an observations-driven prediction model to quantify the soil moisture variations daily, predict county-based meteorology and evaluate the cause of cyclones and heavy rainfall in certain areas of India. In our work, we applied a deep learning-based methodology to predict soil moisture. For the prediction model, we fused Feed Forward Neural Networks with the Gated Recurrent Unit (GRU) model and present the prediction results. We have used climatic as well as environmental data published by the Indian Meteorological Department (IMD) Warning from 2011. The collected data is time-series data. Comparisons and the relationship that exists between soil moisture and meteorological data are made and analyzed. The soil moisture of the South Indian states Karnataka, Andhra Pradesh and Tamil Nadu are predicted from weather data using a hybrid deep learning model. The evaluations of the proposed work using Mean Absolute Error (MAE), Mean Squared Error (MSE), Root Mean Squared Error (RMSE) and R-squared (R2 ) against Non-hybrid Neural Network models such as Artificial Neural Networks (ANN), Convolutional Neural Networks, and Gated Recurrent Unit (GRU) models is analyzes where our model has given better results.

Wytwarzanie miniaturowych sensorów elektrochemicznych i matryc sensorów na podłożu krzemowym

Zaborowski M., Domański K., Prokaryn P., Wawrzyniak U., Ciosek P., Wróblewski W., Grabiec P.

Elektronika : konstrukcje, technologie, zastosowania

2012

Vol. 53, nr 6

21-22

Opracowane zostały trzy rodzaje sensorów woltamperometrycznych na podłożach mono-Si. W pracy opisano proces technologiczny ich wytwarzania. Zaprezentowano zdjęcia skaningowe powierzchni Au i AgCl oraz zdjęcia struktur sensorowych. Struktury zostały scharakteryzowane elektrochemicznie w testach redoks.

Three types of voltamperometric chemical sensors have been developed on mono-Si substrates. A process of fabrication is described in the paper. Au and AgCl surface SEM examination together with sensor chip images are presented. Chips have been electrochemically characterized in redox tests.