Degradation Models and Maintenance Strategies for Reinforced Concrete Structures in Coastal Environments under Climate Change: A Review
Modern engineering faces challenges in ensuring technical standards for service, durability,
and sustainability. Political, administrative, and budgetary factors, coupled with climate …
and sustainability. Political, administrative, and budgetary factors, coupled with climate …
Bayesian regularized artificial neural network model to predict strength characteristics of fly-ash and bottom-ash based geopolymer concrete
Geopolymer concrete (GPC) offers a potential solution for sustainable construction by
utilizing waste materials. However, the production and testing procedures for GPC are quite …
utilizing waste materials. However, the production and testing procedures for GPC are quite …
Mapping the chloride-induced corrosion damage risks for bridge decks under climate change
Climate change is expected to alter the environmental factors that are known to influence the
corrosion process, creating additional uncertainties in the long-term performance of …
corrosion process, creating additional uncertainties in the long-term performance of …
Representative elementary volumes for 3D modeling of mass transport in cementitious materials
N Ukrainczyk, EAB Koenders - Modelling and simulation in …, 2014 - iopscience.iop.org
Representative elementary volumes (REV) are of major importance for modeling the
transport properties of multi-scale porous materials. REVs can be used to schematize …
transport properties of multi-scale porous materials. REVs can be used to schematize …
Prediction of strength characteristics of cement composite using artificial neural network
The design of concrete is still time-consuming, reliant on experience, and unpredictable.
Concrete is a heterogeneous, complex substance comprised of cement, water, fine and …
Concrete is a heterogeneous, complex substance comprised of cement, water, fine and …
[HTML][HTML] Artificial Neural Network Application in Construction and the Built Environment: A Bibliometric Analysis
Over the past decade, there has been a dramatic increase in the use of various technologies
in the Architecture, Engineering, and Construction sector. Artificial intelligence has played a …
in the Architecture, Engineering, and Construction sector. Artificial intelligence has played a …
Smart database design for concrete durability analysis-An application in the Hongkong-Zhuhai-Macau bridge
A complete durability database that provides consistent, reliable information is of great
significance for concrete durability analysis. The critical challenge is that most durability …
significance for concrete durability analysis. The critical challenge is that most durability …
Prediction of chloride content in concrete using ANN and CART
MS Asghshahr, A Rahai… - Magazine of Concrete …, 2016 - icevirtuallibrary.com
Chloride-induced corrosion of concrete structures in marine areas is a serious problem and
is generally affected by several factors. Chloride concentration is an important parameter for …
is generally affected by several factors. Chloride concentration is an important parameter for …
An artificial neural network model for the corrosion current density of steel in mortar mixed with seawater
Corrosion is a very complicated phenomenon in the field of science and engineering. Over
the years, several numerical models have been developed to predict the damage caused by …
the years, several numerical models have been developed to predict the damage caused by …
Prediction of the degree of steel corrosion damage in reinforced concrete using field-based data by multi-gene genetic programming approach
Unanticipated failure of reinforced concrete structures due to corrosion of steel rebar
embedded in concrete causes to increase the demand for finding methods to forecast the …
embedded in concrete causes to increase the demand for finding methods to forecast the …