Problems with reinforced concrete industrial floors with regard to subsoil swelling (original) (raw)
Related papers
Need to Identify Parameters of Concrete in the Weakest Zone of the Industrial Floor
IOP Conference Series: Materials Science and Engineering
The ways in which industrial floors are exploited leads to the requirement for the highest strength of their upper zone. Physical phenomena occurring during the compaction and hardening of the concrete cause different strength distributions. In the top zone of industrial floors, the strength is significantly lower (over a dozen MPa) than the strength in the bottom zone (several dozen MPa). Standard tests of control samples do not detect this fact. Processes for the application and finishing of embedded mineral-aggregate hardeners (dry shakes) can be regarded as uncontrolled. The effects of the use of dry shakes are not evaluated. In combination with the phenomenon of bleeding, they often fail by delamination. This paper presents the results of industrial floor testing. The ultrasonic pulse velocity method with dry point contact transducers was used. The results show how upper layer strength was reduced, and how dry shakes application affected the strength of the floor. The strength distribution in hardened concrete, which delaminated from the rest of the floor was presented as well. The extension of compulsory control tests of concrete samples was proposed. In the authors' opinion, particular attention should be paid to 3 centimetres of the upper layer.
Aggregate containing certain constituents can react with alkali hydroxides in concrete. Alkali-Aggregate Reaction, (AAR) causes concrete expansion, micro cracks, and finally, visible cracks in the concrete. Therefore, the reactivity is potentially harmful only when it produces significant expansion. Due to the continuous hydration reaction in moist environment in structures such as concrete dams adjacent to water, the reaction can continue whilst the concrete structure ages. The expansion of the concrete volume produced by the production of reaction products, such as silica gel, affects the structure strains. This strain is related to temperature, humidity, aggregate activity and stress on the structure whereas concrete properties, such as modulus of elasticity and tensile strength are reduced during the reaction. AAR may occur when siliceous aggregates (Alkali-Silica Reactivity, ASR) or carbonate aggregates (Alkali-Carbonate Reactivity, ACR) are used in concrete mixes, and failures may result in progressive deterioration, requiring costly repairs and rehabilitation of concrete structures to maintain their expected function. This paper reviews the experimental research carried out in Iran regarding aggregate sources that are used to make concrete in Roodbal Lorestan hydropower dam project. The global expansion estimates are fed into the artificial neural network (AAN) to prepare a neural network which can predict expansion and characterize the level of damages that may occur in the future.
GeoScience Engineering, 2015
Nowadays many problems concerning industrial floors or floors in shopping centres occurred when local geological characterization is not adequately considered by structural designers, material selection is not evaluated properly and in time for future stability, or consolidation of soft organic subsoil laid in active zone is not taken into account during design evaluation. Similar problems occur when flooding effects on subbase layers cause a new settlement of the upper floor structure. Generally speaking, majority of these symptoms of floor damage have their origin in underestimation of the geotechnical risk. At some locations, the selection of support structure and material type is not adequate due to lack of experience and in order to offer the lowest price as a contractor.
Improvement of Collapsible Soil Conditions for Industrial Floors
Soil Testing, Soil Stability and Ground Improvement, 2017
Unsaturated surface soils with porosities above 50% cover great extensions of areas in Midwest Brazil. Because of their large volumes of voids, these soils undergo great strain under loads. In addition, many of these soils are collapsible, i.e., when the soils are under load and in case of a significant increase in the moisture content or saturation of the soil, the structure collapses, thus producing unacceptable displacement values for the buildings. Because of these characteristics, problems often occur in industrial floors, pavements and other types of slabs on ground and shallow foundations. To solve this problem, compaction of the topsoil is performed before starting the construction. For this study, the soil characteristics are analyzed using both geotechnical laboratory tests and field tests in order to predict the soil behavior in terms of deformability, resistance and collapsibility. The study was conducted at the experimental site located at the State University of Campinas-Unicamp, in the municipality of Campinas, State of São Paulo, Brazil. The geotechnical properties of the subsoil were determined by collecting undisturbed samples down to 8 m in depth and deformed samples up to 9 m of depth (impenetrable). Simple recognition surveys were performed: standard penetration test (SPT) and electric static cone penetration test (CPT). The edometric tests conducted on undisturbed samples with flooding at different levels of stress revealed collapsible characteristics of the soil. With the conduction of tri-axial tests (CU), numerical values were obtained for the angle of friction and the cohesion intercepts for each depth. Paschoalin Filho (2008) verified a significant reduction in these values with soil saturation. The influence of soil deformability and of the type of load on industrial floors is analyzed. The results indicate huge influence of soil deformability in the case of distributed loads, and a minor influence in case of concentrated loads. The thickness of the compacted soil layer is very important to the definition of the modulus of subgrade reaction (k) for the studied soil.
This paper presents an investigation into the problems encountered in industrial concrete floors on the ground. Shrinkage, acid attack, concrete quality, crazing, curling, durability issues and design considerations are addressed. Case studies from South African companies have been included to illustrate the problems and demonstrate how designs can be done to avoid such issues. Guidelines are proposed for fixing surface beds when problems have occurred. Overall it can be seen that floors are highly susceptible to a variety of problems. However, through good design and construction practices high quality surfaces can be provided for the industrial sector. It has been noted that few engineers and contractors are capable of successfully designing and constructing industrial concrete floors. This requires special consideration by the industry.
Elastic modulus of ASR-affected concrete: An evaluation using Artificial Neural Network
Computers and Concrete, 2019
Alkali-silica reaction (ASR) in concrete can induce degradation in its mechanical properties, leading to compromised serviceability and even loss in load capacity of concrete structures. Compared to other properties, ASR often affects the modulus of elasticity more significantly. Several empirical models has thus been established to estimate elastic modulus reduction based on the ASR expansion only for condition assessment and capacity evaluation of the distressed structures. However, it has been observed from experimental studies in the literature that for any given level of ASR expansion, there are significant variations on the measured modulus of elasticity. In fact, many other factors, such as cement content, reactive aggregate type, exposure condition, additional alkali and concrete strength, have been commonly known in contribution to changes of concrete elastic modulus due to ASR. In this study, an artificial intelligent model using artificial neural network (ANN) is proposed for the first time to provide an innovative approach for evaluation of the elastic modulus of ASR-affected concrete, which is able to take into account contribution of several influence factors. By intelligently fusing multiple information, the proposed ANN model can provide an accurate estimation on modulus of elasticity, which shows a significant improvement from empirical based models used in current practice. The results also indicate that expansion due to ASR is not the only factor contributing to the stiffness change, and various factors have to be included during the evaluation.
2012
The evaluation of structural performance of existing concrete buildings, built according to standards and materials quite different to those available today, requires procedures and methods able to cover lack of data about mechanical material properties and reinforcement detailing. To this end detailed inspections and test on materials are required. As a consequence tests on drilled cores are required; on the other end, it is stated that non-destructive testing (NDT) cannot be used as the only mean to get structural information, but can be used in conjunction with destructive testing (DT) by a representative correlation between DT and NDT. The aim of this study is to verify the accuracy of some formulas of correlation available in literature between measured parameters, i.e. rebound index, ultrasonic pulse velocity and compressive strength (SonReb Method). To this end a relevant number of DT and NDT tests has been performed on many school buildings located in Cesena (Italy). The abo...
Applied Sciences, 2021
The objective of this study is to compare conventional models used for estimating the load carrying capacity of reinforced concrete (RC) members, i.e., Current Design Codes (CDCs), with the method based on different assumptions, i.e., the Compressive Force Path (CFP) method and a non-conventional problem solver, i.e., an Artificial Neural Network (ANN). For this purpose, four different databases with the details of the critical parameters of (i) RC beams in simply supported conditions without transverse steel or stirrups (BWOS) and RC beams in simply supported conditions with transverse steel or stirrups (BWS), (ii) RC columns with cantilever-supported conditions (CWA), (iii) RC T-beams in simply supported conditions without transverse steel or stirrups (TBWOS) and RC T-beams in simply supported conditions with transverse steel or stirrups (TBWS) and (iv) RC flat slabs in simply supported conditions under a punching load (SCS) are developed based on the data from available experimen...
Estimated of Concrete Compressive Strength by Using Neural Network and Machine Learning
2021
Abstract: The most fundamental input of the construction sector is concrete, which would be a massively complicated element. Concrete is among the most common structural construction materials due to its strength. Since some manufacturers manufacture out of reach and low quality, there is a growing demand for earthquake-resistant design in the fully prepared concrete industry. Concrete's strength-gaining properties are influenced by a variety of factors. This research aims to use the results of early compressive strength tests to predict strength properties at various ages. The ability to estimate the determination and strength of normal concrete using the early day strength properties result has been examined. Including both concrete and regional concrete mixes, a basic numerical equation forecast the concrete strength at any age is proposed. The goal of this article is to show how artificial neural networks (ANN) and machine learning can be used to forecast the compressive str...