Simplified predictive ANN model for ultimate compressive strength of circular RC columns using CFRP as confinement

Today, retrofitting structures became dominant due to the changes in codes and deterioration of structures. One way of retrofitting reinforced concrete (RC) structure columns is by the application of Carbon Fiber Reinforced Polymer (CFRP). This method uses epoxy resin as the binding materials together with carbon fiber sheets to form a fiber-reinforced polymer matrix termed as CFRP wrapped arounc RC columns. The use of CFRP is found to be an effective technique of providing structural strengthening that is lighter, non-corrosive, and less labor intensive than the application of steel plate. At De La Salle University year 2006, experiments and testing of fabricated circular RC columns reinforced with CFRP were done to acquire numerous local data together with the author as the adviser of the researches. With these experimental data, conjunction of foreign published data and local data were used to conduct and analyze the strength performance of CFRP in concrete. From the Self Organized Map (SOM), two classifications were derived from the foreign and local data available. It was observed that the CFRP as a retrofitting material behaved in two ways: active and passive. If the volumetric ratio of steel is low, then the tendency of the CFRP will be active that causes higher development in ultimate confined compressive strength. If the volumetric ratio of steel is high, then the tendency of the CFRP will be passive that causes lower development in ultimate confined compressive strength. In Back-Propagation (BP), a simplified version of a model can be achieved having only 2 input parameters pcfrp (volumetric ratio of CFRP to concrete) and ps (volumetric ratio of steel ties to concrete). With these models, parametric studies were made to investigate the differences in the behavior of both classes. The combination of SOM and BP proves to be effective in classifying and promoting good preditions in the ultimate confined compressive strength of circular RC columns

Assessment of time and costs of two formwork methodologies in the Philippines using BIM simulation

In the Philippine construction industry, choices of formwork methodology is critical to contractors or client/project managers. Cost and time are the parameters commonly considered to address which method is recommended for a project. In this study, simulation using BIM was made from input parameters taken from actual project observations and data collection from five projects. Two methods were considered: method A (traditional forms) and method B (steel decks). The output parameters after the BIM simulation were processed cost and time. A statistical t-test was conducted for both process costs and time durations to differentiate between the two methods. It was found out that the process costs for overall, columns, and beams of method A were not statistically different from method B, while the slab process cost was significantly different. This indicated that only slab process cost was relatively expensive for method B. For the duration, both the columns and beams were not statistically different, while overall and slabs\u27 duration was significantly different. It showed that overall duration and slab process duration is relatively lower for method B. This paper showed that BIM simulation could help managers in their decision on choosing the construction methodology to balance cost and time of their project. © International Journal on Advanced Science, Engineering and Information Technology

Acoustic emission test in visualizing crack progression for concrete beams

In this paper, acoustic emission (AE) test was used to assess concrete beams having a size of 100mm x 100mm x 400mm length with water-cement ratio of 0.50. Two types of beam were considered, plain concrete beams and short steel fiber-reinforced beams. There were three parameters used in acoustic emission test: AE hits, AE location, and AE energy. The total AE hits were divided into three percentile of AE energy all throughout the test. These are 100th, 25th, and 10th percentile of AE energy. This was done to differentiate significant AE signals with large AE energy from the less significant AE signals with small energy. It was found out that short steel fiber-reinforced concrete beams produced large number of total AE hits compared to ordinary concrete beams. The crack progression was clearly visualized at 10th percentile of AE energy

Modeling the confining effect of carbon FRP and steel in circular RC columns using artificial neural networks

Confinement of concrete columns using steel and carbon fiber reinforced polymer (CFRP) increases the ultimate compressive strength and ductility. Since there are now extensive experimental data on confined RC columns, it may be useful to combine and reanalyze them to develop empirical models that can give reasonable predictions of the ultimate confined compressive strength of RC columns. Because of the various factors affect the compressive strength of RC columns, modeling becomes difficult especially when pre-existing transverse steel reinforcements and CFRP are both used as confining materials. This study presents the capability of artificial neural networks (ANNs) in modeling the confined compressive strength of circular RC columns. The effect of various parameters such as ρs, ρcc, ρCFRP, L, d, D, fyh, fCFRP, and f\u27c are considered in the development of ANN models

Optimizing compressed Earth blocks mix design incorporating rice straw and cement using artificial neural network

Compressed earth blocks (CEB) in construction is an alternative way of promoting sustainable construction building materials. Compressed earth blocks are used as replacement to concrete masonry wall units. It has many advantages in terms of material cost, thermal properties, embodied energy, sound and fire proofing. In this study, production of 250 CEBs was made with dimension of 290mm×140mm ×100mm. With the available data, Self-Organizing Map (SOM) toolbox was used to classify results according to the parameters that have similarities. The groupings that were classified through SOM were observed, analysed and was related to the compressive strengths of CEBs. Two Self Organizing Map (SOM) Models were derived in the study. These are Model E and Model F. Model E and Model F contains 2 input parameter. Model E has 4 classifications: Group A and C classified CEBs that are above the strength requirement of Philippine National Standard (PNS). Group B and D clustered the CEBs with the lowest compressive strength value. Overall, Model E clustered the groups into similar characteristics. Model E showed that CEB with 10% cement and above with any fiber content conforms to the requirement of PNS under TYPE 2 CHB. Model F has also 4 classifications: Group A and C classified CEBs that are above the strength requirement of PNS. Group B and D clustered the CEBs with the lowest compressive strength value. Model F showed that any fiber content can be used in combination with 10% or more Cement to achieve the requirement of PNS Type 2 CHB. © 2017 IEEE

Confinement effect of steel ties and/or carbon FRP in circular RC columns using neural network

Carbon fiber reinforced polymer (CFRP) is now commonly used in structural repair, strengthening and retrofitting of reinforced concrete (RC) members such as columns and beams. In retrofitting and strengthening RC columns, CFRP is wrapped around existing columns, which contain both longitudinal steel bars and lateral steel ties or hoops. Empirical models to predict the effect of confinement due to CFRP in the enhancement of the compressive strength of RC columns have been developed. However, an understanding of the interaction between the lateral steel ties and the CFRP on confinement and enhancement of compressive strength has still to be explored. Using the experimental data available in the literature, parameters such as ρs ρcc, ρCFRP, L, d, D, fyh, fyCFRP, and f’c were considered. The study used artificial neural network (ANN) modeling to predict the confined ultimate compressive strength, f’cc, produced by wrapping CFRP externally from circular sections reinforced with steel ties and longitudinal bars. Training different architectures of ANN models, and testing the derived models from existing models were done to arrive at an acceptable model. With the acceptable ANN model, the possible interaction between the two confining materials in the enhancement or increase of the compressive strength of circular columns was studied. © 2005 EUCENTRE. All rights reserved

Air-coupled nonlinear ultrasonic test for reinforced concrete beams

Air-coupled ultrasonic test is a non-destructive test method for investigating damage in material. In this paper, reinforced concrete beams with one 8-mm diameter rounded bar were casted and tested under four-point bending test with water-cement ratio of 40% and 60%. The transducers were placed and focused on the horizontal surface with induced 3mm notch at the midpoint where maximum tension occurred and crack formation was located. Frequency domain waveform was used specifically to analyze second harmonic generation (SHG). There were two metrics used under the SHG, these were: second harmonic amplitude (SHA) and second harmonic ratio (SHR). The SHR proved to be consistent for both water-cement ratio and it behaved increasing as damage in tension increases. © IABSE Conference, Kuala Lumpur 2018: Engineering the Developing World - Report. All rights reserved

Neural network mapping in the simplified design of mix proportions using coal bottom ash waste in concrete hollow blocks

In the operation of coal-fired power plants in the Philippines, the pulverized coal which is used as a source of energy and depending on its coal burning furnace, tends to produce approximately 80% of Coal Fly Ash and 20% of Coal Bottom Ash. Researches and studies have shown that Coal Bottom Ash can be used as a road base subbase aggregate, structural fill material (ASTM E1861-97), and as fine aggregates in asphalt paving and flowable fill. From recent studies done by Gallardo et. al. in De La Salle University-Manila, Coal Bottom Ash was used as partial substitute to sand for building materials like Concrete Hollow Blocks complying to the Philippine National Standards. The casting and testing of 429 specimens of four-inch-thick hollow blocks and variable mix proportions were considered in the research. However, with the data produced, design of simplified mix proportions was not yet done and still to be modeled. Using neural network self-organizing map to classify organized data sets, a simplified approach to mix proportions was made to meet the mechanical properties needed to comply with the Philippine National Standards in Concrete Hollow Blocks