Florante D. Poso, Jr.
23 Publications
Scopus ID: 85212846502
DOI: 10.1063/5.0162444
AIP Conference Proceedings, (2023), Vol. 2868, pp. 020005
Conference Paper | Published: August 10, 2023
Abstract
Fiber-reinforced polymer (FRP) is an innovative material in the construction industry. It is beneficial because of its toughness, and unlike steel, it is not prone to corrosion. Some research studies focus its behavior as a reinforcement in concrete while deriving several equations pertaining to its shear strength capacity. This study used the artificial neural network modeling technique to derive a more accurate solution to predict concrete shear capacity with FRP as reinforcement. Experimental data from previous studies were collected and used to train the model. The parameters considered were compressive strength of concrete, FRP ratio, beam dimensions, and modulus of elasticity. As a result, the model consistently provides a better prediction of the shear capacity of concrete against existing models like ACI 440.1R-03, ACI 440.1R-06, and El-Sayed. Furthermore, the ANN model showed no sign of disarray in predicting every parameter compared to other existing models. According to ACI 440.1R-06, FRP bars largely affect the total shear capacity of concrete. In the model provided by ACI, FRP reinforcement’s axial stiffness accounts linearly to the shear strength capacity of concrete. Since then, the predicted capacity in accordance with the ACI was excessively conservative. With respect to the derived model, axial stiffness offered a variation in the shear capacity. The proposed ANN model can be utilized for the design since the minimum ratio between the actual test result yields to 0.77 which is greater than the strength reduction factor of 0.75. Parametric studies were also conducted to show the effect of the modulus of elasticity of FRP, FRP ratio, and beam dimensions on the shear capacity.
Scopus ID: 85199873173
2023 IEEE 15th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM), (2023), pp. 1-5
Conference Paper | Published: January 1, 2023
Abstract
Riverbank collapse was recorded in the Philippines especially during typhoons and heavy rains. To analyze the possibility of failure, Slope/W under the Geostudio package was used as a finite element modeling technique in the study. The simulation determined the effect of the factor of safety (FOS) from the six (6) different assumed slopes and 15 different soil properties. The assumption of the present paper is that the properties of the soil and slope of the riverbank can determine the stability status of the sloping riverbank. There was a total of 90 simulations that were analyzed using the Morgenstern-Price method. The simulation results concluded that the highest and safe values of the factor of safety were recorded in simulations 1, 5 and 12 which are all more than 1.50. The simulations with a lower value of cohesion resulted in a lower value of the factor of safety. The correlation assessment result revealed that the slope instability or failure of slopes of riverbanks can be attributed to the cohesion values and the angle of internal friction (ϕ). It is recommended using a flatter slope and high values of cohesion which can be attained by riverbank improvement. If lower values of cohesion were detected, additional measures like bank stability should be proposed. The measures to be implemented should improve the FOS value which would improve the stability of slopes, thus preventing the vulnerability to riverbank collapse.
Scopus ID: 85159404536
2022 IEEE 14th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM), (2022), pp. 1-5
Conference Paper | Published: January 1, 2022
Abstract
Technology in construction has been attempting to discover eco-friendly materials, to identify waste products that can be processed as an alternative supplement to cement. The study utilizes sugar cane bagasse ash (SCBA) to produce a bagasse ash blended concrete. There were 15 previous experimental studies that were gathered and analyzed which have the same variables in terms of determining the mechanical proeprties of the blended concrete with SCBA. The variables that were considered are: compressive strength, cement content (CC), fine aggregate (FA) and coarse aggregate (CA) content, water-cement ratio (W/C), water content (WC), and sugarcane bagasse ash content. 74 different data sets in all were obtained. The study's goal is to develop a prediction model for estimating the mechanical properties of concrete made with SCBA. The work employed MATLAB R2021a neural network (NN) toolbox for model development and simulation of the dataset with the use of the backpropagation ANN. The best model was observed to have a structure of 7-7-1 (input-hidden-output) having the highest R all value and lowest AIC value, with a mean absolute percentage error (MAPE) is 3.718% considered to be a highly accurate model. The relative importance (RI) showed that the FA, CA, and CC were the most significant factors to the CS while water and SCBA were the least influential parameters. The overall findings reveal that the MAPE of the compression strength prediction model decreased from 3.718% to 3.519% exhibiting a 5.35% improvement in the model’s performance.
Scopus ID: 85159468687
2022 IEEE 14th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM), (2022), pp. 1-6
Conference Paper | Published: January 1, 2022
Abstract
Earthquakes or seismic events cause several disturbances in the ground which can harm or damage the structural stability and could turn fatal. Liquefaction causes a sudden movement shift that is out of sync with the rest of the structure. This might cause several structural damages to the property leading to casualties. In the Philippine geographical context, the West Valley Fault which traverses Metro Manila is a seismic threat capable of producing a maximum magnitude of 7.2. This study aims to assess the probability of liquefaction in Farnecio St., Quaipo, Manila as well as the determination whether the structures present will suffer from critical failure or not. Probabilistic Seismic Hazard Analysis and Monte Carlo Simulation were used to determine the seismic hazard. Recorded earthquake history from the Philippine Institute of Volcanology and Seismology was used as part of the seismic analysis. The seismic hazard analysis shows that a magnitude 5.3 earthquake has a 44.44 % probability of occurrence within the 10-to-20-kilometer distance from the seismic source. A peak ground acceleration of 0.458g and 0.548g was also determined for return periods of 500 and 2500 years for which a Uniform Hazard Response Spectrum was generated. The probability of damage for 2% in 50 years and 10% in 50 years is 39.63% and 30.41%, respectively.
Scopus ID: 85159430839
2022 IEEE 14th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM), (2022), pp. 1-5
Conference Paper | Published: January 1, 2022
Abstract
The paper aims to examine the factors that affects the successful implementation of the Mastery-based Individualized Learning Enhancement System (MILES) in the Far Eastern University (FEU) Institute of Technology. Two periods were analyzed which are the initial implementation, and this is the start of the pandemic period, and the year after the initial implementation of MILES. The Artificial Neural Network (ANN)-Particle Swarm Optimization (PSO)-based Sensitivity Analysis (SA) was utilized to determine the relative importance (RI) index among the influencing factors that affects the students’ level of satisfaction of the MILES implementation. Survey questionnaires were deployed through the canvas platforms and were answered by the students. In the initial survey, a total of 5763 students responded. For the SY 2020-2021, it was observed that the most influential variable to the student’s performance during the MILES Implementation is Course Adviser Rating while the parameters with the least impact to the student’s performance is the Student’s Status as regular or irregular student. For the survey on SY 2021-2022, the highest relative index is for the lesson preference while the lowest importance index is for the opportunities. Findings of the study shows that the use of NN-PSO based sensitivity analysis is an effective tool for establishing the significance of each variable to a target output.
Scopus ID: 85159477384
2022 IEEE 14th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM), (2022), pp. 1-6
Conference Paper | Published: January 1, 2022
Abstract
Carbonation is a dangerous threat to concrete since it reduces the alkalinity of normal or self-compacting concrete (SCC), allowing iron to corrode and spall the cover. The goal of this research is to use an artificial neural network to create a corrosion prediction model for steel in self-compacting concrete that has been subjected to carbonation. In this study, MATLABR2019a was used to create a feedforward back propagation neural network. As a training function, the researchers utilized the Levenberg-Marquardt back propagation (TRAINLM) which adjusts weights and bias values using Levenberg-Marquardt optimization. The researchers used gradient descent with momentum weight/bias learning (LEARNGDM) for the adaptation learning function, which is a technique that aids the gradient in determining which way to go. The network’s performance was measured using the mean square error (MSE). The Hyperbolic tangent sigmoid transfer function (TANSIG) was also employed as the transfer function since the values obtained by this function range from +1 to -1, considering both the positive and negative aspects of the parameter. To minimize overfitting, the number of hidden nodes should be fewer than the number of input parameters. The researchers tested 4-12 hidden nodes. Modeling was done using data from 102 experimental studies of self-compacting concrete exposed to corrosion. Using feed-forward back propagation ANN with 1 hidden layer and 8 hidden nodes, a Pearson R-value of 0.98748 and a mean square error of 0.5725 were obtained. The factor that most affect the carbonation depth were water-cement ratio and fly ash content. The suggested model was able to analytically describe the connection and behaviors of the various mixtures to the carbonation depth in the parametric investigation. The parameters characteristics were likewise described by the model.
Scopus ID: 85159491771
2022 IEEE 14th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM), (2022), pp. 1-5
Jenny B. Calot, James Bryan R. Galang, ... Lady Lyn E. Escarieses
Conference Paper | Published: January 1, 2022
Abstract
Low Impact Development (LID) is a green infrastructure approach to ease the surface runoff that arises due to climate change and from an increasing impervious surface area caused by urbanization. This study aims to determine which LID control is best suited for Barangay San Rafael, San Jose Del Monte, Bulacan. Using Storm Water Management Model (SWMM), a hydraulic model of the area was created to apply the LIDs and simulate a runoff. The data used in SWMM for the runoff simulation is the monthly rainfall values for year 2020. Based on the simulation using SWMM, the existing drainage system has a high total flood volume with total flood volume of 243.511 liters. Based on the data collected from SWMM, the most effective combination with total flood volume of 50.884 liters was the combination of all the LID practices. The study has used three (3) different LID practices and the combinations of the LID practices to obtain the ideal LID combination namely, Bioretention Cell, Bioswale, Bioswale and Permeable Pavement. In the final analysis, the combination of Permeable Pavement, Bioretention Cell, and Bioswale is the best combination out of the three LID controls mentioned. Bioretention Cells are primarily used in parking lot islands, traffic islands, and driveway runoff. The same is true for Permeable Pavement, which is used mainly on roadways and parking lot islands. Considering the total flood volume that the SWMM calculated, the combination of the three LID parameters alone has the lowest total flood volume.
Scopus ID: 85159433354
2022 IEEE 14th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM), (2022), pp. 1-4
Conference Paper | Published: January 1, 2022
Abstract
The major problem when it comes to homogeneous earth dams is the slope stability of the dam. Geo Studio is a software using finite element analysis to evaluate the performance of hydraulic structures. The simulation software can satisfactorily analyze of different conditions, soil parameters, analysis methods and applications. This study aims to simulate different combination designs of a homogeneous earth dam. It will obtain the factor of safety on each combination design of a homogeneous earth dam for slope stability due to downstream flow. A total of 98 simulations were analyzed to check the factor of safety (FOS) of the different soil properties and slope ratio combinations. Throughout all the 98 simulations there is a change in the values of the factor of safety depending on the slope and the soil type used. In the simulation data the highest value of the factor of safety of 2.890 is from the combination of slope of 2V:1H and MH (silt with a high plasticity), while the lowest value of factor of safety of 0.454 is from the combination of slope 2:1 and SP (poorly graded, small silt). This study uses Pearson’s R Correlation method to solve for the relationship between the slope and the factor of safety. The computed r value is 0.616 and is greater than the r tabular value of 0.1946 with 96 degrees of freedom and 0.05 level of significance. It is recommended using the slope 1V:2H since it has the widest base, and has a desirable value for factor of safety, which would prevent the susceptibility to failure of the dam.
Scopus ID: 85159461464
2022 IEEE 14th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM), (2022), pp. 1-6
Conference Paper | Published: January 1, 2022
Abstract
The daily maximum multi-annual series including the rainfall frequency analysis, are one of the inputs for the design process for stormwater management, that entails numerous procedures: (a) rainfall data gathering from Philippine Atmospheric Geophysical and Astronomical Services Administration (PAGASA), (b) information gathering, and (c) checking all received datasets for missing or different data. To address these setbacks, 6 rain gauge stations located in Region VIII, Visayas, Philippines were used to first determine whether or not the Gumbel Extreme Value (GEV) was the better suitable method to use in producing Rainfall Intensity Duration Frequency (RIDF) than Log-Pearson Type III (LP3) by performing Chi-square test; secondly, to select the better RIDF values; and lastly, the isohyetal maps should be developed for return periods of 2, 5, 10, 25, 50, and 100 years. GEV was a better fit for the x2 values (27.96, 54.59, 52.82, 87.96, 11.78, 7.66) obtained through chi-square test were close to or smaller than the critical value of 30.144. The RIDFs produced in GEV were used in plotting isohyetal maps. In all return periods, Borongan generated the highest rainfall intensity value.
Scopus ID: 85159487630
2022 IEEE 14th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM), (2022), pp. 1-7
Conference Paper | Published: January 1, 2022
Abstract
As the Philippine Government continues to encourage the use of modular construction for its fast completion rate, still, the said innovative method is not well-known and practiced in the Philippines. The aim of this study is to analyze the modular construction system as a feasible solution for the Philippine's housing crisis and construction delays, as well as for its wide applicability in the Philippines for residential housing projects by the means of comparing its project duration to the conventional way. This seeks to identify if there are significant differences between the two construction methods. The Jamovi Software was used to execute the one-tailed independent samples t-testing. A survey was also done to compare and validate the results of the statistical analysis. Based on the findings, modular construction was found substantially faster, but in some instances, the difference between the overall project duration of conventional and modular construction does not vary significantly. Based on the survey result, 77.67% of the respondents agreed that modular construction is faster in terms of project duration. Although the numerical results revealed that the differences are not considered as statistically significant, still, modular construction takes the upper hand by looking at the average construction time, in which the survey respondents also believed. With that, the potential of modular construction can still be recognized as a feasible solution to the construction delays and the Philippines' housing crisis.