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Data article: Genetic algorithm model and data files to assess JONSWAP spectra coefficients: MATLAB code

Manuscript title: Genetic algorithm model and data files to assess JONSWAP spectra coefficients: MATLAB code

Authors: Rueda-Bayona, J.G., Guzmán, A

Data in Brief (ISSN: 2352-3409). Available online: August 19, 2020. 106196 (In press).  

Abstract: This data article presents the structure of a Genetic Algorithm model written in a MATLAB code for finding the 1D JONSWAP spectra parameters when measured raw spectra is not available. The JONSWAP spectra is widely used in Coastal, Offshore, and Ocean Engineering for determining wave parameters for structure designing and numerical modeling. However, finding proper spectra parameters may be difficult because of the limitations of parameterized equations to do so and the high non-linear relation between the alpha and gamma coefficients. This GA model can find the alpha and gamma parameters for specific locations considering sea-state's evolution and water-depth transitions. The application of the GA model of this data article is shown in Rueda-Bayona et al.

Keywords: Genetic algorithms; JONSWAP; numerical modeling; waves; MATLAB

Research article: Selection of JONSWAP Spectra Parameters During Water-depth and Sea-state Transitions

Manuscript title: Selection of JONSWAP Spectra Parameters During Water-depth and Sea-state Transitions

Authors: Rueda-Bayona, J.G., Guzmán, A, Cabello, J.

Journal of Waterway, Port, Coastal, and Ocean Engineering (ISSN (print): 0733-950X | ISSN (online): 1943-5460). Vol. 146, Issue 6 – July 2020 (online); November 2020 (printed). 

Abstract: The design of marine structures requires the simulation of wave parameters that consider sea-state and water-depth transitions. Proper selection of the model coefficients (e.g., alpha and gamma of the JONSWAP spectra) is then required, because of the wave-hydrodynamic nonlinearities during these ocean processes. Therefore, the model coefficient selection should be tested using a nonlinear analysis to assess the effect of the selected spectra coefficients over the modeled wave parameters. The present study performed a design of experiment (DOE)-analysis of variance (ANOVA) and probability analysis to assess the effect of alpha and gamma parameters over the significant wave height (Hs) and peak period (Tp) during sea-state and water-depth transitions. The DOE-ANOVA demonstrated for the mean and extreme wave states of the study area that alpha and gamma parameters positively affect the Hs behavior in deep and intermediate waters. Furthermore, the standardized effects of alpha and gamma over the Tp during extreme wave states suggest quadruplets of wave–wave interactions. The joint and normal probability distributions of alpha and gamma for extreme and normal waves showed a Gaussian distribution, allowing identification of specific alpha and gamma values for the JONSWAP spectra model. The selected alpha and gamma parameters were then validated through the comparison of the modeled Hs (JONSWAP) against other local studies. Considering its relevance in design strategies for offshore structures, this research contributed to the understanding of the nonlinear effects of alpha and gamma parameters over the Hs and Tp during variations of water depth and wave states, easing the selection of the model coefficients.

Keywords: DOE-ANOVA; JONSWAP spectra; Numerical modeling; Probability; Waves

Research article: Performance evaluation of structures with reinforced concrete columns retrofitted with steel jacketing

Manuscript title: Performance evaluation of structures with reinforced concrete columns retrofitted with steel jacketing

Authors: Villar-Salinas, S., Guzmán, A., Carrillo, J.

Journal of building engineering (ISSN: 2352-7102). May 2020. Available online: 17 June 2020.

Abstract: Several existing reinforced concrete (RC) buildings fail to conform with current seismic codes, increasing its susceptibility to damage and collapse during earthquakes. A concern for building upgrading and rehabilitation has grown considerably in the last decades. However, there is limited information related to the seismic performance of RC buildings retrofitted with steel jacketing. Retrofitting of RC buildings leads to different techniques that have been developed in the last decades. The selection of adequate techniques commonly depends on desired performance levels, financial criteria, or other non-technical judgment. This paper assesses the seismic performance of a six-story RC building retrofitted with steel jacketing that is located in Cartagena de Indias (Colombia). The building was designed and constructed in 2010 without considering the requirements prescribed by the NSR-10 Colombian code. In 2017, another building collapsed in the same city for several non-compliances with Colombian seismic code. This investigation focuses on the seismic upgrading of the building, studying the influence of different material properties of the existing building and load scenarios on the building behavior. The proposed steel jacketing improves the compressive and flexural capacity of retrofitted columns, along with the ductility of the building.

Keywords: Seismic performanceSeismic retrofittingRC buildingsNonlinear modelingSteel jacketing 

Research article: Use of sludge ash from drinking water treatment plant in hydraulic mortars

Manuscript title: Use of sludge ash from drinking water treatment plant in hydraulic mortars

Authors: Bohórquez, K., Pacheco, E., Guzmán, A., Avila, Y., Cano, H. & Valencia, J

Materials Today Communications. January 16 2020.

Abstract: The present study investigated the use of sludge ash from water treatment plants as supplementary cementing material, elaborating hydraulic mortars with different levels of cement replacement by sludge ash (10 wt% and 30 wt%) and different temperatures of calcination (600 °C and 800 °C). Characterization of sludge ash and mortars includes XRF, XRD, particle size distribution by laser diffraction, compressive strength, and SEM-EDS. The results show that SiO2, Al2O3, and Fe2O3 compose 90 % of the sludge ash, and it has potential pozzolanic activity. It is evidenced that there is a significant influence of the variable ratio of sludge ash:cement in the compressive strength of the mortar cubes over other variables. Overall, this study showed that the sludge ash could be considered as a viable and sustainable alternative for the construction sector. Despite the benefits of the suggested replacement, the presence of amorphous SiO2 requires a review of long-time chemical behavior..

Keywords: Supplementary cementitious material; Sludge ash; Compressive strength; Characterization; Construction materials

Research article: Genetic algorithms to determine JONSWAP spectra parameters

Manuscript title: Genetic algorithms to determine JONSWAP spectra parameters

Authors: Juan Gabriel Rueda-Bayona, Andrés Guzmán, Rodolfo Silva

Ocean Dynamics. January 09 2020.

Abstract: The genetic algorithm (GA) model presented here provides specific JONSWAP parameters that can be used for wave modelling. This work describes a validated heuristic model based on GA, to select JONSWAP spectra parameters, regardless of water depth restrictions and sea state conditions. The identification of the JONSWAP spectra parameters is difficult, as the alpha and gamma coefficients have scattered distributions that modulate the spectral peak energy. In addition, the selection of alpha and gamma coefficients from in situ free surface records may be difficult and time-consuming, because of the amount of data and nonlinearities involved. The proposed model uses either in situ or numerically modelled wave data and has three main steps: (1) generation and crossover, (2) minimisation of the cost function ΔHs, defined as the minimum difference between the calculated artificial significant wave height and the in situ wave height (instrumented or modelled), and (3) mutation and natural selection. To apply the model, in situ wave data measured by an acoustic Doppler current profiler over 5.5 months was used in this research. The results show a high correlation (r^2), of 0.95, between the best fitted curves of modelled spectra and measured data.

Keywords: Genetic algorithm; JONSWAP; parameters; spectral peak energy