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The existence of soft soil in offshore areas may lead to the amplification of vibration received from offshore facilities, especially from the existing fixed-jacket platforms, which were designed without provision to seismicity, as in Malaysian water. Therefore, this study was designed to develop a seismic microzonation map and a soil amplification factor map according to soil type; we propose horizontal response spectra and site coefficient values (Ca and Cv) for the Malay Basin. A one-dimensional nonlinear analysis of layered soil (NERA) was used in the ground response analysis for six selected seismic events under five return periods of 100, 200, 500, 1000, and 2500 years. Soil amplification factors for soil types D and E showed a decreasing trend from 100 years to 2500 years. Two designed horizontal response spectra are proposed (for soil type D and E) under average and envelope conditions; a comparison with ISO showed that the proposed spectra were higher, especially for soil type E. To summarize, the seismicity effect should be included in the development of offshore industries as findings indicated that soil amplification occurred in soil types D and E at the Malay Basin.

Graphene oxide-modified rubberized engineered cementitious composite (GO-RECC) is attracting the attention of researchers because of the reported benefits of the GO and crumb rubber (CR) on the strength and deformation properties of the composite. While it is well established that GO negatively affects the workability of cementitious composites, its influence on the attainment of the desired self-compacting (SC) properties of ECC has not yet been thoroughly investigated, especially when combined with crumb rubber (CR). In addition, to simplify the number of trial mixes involved in designing SC-GO-RECC, there is a need to develop and optimize the process using Design of Experiment (DOE) methods. Hence, this research aims to investigate and model using response surface methodology (RSM), the combined effects of the GO and CR on the SC properties of ECC through the determination of T500, slump flow, V-funnel, and L-box ratio of the SC-GORECC as the responses, following the European Federation of National Associations Representing for Concrete (EFNARC) 2005 specifications. The input factors considered were the GO by wt.% of cement (0.02, 0.04, 0.06, and 0.08) and CR as a replacement of fine aggregate by volume (5, 10, and 15%). The results showed that increasing the percentages of GO and CR affected the fresh properties of the SC-GORECC adversely. However, all mixes have T500 of 2.4 to 5.2 s, slump flow of 645 to 800 mm, V-funnel time of 7.1 to 12.3 s, and L-box ratio (H2/H1) of 0.8 to 0.98, which are all within acceptable limits specified by EFNARC 2005. The developed response prediction models were well fitted with R2 values ranging from 91 to 99%. Through the optimization process, optimal values of GO and CR were found to be 0.067% and 6.8%, respectively, at a desirability value of 1.0.

Steel plates with openings are among the important ship structural components used in the ship’s hull to withstand the hydrostatic forces of the ocean, which cause sagging and hogging moments at the ship’s bottom. The existence of openings on plates can cause structural rupture, stress concentration and a decrease in ultimate strength. This research is aimed at investigating the influence of selected parameters on the ultimate capacity of steel plates with rectangular holes subjected to axial stress, using ANSYS finite element analysis (FEA) under its non-linear static structural programme. The main parameters investigated in this paper are the plate thickness, opening aspect ratio, number of openings, position of openings, and the boundary condition of the plate. The influence of these parameters on the stress of plates and their deformation was evaluated. The comparison of the numerical simulation with the well-established analytical method using the Navier solution and Roark’s Formulas showed a good agreement. Finite Element Analysis of Steel Plates with Rectangular Openings Subjected to Axial Stress

The current oil industry is moving towards digitalization, which is a good opportunity that will bring value to all its stakeholders. The digitalization of oil and gas discovery, which are production-based industries, is driven by enabling technologies which include machine learning (ML) and big data analytics. However, the existing Metocean system generates data manually using sensors such as the wave buoy, anemometer, and acoustic doppler current profiler (ADCP). Additionally, these data which appear in ASCII format to the Metocean system are also manual and silos. This slows down provisioning, while the monitoring element of the Metocean data path is partial. In this paper, we demonstrate the capabilities of ML for the development of Metocean data integration interoperability based on intelligent operations and automation. A comprehensive review of several research studies, which explore the needs of ML in oil and gas industries by investigating the in-depth integration of Metocean data interoperability for intelligent operations and automation using an ML-based approach, is presented. A new model integrated with the existing Metocean data system using ML algorithms to monitor and interoperate with maximum performance is proposed. The study reveals that ML is one of the crucial and key enabling tools that the oil and gas industries are now focused on for implementing digital transformation, which allows the industry to automate, enhance production, and have less human capacity. Lastly, user recommendations for potential future investigations are offered.

One of the primary causes of the low mechanical properties of rubberized concrete is the weak bond between crumb rubber (CR) and hardened cement paste. Many CR pretreatment techniques have been researched in an attempt to mitigate this problem. The NaOH pretreatment method is one of the most widely used, although the reported results are inconsistent due to the absence of standardized NaOH pretreatment concentrations and CR replacement levels. This study aims to develop models for predicting the mechanical and shrinkage properties of NaOH-pretreated CR concrete (NaOH-CRC) and conduct multi-objective optimization using response surface methodology (RSM). The RSM generated experimental runs using three levels (0, 5, and 10%) of both NaOH pretreatment concentration and the CR replacement level of fine aggregate by volume as the input factors. At 28 days, the concrete’s compressive, flexural, and tensile strengths (CS, FS, and TS), as well as its drying shrinkage (S), were evaluated as the responses. The results revealed that higher CR replacements led to lower mechanical strengths and higher shrinkage. However, the strength loss and the shrinkage significantly reduced by 22%, 44%, 43%, and 60% for CS, FS, TS, and S, respectively, after the pretreatment. Using field-emission scanning electron microscopy (FESEM), the microstructural investigation indicated a significantly reduced interfacial transition zone (ITZ) with increasing NaOH pretreatment. The developed RSM models were evaluated using ANOVA and found to have high R2 values ranging from 78.7% to 98%. The optimization produced NaOH and CR levels of 10% and 2%, respectively, with high desirability of 71.4%.