Using Big Data to manage safety-related risk in the upstream oil and gas industry: A research agenda

Despite considerable effort and a broad range of new approaches to safety management over the years, the upstream oil & gas industry has been frustrated by the sector’s stubbornly high rate of injuries and fatalities. This short communication points out, however, that the industry may be in a position to make considerable progress by applying “Big Data” analytical tools to the large volumes of safety-related data that have been collected by these organizations. Toward making this case, we examine existing safety-related information management practices in the upstream oil & gas industry, and specifically note that data in this sector often tends to be highly customized, difficult to analyze using conventional quantitative tools, and frequently ignored. We then contend that the application of new Big Data kinds of analytical techniques could potentially reveal patterns and trends that have been hidden or unknown thus far, and argue that these tools could help the upstream oil & gas sector to improve its injury and fatality statistics. Finally, we offer a research agenda toward accelerating the rate at which Big Data and new analytical capabilities could play a material role in helping the industry to improve its health and safety performance.

Superhydrophobic fabrics for oil-water separation based on the metal organic charge transfer complex CuTCNAQ

This work reports on the fabrication of a superhydrophobic nylon textile based on the organic charge transfer complex CuTCNAQ (TCNAQ = 11,11,12,12-tetracyanoanthraquinodimethane). The nylon fabric that is metallized with copper undergoes a spontaneous chemical reaction with TCNAQ dissolved in acetonitrile to form nanorods of CuTCNAQ that are intertwined over the entire surface of the fabric. This creates the necessary micro and nanoscale roughness that is required for the Cassie-Baxter state thereby achieving a superhydrophobic/superoleophilic surface without the need for a fluorinated surface. The material is characterised with SEM, FT-IR and XPS spectroscopy and investigated for its ability to separate oil and water in two modes, namely under gravity and as an absorbent. It is found that the fabric can separate dichloromethane, olive oil and crude oil from water and in fact reduce the water content of the oil during the separation process. The fabric is reusable and tolerant to conditions such as seawater, hydrochloric acid and extensive time periods on the shelf. Given that CuTCNAQ is a copper based semiconductor may also open up the possibility of other applications in areas such as photocatalysis and antibacterial applications.

Evaluation of oil production from oil palm empty fruit bunch by oleaginous micro-organisms

Oil palm empty fruit bunch (EFB) is a readily available, lignocellulosic biomass that has potential to be utilized as a carbon substrate for microbial oil production. In order to evaluate the production of microbial oil from EFB, a technical study was performed through the cultivation of oleaginous micro-organisms (Rhodotorula mucilaginosa, Aspergillus oryzae, and Mucor plumbeus) on EFB hydrolyzates. EFB hydrolyzates were prepared through dilute acid pre-treatment of the biomass, where the liquid fraction of pre-treatment was detoxified and used as an EFB liquid hydrolyzate (EFBLH). The solid residue was enzymatically hydrolyzed prior to be used as an EFB enzymatic hydrolyzate (EFBEH). The highest oil concentrations were obtained from M. plumbeus (1.9 g/L of oil on EFBLH and 4.7 g/L of oil on EFBEH). In order to evaluate the feasibility of large-scale microbial oil production, a techno-economic study was performed based on the oil yields of M. plumbeus per hectare of plantation, followed by the estimation of the feedstock cost for oil production. Other oil palm biomasses (frond and trunk) were also included in this study, as it could potentially improve the economics of large-scale microbial oil production. Microbial oil from oil palm biomasses was estimated to potentially increase oil production in the palm oil industry up to 25%, at a cheaper feedstock cost. The outcome of this study demonstrates the potential integration of microbial oil production from oil palm biomasses with existing palm oil industry (biodiesel, food and oleochemicals production), that could potentially enhance sustainability and profitability of microbial oil production.

Microbial oil production from sugarcane bagasse hydrolysates by oleaginous yeast and filamentous fungi

This study investigated the potential use of sugarcane bagasse as a feedstock for oil production through microbial cultivation. Bagasse was subjected to dilute acid pretreatment with 0.4 wt% H2SO4 (in liquid) at a solid/liquid ratio of 1:6 (wt/wt) at 170 °C for 15 min, followed by enzymatic hydrolysis of solid residue. The liquid fractions of the pretreatment process and the enzymatic hydrolysis process were detoxified and used as liquid hydrolysate (SCBLH) and enzymatic hydrolysate (SCBEH) for the microbial oil production by oleaginous yeast (Rhodotorula mucilaginosa) and filamentous fungi (Aspergillus oryzae and Mucor plumbeus). The results showed that all strains were able to grow and produce oil from bagasse hydrolysates. The highest oil concentrations produced from bagasse hydrolysates were by M. plumbeus at 1.59 g/L (SCBLH) and 4.74 g/L (SCBEH). The microbial oils obtained have similar fatty acid compositions to vegetable oils, indicating that the oil can be used for the production of second generation biodiesel. On the basis of oil yields obtained by M. plumbeus, from 10 million t (wet weight) of bagasse generated annually from sugar mills in Australia, it is estimated that the total biodiesel that could be produced would be equivalent to about 9% of Queensland’s diesel consumption.

Can current force fields reproduce ring puckering in 2-O-sulfo-α-l-iduronic acid? A molecular dynamics simulation study

The monosaccharide 2-O-sulfo-α-l-iduronic acid (IdoA2S) is one of the major components of glycosaminoglycans. The ability of molecular mechanics force fields to reproduce ring-puckering conformational equilibrium is important for the successful prediction of the free energies of interaction of these carbohydrates with proteins. Here we report unconstrained molecular dynamics simulations of IdoA2S monosaccharide that were carried out to investigate the ability of commonly used force fields to reproduce its ring conformational flexibility in aqueous solution. In particular, the distribution of ring conformer populations of IdoA2S was determined. The GROMOS96 force field with the SPC/E water potential can predict successfully the dominant skew-boat to chair conformational transition of the IdoA2S monosaccharide in aqueous solution. On the other hand, the GLYCAM06 force field with the TIP3P water potential sampled transitional conformations between the boat and chair forms. Simulations using the GROMOS96 force field showed no pseudorotational equilibrium fluctuations and hence no inter-conversion between the boat and twist boat ring conformers. Calculations of theoretical proton NMR coupling constants showed that the GROMOS96 force field can predict the skew-boat to chair conformational ratio in good agreement with the experiment, whereas GLYCAM06 shows worse agreement. The omega rotamer distribution about the C5–C6 bond was predicted by both force fields to have torsions around 10°, 190°, and 360°.

Channelled porous TiO2 synthesized with a water-in-oil microemulsion

Porous titanium dioxide synthesized with a bicontinuous surfactant template is a promising method that leads to a high active surface area electrode. The template used is based on a water/isooctane/dioctyl sodium sulfosuccinate salt together with lecithin. Several parameters were varied during the synthesis to understand and optimize channel formation mechanisms. The material is patterned in stacked conical channels, widening towards the centre of the grains. The active surface area increased by 116% when the concentration of alkoxide precursors was decreased and increased by 241% when the template formation temperature was decreased to 10C. Increasing the oil phase viscosity tends to widen the pore aperture, thus decreasing the overall active surface area. Changing the phase proportions alters the microemulsion integrity and disrupts channel formation.

Fluorescent Fields: electric lighting and the rationalization of the modern corporate workplace

This study investigates the implications of the introduction of electric lighting systems, building technologies, and theories of worker efficiency on the deep spatial and environmental transformations that occurred within the corporate workplace during the twentieth century. Examining the shift from daylighting strategies to largely artificially lit workplace environments, this paper argues that electric lighting significantly contributed to the architectural rationalization of both office work and the modern office environment. Contesting the historical and critical marginalization of lighting within the discourse of the modern built environment, this study calls for a reassessment of the role of artificial lighting in the development of the modern corporate workplace. Keywords: daylighting, fluorescent lighting, rationalization, workplace design

Deeper and wider fully convolutional network coupled with conditional random fields for scene labeling

Deep convolutional neural networks (DCNNs) have been employed in many computer vision tasks with great success due to their robustness in feature learning. One of the advantages of DCNNs is their representation robustness to object locations, which is useful for object recognition tasks. However, this also discards spatial information, which is useful when dealing with topological information of the image (e.g. scene labeling, face recognition). In this paper, we propose a deeper and wider network architecture to tackle the scene labeling task. The depth is achieved by incorporating predictions from multiple early layers of the DCNN. The width is achieved by combining multiple outputs of the network. We then further refine the parsing task by adopting graphical models (GMs) as a post-processing step to incorporate spatial and contextual information into the network. The new strategy for a deeper, wider convolutional network coupled with graphical models has shown promising results on the PASCAL-Context dataset.

Context-based assessment: Creating opportunities for resonance between classroom fields and societal fields

There is on-going international interest in the relationships between assessment instruments, students’ understanding of science concepts and context-based curriculum approaches. This study extends earlier research showing that students can develop connections between contexts and concepts – called fluid transitions – when studying context-based courses. We provide an in-depth investigation of one student’s experiences with multiple contextual assessment instruments that were associated with a context-based course. We analyzed the student’s responses to context-based assessment instruments to determine the extent to which contextual tests, reports of field investigations, and extended experimental investigations afforded her opportunities to make connections between contexts and concepts. A system of categorizing student responses was developed that can inform other educators when analyzing student responses to contextual assessment. We also refine the theoretical construct of fluid transitions that informed the study initially. Implications for curriculum and assessment design are provided in light of the findings.