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The utilisation of travel surveys can uncover layers of information regarding travel behaviour, travel needs, and more. The collected information is utilised to make strategic planning choices when reorganising or planning new built environments. Over the years, the methods for conducting travel surveys have changed from manual interviews and paper forms to automated travel diaries which are monitoring the trips made by the survey participants. With the fast progression of technological advancements, new possibilities for operationalising said types of automated travel diaries can be changed from utilising mobile devices to wearable devices. Wearable devices are often equipped with sensors which can collect continuous biometric data from sources which are not reachable from standard mobile devices such as smartphones. The biometric data that can be collected through wearable devices ranging from heart rate and blood pressure to temperature and perspiration, given the proper sensors. This advancement opens for new possible layers of information in the collection of travel data. Such biometric data can be used to derive psychophysiological conditions related to cognitive load, which can uncover more in-depth knowledge regarding stress and emotions, given the right variables and sample rate. This paper aims to explore the possibilities in terms of data analysis on a data set collected through a software combining traditional travel survey data, such as position and time, with biometric data, in this case; heartrate, to gain knowledge of the implications of such collected data. The knowledge about the implications of spatial configurations can be used in the planning phase of new areas, in order to create more accessible environments, as the information could be used to make neutral, or even encouraging, environments for travellers. This work is currently not under review but is intended to be submitted to the “International Conference on Transport Survey Methods” once the call for submissions is opened.QCR 20191022

We report the design, fabrication, and characterization of ultralight coatings that employ Salisbury screen principles and the unique nature of ITO to achieve frequency selective broadband emissivity. Our coating comprises 60 nm SiO2, 10 nm ITO, 2.3 µm NeXolv LaRC CP1 polyimide and 300 nm Ag, and achieves an aerial mass of 4.07 gm-2. It has a calculated and measured visible spectrum reflectivity of R = 0.893 and R = 0.896 respectively when weighted against AM0 from 300 nm to 1800nm; and a calculated and measured IR spectrum emissivity of e = 0.574 and e = 0.554 weighted against a 300 K blackbody respectively. This simple coating design, fabricated on the centimeter scale, achieves broadband frequency selectivity, with the highest reported thermal performance for an ultralight sun-facing radiative energy management structure.

Travel surveys can uncover information regarding travel behaviour, needs, and more. Collected information is utilised to make choices when reorganising or planning built environments. Over the years, methods for conducting travel surveys have changed from interviews and forms to automated travel diaries in order to monitor trips made by travellers. With the fast progression of technological advancements, new possibilities for operationalising such travel diaries can be implemented, changing from utilising mobile to wearable devices. Wearable devices are often equipped with sensors which collect continuous biometric data from sources that are not reachable from standard mobile devices. Data collected through wearable devices range from heart rate and blood pressure to temperature and perspiration. This advancement opens new possible layers of information in the collection of travel data. Such biometric data can be used to derive psychophysiological conditions related to cognitive load, which can uncover in-depth knowledge regarding stress and emotions. This paper aims to explore the possibilities of data analysis on the data collected through a software combining travel survey data, such as position and time, with heartrate, to gain knowledge of the implications of such data. The knowledge about the implications of spatial configurations can be used to create more accessible environments. QC 20211005

Human factors are identified as the major contributor to oil and gas drilling and other operations related accidents. Offshore oil and gas operations involve complex scenarios and decision-making with potentially catastrophic consequences. The current simulation-based training modules are often criticized for their lack of objective and validated measures for human factors and non-technical skills. There is also a need to include measures for enhanced situational awareness and decision-making for the offshore drilling crew. In this study, we present holistic human-centered training framework equipped with assessment techniques to analyses situational awareness of partcipants in customized well-control operations. The training exercise used in this work included real-time well control operation customized for drilling break and kick detection scenarios. The assessment approach consisted of eye-tracking data analysis, questionnaire analysis, checklist score analysis, and communication log analysis. After individual analysis from each technique, a new framework was developed to triangulate results from each technique to provide a comprehensive assessment. The participants included seven group of novices and one group of experts. The preliminary results indicate significant differences between the situation awareness and performance of participants. Furthermore, there were observed notable differences between the perceptual, comprehensive, and projection ability of novices and experts in routine jobs on a drilling platform. The eye-tracking data features included fixation count and fixation duration, and it was inferred that eye-tracking results can be representative of cognitive abilities of the partcipants. Furthermore, the fixation count and duration results were highly correlated with the checklist scores. Overall, the adopted methodology in this study have potential to open new avenues for human- centered training framework and improvement in traditional assessment approach. Furthermore, it can also be helpful in understanding of cognitive responses of the offshore professionals.

Jets at higher Reynolds numbers have a high concentration of energy in small scales in the nozzle vicinity. This is challenging for large-eddy simulation, potentially placing severe demands on grid density. To circumvent this, we propose a novel procedure based on well-known Reynolds number (Re) independent of jets. We reduce the jet Re while rescaling the boundary layer properties to maintain incoming boundary layer thickness consistent with high Re jet. The simulations are carried out using hybrid large-eddy simulation type of approach which is incorporated by using near-wall turbulence model with modified properties. No subgrid scale model is used in these simulations. Hence, they effectively become numerical large-eddy simulation with Reynolds-averaged Navier–Stokes covering the full boundary layer region. The noise post-processing is carried out using the Ffowcs-Williams-Hawking approach. The simulations are made for Mach numbers (M) of 0.75 and 0.875 (cold and hot). The results for the overall sound pressure level are observed to be within 2–3% of the measurements, and directivity of sound is also captured accurately for both the cases. Hence, the low Re simulations can be more beneficial in saving time and cost while providing reasonably accurate results.

Large-eddy simulations are performed for hot and cold jets with and without a flight stream. The acoustic and flight stream Mach numbers are 0.875 and 0.3, respectively. The temperature ratios for the hot and cold jets are 2.7 and 1.0, respectively. The mean flow field results are in good agreement with the measurements. The Ffowcs Williams–Hawkings equation is used to predict far-field noise. Several axisymmetric Ffowcs Williams–Hawkings surfaces at increasing radial distances are used. They show that the surfaces closer to the jet can be affected by the hydrodynamic pressure. It is important to close the Ffowcs Williams–Hawkings surfaces at the ends to account for all the acoustic signals emanating from the jet. In this work, 11 end discs are used at the downstream end of the Ffowcs Williams–Hawkings surface. It is found that the simple averaging processes to cancel hydrodynamic sound at the end discs are insufficient for slowly decaying jets. In such cases, a partially closed disc can be a better choice. To remove hydrodynamic signals, a filtering scheme for the end discs is suggested. For slowly decaying jets, this gives better results.

A direct numerical simulation (DNS) of a plane wall jet is performed at a Reynolds number of $Re_{j}=7500$. The streamwise length of the domain is long enough to achieve self-similarity for the mean flow and the Reynolds shear stress. This is the highest Reynolds number wall jet DNS for a large domain achieved to date. The high resolution simulation reveals the unsteady flow field in great detail and shows the transition process in the outer shear layer and inner boundary layer. Mean flow parameters of maximum velocity decay, wall shear stress, friction coefficient and jet spreading rate are consistent with several other studies reported in the literature. Mean flow, Reynolds normal and shear stress profiles are presented with various scalings, revealing the self-similar behaviour of the wall jet. The Reynolds normal stresses do not show complete similarity for the given Reynolds number and domain length. Previously published inner layer budgets based on LES are inaccurate and those that have been measured are only available in the outer layer. The current DNS provides fully balanced, explicitly calculated budgets for the turbulence kinetic energy, Reynolds normal stresses and Reynolds shear stress in both the inner and outer layers. The budgets are scaled with inner and outer variables. The inner-scaled budgets in the near wall region show great similarity with turbulent boundary layers. The only remarkable difference is for the turbulent diffusion in the wall-normal Reynolds stress and Reynolds shear stress budgets. The outer layer interacts with the inner layer through turbulent diffusion and the excess energy from the wall-normal direction is transferred to the spanwise direction.

We report the design, fabrication, and characterization of ultralight highly emissive structures with a record-low mass per area that emit thermal radiation efficiently over a broad spectral (2 to 30 microns) and angular (0-60°) range. The structures comprise one to three pairs of alternating metallic and dielectric thin films and have measured effective 300 K hemispherical emissivity of 0.7 to 0.9 (inferred from angular measurements which cover a bandwidth corresponding to 88% of 300K blackbody power). To our knowledge, these micron-scale-thickness structures, are the lightest reported optical coatings with comparable infrared emissivity. The superior optical properties, together with their mechanical flexibility, low outgassing, and low areal mass, suggest that these coatings are candidates for thermal management in applications demanding of ultralight flexible structures, including aerospace applications, ultralight photovoltaics, lightweight flexible electronics, and textiles for thermal insulation.

We have fabricated a functional prototype of an ultralight power converter tile; a modular building block for a space-based solar power system. The tile is $\sim 10\mathrm \times 15$ cm in area, and weighs $\sim 1.5$ kg/$\text{m}^{\mathbf {2}}$. It comprises a photovoltaic (PV) solar energy collector, a radio-frequency (RF) power converter, and an array of transmission antennas. The PV collector subassembly utilizes $\sim 15\mathrm {x}$, 1D parabolic trough reflective concentrators with triple-junction (3J) solar cells. It has areal mass of $\sim 0.8$ kg/$\textbf{m}^{\mathbf {2}}$, 74% optical efficiency, and a peak specific power of $\sim 230\mathrm {W} /$kg. We demonstrated wireless power transmission over a distance of $\sim 50$ cm in our lab. Analysis of the sources of mass and inefficiency suggest a path towards achieving dramatically higher performance with future designs.

Scattering particles constitute a key light trapping solution for thin film photovoltaics where either the particles are embedded in the light absorbing layer or a thick layer of them is used as a reflector. Here we introduce a monolayer of wavelength-scale core-shell silica@Ag particles as a novel light trapping strategy for thin film photovoltaics. These particles show hybrid photonic-plasmonic resonance modes that scatter light strongly and with small parasitic absorption losses in Ag (1.5%). In addition, their scattering efficiency does not vary significantly with the refractive index of the surrounding medium. A monolayer of these particles is applied as the top-scattering layers in a dye-sensitized solar cells and it improves the short-circuit current density of a cell with 7 μm-thick dye-sensitized layer by 38%. Optical measurements of the scattering properties of these particles confirm that the strong scattering and low-parasitic absorption losses constitute the main reason for this efficient light trapping.