Theoretical Impact of Building Façade Thickness on Daylight Metrics and Lighting Energy Demand in Buildings: A Case Study of the Tropics

In daylighting design, variation of building façade thickness (f) will result in variation of the daylight opening areas, which in turn will modify the values of daylight metrics within the space. However, studies dedicated to investigating the impact of varying f on indoor daylight metrics are relatively scarce. This study, therefore, aims to assess the theoretical impact of various façade thicknesses on various daylight metrics and lighting energy demands in a reference office space. Analytical calculations are performed using an outdoor diffuse illuminance profile of a tropical city. The building façade thickness values are varied within 0–0.50 m, at window-to-wall ratios (WWR) of 25%, 50%, and 75%. Based on sensitivity analysis, it is found that variation of f yields different impacts on the observed metrics, with sDA300/50% being the least influenced. Among all metrics in the central calculation point, DA300, UDI-a, and UDI-a′ yield relatively small coefficients of variation, and thus, have the lowest uncertainty with respect to f. Among all metrics for the entire room, sDA300/50% and sUDI-a50% have the lowest uncertainty, with interquartile ranges of no more than 0.4%. Overall, the contribution of this study is providing insight into the impact of façade thickness on various daylight metrics in indoor spaces, particularly in the worst-case scenario under the standard CIE overcast sky.

Experimentally identified models of McKibben soft actuators as primary movers and passive structures

Soft robots join body and actuation, forming their structure from the same elements that induce motion. Soft actuators are commonly modeled or characterized as primary movers, but their second role as support structure introduces strain-pressure combinations outside of normal actuation. This manuscript examines a more complete set of possible strain-pressure combinations for McKibben actuators, including passive, or unpressurized, deformation, pressurized extension and compression of a pressurized actuator beyond the maximum actuation strain. Each region is investigated experimentally, and empirical force-displacement-pressure relationships are identified. Particular focus is placed on ensuring empirical relationships are consistent at boundaries between an actuator's strain-pressure regions. The presented methodology is applied to seven McKibben actuator designs, which span variations in wall thickness, enclosure material and actuator diameter. Empirical results demonstrate a trade-off between maximum contraction strain and force required to passively extend. The results also show that stiffer elastomers require an extreme increase in pressure to contract without a compensatory increase in maximum achieved force. Empirical force-displacement-pressure models were developed for each variant across all the studied strain-pressure regions, enabling future design variation studies for soft robots that use actuators as structures.

A Novel Computer-Controlled Maskless Fabrication Process for Pneumatic Soft Actuators

Template-based and additive manufacturing techniques have demonstrated some fabrication routes for creating pneumatic soft actuators. However, as the complexity and capability of the actuators continue to develop, the limitations of these approaches are becoming evident. These include difficulties for design variations, process speed and resolution, material compatibility and scalability, which hinder and restrict both the possible capabilities of the technology and its transition from research to industry. This body of work presents a computer-controlled, maskless manufacturing process with a different approach to allow for high-speed, low-cost and flexible creation of pneumatic soft actuation networks comprising multi-material construction. This was investigated through a bespoke fabrication platform that provides computer-controlled localised plasma treatment to selectively modify the chemical behaviour on the surface of silicone and polyethylene terephthalate (PET) bodies. The altered surface chemistry facilitated selective bond formation between the treated parts of the surface and, consequently, greater design variation and control over the pneumatic chambers that were formed. Selective treatment patterns allowed nonlinear pneumatic chamber designs to be created, and the strength of bonded silicone structures was shown to facilitate large deformations in the actuators. Furthermore, the different interactions between the plasma and silicone were leveraged to achieve feature sizes of <1 mm and treatment speeds of 20 mm2 per second of exposure. Two multi-material pneumatic soft actuators were then fabricated to demonstrate the potential of the platform as an automated manufacturing route for soft actuators.

Surface Defect Detection using Novel Histogram Distance-based Multiple Template Anomalies Detection Algorithm

Surface defects in manufacturing are top challenges in various manufacturing field including LED manufacturing, die manufacturing and printing industry. Quality control through automated surface defect detection has been an emphasis to speed up the production without jeopardizing the quality of the product. However, complexity and flexibility in product design, specification and dataset availability posted challenges in existing referential-based algorithm. Golden template-based algorithms are sensitive to misalignment and product variations. Deep learning and its variant can be used as non-linear filter to segment anomalies area. However, deep learning requires huge labelled database and consume long learning time. Similarly, maximum likelihood-based algorithms require large database for learning. This research proposes a novel histogram distance based multiple templates anomalies detection (MTAD) algorithm to segment surface defect. Histogram distance based on kernel-wise histograms stacked across illumination normalized database of similar size can describe the degree of anomaly intuitively across the image. Then, surface defect can be justified intuitively according to anomaly heat map generated. The algorithm is tested against industrial samples and it can handle texture and design variation existed in the product while catching anomaly in real time. This research suggests future studies on extending dimensionality of the histogram. Suggested algorithm has wide range of application other than surface defect detection. For examples, video motion detection, decolorization detection on industrial lighting.

Design Variation of a Dual-Antigen Liposomal Vaccine Carrier System

The enclosed work focuses on the construction variables associated with a dual-antigen liposomal carrier, delivering encapsulated polysaccharides and surface-localized proteins, which served as a vaccine delivery device effective against pneumococcal disease. Here, the goal was to better characterize and compare the carrier across a range of formulation steps and assessment metrics. Specifically, the vaccine carrier was subjected to new methods of liposomal formation, including alterations to the base components used for subsequent macromolecule encapsulation and surface attachment, with characterization spanning polysaccharide encapsulation, liposomal size and charge, and surface protein localization. Results demonstrate variations across the liposomal constructs comprised two means of surface-localizing proteins (either via metal or biological affinity). In general, final liposomal constructs demonstrated a size and zeta potential range of approximately 50 to 600 nm and −4 to −41 mV, respectively, while demonstrating at least 60% polysaccharide encapsulation efficiency and 60% protein surface localization for top-performing liposomal carrier constructs. The results, thus, indicate that multiple formulations could serve in support of vaccination studies, and that the selection of a suitable final delivery system would be dictated by preferences or requirements linked to target antigens and/or regulatory demands.