Light scattering is a fundamental property that can be exploited to create essential devices such as particle analysers. The most common particle size analyser relies on measuring the angle-dependent diffracted light from a sample illuminated by a laser beam. Compared to other non-light-based counterparts, such a laser diffraction scheme offers precision, but it does so at the expense of size, complexity and cost. In this paper, we introduce the concept of a new particle size analyser in a collimated beam configuration using a consumer electronic camera and machine learning. The key novelty is a small form factor angular spatial filter that allows for the collection of light scattered by the particles up to predefined discrete angles. The filter is combined with a light-emitting diode and a complementary metal-oxide-semiconductor image sensor array to acquire angularly resolved scattering images. From these images, a machine learning model predicts the volume median diameter of the particles. To validate the proposed device, glass beads with diameters ranging from 13 to 125 µm were measured in suspension at several concentrations. We were able to correct for multiple scattering effects and predict the particle size with mean absolute percentage errors of 5.09% and 2.5% for the cases without and with concentration as an input parameter, respectively. When only spherical particles were analysed, the former error was significantly reduced (0.72%). Given that it is compact (on the order of ten cm) and built with low-cost consumer electronics, the newly designed particle size analyser has significant potential for use outside a standard laboratory, for example, in online and in-line industrial process monitoring.
MULTIFILE
Stormwaters, flowing into storm sewers, are known to significantly increase the annual pollutant loads entering urban receiving waters and this results in significant degradation of the receiving water quality. Knowledge of the characteristics of stormwater pollution enables urban planners to incorporate the most appropriate stormwater management strategies to mitigate the effects of stormwater pollution on downstream receiving waters. This requires detailed information on stormwater quality, such as pollutant types, sediment particle size distributions, and how soluble pollutants and heavy metals attach themselves to sediment particles. This study monitored stormwater pollution levels at over 150 locations throughout the Netherlands. The monitoring has been ongoing for nearly 15 years and a total of 7,652 individual events have been monitored to date. This makes the database the largest stormwater quality database in Europe. The study compared the results to those presented in contemporary international stormwater quality research literature. The study found that the pollution levels at many of the Dutch test sites did not meet the requirements of the European Water Framework Directive (WFD) and Dutch Water Quality Standards. Results of the study are presented and recommendations are made on how to improve water quality with the implementation of Sustainable Urban Drainage Systems (SUDS) devices.
DOCUMENT
A local operating theater ventilation device to specifically ventilate the wound area has been developed and investigated. The ventilation device is combined with a blanket which lies over the patient during the operation. Two configurations were studied: Configuration 1 where HEPA-filtered air was supplied around and parallel to the wound area and Configuration 2 where HEPA-filtered air was supplied from the top surface of the blanket, perpendicular to the wound area. A similar approach is investigated in parallel for an instrument table. The objective of the study was to verify the effectiveness of the local device. Prototype solutions developed were studied experimentally (laboratory) and numerically (CFD) in a simplified setup, followed by experimental assessment in a full scale mock-up. Isothermal as well as non-isothermal conditions were analyzed. Particle concentrations obtained in proposed solutions were compared to the concentration without local ventilation. The analysis procedure followed current national guidelines for the assessment of operating theater ventilation systems, which focus on small particles (<10 mm). The results show that the local system can provide better air quality conditions near the wound area compared to a theoretical mixing situation (proof-of-principle). It cannot yet replace the standard unidirectional downflow systems as found for ultraclean operating theater conditions. It does, however, show potential for application in temporary and emergency operating theaters
DOCUMENT
Thermal disinfection is probably the oldest water treatment method ever used. Similarly to other disinfection processes, it targets the inactivation of pathogenic (micro)organisms present in water, wastewater and other media. In this work, a pilot-scale continuous-flow thermal disinfection system was investigated using highly contaminated hospital wastewater as influent without any pre-treatment step for turbidity removal. The results proved that the tested system can be used with influent turbidity as high as 100 NTU and still provide up to log 8 microbial inactivation. Further results have shown energy consumption comparable to other commercially available thermal disinfection systems and relatively low influence on the investigated physical–chemical parameters.
DOCUMENT
Introducing a hyperbolic vortex into a showerhead is a possibility to achieve higher spray velocities for a given discharge without reducing the nozzle diameter. Due to the introduction of air bubbles into the water by the vortex, the spray is pushed from a transition (dripping faucet) regime into a jetting regime, which results in higher droplet and jet velocities using the same nozzle diameter and throughput. The same droplet and jet diameters were realized compared to a showerhead without a vortex. Assuming that the satisfaction of a shower experience is largely dependent on the droplet size and velocity, the implementation of a vortex in the showerhead could provide the same shower experience with 14% less water consumption compared to the normal showerhead. A full optical and physical analysis was presented, and the important chemical parameters were investigated.
DOCUMENT
The use of machine learning in embedded systems is an interesting topic, especially with the growth in popularity of the Internet of Things (IoT). The capacity of a system, such as a robot, to self-localize, is a fundamental skill for its navigation and decision-making processes. This work focuses on the feasibility of using machine learning in a Raspberry Pi 4 Model B, solving the localization problem using images and fiducial markers (ArUco markers) in the context of the RobotAtFactory 4.0 competition. The approaches were validated using a realistically simulated scenario. Three algorithms were tested, and all were shown to be a good solution for a limited amount of data. Results also show that when the amount of data grows, only Multi-Layer Perception (MLP) is feasible for the embedded application due to the required training time and the resulting size of the model.
DOCUMENT
We present a simple analytical formalism based on the Lorentz-Scherrer equation and Bernoulli statistics for estimating the fraction of crystallites (and the associated uncertainty parameters) contributing to all finite Bragg peaks of a typical powder pattern obtained from a static polycrystalline sample. We test and validate this formalism using numerical simulations, and show that they can be applied to experiments using monochromatic or polychromatic (pink-beam) radiation. Our results show that enhancing the sampling efficiency of a given powder diffraction experiment for such samples requires optimizing the sum of the multiplicities of reflections included in the pattern along with the wavelength used in acquiring the pattern. Utilizing these equations in planning powder diffraction experiments for sampling efficiency is also discussed.
DOCUMENT
Background: Particulate matter (PM) exposure is an important health risk, both in daily life and in the workplace. It causes respiratory and cardiovascular diseases and results in 800,000 premature deaths per year worldwide. In earlier research, we assessed workers’ information needs regarding workplace PM exposure, the properties and effects of PM, and the rationale behind various means of protection. We also concluded that workers do not always receive appropriate risk communication tools with regards to PM, and that their PM knowledge appears to be fragmented and incomplete. Methods: We considered several concepts for use as an educational material based on evaluation criteria: ease of use, costs, appropriateness for target audiences and goals, interactivity, implementation issues, novelty, and speed. We decided to develop an educational folder, which can be used to inform employees about the properties, effects and prevention methods concerning PM. Furthermore, we decided on a test setup of a more interactive way of visualisation of exposure to PM by means of exposimeters. For the development of the folder, we based the information needs on our earlier mental models-based research. We adjusted the folder based on the results of ten semi-structured interviews evaluating its usability. Results: The semi-structured interviews yielded commentaries and suggestions for further improvement, which resulted in a number of alterations to the folder. However, in most cases the folder was deemed satisfactory. Conclusion: Based on this study, the folder we developed is suitable for a larger-scale experiment and a practical test. Further research is needed to investigate the efficacy of the folder and the application of the exposimeter in a PM risk communication system.
DOCUMENT
In order to gain a more mature share in the future energy supply, green gas supply chains face some interesting challenges. In this thesis green gas supply chains, based on codigestion of cow manure and maize, are considered. The produced biogas is upgraded to natural gas quality and injected into the existing distribution gas grid and thus replacing natural gas. Literature research showed that relatively much attention has been paid up to now to elements of such supply chains. Research into digestion technology, agricultural aspects of (energy) crops and logistics of biomass are examples of this. This knowledge is indispensable, but how this knowledge should be combined to help understand how future green gas systems may look like, remains a white spot in the current knowledge. This thesis is an effort to fill this gap. A practical but sound way of modeling green gassupply chains was developed, taking costs and sustainability criteria into account. The way such supply chains can deal with season dependent gas demand was also investigated. This research was further expanded into a geographical model to simulate several degrees of natural gas replacement by green gas. Finally, ways to optimize green gas supply chains in terms of energy efficiency and greenhouse gas reduction were explored.
DOCUMENT
Atherosclerosis is the development of lipid-laden plaques in arteries and is nowadays considered as an inflammatory disease. It has been shown that high doses of ionizing radiation, as used in radiotherapy, can increase the risk of development or progression of atherosclerosis. To elucidate the effects of radiation on atherosclerosis, we propose a mathematical model to describe radiation-promoted plaque evelopment. This model distinguishes itself from other models by combining plaque initiation and plaque growth, and by incorporating information from biological experiments. It is based on two consecutive processes: a probabilistic dose-dependent plaque initiation process, followed by deterministic plaque growth.
DOCUMENT
