In order to apply smart charging it is key to be able to forecast the connection and charging time of charging sessions at the start of the connection. For, if you know how long a session will last, one can assign an appropriate smart charging strategy for that session. For instance by postponing the charging to a moment with lower energy prices or more renewable energy generation. This study presents the work of SIMULAAD in predicting charging and connection times.
Traditional IMU based PDR systems suffer from rapidly growing drift effects due to the inherent bias of the inertial sensor. Many existing solutions to mitigate this problem use aiding sensors or information as heuristics or map data. We propose a new optimization framework to solve the PDR estimation problem where the sensors biases are explicitly included as state variables and therefore be used to correct for bias effects in the PDR. By using a smoothing approach and exploiting the rigid structure of a MIMU array one can solve for the slowly varying sensor biases. This paper presents the method and gives an exemplary result of a walking trial. Good agreements in the position and orientation with an optical reference system were found. Moreover, accelerometer and gyroscope biases could be estimated accordingly. Further research includes the performance of more experiments under various conditions such that a more quantitative evaluation can be obtained. In addition, an exploration of a (pseudo) realtime filter version would be valuable such that the system can be applied online.
MULTIFILE
For long flights, the cruise is the longest phase and where the largest amount of fuel is consumed. An in-cruise optimization method has been implemented to calculate the optimal trajectory that reduces the flight cost. A three-dimensional grid has been created, coupling lateral navigation and vertical navigation profiles. With a dynamic analysis of the wind, the aircraft can perform a horizontal deviation or change altitudes via step climbs to reduce fuel consumption. As the number of waypoints and possible step climbs is increased, the number of flight trajectories increases exponentially; thus, a genetic algorithm has been implemented to reduce the total number of calculated trajectories compared to an exhaustive search. The aircraft’s model has been obtained from a performance database, which is currently used in the commercial flight management system studied in this paper. A 5% average flight cost reduction has been obtained.
MULTIFILE
Mycelium biocomposites (MBCs) are a fairly new group of materials. MBCs are non-toxic and carbon-neutral cutting-edge circular materials obtained from agricultural residues and fungal mycelium, the vegetative part of fungi. Growing within days without complex processes, they offer versatile and effective solutions for diverse applications thanks to their customizable textures and characteristics achieved through controlled environmental conditions. This project involves a collaboration between MNEXT and First Circular Insulation (FC-I) to tackle challenges in MBC manufacturing, particularly the extended time and energy-intensive nature of the fungal incubation and drying phases. FC-I proposes an innovative deactivation method involving electrical discharges to expedite these processes, currently awaiting patent approval. However, a critical gap in scientific validation prompts the partnership with MNEXT, leveraging their expertise in mycelium research and MBCs. The research project centers on evaluating the efficacy of the innovative mycelium growth deactivation strategy proposed by FC-I. This one-year endeavor permits a thorough investigation, implementation, and validation of potential solutions, specifically targeting issues related to fungal regrowth and the preservation of sustained material properties. The collaboration synergizes academic and industrial expertise, with the dual purpose of achieving immediate project objectives and establishing a foundation for future advancements in mycelium materials.
Nano and micro polymeric particles (NMPs) are a point of concern by environmentalists and toxicologist for the past years. Their presence has been detected in many environmental bodies and even in more recently human blood as well. One of the most common paths these particles take to enter living organisms is via water consumption. However, despite the efforts of different academic and other knowledge groups, there is no consensus about standards methods which can be used to qualifying and quantifying these particles, especially the submicrometric ones. Many different techniques have been proposed like field flow fractionation (FFF) followed by multi angle laser scattering (MALS), pyrolysis-GC and scanning electron microscopy (SEM). Additionally, the sampling collection and preparation is also considered a difficult step, as such particles are mostly present in very low concentration. Nanocatcher proposes the use of submerged drones as a sampling collection tool to monitor the presence of submicrometric polymeric particles in water bodies. The sample collections will be done using special membrane systems specially designed for the drone. After collected, the samples will be analysed using FFF+MALS, SEM and Py-GC. If proven successful, the use of submerged drones can strongly facilitate sampling and mapping of submicrometric polymeric particles in water bodies and will provide an extensive and comprehensive map of the presence of these particles in such environment.
To optimize patient care, it is vital to prevent infections in healthcare facilities. In this respect, the increasing prevalence of antibiotic-resistant bacterial strains threatens public healthcare. Current gold standard techniques are based on classical microbiological assays that are time consuming and need complex expensive lab environments. This limits their use for high throughput bacterial screening to perform optimal hygiene control. The infection prevention workers in hospitals and elderly nursing homes underline the urgency of a point-of-care tool that is able to detect bacterial loads on-site in a fast, precise and reliable manner while remaining with the available budgets. The aim of this proposal titled SURFSCAN is to develop a novel point-of-care tool for bacterial load screening on various surfaces throughout the daily routine of professionals in healthcare facilities. Given the expertise of the consortium partners, the point-of-care tool will be based on a biomimetic sensor combining surface imprinted polymers (SIPs), that act as synthetic bacterial receptors, with a thermal read-out strategy for detection. The functionality and performance of this biomimetic sensor has been shown in lab conditions and published in peer reviewed journals. Within this proposal, key elements will be optimized to translate the proof of principle concept into a complete clinical prototype for on-site application. These elements are essential for final implementation of the device as a screening and assessment tool for scanning bacterial loads on surfaces by hospital professionals. The research project offers a unique collaboration among different end-users (hospitals and SMEs), and knowledge institutions (Zuyd University of Applied Sciences, Fontys University of Applied Sciences and Maastricht Science Programme, IDEE-Maastricht University), which guarantees transfer of fundamental knowledge to the market and end-user needs.
