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Multi-waypoint global path planning for unmanned surface vehicles in confined environments
No full textMotivated by the SeaClear2.0 Project's aim to clean ports and coastal areas using aerial and marine robotics, this work focuses on the reference generation for autopilots of Uncrewed Surface Vehicles (USVs) deployed in confined areas, such as, rivers, channels, ports or harbours. In the envisioned scenario, a USV must navigate through multiple waypoints, which roughly sketch the intended route. The planned route is based on available chart data and doesn't take in consideration optimality of the route or uncharted obstacles. The study implements a global path planner consisting in an A*algorithm, extendable via Genetic Algorithm (GA), for particular scenarios, where the order of the given waypoints is not enforced. In addition, a kinematics-based path planner using the Line-of-Sight (LoS) algorithm is developed for creating the reference vector for the USV control system. The global path planner and LoS algorithms are tested both in simulation and in sea trials, using a medium-sized USV. For the simulation environment, a digital twin of the USV is used. The sea trials validate the concept in a representative environment. The entire software solution is developed under Robot Operating System 2 (ROS2) framework and implements Guidance Navigation and Control (GNC) architecture, commonly used for autonomous navigation of USVs. The global path planning algorithm efficiently handles multi-waypoint selection and finds the shortest path between each two waypoints while avoiding known static obstacles. Additionally, the LoS algorithm generates reliable references for the vessel's autopilot. The novelty of the proposed solution consists in the usage of meta-heuristic algorithms for solving a discrete optimisation problem and in the integration of nautical chart data within the global path planner. The paper highlights the potential of the robotic solution for maritime applications, beyond the chosen scenario, when coupled with a complete GNC solution
Hydropeaking remediation: stranding tests with trout larvae from natural reproduction and recommendations for the planning of remediation measures
No full textDer Fachtext beschäftigt sich mit der Strandungsproblematik von Fischen infolge von Schwall-Sunk-Ereignissen in Gewässern. Im Mittelpunkt stehen Strandungsversuche mit Forellenlarven aus natürlicher Reproduktion, die in einem freien Fließgewässer durchgeführt wurden. Diese Versuche zielten darauf ab, das Strandungsrisiko unter verschiedenen Bedingungen zu untersuchen und Empfehlungen für die Planung von Sanierungsmaßnahmen zu geben. Die Ergebnisse zeigen, dass das Strandungsrisiko stark von der Pegelrückgangsrate und der Größe der Wasserwechselzone abhängt. Besonders interessant ist die Beobachtung, dass das Strandungsrisiko auf den ersten drei Metern der Wasserwechselzone deutlich zunimmt. Die Versuche liefern wertvolle Daten für die Modellierung natürlicher Abflussbedingungen und unterstreichen die Bedeutung einer genauen Kenntnis der Emergenzzeiträume von Forellenlarven für erfolgreiche Sanierungsmaßnahmen
Hybrid optimization methodologies for the design of chemical processes
No full textProcess synthesis and design problems in chemical engineering usually require a solution to complex nonlinear optimization problems with continuous and discrete decision variables. The resulting mixed-integer nonlinear programming problems are particularly hard to solve, and different strategies are frequently applied for their solution. Gradient-based optimization enables fast computations, exploiting local sensitivity information, but is usually limited to local optima for nonconvex problems, whereas derivative- free optimization methods can be linked to available simulation models, with little effort, but also without any guarantee of optimality. Metaheuristics, especially swarm intelligence and population-based algorithms, are frequently applied for simulation-based process optimization, overcoming the lack of gradient information, at the cost of a considerable number of simulations. Another strategy that is receiving increasing interest builds on surrogate models that are first generated based on an initial sampling of process simulations for systematically varied design variables. Tractable surrogate models do provide the necessary sensitivity information that enables efficient gradient-based optimization, while being only an approximation of the original problem. Each strategy has its advantages and limitations, and no single best option is generally favorable for all kinds of problems. Thoughtful combinations of different strategies have the potential to overcome or at least reduce the individual limitations, while simultaneously combining the strengths of the individual methods. The current chapter provides an introduction and overview of such hybrid optimization methodologies, together with some illustrations of their use for applications in chemical engineering. Several case studies, including utility and entrainer selection, illustrate the performance of hybrid optimization methods and indicate the ability to solve even more complex design problems
Stability and interaction effects of grid-forming virtual synchronous machines within an IEEE 9-bus system
No full textThe transition to converter-interfaced generation presents new challenges for maintaining power system stability. Stability problems can be caused by interactions induced by converter controls. This paper examines the impact of different grid-forming (GFM) virtual synchronous machine (VSMs) designs on the stability and interactions within an IEEE 9-Bus benchmark system, comprising two voltage source converters (VSCs) and a Thévenin equivalent. A mathematical representation of the system enables eigenvalue and participation factor analyses, offering deeper insights into the causes of interactions and stability issues.The small-signal stability analyses reveal that VSMs based on the Current-Controlled Quasi-Stationary Electrical Model (CC-QSEM) are prone to instability in weak grid conditions due to interactions with current and grid states. In contrast, VSMs using the Transient Virtual Resistor (TVR) design exhibit greater robustness and reduced sensitivity of the eigenvalue movement to varying grid strengths. Nonlinear time-domain simulations confirm these findings, highlighting the importance of virtual impedance configuration in enhancing system robustness.This paper provides recommendations for selecting VSM strategies to improve stability across a range of operating conditions. Furthermore, it highlights the necessity of considering a minimum of two converters to take interactions between the converters into account
Design of surgical impaction instruments matters
No full textBackground: Femoral stem impaction in total hip arthroplasty is commonly performed by mallet blows on a metal impactor attached to the stem. Factors including the surgeon, the impactor, and the patient can influence the impaction. A wide range of impactors, varying in design and thus in mass and stiffness, are available. However, little is known about their influence on the force transmission and, consequently, about the proportion of the mallet force that ultimately reaches the implant. This study aimed to investigate the force transmission through the impactor for different impactor designs, while investigating different patient-specific femur-tissue systems in situ and in silico. Methods: The mallet and impactor forces of 9 consecutive blows on seated femoral stems were measured for 2 different approaches on each of 4 cadavers. The mallet-implant force transmission was calculated using a phenomenological model for 2 different impactor designs. Results: The attenuated force in the impactor achieved approximately 65% to 75% of the corresponding mallet peak force, regardless of cadaver or surgical approach. Measuring the force distant from the tip resulted in an overestimation of the transferred forces. Depending on impactor design just 24% to 47% of the applied mallet peak force reached the implant itself. Conclusions: The force transmission for overcritical mallet blows can be regarded as independent from patient- and approach-specific boundary conditions and primarily dependent on the impactor design. Surgeons must be aware of this relationship and exercise caution when using other or novel instruments to prevent intraoperative complications
Efficient optical coating design using an autoencoder-based neural network model
No full textOptical thin-film coatings are integral to modern photonics and in particular to ultrafast lasers, providing precise control of dispersion and reflectivity, thus enabling tailored pulse shaping. Designing these coatings represents an inverse problem, requiring the mapping of desired optical properties to physical designs, a task that poses major challenges for traditional heuristic methods, which often rely on time-consuming, expert-guided iteration and can be constrained by the choice of an initial starting point. Here, we present an artificial intelligence (AI) framework for optical thin-film coating design that accelerates the design process, achieving excellent performance characteristics without expert intervention. We discuss our AI approach and demonstrate the capabilities of our algorithm by designing a complex broadband high-reflectivity mirror with state-of-the-art performance characteristics including a group delay dispersion covering a spectral range of 940 nm to 1120 nm
A comprehensive approach to incorporating intermolecular dispersion into the openCOSMO-RS model. Part 2: atomic polarizabilities
No full textOpenCOSMO-RS is an open-source predictive thermodynamic model that can be applied to a broad range of systems in various chemical and biochemical engineering domains. This study focuses on improving openCOSMO-RS by introducing a new dispersion term based on atomic polarizabilities. We evaluate different methods for processing polarizability data, including scaling and combining it to compute segment-segment dispersion interaction energies, with a focus on halocarbon systems. The results demonstrate that the modified model outperforms our previous method developed in the first part of this work Grigorash et al. (2024), while at the same time requiring fewer adjustable parameters. The approach was applied to a broad dataset of over 50,000 data points, consistently increasing the accuracy across a variety of data types. These findings suggest that atomic polarizability is a valuable descriptor for refining dispersion interactions in predictive thermodynamic models
Assessment of low impact development strategies with multi-scale, multi-criteria decision making approaches for urban flood resilience
No full textUrbanization exacerbates runoff, peak flow unpredictability, deterioration of water quality, and the Urban Heat Island Effect. Low-income, flood-prone areas are disproportionately impacted by weak governance and inadequate infrastructure. All of which influence water, energy, and equality balance. As preventing urban development is unfeasible, Low Impact Development (LID) provides a viable alternative. We offer a multi-scale framework that incorporates LID solutions for stormwater management in Ankara, Türkiye; therefore, filling the gap in holistic, multidisciplinary, and multiscale approaches via engineering and urban planner perspectives. Our framework contains: (i) Multi-Criteria Decision Making (MCDM)-Driven Pixel Scale Analysis of WorldView-4 images to create Land Use Land Cover (LULC) data using Random Forest (81.34% accuracy) on Google Earth Engine and SRTM-based slope and flow accumulation data. Using expert opinion and literature, we created and scored criteria matrices for LULC, slope, flow accumulation, and cost. This resulted in detailed LID suitability maps via the MCDM algorithm by the R programming language. (ii) Expert-Driven Neighborhood Scale Analysis for prioritization of LID based on urban parameters such as slope, surface morphology, population density, impervious surfaces, road networks, and runoff hotspots by the junction areas that emerge from the overlapping of the areas. Bioretention cells are suggested for 42.9% of the research area, rain barrels for 19.6%, and vegetative filter strips for 1.4%. Expert-Driven analysis facilitates prioritizing, whereas MCDM-Driven analysis gives pixel-level LID placement recommendations. This scalable, multidisciplinary framework provides a solid model for urban water management that may influence urban planners and policymakers in Ankara and other cities throughout the world
Applications and architecture for UWB localization in aircraft cabins and aviation
No full textObtaining data from real-time location systems (RTLS) is critical in aviation for enhancing operational workflows, reliability, and passenger services. For example, applications such as wheelchair tracking, baggage management, seat-specific service delivery, and equipment monitoring require accurate and continuous positioning information within both aircraft cabins and airport terminals. Ultra-Wideband (UWB) technology, characterized by high accuracy for indoor localization, low latency and robustness against interference, can be employed to address these needs. This paper presents a platform architecture utilizing UWB localization that can be integrated into the cabin and can be certified in accordance with aviation regulations to support various applications on ground and in-flight. The architecture comprises modular edge cloud systems deployed across aircraft and ground environment, interconnected to enable efficient data exchange and hosting of location-based services. The onboard system integrates the ARINC 853 Cabin Secure Media-Independent Messaging (CSMIM) standard to ensure secure and standardized communication of localization data across the cabin network. The overall UWB RTLS is based on Kubernetes edge cloud platforms enabling the deployment and management of various location-based applications. Secure communication between aircraft and ground edge clouds is maintained through a virtual private network (VPN). Exemplary use cases include wheelchair tracking across airport and cabin environment and passenger-tailored onboard services such as meal ordering and serving tied to seat localization. The presented system and architecture support improvements in process efficiency and the delivery of personalized services, contributing to a unified, data-driven and smart aviation ecosystem