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Frost/Defrost Models for Air-Source Heat Pumps with Retained Water Refreezing Considered
Get PDFCyclic frosting and defrosting operations constitute acommon characteristic of air-source heat pumps in coldclimates during winter. Simulation models that can capturesimultaneous heat and mass transfer phenomena associatedwith frost/defrost behaviors and their impact on theoverall heat pump system performance are of criticalimportance to improved controls of heat delivery and frostmitigation. This paper presents a novel frost formulationusing an enthalpy method to systematically capture allphase-change behaviors including frost formation andmelting, retained water refreezing and melting, and waterdrainage during cyclic frosting and defrosting operations.A Fuzzy modeling approach is proposed to smoothly switchsource terms when evaluating the dynamics of frost andwater mediums for numerical robustness. The proposedfrost/defrost model is incorporated into a flat-tubeoutdoor heat exchanger model of an automotive heat pumpsystem model to investigate system responses under cyclicoperations of frosting and reverse-cycle defrosting
Direct Ammonia Solid Oxide Fuel Cell Stack: Modelling and Experimental Validation
Get PDFInterest in ammonia as an energy carrier is growing due toits superior storage and transport properties compared tohydrogen. The objective of this work is to construct auseful tool for predicting the behavior of a solid oxidefuel cell (SOFC) stack fed directly with ammonia. Thisconfiguration is particularly interesting because theinternal cracking of ammonia eliminates the need for anexternal cracker, thus reducing the overall cost of thesystem. The ammonia decomposition reaction was implementedin the anode channel of the stack and calibrated againstliterature results. The model was then validated in theohmic region only by calculating the area specificresistance (ASR) and comparing the results withexperimental data collected at the Bruno Kessler Foundation(FBK) laboratory. This SOFC model can therefore be used asa starting point for the analysis of a scale-up application
Model-Based Control Design for a Multi-Stacks SOC System
Get PDFIn response to growing interest in high-temperatureelectrolysis, CEA-Liten has developed multi-stack SolidOxide Cell (SOC) testing equipment comprising fourelectrolyser stacks. Each stack includes multiple cells,and together they form a module housed within a sharedthermal enclosure and connected to a balance of plant. Thissetup supports the development of innovative controlstrategies, essential due to the stacks’ sensitivity tooperating conditions. To mitigate risks and costsassociated with testing new strategies directly on thephysical system, a Model in the Loop approach wasimplemented. The model replicates the real module’scharacteristics and operational capabilities, allowing safeand efficient design and validation of control strategies.Various transition scenarios between operatingconditions—tailored to diverse production needs andconstraints—were developed and validated using the modelbefore real-world implementation. This paper presents themodel-based control methodology and compares experimentalresults with simulations
Yet Another Residential District Simulator: yards for Controller Development in the Residential Built Environment
Get PDFInnovation in residential energy systems drives researchefforts towards novel building and district controlstrategies. Development and testing of such strategiesrequires advanced, interactive building and districtsimulators. This paper presents yards, an interactivesimulator that combines the modelling capabilities ofModelica with a language-agnostic and cross-platforminterface for controller development. yards offersmodelling flexibility beyond that of existing tools, as anycustom, user-provided building or district model can beimplemented easily. A case study demonstrates how yards canbe used to simulate a tiny cluster of buildings
Facilitating the use of Physics-Based Simulations on Embedded Devices by running FMUs from MicroPython
Get PDFPhysics-based simulations (PBS) are increasingly valuablefor real-time applications in embedded systems, yetintegrating them on resource-constrained devices remainschallenging. This paper presents ufmu, a lightweightframework that enables execution of FMI 2.0-compliantFunctional Mock-up Units (FMUs) within the MicroPythonenvironment, targeting platforms such as the ESP32. Theproposed approach translates FMU model descriptions into Cstructures, integrates them into MicroPython firmware, andexposes a minimal Python API for simulation control,enabling model-based computations on-device without clouddependencies. We evaluate the framework using a standardFMU model, comparing performance across ESP32, Unix, andplain C environments in terms of memory usage, executiontime, and firmware size. Despite the ESP32's hardwarelimitations, the results demonstrate that meaningfulsimulations can be achieved efficiently, with minimalmemory overhead. All code, documentation, and experimentinstructions are freely available under an MIT license,supporting reproducibility and adoption in education,prototyping, and embedded research.This work also lays the foundation for future integrationwith eFMI and the FMI 3.0 standard
Modeling Fuel Cell Electric Vehicle for Performance Prediction and Optimal Component Selection
Get PDFThis study involves modeling and simulating a Fuel Cell Electric Vehicle (FCEV) to predict whether it meets the target performance requirements. The FCEV model includes an electrified powertrain, composed of a hydrogen fuel cell, motor, battery, and controller, along with a chassis model. A test environment was also modeled to evaluate these components. Different combinations of chassis and motor candidates were examined to predict vehicle performance for each configuration and determine if the target requirements were met. The results of this study served as a reference for selecting optimal components during the development process
Airport electrification and electromagnetic emissions – standards and challenges
Get PDFThe growing demand for electrification increases the likelihood of airport system interferencecaused by electromagnetic emissions. Studies have shown that equipment, installations, andvehicles (including trains, cars, and aircraft) may exceed emissions limits established by manyairports. While minor airport system disruptions, such as radio noise squelch, have been presentfor years, rising emissions may pose risks to critical radio communication and navigationsystems potentially leading to severe consequences.
This work provides an overview of airport-related electromagnetic emission standards, comparingproduct-specific standards with current airport emission regulations. The analysisevaluates emission limits across various standards, emphasizing measurement methods, such asdistance, bandwidth, and detectors, alongside their underlying principles. The paper outlineskey challenges which may impact airport operations as electrification expands within both theairport environment and aircraft themselves.
Results highlight the complexity of diverse airport environments, showing that a single standardacross an entire airport is impractical. Some equipment will inevitably produce emissions,making product (family) standards, which are hierarchically superior to generic ones, a priority.Notably, road vehicles, high-power equipment and electronic discharge machining productsmay emit significantly more than current regulations permit. Furthermore do preliminarymeasurements indicate that electrically propelled aircraft, airport installations and ground powerunits generate substantial emissions, with high likelihood exceeding defined limits.
Overall, the findings presented indicate that further investigations are relevant for standardisation,its implementation, and the impact of emissions from various sources on airport operations
Quantum-Enhanced Predictive Maintenance for Aerospace Robotic Arms
No full textThe integration of quantum computing and neural networks has emerged as a transformative approach for addressing complex industrial challenges, particularly in predictive maintenance.This paper is the result of insights gained during the development of a Proof of Concept (PoC) in collaboration with Embraer, a leading aerospace company in Brazil, and SENAI UpLab, an innovation and technology hub of SENAI, one of Brazil’s foremost institutions for industrial education and applied research. Traditional predictive maintenance methods often struggle with the high-dimensional data and complex failure patterns inherent in aerospace systems. Leveraging the principles of quantum mechanics, QNNs and QSVCs offer enhanced computational power and the ability to process vast datasets exponentially faster than classical machine learning approaches. We propose a novel hybrid framework that combines QNNs and QSVCs, utilizing quantum superposition, entanglement, and kernel-based quantum algorithms to model the degradation patterns of robotic arm components. This enables early detection of potential failures and optimizes maintenance schedules with improved accuracy. The framework is validated using real-world data from aerospace robotic systems provided by EMBRAER, demonstrating superior performance in terms of accuracy, efficiency, and robustness compared to classical machine learning methods. Our results, supported by the collaboration with SENAI UpLab, highlight the potential of quantum-enhanced techniques, including QNNs and QSVCs, to revolutionize predictive maintenance in the aerospace industry, reducing downtime, minimizing costs, and enhancing operational safety. This study contributes to the growing body of research at the intersection of quantum computing and industrial applications, paving the way for future advancements in intelligent maintenance systems
Impact of HUD Design on Cognitive Load in UAV Control
Get PDFThis study analyzes the influence of mental workload on physiology of 24 individuals with flight deck experience during a remote control of an uncrewed aerial vehicle (UAV). The UAV operates without line-of-sight communication, so any command given by the pilot has a two-second delay due to the satellite link. To assist the pilot, two flight data display interfaces (HUDs) were developed. During the simulation, physiological responses were monitored using electrodermal activity (EDA) sensors, electrocardiograms (ECG) and eye tracking. Besides the physiological data, the research also uses subjective workload assessments such as the NASA Task Load Index (NASA-TLX), the Subjective Workload Dominance technique (SWORD), and the Instantaneous Self-Assessment (ISA). Results indicated that designed HUDs influenced cognitive load and flight accuracy leading to lower workload and performance improvement. These results highlight the need for more adaptable interfaces. As a future perspective, the usage of adaptive operator support systems is recommended, adjusting interfaces and automation levels according to the user’s cognitive state, enabling a more efficient and safer interaction with advanced aviation systems
XSL-HoReCo and GoSt-ParC-Sign: Two New Signed Language - Written Language Parallel Corpora
Get PDFDevelopments in language technology targeting signed languages are lagging behind in comparison to the advances related to what is available for so-called spoken languages.1 This is partly due to the scarcity of good quality signed language data, including good quality parallel corpora of signed and spoken languages. This paper introduces two parallel corpora which aim at reducing the gap between signed and spoken-only language technology: The XSL Hotel Review Corpus (XSL-HoReCo) and the Gold Standard Parallel Corpus of Signed and Spoken Language (GoSt-ParC-Sign). Both corpora are available through the CLARIN infrastructure