Linköping Electronic Conference Proceedings
Not a member yet
1113 research outputs found
Sort by
A New Multi-Agent Simulator Framework Using Hopsan and Unreal 5.3
Get PDFUnmanned Aircraft Systems (UAS) research increasingly requires high-performance, multi-agent simulation environments that integrate realistic dynamics with immersive visualization. This paper introduces a distributed co-simulation framework that seamlessly combines the dynamic modeling capabilities of Hopsan with the advanced rendering and interaction tools of Unreal Engine 5.3. Communication between the two platforms is achieved through a lightweight, User Datagram Protocol (UDP) based plugin, which supports bi-directional real-time data exchange and is complemented by a USB Raw Input plugin to integrate human-in-the-loop joystick control. The proposed framework was validated across progressively complex scenarios. First, a single F‑16 aircraft data model was imported from Hopsan, encompassing waypoint-guided dynamics, atmospheric effects, actuation, and geoid-based altitude calibration. Its state reinforced by Hopsan was visualized in Unreal in real-time. Second, the platform was extended to support two independent F‑16 agents, each communicating via dedicated UDP ports, thereby demonstrating modular, scalable, multi-agent operation. Third, we introduced a Human Machine Interface (HMI) scenario, where one aircraft was piloted manually via joystick input, while the second autonomously followed the same waypoint sequence. This validated the framework’s capacity to handle human interaction in a multi-agent context. Results evidence synchronized simulation at real-time performance, accurate environmental interactions (terrain, wind, collision), and reliable human-in-the-loop control. The framework’s architecture promotes modularity, scalability, and deployment flexibility across multiple machines. Future enhancements will explore tighter coupling with Unreal’s environmental physics, adoption of fluid dynamics, and scaling to larger agent ensembles. By integrating open-source dynamical modeling with high-fidelity graphical simulation, this platform offers a robust foundation for UAS mission planning, operator training, and AI-driven control validation
Dynamic modeling of a liquid piston compressor system including conjugate heat transfer
Get PDFEfficient and cost-effective hydrogen storage necessitatesquick compression across significant pressure ranges(usually up to 700 bar), while keeping heat generation to aminimum during the process. This can be achieved byimproved understanding of gas-to-wall heat transferenhancement in hydrogen compression systems, careful designand operational optimisation. In this context, the presentpaper introduces a 0D/1D lumped numerical model of a liquidpiston compressor for hydrogen applications. Heat transferis considered as (i) convective at the liquid-gasinterface, (ii) conductive within the gas volume based on a1D approach accounting for thermal stratification, and(iii) as conjugate at the gas-to-wall interface. To achievea pressure ratio of 30 (from 15 to 450) bar, at a powerdensity of approximately 65kW /m3 , the compression energycost reaches 1.85kW h/kg. Further, various standardpressure vessels materials with different thermal andmechanical properties are considered, highlighting thepotential compromise between lightweight and thermalefficiency
Technical concepts of airport infrastructure for charging battery-electric aircraft
No full textThe paper presents results from the research project “Flexible and automated aircraft charging via energy storage at airports” (FAACE), studying how airport infrastructure could be designed to meet the requirements of future aviation and propulsion technologies. The project is limited to focusing on concepts for charging battery-powered electric aircraft. As there are currently major uncertainties regarding the technical, operational and business developments in electric aviation, it is desirable to design for flexibility in the airport infrastructure.
This paper outlines the scope of the problem in terms of airport and aircraft assumptions, and proposes four different technical concept topologies for the charging infrastructure system, where some are presented with several possible variants. Some of the concept topologies explored include mobile or fixed power electronics components, as well as including possible battery storage systems, that can also be stationary or mobile. The mobile technical solutions utilize an automated vehicle that can take charging equipment and / or a battery storage unit close to the aircraft. Furthermore, we propose several evaluation criteria which are used to make a concept comparison, assuming some general characteristics of the aircraft, the airport, and their operation. These include estimates of energy efficiency, load to the electrical grid, flexibility and scalability aspects, land usage, electromagnetic interference aspects and very approximative costs.
The advantages and disadvantages of the different concepts are discussed, and we describe situations when some of these concepts would be found to be most suitable, which depends on the exact criteria prioritization from the airport perspective. The comparison is visualized by providing calculation examples.
Results show that no single concept fits all airport types; fixed infrastructure offers high efficiency but low flexibility, while mobile and hybrid solutions provide adaptability at the cost of complexity and lower efficiency. The suitability of each concept depends strongly on airport size, traffic patterns, and infrastructure priorities
Kreativt ätande: Mat och låtsaslek i förskolans måltider
Get PDFDetta är en kortare version av en artikel tidigare publicerad som: Wiggins, S., Willemsen, A., & Cromdal, J. (2023). Eating Prickly Peas: Sharing Play Worlds During Preschool Meals. International Journal of Early Childhood. https://doi.org/10.1007/s13158-023-00380-
Pipeline-Based Automated Integration and Delivery Testing of Simulation Assets with FMI/SSP in a Railway Digital Twin
Get PDFRailway infrastructure systems have recently been enhanced through the use of the digital twin (DT) concept, enabling visualization and control in a virtual environment while effectively mitigating life cycle costs. This work provides insights into the development and operations (DevOps) of a railway DT platform and highlights the automation and management of asset integration and processing based on the FMI and SSP interface standards through the use of the Continuous Integration / Continuous Delivery pipeline technology. This offers long-term durability, pausability, remote triggering, open-source and workflow design capabilities, and connectivity to other tools such as version control systems and code analysis tools. In this research paper, we present an anti-slip cosimulation model of a railway vehicle as a use case example to demonstrate the pipeline-oriented automation and management in combination with a version control system and code analysis tool within the platform
Simulation and Cost Estimation of CO2 Capture with alternatives for doubled capacity
Get PDFThis study presents a techno-economic assessment of an amine-based carbon capture technology. The aim is to compare different methods to evaluate the cost effect of doubling the capacity. A base case was established in Aspen HYSYS with 15 m absorber packing height, 6 m desorber packing height, removal efficiency of 85 % and a heat exchanger minimum temperature approach (ΔTmin) of 10 °C. Then dimensioning and cost estimation was carried out using Aspen HYSYS spreadsheets to automatically calculate CAPEX, OPEX and carbon capture cost per ton CO2 captured. To estimate the Bare Erected Cost (BEC), the Enhanced Detailed Factor (EDF) and the Aspen Process Economic Analyzer (APEA) were employed. The EDF method determines the installation cost of each piece of equipment, while the Nazir-Amini method only offers the Total Plant Cost (TPC). Applying the EDF method, the TPC for the base case, the doubled feed gas case and the two-absorber case were calculated to 76, 141 and 150 MEuro respectively. The estimated annual OPEX for the base case was 42.5 MEuro, while for the two alternatives the OPEX was very close to the double of the base case. The estimated carbon capture cost for the base case, two-absorber case, and double feed gas scenario were 52.4 €/ton, 51.8 €/ton, and 50.5 €/ton, respectively. The study demonstrates that a combination of Aspen HYSYS simulation, APEA and the EDF method is an effective method to evaluate different alternatives for increasing the capacity
Design of electrified fluidized bed calciner for direct capture of CO2 from cement raw meal
Get PDFUsing green electricity to calcine the raw materials and combining this with storage of the pure CO2 generated in the calcination process can significantly reduce CO2 emissions in the cement industry, which generates around 7 % of the global CO2 emissions.In this study, a lab-scale electrically heated fluidized bed calciner, operating with a mixture of fine meal particles and coarse inert particles, is simulated using CPFD software. The electrification of the reactor is done using several horizontal cylinders, which are electrically heated to provide energy both for heating the raw meal (with 77% CaCO3) up to the calcination temperature and for calcination (CaCO3 CaO + CO2). The reactor design is done based on a specified electrical energy input, the gas velocity required for fluidization of coarse inert particles and the velocity required for entrainment of the fine calcined particles. A fluidization velocity of 0.3 m/s appears to be optimal for the reactor, whereas 0.8 m/s resulted in complete entrainment of the bed. The maximum calcination degree achieved was 90% when operating with preheated meal. The average meal residence time was found to be 24-26 s
Phase Transformations in Steelmaking Slags: A Thermodynamic Approach
Get PDFIn addition to solidification, steelmaking slags may undergo phase transformations in solid state during their cooling process. The mineralogy of these oxide slags is significantly influenced by the chemical composition and cooling rate. For the phases forming, two distinct solidification modes can be assumed, depending on the cooling rate: equilibrium cooling and Scheil–Gulliver cooling. Characterization methods, such as scanning electron microscopy (SEM) and electron probe microanalyzer (EPMA) allow analyzing the elemental composition of individual phases. Here, computational thermodynamics were applied in phase identification of crystallized electric arc furnace (EAF) slags. FactSage 8.3 thermodynamic calculation software was used to estimate the composition of stable phases as a function of temperature. Solid solutions with varying compositions were considered in this study. The calculation results from two solidification modes, i.e., equilibrium cooling and Scheil-Gulliver cooling, were saved in Excel spreadsheets. A MATLAB script was developed to go through the results and find the phase with a composition closest to the input values. For both solidification modes, the composition and temperature best fitting the input analysis was determined. The input is the elemental composition of the phase of interest, acquired using EPMA. After the data processing, the results are visualized in graphs, illustrating the analyzed and estimated compositions of the identified solid solution phase and its occurrence temperature
Machine Learning -based Optimization of Biomass Drying Process: Application of Utilizing Data Center Excess Heat
Get PDFThe utilization of biomass as a renewable energy source holds significant promise for climate mitigation efforts. Excess heat from Nordic data centers offers opportunities for sustainable energy utilization. This research explores the feasibility of using data center excess heat for biomass drying to enhance the biomass energy value. In this study, the challenge of predicting biomass moisture under demanding measurement conditions is addressed by developing a predictive model for exhaust air humidity from the dryer. This model indirectly describes biomass moisture and employs machine learning methods such as linear regression model (LM), gradient boosting machines (GBM), eXtreme gradient boosting (XGBoost), random forest (RF), and multilayer perceptron (MLP), while enhancing transparency through explainable artificial intelligence (XAI) techniques for analyzing and visualizing humidity fluctuations. Based on this study, it can be demonstrated that tree-based ensemble methods GBM, RF, and XGBoost can accurately predict the humidity of air exiting the dryer with coefficient of determination from 0.88 to 0.89. Weather conditions, supply air humidity, and dryer fan speed emerged as key factors affecting drying efficiency, providing actionable insights for process optimization. Specific thresholds for these features can be defined to facilitate process settings. Moreover, improving system air tightness enhances drying efficiency and mitigates weather effects. The model shows promising predictive capabilities for exhaust air humidity, enabling future dynamic modeling to indirectly predict biomass end moisture, enabling adaptive control of drying processes, optimizing production capacities, and advancing sustainable energy through AI-driven solutions
Ice Hockey Action Recognition via Contextual Priors
Get PDFSkeleton-based action recognition models, which are developed for generic human-pose data, struggle with ice-hockey broadcasts player action recognition, where the players appear smaller, move abruptly, and wield sticks that are invisible to standard skeleton models. To address these issues, we propose CP-Hockey, a context-aware pipeline that incorporates two domain-specific priors. First, a temporal player’s boundingbox normalization stabilizes player scale across the player tracklet, raising top-1 accuracy from 31 % to 57 % on a six-class NHL dataset. Second, we design hockey-specific skeletons that include stick end-points and optional detailed head landmarks. A 15-keypoint body-plus-stick model improves the accuracy to 64 %, while our full 20-keypoint configuration reaches 65 %. Experimental results with STGCN++ and 2s-AGCN show that both contextual priors are necessary: scale normalization reduces spatial jitter, and stick keypoints disambiguate visually similar movements such as stickwork versus striking a puck with a stick. CP-Hockey establishes a strong baseline for fine-grained ice-hockey analytics and provides a blueprint for adapting skeleton pipelines to other equipment-centric sports