Linköping Electronic Conference Proceedings
Not a member yet
1113 research outputs found
Sort by
Scalable Higher-order Nonlinear Solvers via Higher-order Automatic Differentiation
Get PDFThis paper demonstrates new methods and implementations ofnonlinear solvers with higher-order of convergence, whichis achieved by efficiently computing higher-orderderivatives. Instead of computing full derivatives, whichcould be expensive, we compute directional derivatives withTaylor-mode automatic differentiation. We first implementHouseholder's method with arbitrary order for one variable,and investigate the trade-off between computational costand convergence order. We find that the second-ordervariant, i.e., Halley's method, to be the most valuable,and further generalize Halley's method to systems ofnonlinear equations and demonstrate that it can scaleefficiently to large-scale problems. We further applyHalley's method on solving large-scale ill-conditionednonlinear problems, as well as solving nonlinear equationsinside stiff ODE solvers, and demonstrate that it couldoutperform Newton's method
Absolut Modelica library
Get PDFThis publication presents a Modelica library developed toinvestigate absorption thermodynamic cycles, with specialattention to the absorption heat exchanger (AHE). Thelibrary includes models for different absorption cycles atvarious levels of detail, most of which have been validatedagainst literature values. The absorption heat exchanger(AHE) concept is also described. The main components usedto develop a dynamic AHE model, together with validationresults based on laboratory measurements, are described indetail
Digital Human Body Model for Occupant Monitoring System
Get PDFOccupant monitoring systems have been developed and used for Autonomous Driving (AD) level 3+. These occupant monitoring systems have limitations in accuracy and measurement items. To compensate for this, a Digital Human Body Model (DHBM) based on the Modelica language is developed, and its features are introduced. Inverse Kinematics (IK) and Inverse Dynamics (ID) DHBMs are interlocked with the occupant monitoring system to increase measurement accuracy and calculate various information such as motion sickness and fatigue. However, simulation of occupant behavior prediction is impossible. Forward Dynamics (FD) DHBM is a model that implements the characteristics of the live human studied through experiments and can predict occupant behavior. However, parameter verification is necessary to trust the results of FD DHBM. It is developing real-time validation and parameter update algorithms for FD DHBM using occupant monitoring data, which are expected to be available in various fields such as comfort and safety
Modelling And Simulation of a Batch Reverse Osmosis Process Using Modelica
Get PDFBatch operation of reverse osmosis (RO) has emerged as a promising strategy for enhancing energy efficiency and reducing fouling in seawater and brackish water desalination applications. This study implements a transient numerical model using Modelica to investigate the behavior of a batch seawater RO (BSWRO) system. The feed solution volume decreases and its salinity increases with time. It is pressurized by pumping product water into the other side of a piston. The model incorporates features such as the feed solution residence time in the inlet and outlet piping and captures the local variation in flux and concentration polarization over the membrane area. The instantaneous power consumption of the high-pressure and circulation pumps is calculated. The ease of adoption of Modelica underscores its utility in simulating complex transient and non-linear phenomena. The developed model can be expanded in the future to answer questions related to optimal control of batch RO systems
Augmenting Aerospace System Design Using Large Language Models
Get PDFThe democratization of artificial intelligence, exemplified by the widespread availability of ChatGPT since late 2022, presents significant opportunities for innovation in engineering system design. This paper explores how large language models (LLMs), particularly ChatGPT, can support and partially automate engineering design processes by generating system configuration rules and conceptual system architectures.
The methodology is demonstrated using case studies on hybrid-electric propulsion systems and actuation system design. LLMs are used to generate system configurations represented as UML component diagrams. Recognizing the non-deterministic behaviour of LLMs, a structured prompting methodology is proposed. This includes reusable prompt templates combined with embedded examples (micro templates), allowing increased reproducibility and specificity.
Furthermore, the study shows how LLMs can be used to generate Python scripts that act as configurators, producing system descriptions within specified design freedoms. These scripts enable iterative expansion, refining the architecture over time. The outputs are exportable to simulation environments, allowing further analysis and optimisation.
Integration with LLM APIs within engineering tools enables interactive expansion of system diagrams into subsystems and detailed components, streamlining complexity management. LLMs also demonstrate potential for embedding regulatory and functional requirements into generated designs, aiding compliance.
These findings highlight the potential of LLMs to transform aerospace system design by improving efficiency, traceability, and early-phase exploration of system architectures
Redundant Digital Hydraulic Actuators for Flight Control Surfaces
Get PDFThe aircraft industry is continually driven to improve energy efficiency in response to environmental concerns and cost reduction. Among solutions available in the field, hydraulics is commonly chosen to deliver crucial functions for its known reliability, precise controllability, and high stiffness. Additionally, when compared to competing technologies in development, hydraulic systems are far less susceptible to jamming, heat rejection problems, and premature wear. In the current context, digital hydraulics emerges as a promising alternative to conventional hydraulics, greatly increasing energy efficiency while keeping the robustness of fluid power systems. Aiming to apply this technology to aircraft systems, this paper introduces enhancements for the digital hydraulic topologies developed at LASHIP/UFSC that allow them to be applied in critical tasks, such as flight control actuation, achieving reliability and performance criteria, beyond the increase in efficiency. These topologies were refined with segregation and independence principles, as is standard in aircraft. The solutions address both centralized (easier to adapt to existing aircraft designs) and distributed hydraulic systems (coherent with the More Electric Aircraft concept). Furthermore, to evaluate the feasibility of the systems, the study correlates industrial components and aeronautical systems through systematic analogy, resulting in an estimate of the size and weight of digital hydraulic systems if designed for the aeronautical industry. The resulting digital hydraulic systems adhere to the reliability practices and safety standards employed in aircraft flight control while showing similar sizes and weights to the current solutions
Återgå och återuppta: vikten av pågående relationer och lekar i barns val av aktiviteter i fritidshem
Get PDFHur kan vi organisera för inkludering? En multipel fallstudie över det svenska tvålärarsystemet
Get PDFUnlocking the Corpus: Enriching Metadata with State-of-the-Art NLP Methodology and Linked Data
Get PDFIn research data management, metadata are indispensable to describing data and are a key element in preparing data according to the FAIR principles. Metadata in catalogues and registries are usually recorded either by archivists or subject matter experts, i.e. researchers involved in the creation or assembling of the data, or provided in the data preparation workflow. Extracting metadata from textual research data is currently not part of most metadata workflows, even more so if a research data set can be subdivided into smaller parts, such as a newspaper corpus containing multiple newspaper articles. If we look at descriptive metadata from a large corpus of newspapers, the basic metadata may consist of information, for example, about the title, or year of publication. Our approach is to add semantic metadata on the text level to facilitate the search over data. We show how to enrich metadata with three methods: named entity recognition, keyword extraction, and topic modeling. The goal is to make it possible to searchfor texts that are about certain topics or described using certain keywords or to identify people, places, and organisations mentioned in texts without actually having to read them
Data Reconciliation for Industrial Experiments
Get PDFThe paper presents the use of data reconciliation to bettercharacterize the operating state of experimentalinstallations in an industrial context. The paper focuseson the development of a data reconciliation approach usingthe OpenModelica prototype to study first the detection ofthe defects in an experimental hydraulic test loop, butalso the characterization of good measurement data in anHVAC testing facility. Data reconciliation is shown to beeffective for the most pronounced defects intentionallyintroduced in the system. Regarding the characterization ofmeasurements, data reconciliation identified two initiallyunnoticed invalid experiments