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https://odr.chalmers.se/handle/20.500.12380/47

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Electric fan performance and noise modelling. An investigation of installation effects on the performance and the noise produced
(2024) Pardesi, Muhammad Mustafa; Chalmers tekniska högskola / Institutionen för mekanik och maritima vetenskaper; Chalmers University of Technology / Department of Mechanics and Maritime Sciences; Andersson, Niklas; Etemad, Sassan
This thesis investigates the effects of installation configurations on the performance and acoustic output of an electric fan using computational approaches. The study focuses on the aerodynamic and acoustic characteristics of axial fans installed in various configurations, including the use of cylindrical ducts and bellmouths. A CFD model was developed and validated against experimental data to assess fan performance in terms of pressure rise and sound power. Key distortion metrics, such as the Circumferential Distortion Index (CDI), were introduced to quantify non-uniformities in the pressure distribution. The study reveals that while the addition of certain components, such as bellmouths, improved the flow uniformity and reduced distortion, their impact on acoustic output was less straightforward. Additionally, an obstruction study was conducted to evaluate the effect of partial blockage on fan performance and distortion. The results provide insights into the relationship between installation effects and fan efficiency, pressure rise, and noise production, supporting potential design optimizations for fan installations in industrial applications.
Knock mitigation study on alternative fuel heavy duty engines
(2024) Katsikioti, Dimitra; Chalmers tekniska högskola / Institutionen för mekanik och maritima vetenskaper; Chalmers University of Technology / Department of Mechanics and Maritime Sciences; Dahlander, Petter; Hansson, Axel
With increasingly stricter emissions regulations and a growing demand for higher efficiency, alternative fuels are becoming more viable alternatives to fossil fuels. Methane, for example, can be used in conventional combustion engines with minimal modifications, meeting lower emission targets. However, engines running on alternative fuels still face issues common to conventional engines, such as “knock,” which limits their efficiency. This thesis investigates the manifestation of knock in alternative fuel engines and proposes a method to prevent it while maintaining high efficiency. The method utilizes Model Predictive Control (MPC) and Artificial Neural Networks (ANNs). A detailed outline of the proposed controller is provided, along with the rationale behind its key structural characteristics. The use of ANNs to model the system’s state is also explored and evaluated. The controller is tested under various operating conditions and tuning settings to verify its effectiveness and identify optimal tuning. The proposed control method performed well in the selected cases and setup. Further improvements to both the controller and neural network structure are suggested to enhance performance. This thesis establishes that MPC can improve engine performance and prevent unfavorable operating conditions. Initially useful for engine mapping, the controller has future potential for direct implementation on the ECU.
Developing of a numerical framework for transonic axial compressor analysis
(2024) Hessman Ranman, Robert; Chalmers tekniska högskola / Institutionen för mekanik och maritima vetenskaper; Chalmers University of Technology / Department of Mechanics and Maritime Sciences; Xixto, Carlos; Sjögren, Oliver
Modern engineering in the aerospace field of operations is transitioning from real experimental testing to heavily relying on computer-aided engineering (CAE). Computational fluid dynamics (CFD) is a great tool for obtaining estimates of real operations but computational limitations often lead to the implementation of simplified models of the full governing equations, rendering estimates with a limited accuracy. Validating numerical results to experimental data is a great way of bridging the gap between virtual and real operation, and further provides weight to the validity of the results to the aeronautical engineering community. At Ecole Centrale de Lyon a carbon fiber fan stage has been designed as a reference test case for state-of-the-art fan stage technology, in collaboration with the engine manufacturer Safran. The test case named CATANA is intended as a platform for collaboration between universities and research agencies and to support validation of simulation codes by providing experimental data. In this thesis, the numerical and experimental results generated at Ecole Centrale de Lyon on the CATANA test case is used to establish and validate a numerical framework developed to further be used in a parametric study of fan blade design. The framework is presented in three phases, grid generation, simulations, and validation with CATANA data. The baseline case is established with a low Reynolds number RANS turbulence model with the assumption of steady-state. To further reduce the overall computational load of any given blade design the spacial resolution requirements of a low and high Reynolds’s number turbulence models are investigated by integrating a low-Re k-ε model in the framework in parallel to a high-Re k-ω SST model. The thesis covers an in-depth presentation of meshing routines and numeric setup for both models as well as the implementation of custom external convergence criteria. As a final part of the thesis, the effects of removing the stator from the fan stage are investigated by comparing spanwise distributions and mass flow averaged data downstream of the rotor.
Statistical Safeguards: Redefining Col lision Avoidance with Probability Theory: Employing Statistical Decision-Making to Enhance Safety in Mixed Traffic Environments
(2024) Hjertén Brink, Sebastian; Chalmers tekniska högskola / Institutionen för mekanik och maritima vetenskaper; Chalmers University of Technology / Department of Mechanics and Maritime Sciences; Forsberg, Peter; Hedvall Fogelquist, Martin
This thesis introduces a probabilistic collision avoidance system that employs statistical decision-making in order to enhance the safety of mixed traffic environments. Central to this approach is the representation of vehicle positions as normal probability distributions, which are convolved with real-time sensor data to assess risks more accurately and reduce the unnecessary emergency stops. The research develops and implements a dynamic collision probability threshold, that is derived from safety integrity levels (SIL), which is imperative for complying with the rigorous safety standards and regulations. Simulations and analytical methods were used to validate the effectiveness of the proposed algorithm and demonstrating its potential in decision-making in emergency situations. Thus a a scalable solution for collision avoidance is presented in the form of an algorithm that can be integrated into existing safety systems, in order to enhance the operational efficiency for mixed traffic environments.
Assessment of brake wear emissions from a brake rig
(2024) Suresh, Nandu; Chalmers tekniska högskola / Institutionen för mekanik och maritima vetenskaper; Chalmers University of Technology / Department of Mechanics and Maritime Sciences; Sjöblom, Jonas; Sjöblom, Jonas
As the number of vehicles on the road continues to rise, and solutions for exhaust emissions have been developed, non-exhaust emissions are becoming increasingly prominent, particularly brake wear emissions. Non-exhaust emissions could be extremely harmful to humans and can cause premature deaths. Hence it is necessary to identify the problematic particles among the brake particles to mitigate the harmful effect of brake wear emissions on health. This project aims to find the properties and composition of brake particles generated from a brake system comprising a brake disc and a pair of brake pads of a light-duty vehicle. With multiple standardised driving cycles available, rig-based testing can be done with proper infrastructure, and brake particles can be sampled and analysed properly. The new upcoming Euro 7 legislation limits the PM10 emissions from the brakes of light-duty vehicles to 3 mg/km. Brake particles were generated using a custom drive cycle suitable for the operation of the brake rig, followed by the sampling and assessment of the particles using Dekati ELPI+ and further analysis was done using SEM-EDX to get microscopic pictures of brake dust as well as its chemical composition. For the test cycle and operating conditions, most of the particles formed were in the region of PM10. Particle size distribution (PSD) curves are plotted for a better understanding of different conditions like the re-suspension of brake particles. The effects of temperature, brake pressure and speed on the formation of brake particles are analysed in the form of PSD curves. Metals like Fe and Ca were found to be the dominant materials among the larger particles and elements like C, O, Si etc made up most of the smaller particles. Principal component analysis, together with SEM-EDX results validates that.

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