Producing iron ore pellets in grate-kiln plants involves several steps in order to obtain the final product. During the induration, the pellets are fired inside a rotary kiln; a large rotating oven, with two channels through which secondary process air enters. The secondary air channels are divided by the so-called back plate, causing an area of reduced velocity to form as the air flows past it. Current plants use coal to produce a flame inside the rotary kiln which heats the pellets. The coal flame is long and stable, and gives an even temperature profile inside the rotary kiln, something that is important for the quality of the pellets. As industries are transitioning towards more environmentally friendly processes and solutions, there is a desire to eliminate the use of fossil fuels such as coal. One alternative fuel of interest is hydrogen, since it can be produced and used without CO2 emissions. The issue with replacing the coal with hydrogen directly in the rotary kiln is that mixing with the surrounding secondary process air, necessary for combustion, occurs too quickly. This results in a flame that is short and intense, negatively impacting the pellet quality. Hence, different methods of injecting the hydrogen into the rotary kiln need to be investigated.

This thesis investigates the use of a so-called coaxial jet to control the mixing of fuel and secondary air. The coaxial jet consists of a central round jet mounted in the back plate, through which hydrogen is issued. Surrounding the inner jet is an annular outer jet, issuing either hydrogen or a different fluid. By altering the parameters of the coaxial jet, mixing of the hydrogen fuel and the surrounding secondary air can be controlled, making it possible to tune the resulting flame. To investigate the effect of different parameter values, Computational Fluid Dynamics (CFD) simulations are used. As a first step a simplified, axisymmetric model of the rotary kiln is modeled in 2D. This approach reduces the computational effort, enabling large amounts of parameter values to be evaluated. The so-called momentum flow ratio of the outer jet to the inner jet, Mjet, is used to compare different configurations of the coaxial jet. By increasing or decreasing the outer jet velocity, the value of Mjet is increased or decreased, respectively.

Two scenarios for the coaxial jet are considered; the first is using hydrogen through both the inner and the outer jet, and the second is using air instead of hydrogen through the outer jet. In Paper A, it is found that when using hydrogen through both the inner and outer jet, the potential core can be extended by decreasing the value of Mjet. This is achieved by decreasing the velocity of the outer jet, and thus providing a more gradual change in velocity between the high velocity inner jet, and the relatively slow secondary air. As a result the shear is reduced and the mixing is delayed. Among the values considered, Mjet = 0.25 produces the longest jet core and least mixing. This configuration, however, experiences recirculation and accumulation of hydrogen in a wake behind the back plate. If the outer jet fluid is substituted for air (Paper B) a different trend is seen, in which an increase of Mjet is beneficial for the jet length. The increased outer jet velocity, and thus momentum, enables the inner jet to be protected over a greater distance. Mjet = 2, the highest considered value, provides the longest hydrogen jet potential core and the most contained jet close to the jet exit. This is an indication that mixing with the secondary air is delayed. Further downstream, on the other hand, the increased shear that comes with higher Mjet -values contributes to increased mixing and spread.

Lastly, a three-dimensional model is simulated in Paper C, offering insights into a more complete view of the flow field inside the rotary kiln. Three-dimensional as well as transient characteristics of the flow are scrutinized, showing that there are effects not captured by the simplified steady-state 2D model. Unsteadiness along the jet core boundary, as well as a difference in the prediction of the flow behind the back plate, contribute to a difference in the jet evolution between the 3D model and the 2D model. The main conclusion from this investigation is that the simplified axisymmetric model of the rotary kiln fails to capture important features of the flow field, making it unsuitable to use for predicting accurate details about the coaxial jet evolution. The findings from this thesis will be used as a basis for the continued work, which includes investigating the influence of additional parameters on the mixing and flow field, as well as conducting experiments to enable validation of the numerical simulations.

Driven by innovation and cost reductions, the space industry is experiencing rapid growth. The proliferation of human-made objects launched into Earth orbits presents significant environmental challenges. If not properly addressed, continued growth at the current rate could lead to negative impacts both in space and on Earth.

The space industry has begun exploring sustainable practices, though most efforts focus on addressing issues that are related to the space environment. This neglects the impact on Earth and its atmosphere. Progress has been made in reuse of rocket bodies, however the benefits of satellite reuse remain largely disregarded. For example, the environmental impact of satellite constellations that are currently designed with large amounts of single use satellites, is still underexplored.

This underscores the critical research gap in understanding the fast-growing space industry’s impact on the environment and advancing knowledge related to satellite reuse. Therefore, the objective of this thesis is to explore satellite reuse and its contribution to space sustainability. The research starts by exploring how the fast-growing space industry impacts the environment and then examines if satellite reuse could help mitigate this impact. It ends with asking why satellite reuse is not yet widespread.

The research in this thesis employs a mixed-method approach, starting with industry expert interviews to gain insight into the current state of practice for satellite reuse. Building upon these interviews, two scoping studies were conducted to further the understanding on how satellite reuse could be achieved.

The findings emphasize the importance for the space industry to initiate an industrial transformation and develop sustainability-driven innovation rather than having a focus on mostly commercial gains. The absence of necessary practices and technologies for satellite reuse have been identified in three critical building blocks: (1) reverse logistics systems to retrieve and process satellites for reuse, (2) design practices that enable reuse, and (3) business models that ensure financial viability. Focusing on these three areas can advance sustainable practices in the space industry and could contribute to the mitigation of its negative environmental impact. The presented findings can provide valuable insights for policymakers and industry stakeholders, to rethink practices and to prioritize sustainability in space activities.

As robots are increasingly integrated into large and dynamic environments alongside humans, there is a pressing need for efficient onboard solutions to fundamental robotic operations, such as navigation and decision-making. Existing solutions often rely on computationally intensive processes that do not scale well in larger environments, leading to long computation times. This can result in unsafe and non-adaptive behaviors, as during the planning phase the robot continues to move along an old and potentially dangerous path increasing the risks of accidents or emergency.This thesis addresses this challenge by developing human-inspired light-weight methods, that enhance robotic navigation and environment understanding.

The central framework presented in this thesis introduces a novel human-like method for navigation and environment segmentation using 2D grid maps, focusing on extracting structural-semantics, such as intersections, pathways, dead ends, and paths to unexplored areas. The framework also generates sparse topometric maps for lightweight robotic navigation by using structural-semantic information. Compared to the state-of-the-art, where map segmentation either utilizes features that are specific to some indoor environments or segments into arbitrary regions that do not convey semantically meaningful information about the environment, the semantic topometric map captures structural-semantic information, which can easily be utilized by robots in a variety of missions. The proposed framework has been validated on multiple maps of different sizes and types of environments. In comparison with the state-of-the-art topological maps generated by Voronoi-based solutions, the proposed framework shows a significant reduction in complexity and computation times required in solving navigation problems. 

The utility of structural semantics is demonstrated through a novel autonomous exploration strategy that integrates structural-semantic information with conventional metric data for goal/frontier selection and employs the semantic topometric map for navigating to a frontier. The effectiveness of the exploration strategy is demonstrated in real-world experiments, showcasing improved exploration speed and computational efficiency compared to frontier-based exploration methods using only metric information. 

In order to enable the methods presented in this thesis to operate over 3D maps, this thesis introduces an approach for converting 3D voxel maps into 2D occupancy maps augmented with height and slope information. Moreover, a method for converting paths generated in 2D into 3D paths is proposed. This allows for the use of structural-semantic segmentation and efficient topometric map-based navigation planning for both UAVs and UGVs. These contributions together enable lightweight and fast environment segmentation and navigation planning for a multitude of robot types, and leveraging structural-semantic information leads to a more human-like approach toward robotic navigation and environment understanding. 

Structural Health Monitoring (SHM) using ultrasonic guided waves is an advanced and efficient technique for evaluating the integrity of critical infrastructure such as pipelines, pressure vessels, and aerospace structures. Despite its numerous advantages, the reliability and effectiveness of guided wave-based SHM systems are often compromised by environmental and operational variations, particularly temperature fluctuations. Temperature changes significantly influence wave propagation by altering material properties, wave velocity, and signal behaviour. These variations lead to signal misalignment and reduced defect detection accuracy, posing a major challenge for real-time monitoring systems. This research addresses the impact of temperature-induced signal variations by developing robust baseline signal strategies to improve temperature compensation in guided wave-based SHM systems.

The study introduces Dynamic Time Warping (DTW) and its advanced adaptations as key methods for aligning signals under fluctuating thermal conditions. DTW is a widely used signal processing technique that optimizes the alignment between two signals by stretching or compressing their time domains, ensuring accurate comparison and analysis. The quadratic computational complexity of DTW poses a significant challenge for its application in Structural Health Monitoring (SHM) using guided waves, particularly for real-time operations under changing Environmental and Operational Conditions (EOCs). 

To address this, the first approach employs a DTW approximation to accelerate the warping process, called Fast-DTW achieving significant computational efficiency without compromising much on performance. In contrast, the second approach uses the Full DTW algorithm but improves its efficiency by incorporating the Sakoe-Chiba constraint to restrict the warping path to a narrow region around the diagonal, effectively reducing computational cost. Additionally, the method leverages the fact that temperature-induced shifts in guided wave signals are typically limited to a few time stamps. Third, we propose a global constraint for temperature compensation of guided waves, referred to as the Triangular Global Constraint (Tri-DTW). The performance of the proposed method is compared with the Sakoe-Chiba Global Constraint (SC-DTW). Tri-DTW performs well, demonstrating better warping performance with four times reduced computational complexity. Finally, we present Hilbert-DTW, a novel approach that extracts the envelope and phase of signals and leverages phase differences to achieve accurate alignment. This method reformulates the cost matrix to prioritize signal alignment while preserving amplitude variations, eliminating the need for constraints or modified DTW variants.

Collectively, these strategies provide a robust framework for baseline signal management and temperature compensation in guided wave-based SHM systems. By improving signal alignment accuracy and reducing distortion caused by temperature effects, the proposed methods significantly enhance the reliability, adaptability, and performance of SHM technologies.

In conclusion, this research advances the field of SHM by addressing temperature-induced challenges through innovative signal processing techniques. The integration of fast DTW algorithms, optimized constraints, and the Hilbert-DTW provides a comprehensive solution for maintaining SHM system performance under varying thermal conditions, enabling more reliable and accurate monitoring of critical infrastructure.