Introduction to the mathematical concept of networks, and to two important optimization problems on networks: the transshipment problem and the shortest path problem. Short introduction to the modeling power of discrete optimization, with reference to classical problems. Introduction to the branch and bound algorithm, and the concept of cuts.

Uncooperative Rendezvous in Space: Design of an Electronic Architecture for High Performance Avionic with Multi Sensor Input and Intensive Data Rate.

Michaël Yannick Juillard

Active Debris Removal missions consist of sending a satellite in space and removing one or more debris from their current orbit. A key challenge is to obtain information about the uncooperative target. By gathering the velocity, position, and rotation of the desired object, the satellite is able to plan its trajectory and define the sequence of approach. It requires the use of a variety of sensors with often a high data rate. For this task, a dedicated payload computer is envisioned with the responsibility of processing the information from the various rendezvous sensors. This component has the goal to provide meaningful information to the main satellite computer about the targeted debris. The focus of this work is on the data processing, the number of elements, and the electrical energy with constraints due to internal communication.First, an avionic testbench was built at the EPFL Space Center to assess early hardware and software architectures. The goal is to enable Hardware-In-the-Loop testing while developing the payload computer. A communication data bus has been implemented between the Platform and the Payload On-Board Computer. Emphasis was placed on the reliability of the high-level protocol and multiple concepts for improvement were analyzed.In a second phase, the testbench has been extended to support other data buses. The aim was to develop a reliable and efficient backup or fall-back data bus in case of failure in the main link. Four data buses have been tested with extensive analyses on their resilience to error and the efficiency of their data exchange.In parallel, extensive work has been performed to develop a simulation and optimization tool. Its goal is to support the design of payload avionic architectures for ADR missions by providing trade-offs and analyses. In the first iteration, a simulator has been created with instances of various high-level elements modeled.The second iteration introduced the additional dimension of optimization. It is trying to determine the best set of instruments and algorithms to use. With this capability, numerous analyses have been conducted on the influence of various parameters linked to the general optimizer behavior. It allows us to better understand the strength and limitations of the tool.The third step regarding the tool was to start its verification. The task has been to develop an Hardware-In-the-Loop architecture to compare its behavior with the results of the optimizer. The implementation of various mock-up algorithms enables the verification of their models in the tool. These analyses guarantee the feasibility of the outputted solution.The last part was dedicated to the creation and analysis of a realistic payload avionic architecture. The goal was to test the capability of the tool with hardware elements inspired by actual components. This work has shown the procedure to efficiently use the tool in the design phase of a mission.In conclusion, the work on the communication between the Payload and the Platform On-Board Computer has brought valuable lessons and experiences to the projects. They can now be used for the establishment of the high-level protocol into ClearSpace-1 flight software. In addition, the optimizer created allows tackling the design of complex payload avionic architecture where mass saving and processing resources are crucial. It is an essential point to develop a highly efficient payload computer for an Active Debris Removal satellite.

EPFL2022

Towards sufficiency in housing: Agent-based model and transition scenarios

Margarita Agriantoni

Research problem: Housing is responsible for a considerable part of global resource consumption. In Switzerland, it accounts for almost one third of the country's CO2 emissions and half of the total energy demand. Thus, housing plays an important role in the transition to sustainable development. Housing has been thoroughly studied from a disciplinary perspective, e.g., economics, social sciences, psychology, engineering. However, little attention has been paid to housing as a system of interrelated actors, e.g., developers, owners, tenants and state, whose actions might be described by different disciplines. Aim: The aim of this thesis is to investigate how a change in the construction practices of property owners in combination to a more space-efficient allocation of dwellings to households and a behavioural change of tenants can achieve a substantial reduction in the environmental impact of housing. This dissertation focuses on the interrelations of housing actors, concentrating mainly on the property owners and explores which measures and to what extent can lead to a reduction of space consumption of housing.Methods: Housing is characterised by a high level of complexity, therefore a transdisciplinary approach is adopted. Firstly, the Swiss housing market and its unique attributes are studied. However, in this thesis, we study a subset of the Swiss rental housing market; it comprises two housing cooperatives: ABZ in Zurich and SCHL in Lausanne as well as the insurer and asset manager Swiss Mobiliar. Their housing stocks, of approximately 10,000 dwellings, are examined in depth and are used as a case study. Extensive data gathering allowed to create an exhaustive inventory of the building stock of the three property owners. The data on tenants was limited, thus, we conducted a tenant survey. Furthermore, a series of workshops with both tenants and property owners were organised to study their decision-making processes. A bottom-up agent-based model (ABM) is built, which portrays the case study housing system. The main actors of the rental housing market (property owners and households) are represented in the model by agents; the owner agents make decisions about their building stock and tenants, while the household agents choose a dwelling based on their needs and housing preferences. The dynamic evolution of both owners and households and the interaction between them is simulated in the model and allows the study of emergent phenomena. The present thesis attempts the assessment of the environmental impact of housing through the lens of housing sufficiency. Space consumption, in terms of dwelling surface and floor area per capita, is considered as the largest determinant of resource consumption.Results: The simulation results show that measures taken to decrease the environmental impact of housing and space consumption are inadequate if owners do not change their construction practices and households do not actively change their housing behaviour. Most measures explored in this thesis, if implemented individually, succeed in reducing the rate of increase in space consumption but fail to reverse the upward trend. A more space-efficient allocation of dwellings to households proves to have a certain effect. However, only when combined with other measures, such as the densification of the existing building stock and a change in construction practices, a significant decrease of environmental impact is observed.

EPFL2022

Quantum-based approach for laboratory risk assessment and decision-making

Ruoxing Liao

With the rising focus on academic safety, there has been an effort to improve the academic safety climate and develop lab-specific risk assessment tools. Despite the progress made in recent years, there is still a deficit of reliable data statistics on safety events and risk assessment in academia, making it difficult to perform full-scale analysis. Moreover, the rapid turnover of personnel and the highly dynamic research tasks in a laboratory environment impede the implementation of classical and well-established risk management strategies, which are usually time-consuming and resource-intensive. Laboratory safety management is always challenging due to lack of data and effective methods. The end of safety management is usually the selection of risk mitigation measures. In the laboratory risk management process, decisions are often made through discussion and compromise. In this regard, it would be beneficial to provide a tool that can support in resource allocation and prioritization of actions. The goal of this project is to develop a decision support tool to assist in the selection of optimal and appropriate preventive or corrective measures in the lab safety management process. The use of decision tools such as Multi-Criteria Decision Making (MCDM) can effectively abstract complex laboratory management problems into a decision framework. This study focuses on the ranking process of competitive corrective measures. Combining the results of interviews and questionnaires, five evaluation criteria were proposed for the normative process of multi-criteria decision making. They are: Residual Risk, Risk reduction, Personnel reliability, Technical reliability, and Cost. classical methods TOPSIS and WSM have been evaluated during the study, and emerging quantum decision making methods have been explored. All three methods are used to simulate the laboratory safety decision making process, and they all present good consistency. Different weighting methods have also been applied to the model and two case studies have been conducted. The first case study is designed to construct the model and verify its feasibility, and the second model is used to investigate the process of group decision making. By applying different MCDM methods, the obtained results are discussed and compared to verify the stability and accuracy of the model. The approach proposed in this research is a promising tool. It offers the possibility to be compatible with different MCDM methods and risk assessment methods, and the proposed decision model could be used as a decision support system to help lab managers make better decisions, or it can provide a neutral point of view as an aid. Future work may include fine-tuning the model. In the following stage, decision criteria should be precisely defined, and corresponding quantitative formulas should be proposed to serve the flexible and dynamic laboratory environment.

2022

Uncooperative Rendezvous in Space: Design of an Electronic Architecture for High Performance Avionic with Multi Sensor Input and Intensive Data Rate.

Michaël Yannick Juillard

EPFL2022

Towards sufficiency in housing: Agent-based model and transition scenarios

Margarita Agriantoni

EPFL2022

Quantum-based approach for laboratory risk assessment and decision-making

Ruoxing Liao

2022

Optimization: principles and algorithms - Network and discrete optimization

Uncooperative Rendezvous in Space: Design of an Electronic Architecture for High Performance Avionic with Multi Sensor Input and Intensive Data Rate.

Towards sufficiency in housing: Agent-based model and transition scenarios

Quantum-based approach for laboratory risk assessment and decision-making

Uncooperative Rendezvous in Space: Design of an Electronic Architecture for High Performance Avionic with Multi Sensor Input and Intensive Data Rate.

Towards sufficiency in housing: Agent-based model and transition scenarios

Quantum-based approach for laboratory risk assessment and decision-making