Honors Programme Research Proposal 9 June 2023

INTEGRATING LIFE SUPPORT SYSTEMS IN MARTIAN HABITATS: DESIGNING AN OPTIMIZATION SCHEME FOR INTEGRATION INTO COMPLEX GEOMETRIES

Mohammed Ibrahim – 5741165

TU Delft (the Netherlands)

HPM Project Proposal 4.7

27 June 2023

Supervisor: Dr. Henriette Bier

Abstract:

        The life support system in Martian habitats is a complex and interconnected network of components, with each part relying on coordinated connections. The system's components can be represented as nodes, while the paths symbolize the interconnections between them. With numerous possibilities for node placement and path configuration, a wide range of permutations emerges. This research aims to develop an optimization scheme and design automation for the life support system in Martian habitats, with a focus on reducing weight, facilitating maintenance, and guiding habitat design processes. Specifically, the research focuses on the atmospheric and water components within Martian habitats. It explores the essential requirements of a life support system in this context and addresses the challenges associated with integrating it into the design-to-robotic-production (D2RP) method developed at the Technical University Delft (TUD) proposed by the Robotic Building Lab. By identifying and addressing these constraints, the research aims to contribute to the advancement of efficient and effective integration of life support systems in Martian habitats. 

Introduction:

The life support system

In the field of manned spaceflight, the term Environmental Control and Life Support System (ECLSS) is used to describe the engineered systems within a habitat that are designed to sustain the lives of living beings, including humans and animals. ECLSS can be categorized into three main functions: Air Management, Water Management, and Solid Waste Management (Metcalf, J et al ,2011). Each of these functions can further be broken down into various subfunctions. According to NASA's ECLSS Roadmap (2011), these three primary functions are decomposed into several subfunctions.

1.Atmospheric Management

The Air Subsystem is responsible for maintaining the atmospheric pressure and quality within the cabin. It encompasses various functional areas that ensure proper air circulation, supply, and storage. These include controlling positive and negative pressure, managing carbon dioxide levels, removing moisture (often with the assistance of a Thermal Interface condensing heat exchanger), controlling trace chemical contaminants, managing particulate matter, and handling resource recovery, storage, and recycling. Additionally, the air system includes components designed for emergency scenarios. While these emergency systems serve similar functions as the regular systems, they may utilize different technologies tailored to specific contingency situations. The system can be summarized as follows:

II. Water Management

The Water Subsystem is responsible for gathering wastewater from various sources, recovering and transporting drinkable water, and storing and supplying it at the required level of purity and biological activity. This water serves the needs of the crew and external users for consumption, hygiene, as a reactant in processes, and for meal cleanup and housekeeping purposes. The system includes:

III. Solid waste Management

        

The Waste Subsystem is responsible for gathering waste materials, including packaging waste, human waste, and process waste. The extent of processing these wastes undergo depends on the size of the habitat. It may involve minimal processing to reduce storage requirements and manage odor, rendering the waste biologically inactive, or recycling it into useful commodities to support mission objectives. The subcategories of the waste management are:

Life support systems designed for isolated and confined environments (ICEs), like submarines and Martian habitats, are developed as a physicochemical system. These systems rely on technologies that employ passive or active chemical and physical processes to recycle consumables. For example, an air filter utilizing a metal oxide adsorption bed to remove CO2 from the air. The diagram provided below depicts the interconnectedness of these regenerative systems.

Figure 1: Life support system schematic. Czupalla, Markus. (2003). Analysis of a Spacecraft Life Support System for a Mars Mission. 10.2514/6.IAC-03-IAA.13.3.04.

Design challenges

When constructing habitats on Mars, various factors need to be taken into account, including the geological composition, available materials, the climate, and potential hazards. To address these challenges, the idea of establishing settlements in Martian valleys and underground areas has been proposed by TUD. By constructing habitats below the surface, not only can natural radiation protection be achieved, but there is also improved thermal insulation due to the more stable temperatures underground.

At TUD's Robotic Building Lab, a pioneering approach of Data-driven D2RP (Design to Robotic Production) system has been developed. This innovative system integrates cutting-edge computational design methods with robotic techniques to facilitate the seamless transformation of architectural designs into tangible building structures (Bier et al., 2018). The fundamental concept behind the habitat's design revolves around data-driven simulations of an underground rhizomatic structure, as depicted in Figure 1. Through the employment of 3D printing technology, the resulting rhizomatic habitat showcases a strategically optimized porous configuration that significantly enhances its thermal insulation capabilities by leveraging its inherent porosity. The challenges faced in Mars give rise to the need for a rhizome-based formation, and overlaying such a system with a life support system adds another layer of complexity.

Figure 2: Integrating life support layered approach (Right). Embedded sensor and actuator(left)  Bier, H., Vermeer, E., Hidding, A., & Jani, K. (2021). Design-to-Robotic-Production of Underground Habitats on Mars.

        Several explorations into how to integrate life support in such a design has been explored. (fig. 3). The need for designing lighter and more compact systems is relevant as the life        support system in an isolated system is cumbersome. Finding optimal routes for these connectors in a densely populated environment left behind at the detail design stage and hence can’t promptly access if a form is ideal for integrating a life support system.Developing an optimization scheme that can be implemented in the early design stages informs the decision of selecting a geometry.

Figure 3: Structural analysis with a fragment chosen for further development (left) and Section through underground structure (right). Bier, H., Vermeer, E., Hidding, A., & Jani, K. (2021). Design-to-Robotic-Production of Underground Habitats on Mars.

The aim of this study is to develop a deterministic optimization approach to address the routing problem in both two and three dimensions, with a specific focus on achieving optimal solutions. The problem at hand involves determining an optimal tree network that connects multiple components, with the objective of minimizing the total length of the connectors. The study begins by solving for the optimal locations of each component, taking into consideration their individual characteristics. Furthermore, the problem addresses the challenge of finding the shortest route to connect two specified nodes within a cluttered 3D environment, and proposes strategies to overcome this obstacle.

Problem statement, research question and research objective.

Problem Statement:

The integration of life support systems within the complex geometries of Martian habitats poses challenges in terms of optimal routing of connectors and pathways, limited space for planning routes, and the need for lightweight and compact systems. These challenges require innovative solutions to ensure efficient and effective integration of life support systems within Martian habitats.

Research Question:

How can the routing problem in the integration of life support systems within complex geometries of Martian habitats be addressed, with a focus on optimizing connector routes in three dimensions, considering limited space and the requirements of lightweight and compact systems?

Research Objective:

The objective of this research is to develop a deterministic optimization method to tackle the routing problem in the integration of life support systems within Martian habitats. The research aims to:

  1. Determine optimal locations for life support system components based on their characteristics and requirements.
  2. Address the challenge of finding the shortest routes connecting the components in a 3D cluttered environment, considering limited space and the need for lightweight and compact systems.
  3. Minimize the overall length of connectors and pathways while ensuring efficient and effective integration of life support systems within Martian habitats.
  4. Contribute to the development of guidelines and recommendations for the design and optimization of life support system integration within complex geometries of Martian habitats.
  5. Facilitate the advancement of self-sufficient and sustainable Martian habitats, enabling long-term human presence and exploration on Mars.

Literature study: path optimization problem

While determining the shortest path between two points in a cluttered environment is crucial in applications like robot motion planning, real-world routing problems often involve planning multiple routes, such as pipe routing or cable harness design. In complex interconnected systems such as automobiles, aircraft, and life support systems, a significant number of wires, pipes, and cables are required to connect various components.

An early work in the computer-based design of piping systems introduced an integrated computer-aided piping design system for designing, planning, and fabricating piping systems in ships (Sheridan, H. C., 1976).

Despite the availability of CAD packages to support designers, there was a lack of integration between the CAD model of the pipes and the hull structure. In other words, any modifications to the hull structure did not impact the pipe model, and vice versa (Roh et al.,2007). Consequently, if changes were made to the hull structure, the designer had to manually update the piping model accordingly. To address this limitation, Roh proposed a method that generates the piping model while considering its dependency on the hull structure.

The design of cable layout plays a crucial role in various applications, including wind farm layout design and planning. In wind farm layout design, the objective is to determine the optimal locations for wind turbines based on specific requirements. The optimization model considers constraints such as the minimum and maximum number of turbines, clearance between consecutive turbines to avoid interference of blades, and foundation cost (in the case of offshore wind farms). To facilitate the optimization process, a grid is utilized, which provides potential locations for turbines. The decision variables in the optimization model are binary variables that indicate whether a specific grid point is selected as a turbine location.

Once the layout is optimized, the next challenge is to find an optimal cable connection between all turbines and substations. This problem involves constraints related to cable capacity, the requirement that cables do not cross each other, and limitations on the maximum number of connections to a substation. Figure 4 illustrates a sample layout generated by this approach, which includes 72 turbines and one substation.

Figure 4: Final optimal layout for a wind farm. Fischetti, M., Leth, J. and Borchersen, A. B., 2015, “A Mixed-Integer Linear Programming approach to wind farm layout and inter-array cable routing,” Proceedings of the American Control Conference, American Automatic Control Council, pp. 5907–5912.

Another application of path optimization is in the building industry. The rapid pace of urban modernization has led to the expansion of building scales, resulting in the incorporation of more information and electrical equipment in high-rise buildings. This trend presents new challenges for designing the electrical systems of such buildings. To ensure the efficient operation of electrical equipment, optimize electricity consumption, and reduce investment and maintenance costs, it is important to address the wiring optimization problems specific to high-rise buildings.

One intelligent approach to optimizing the wiring design of electrical equipment in buildings is the utilization of ant colony optimization. This optimization method, originally proposed for continuous space optimization problems, can be adapted to optimize the routing path for high-rise buildings by simulating the foraging behavior of ant colonies in finding the shortest path. By applying this approach, the length of wiring in high-rise buildings can be reduced, and control over power parameters such as voltage drop and line loss can be enhanced, ultimately improving the economic efficiency of the algorithm.

Methodology

Literature reviews

The research will begin by studying the atmospheric and water system of life support in Martian habitats. This involves characterizing each component in the system to determine the factors that influence the positioning of components (nodes). Additionally, the research will analyze the type of connections required between components, providing a foundation for framing the path optimization problem.

Subsequently, the research will explore the current state of the art in path optimization techniques applied across various industries. Industries such as vehicle manufacturing, shipping, and more recently, the building industry have utilized path optimization to enhance system efficiency. The aim is to understand the methods employed in these industries and develop a selection criterion for identifying a suitable system to be explored in this research.

        

Case studies

        

Drawing upon the findings of the Rhizome project funded by the European Space Agency, the research will select relevant case studies from a master studio / workshop. This selection process aims to facilitate a deeper understanding of the project's logic, particularly in relation to Rhizome I and Rhizome II, and how each project's form is generated.

During this stage, it is crucial to comprehend the composition of the habitat enclosure and the challenges associated with integrating a life support system within it. To facilitate the study, one project from the master's studio will be chosen based on performance criteria that encompass disciplines such as constructability and space quality. The preliminary criteria for selecting a project for further exploration are outlined below.

                                    1.Clarity in design

                                2. Structurally resolution

                                3.Thermal insulation

                                4.Material efficiency

                                5.Manufacturability

                                6. Design scalability

After project selection, the research will develop an integration scheme of life support system with the process of D2RP. This is then followed by node and path optimization using a computational flow chart that is inconsideration of:

        

        1.Weight reduction

        2.Maintenance

        3.Constraints of the habitat form and enclosure composition.

Conclusion

In conclusion, this research proposal aims to address the challenges of integrating life support systems into the complex geometries of Martian habitats. The optimization scheme and design automation developed in this study will focus on improving the efficiency and effectiveness of the integration process. By considering factors such as weight reduction, maintenance, and the constraints of habitat forms and enclosure composition, the research seeks to optimize component location and connector pathways in two and three dimensions.

Reference

        

Bier, H., Liu Cheng, A., Mostafavi, S., Anton, A., & Bodea, S. (2018). Robotic Building as           Integration of Design-to-Robotic-Production and  -Operation. In H. Bier (Ed.), Robotic Building (pp. 97–120). Springer International Publishing. https://doi.org/10.1007/978-3-319-70866-
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Bier, H., Vermeer, E., Hidding, A., & Jani, K. (2021). Design-to-Robotic-Production of Underground Habitats on Mars. SPOOL, 8(2), 31–38. https://doi.org/10.7480/spool.2021.2.6075

Czupalla, Markus. (2003). Analysis of a Spacecraft Life Support System for a Mars Mission. 10.2514/6.IAC-03-IAA.13.3.04.

Fischetti, M., Leth, J. and Borchersen, A. B., 2015, “A Mixed-Integer Linear Programming approach to wind farm layout and inter-array cable routing,” Proceedings of the American Control Conference, American Automatic Control Council, pp. 5907–5912.

Metcalf, J., Carrasquillo, R., Peterson, L., Bagdigian, B., & Westheimer, D. (2011). Environmental Control and Life Support (ECLS) Integrated Roadmap Development (Tech. Rep. December). National Aeronautics and Space Administration, Houston, TX.

Roh, M. Il, Lee, K. Y., and Choi, W. Y., 2007, “Rapid generation of the piping model having the relationship with a hull structure in shipbuilding,” Adv. Eng. Softw., 38(4), pp. 215–228.

Sheridan, H. C., 1976, “An overview of a casdac subsystem-computer-aided piping design and construction (CAPDAC ),” Nav. Eng. J., 88(5), pp. 87–98.