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Columbus stowage optimization by cast (cargo accommodation support tool)
Abstract
A challenging issue related to the International Space Station utilization concerns the on-board stowage, implying a strong impact on habitability, safety and crew productivity. This holds in particular for the European Columbus laboratory, nowadays also utilized to provide the station with logistic support. The volume exploitation has to be maximized, in compliance with the given accommodation rules. At each upload step, the stowage problem must be solved quickly and efficiently. This leads to the comparison of different scenarios to select the most suitable one. Last minute upgrades, due to possible re-planning, may, moreover arise, imposing the further capability to rapidly readapt the current solution to the updated status.In this context, looking into satisfactory solutions represents a very demanding job, even for experienced designers. Thales Alenia Space Italia has achieved a remarkable expertise in the field of cargo accommodation and stowage. The company has recently developed CAST, a dedicated in-house software tool, to support the cargo accommodation of the European automated transfer vehicle. An ad hoc version, tailored to the Columbus stowage, has been further implemented and is going to be used from now on.This paper surveys the on-board stowage issue, pointing out the advantages of the proposed approach.
... To overcome and optimize those limiting aspects, VR and AR techniques have been tested with positive results. The tools developed by Thales Alenia Space Italia (TAS-I) for the ISS Columbus laboratory demonstrated how VEs can help in knowledge sharing among groups of different disciplines to optimize different aspects of the same module, especially supporting collaborative frameworks in which perform stage analysis verification such as stowage accommodation activities [120,121]. One of the test case used for assessing the accessibility of the ISS Columbus module is shown in Figure 2 Other examples also exist where VR was used to enhance the space mission design. ...
... A first successful example was implemented by NASA for training the Hubble space telescope flight team [109], where the time required for the EVAs familiarization phases was shorter thanks to the adoption of a VR tool. Additionally, encouraging results have been obtained for the ISS Columbus laboratory stowage operations [120,121]. ...
Space mission design is a complex discipline. Several research studies are currently investigating how to ameliorate the process. Since the decision taken during the early phases of the project are those which affect the most the final solution of a system in terms of architecture, configuration, and cost, more efforts are sunk in these stages for not jeopardizing the entire product life-cycle stages. As the stakeholders and the other actors involved in the design process should face low levels of knowledge associated to the system in the conceptual stages, the decision-making process is intrinsically affected by uncertain results. Each choice made in this risky scenario affects the next design iterations, therefore a suitable design approach is needed. Several methodologies have been proposed by both academia and industry in the field of System Engineering (SE). The current trend is to adopt a Model Based System Engineering (MBSE) approach coupled with Concurrent Engineering (CE) paradigms. The model-based methodology overcomes the weaknesses of a document-based one, aggregating all the relevant information and engineering data into a system model, which evolves as the real system throughout all the product life-cycle phases. The systematic CE approach is able to involve several experts in a multidisciplinary working context, where data, ideas, and solutions are shared at the same time using a common platform. Both the approaches help to shorten time and cost of the overall design process and pre- vent possible mistakes which could worsen the final solution if not identified earlier enough, thus maximizing the efficiency of each design session. However, negotiations still result to be as one of the most complicated and frustrating part of the whole design process. Moreover, the recent space exploration scenarios proposed by national agencies are characterized by multiple actors of different extractions, but commonly participating into shaping future goals. The broader is the international cooperation framework, the more complex will be to design a space mission, especially considering the negotiation goals to be handled by the different experts involved. The present Ph.D. thesis is aiming to cast some lights on the integration of Virtual Reality (VR) within the standard design tools to assist the space mission design process. The creation of a virtual model for simulating different features of a system allows to analyse aspects which may be overlooked, especially in the early design phases, such as ergonomics, operations, and training. The intuitive interaction with human senses and the immersion into a 3D Virtual Environment (VE) guarantee fundamental improvements and evaluation of different solutions that are updated in real-time, benefitting the entire design process, especially the early phases. The visualization of different system features at a single glance permits direct data and information exchange, enabling more direct communications among the design team. The possibility to use a distributed and shared architecture, implemented into a standard Concurrent Design Facility (CDF) setup, enhances in-depth analysis even in the product development phase. This unique VE can simulate functional and physical behaviours of the virtual replica, helping to optimize future space systems. To test the VR-based methodology, a first proof of concept has been generated following the recent incremental and evolutionary architecture strategy of considering the Moon as the next step for the human exploration of Mars and the Solar System. According the exploration roadmaps, a permanent surface base is envisioned as an efficient test-bed for assessing critical technologies to be used for future deep-space endeavours. A preliminary mission scenario has been generated which targets to settle the outpost at the lunar south pole. The peculiar environment conditions make the area rich in volatiles to examine and exploit, especially considering the permanently shadowed regions that are supposed to contain icy water deposits, which are of paramount importance for human missions. A closed-loop power system, comprising solar panels, batteries, fuel cells, electrolysers, has been sized ac- cording the settlement power needs. This research work presents an integrated simulation case study that has been run using a VE to arrive at a preliminary estimate of the performance of both the power system and the VR tool. Virtues and vices of the proposed VR-based methodology have been listed together with possible future improvements for this research field.
... CAST (Cargo Accommodation Support Tool, see [64]) was the resulting dedicated software environment, developed for the purpose by Thales Alenia Space, with ESA funding. A modified version of the tool (see [88]) is currently in use, in support of the ISS Columbus Laboratory on-board stowage activity (see ESA www.esa.int/Our_Activities/Human_Spaceflight/Columbus). A brief overview concerning the ATV cargo accommodation problem and the overall approach adopted (by means of CAST) follows, referring the reader to [64], for a detailed exposition. ...
Packing optimization problems have a wide spectrum of real-word applications, including transportation, logistics, chemical/civil/mechanical/power/aerospace engineering, shipbuilding, robotics, additive manufacturing, materials science, mineralogy, molecular geometry, nanotechnology, electronic design automation, very large system integration, pattern recognition, biology, and medicine. In space engineering, ever more challenging packing optimization problems have to be solved, requiring dedicated cutting-edge approaches.
... Another critical aspect of crewed space mission is stowage and payload accessibility: optimization is desirable to not waste time in retrieving objects and tools, and to operate with them. Successful examples of VR implementation in this field are confirmed by[32][33][34]. The VR technologies are becoming more and more efficient, as it was reported in the previous examples: we do strongly believe that integrating virtual tools in some phases of the product life cycle, including operations and training, could results in major benefits, even though their implementation in standardized industrial process is not yet simple. In this paper we describe a possible VR proof-of-concept to be adopted for a permanent lunar base design. ...
The Moon has again been considered as the starting point for human exploration of the Solar System since few years. National space agencies raise the attention to build up a lunar base station by 2030: according to ESA Technology Roadmaps for Exploration this should be the result of a broad international cooperation. Taking into account an incremental approach to reduce risks and costs of space missions, a lunar outpost can be considered as a test bed towards Mars, allowing to validate enabling technologies, such as water processing, waste management, power generation and storage, automation, robotics and human factors. Our natural satellite is rich in resources that could be used to pursue such goal through a necessary assessment of ISRU techniques. The aim of this research is the analysis of a Moon outpost dedicated to the validation of enabling technologies for human space exploration. Starting from the mission statement, main building blocks of the outpost are identified and feasible evolutionary scenarios are depicted, to highlight the incremental steps to build up the outpost. Main aspects that are dealt with include outpost location and architecture, as well as ISRU facilities, which in a far term future can help reduce the mass at launch, by producing hydrogen and oxygen for consumables, ECLSS and propellant for Earth-Moon sorties and Mars journeys. A test outpost is implemented in a Virtual Reality (VR) environment as a first proof-of-concepts, where the elements are a computer-based mock-ups. The VR facility has a first-person interactive perspective, allowing for specific in-depth analyses of ergonomics and operations. The feedbacks of these analyses are crucial to highlight requirements that might otherwise be overlooked, while their general outputs are fundamental to write down procedures. Moreover the mimic of an astronaut in EVA is useful for pre-flight training, but can also represent an additional tool for failures troubleshooting during the flight controllers nominal operations. This unique simulation environment may offer the largest suite of benefits during the design and development phase, as it allows to design future systems to optimize operations, thus maximizing the mission's scientific return, and to enhance the astronauts training, by saving time and cost. The paper describes how a virtual environment could help to design a Moon outpost for an incremental architecture strategy towards Mars missions.
... Many of the simplest packing models are directly scalable: they lead to GO problems with a quadratically increasing number of non-convex constraints as a function of the number of simple packing objects like points or circles. Let us emphasize that realworld packing applications such as the ones discussed by Fasano (2008), and Fasano et al. (2010) are often far more difficult than the most well-known " highly idealized " challenges. Here we shall discuss general (non-uniform size) circle packings, as one of the well-known test problems. ...
... Many of the simplest packing models are directly scalable: they lead to GO problems with a quadratically increasing number of non-convex constraints as a function of the number of simple packing objects like points or circles. Let us emphasize that realworld packing applications such as the ones discussed by Fasano (2008), and Fasano et al. (2010) are often far more difficult than the most well-known " highly idealized " challenges. Here we shall discuss general (non-uniform size) circle packings, as one of the well-known test problems. ...
The general satellite component layout optimization problems have always focused on satellites with fixed module size, and each component is limited to a specific module or panel. In actual engineering practice, dimensions of microsatellite are no longer constrained strictly, but adjustable within an allowed range. The assignment of the components and the dimensions of the modules should be considered as variable to get better global performance. In this paper, a TS+DE+AFT hybrid algorithm is proposed to solve this component assignment and layout optimization problem for multi-module microsatellite (CALO-MM) considering variable module size, in which tabu search (TS) is mainly used to assign components to the appropriate module, and differential evolution (DE) is used to optimize the layout of the components in each module. An adaptive fine-tuning (AFT) strategy is applied to dynamically adjust the length and height of modules within a maximum envelope size. Demonstration and engineering cases are studied to verify the effectiveness of proposed hybrid algorithm.
Quite a demanding task frequently arises in space engineering, when dealing with the cargo accommodation of modules and vehicles. The objective of this effort usually aims at maximizing the loaded cargo, or, at least, at meeting the logistic requirements posed by the space agencies. Complex accommodation rules are supposed to be taken into account, in compliance with strict balancing conditions and very tight operational restrictions. The context of the International Space Station (ISS) has paved the way for a relevant research and development activity, providing the company with a remarkable expertise in the field. CAST (Cargo Accommodation Support Tool) is a dedicated in-house software package (funded by the European Space Agency, ESA, and achieved by Thales Alenia Space), to carry out the whole loading of the Automated Transfer Vehicle (ATV). An ad hoc version, tailored to the Columbus (ISS attached laboratory) on-board stowage issue, has been further implemented and is to be used from now on. This article surveys the overall approach followed, highlighting the advantages of the methodology put forward, both in terms of solution quality and time saving, through an overview of the outcomes obtained to date. Insights on possible extensions to further space applications, especially in the perspective of the paramount challenges of the near future, are, in addition, presented.
The International Space Station (ISS) is one of the most challenging currently ongoing space programs. It has led to a number of very demanding logistic issues, in particular in relation to the on-orbit maintenance and resource resupply.
A fleet of launchers and vehicles is periodically made available by the most prominent space agencies in order to serve this scope. An overall traffic plan schedules the recurrent upload and download interventions. The relevant Cargo Manifest (delivered by NASA) establishes, for each carrier launch and re-entry, the shipment that is supposed to be transported from Earth to orbit and vice versa.
The European Space Agency (ESA) contributed annually to the ISS logistics from 2008 to 2014, by accomplishing five Automated Transfer Vehicle (ATV) missions. The ATV transportation system was conceived to support the recurrent upload phases from Earth to the ISS.
Within the relevant cargo accommodation context, in addition to tight balancing conditions, intricate three-dimensional packing issues arose. Furthermore, besides the remarkable complexity related, per se, to the loading aspects, very strict deadlines were usually imposed to accomplish the task. Last minute upgrades or even significant changes, moreover, often were expected to take place.
CAST (Cargo Accommodation Support Tool) is a dedicated optimization framework, funded by ESA and developed by Thales Alenia Space to carry out the whole analytical ATV cargo accommodation. This chapter describes the ATV loading problem first. The basic concept of CAST is further outlined, highlighting the advantages of the methodology adopted, both in terms of solution quality and time saving. Current extensions and possible future enhancements are investigated.
The theory and methodology of finding the best possible solution to a broad range of optimization problems has been of interest since the beginnings of modern operations research. The key theoretical results regarding important model types and algorithmic frameworks have been followed by optimization software implementations that are used to handle a large and still growing variety of applications. Our discussion is focused on the practice of nonlinear—specifically including also global and mixed integer optimization, in the context of space engineering applications. We review some of the prominent solution approaches, model development tools, and software implementations of optimization (solver) engines and then relate our discussion to selected applications in space engineering. The review portion of this work cites contributions by our coauthors to the present volume (Fasano and Pintér, Modeling and Optimization in Space Engineering, Springer Science + Business Media, New York, 2012) while also drawing on an extensive list of other sources.
This chapter discusses a research activity recently carried out by Thales Alenia Space, to support International Space Station (ISS) logistics. We investigate the issue of adding a number of virtual items (i.e. items not given a priori) inside partially loaded containers, in order to exploit the volume still available on board as much as possible. Items already accommodated are supposed to be tetris-like, while the additional virtual items are assumed to be parallelepipeds. A mixed-integer non-linear programming (MINLP) model is introduced first, then possible linear (MILP) approximations are discussed, and a corresponding heuristic solution approach is proposed. Guidelines for future research are highlighted, and experimental insights are provided to show the efficiency of the proposed approach.
Our strategic objective is to develop a broadly categorized, expandable collection of test problems, to support the benchmarking
of nonlinear optimization software packages in integrated technical computing environments (ITCEs). ITCEs—such as Maple, Mathematica, and MATLAB—support concise, modular and scalable model development: their built-in documentation and visualization features
can be put to good use also in test model selection and analysis. ITCEs support the flexible inclusion of both new models
and general-purpose solver engines for future studies. Within this broad context, in this article we review a collection of
global optimization problems coded in Mathematica, and present illustrative and summarized numerical results obtained using the MathOptimizer Professional software package.
The MathOptimizer Professional software package combines Mathematica's modeling capabilities with an external solver suite for general nonlinear – global and local – optimization. Optimization models formulated in Mathemat-ica are directly transferred along to the solver engine; the results are seam-lessly returned to the calling Mathematica document. This approach combines the advantages of a high-level modeling system with the Lipschitz Global Optimizer (LGO) algorithm system that has been in use for over a decade.
We consider the problem of orthogonally packing a given set of rectangular-shaped boxes into the minimum number of three-dimensional rectangular bins. The problem is NP-hard in the strong sense and extremely difficult to solve in practice. We characterize relevant subclasses of packing and present an algorithm which is able to solve moderately large instances to optimality. Extensive computational experiments compare the algorithm for the three-dimensional bin packing when solving general orthogonal packings and when restricted to robot packings.
This paper considers packing problems with balancing conditions and items consisting of clusters of parallelepipeds (mutually orthogonal, i.e. tetris -like items). This issue is quite frequent in space engineering and a real-world application deals with the Automated Transfer Vehicle project (funded by the European Space Agency), at present under development. A Mixed Integer Programming (MIP) approach is proposed. The three- dimensional single bin packing problem is considered. It consists of orthogonally placing, with possibility of rotation, the maximum number of parallelepipeds into a given parallelepiped. A MIP formulation of the problem is reported together with a MIP-based heuristic approach. Balancing conditions are furthermore examined, as well as the orthogonal placement (with rotation) of tetris -like items into a rectangular domain.
The problem addressed in this paper is that of orthogonally packing a given set of rectangular-shaped boxes into the minimum number of rectangular bins. The problem is strongly NP-hard and extremely difficult to solve in practice. Lower bounds are discussed, and it is proved that the asymptotical worst-case performance of the continuous lower bound is 1 8 . An exact algorithm for filling a single bin is developed, leading to the definition of an exact branch-and-bound algorithm for the three-dimensional bin packing problem, which also incorporates original approximation algorithms. Extensive computational results, involving instances with up to 60 boxes, are presented: it is shown that many instances can be solved to optimality within a reasonable time limit. 1 Introduction We are given a set of n rectangular-shaped boxes, each characterized by width w j , height h j and depth d j (j 2 J = f1; : : : ; ng), and an unlimited number of identical three-dimensional containers (bins) hav...
This paper focuses on our cargo layout system for an H-II Transfer Vehicle (HTV) and analyzes its capabilities from several perspectives. Careful analysis of our cargo layout system through intensive simulations reveals that the proposed system has the following important capabilities: (1) a reduction in the gap of the HTV's center of gravity without cargo; (2) prior engineering analysis of a cargo layout; (3) support for ground operations; and (4) a reduction in mission cost.
Aerospace industries have largely benefited from technological advances in Virtual Reality and Augmented Reality (VR/AR) simulation, visualization, interaction and mixed reality in various applications areas. Within this contest, the sharing knowledge between technology developers, on ground mission support teams (flight and engineering support teams) and on orbit crew may increasingly drive the definition of future usage scenarios, including systems and payloads maintenance and experimental activities. The paper provides innovative VR/AR design tools and human factors issues enable to increase the effectiveness of the "on orbit "operations in the challenging environment of a human space flight. The approach is based on a "3D immersive virtual scenario" COLUMBUS mock up utilization currently being set up in the Thales Alenia Space -Italia VRLAB at the COSE Centre (CDF) Concurrent Design Facility. The main goal is to enhance the tool suite usability by integrating the software (VR-CAST software and C-CAST software) already used for soft stowage analysis, interfacing a digital mock-up mannequin with human motion simulation software. Human Factors Engineering, in this context, plays a key role in the user needs identification and the tools usability verification process.
We consider the problem of orthogonally packing a given set of rectangular-shaped boxes into the minimum number of three-dimensional rectangular bins. The problem is NP-hard in the strong sense and extremely difficult to solve in practice. We characterize relevant subclasses of packing and present an algorithm which is able to solve moderately large instances to optimality. Extensive computational experiments compare the algorithm for the three-dimensional bin packing when solving general orthogonal packings and when restricted to robot packings.
This paper surveys the basic computational tools which are currently available for the solution of nonlinear programming problems. The intent, however, is not to delimit the research frontiers of Nonlinear Programming theory but rather to consider techniques that have been implemented and are being used to solve practical problems. The discussion is further restricted to methods applicable to broad classes of problems and thus of interest to the generalist. It should be recognized that for specific, highly structured problems specialized techniques may exist which are considerably more efficient.
This paper is the continuation of a previous work (Fasano in 4OR 2: 161–174, 2004), dedicated to a MIP formulation for non-standard 3D-packing issues, with additional conditions. The Single Bin Packing problem (Basic Problem) is considered and its MIP formulation shortly surveyed, together with some possible extensions, including balancing, tetris-like items and non-standard domains. A MIP-based heuristic is proposed to solve efficiently the Basic Problem or any possible extension of it, susceptible to a MIP formulation. The heuristic is a recursive procedure based on a non-blind local search philosophy. The concept of abstract configuration, concerning the relative positions between items, is introduced: the relative positions of items, determined by any abstract configuration, give rise to a feasible solution in an unbounded domain. The heuristic generates a sequence of good
abstract configurations and solves, step by step, a reduced MIP model by fixing the relative positions of items, corresponding to the current abstract configuration.
The number of publications in the area of Cutting and Packing (C&P) has increased considerably over the last two decades. The typology of C&P problems introduced by Dyckhoff [Dyckhoff, H., 1990. A typology of cutting and packing problems. European Journal of Operational Research 44, 145–159] initially provided an excellent instrument for the organisation and categorisation of existing and new literature. However, over the years also some deficiencies of this typology became evident, which created problems in dealing with recent developments and prevented it from being accepted more generally. In this paper, the authors present an improved typology, which is partially based on Dyckhoff’s original ideas, but introduces new categorisation criteria, which define problem categories different from those of Dyckhoff. Furthermore, a new, consistent system of names is suggested for these problem categories. Finally, the practicability of the new scheme is demonstrated by using it as a basis for a categorisation of the C&P literature from the years between 1995 and 2004.
A simulated annealing approach to 3-D packing with multiple constraints. Cosmic Program MFS28700
- R S Daughtrey
R.S. Daughtrey, et al., A simulated annealing approach to 3-D packing with multiple constraints. Cosmic Program MFS28700, Boeing Huntsville AI Center Huntsville, Alabama, 1991.
A MIP approach for solving the stowage problem on-board the International Space Station
- G Fasano
- C Lavopa
- D Negri
- M C Vola
G. Fasano, C. Lavopa, D. Negri, M.C. Vola, A MIP approach for solving the stowage problem on-board the International Space Station, in: 23rd EURO Conference, Bonn, GE, 2009.
Capabilities of a multiagent-based cargo layout system for H-II transfer vehicle
- K Takadama
K. Takadama, et al., Capabilities of a multiagent-based cargo layout system for H-II transfer vehicle, in: 16th IFAC Symposium on Automatic Control in Aerospace, 2004.
A multi-level Mip-based heuristic approach for the cargo accommodation of a space vehicle
- G Fasano
G. Fasano, A multi-level Mip-based heuristic approach for the cargo accommodation of a space vehicle, in: 6th ESICUP Meeting, Valencia, SP, 2009.
Nonlinear programming models: a survey
- R Vanderbei
- D Shanno
MIP-based heuristic for non-standard 3D-packing problems
- Fasano