Science operations planning expertise: A neglected component of mission design

In this paper, Science Operations Planning Expertise (SOPE) is defined as the expertise that is held by people who have the two following qualities. First they have both theoretical and practical experience in operations planning, in general, and in space science operations planning in particular. Second, they can be used, on request and at least, to provide with advice the teams that design and implement science operations systems in order to optimise the performance and productivity of the mission. However, the relevance and use of such SOPE early on during the Mission Design Phase (MDP) is not sufficiently recognised. As a result, science operations planning is often neglected or poorly assessed during the mission definition phases. This can result in mission architectures that are not optimum in terms of cost and scientific returns, particularly for missions that require a significant amount of science operations planning. Consequently, science operations planning difficulties and cost underestimations are often realised only when it is too late to design and implement the most appropriate solutions. In addition, higher costs can potentially reduce both the number of new missions and the chances of existing ones to be extended. Moreover, the quality, and subsequently efficiency, of SOPE can vary greatly. This is why we also believe that the best possible type of SOPE requires a structure similar to the ones of existing bodies of expertise dedicated to the data processing such as the International Planetary Data Alliance (IPDA), the Space Physics Archive Search and Extract (SPASE) or the Planetary Data System (PDS). Indeed, this is the only way of efficiently identifying science operations planning issues and their solutions as well as of keeping track of them in order to apply them to new missions. Therefore, this paper advocates for the need to allocate resources in order to both optimise the use of SOPE early on during the MDP and to perform, at least, a feasibility study of such a more structured SOPE.     

狮子王辛巴的荣耀

寒流袭击的那天,没有冬天的广州突然出奇的寒冷。面对中国百年不遇的寒冷天气,我选择了逃离。连续飞行了14小时,穿越了5个时区,我降落在南半球被阳光燃烧着的肯尼亚首都内罗毕(NAIROBI)。我和一个中国人以及两个法国人,带上本地的黑人司机、厨师和充足的食品、水以及扎营设备,开着那辆带天窗的专业狩猎远征(SAFARI)越野车,做一次彻底的狩猎远征。     

伊朗 谜一样的国度

电视中,每天都有关于伊朗的报道,伴随美国要打击伊朗的叫嚣,让人有种大战迫在眉睫的紧张。我唯恐伊朗再不去,这个国家就会像伊拉克一样,彻底改变当今的面貌。于是在好友的帮助下,展开了这次向往已久的伊朗之行。     

THE JOINT SCIENCE OPERATIONS CENTRE

The Joint Science Operations Centre (JSOC) has been established to provide the operational interface between the Instrument Principal Investigators (PIs) and the European Space Operations Centre (ESOC). Its key task will be to merge inputs from the Cluster instrument teams and to generate the coordinated command schedule for operation of the scientific payload. In addition, it will collect and process data needed to plan those operations and will monitor the performance of the mission and individual instruments. This paper outlines the JSOC subsystems that have been built to carry out these tasks and highlights points of scientific or technical interest within these systems.     

Generic procedure for designing and implementing plan management systems for space science missions operations

This paper is one of the components of a larger framework of activities whose purpose is to improve the performance and productivity of space mission systems, i.e. to increase both what can be achieved and the cost effectiveness of this achievement. Some of these activities introduced the concept of Functional Architecture Module (FAM); FAMs are basic blocks used to build the functional architecture of Plan Management Systems (PMS). They also highlighted the need to involve Science Operations Planning Expertise (SOPE) during the Mission Design Phase (MDP) in order to design and implement efficiently operation planning systems. We define SOPE as the expertise held by people who have both theoretical and practical experience in operations planning, in general, and in space science operations planning in particular. Using ESA’s methodology for studying and selecting science missions we also define the MDP as the combination of the Mission Assessment and Mission Definition Phases. However, there is no generic procedure on how to use FAMs efficiently and systematically, for each new mission, in order to analyse the cost and feasibility of new missions as well as to optimise the functional design of new PMS; the purpose of such a procedure is to build more rapidly and cheaply such PMS as well as to make the latter more reliable and cheaper to run. This is why the purpose of this paper is to provide an embryo of such a generic procedure and to show that the latter needs to be applied by people with SOPE during the MDP. The procedure described here proposes some initial guidelines to identify both the various possible high level functional scenarii, for a given set of possible requirements, and the information that needs to be associated with each scenario. It also introduces the concept of catalogue of generic functional scenarii of PMS for space science missions. The information associated with each catalogued scenarii will have been identified by the above procedure and will be relevant only for some specific mission requirements. In other words, each mission that shares the same type of requirements that lead to a list of specific catalogued scenarii can use this latter list of scenarii (regardless of whether the mission is a plasma, planetary, astronomy, etc. mission). The main advantages of such a catalogue are that it speeds-up the execution of the procedure and makes the latter more reliable. Ultimately, the information associated to each relevant scenario (from the catalogue or freshly generated by the procedure) will then be used by mission designers to make informed decisions, including the modification of the mission requirements, for any missions. In addition, to illustrate the use of such a procedure, the latter is applied to a case study, i.e. the Cross-Scale mission. One of the outcomes of this study is an initial set of generic functional scenarii. Finally, although border line with the above purpose of this paper, we also discuss multi-spacecraft specific issues and issues related to the on-board execution of the plan update system (PUS). In particular, we show that the operation planning cost of N spacecraft is not equal to N times the cost of 1 spacecraft and that on-board non-synchronised operation will not require inter-spacecraft communication. We also believe that on-board PUS should be made possible for all missions as a standard.