Conceptual design of a bioregenerative life support system containing crops and silkworms

This article summarizes a conceptual design of a bioregenerative life support system for permanent lunar base or planetary exploration. The system consists of seven compartments – higher plants cultivation, animal rearing, human habitation, water recovery, waste treatment, atmosphere management, and storages. Fifteen kinds of crops, such as wheat, rice, soybean, lettuce, and mulberry, were selected as main life support contributors to provide the crew with air, water, and vegetable food. Silkworms fed by crop leaves were designated to produce partial animal nutrition for the crew. Various physical-chemical and biological methods were combined to reclaim wastewater and solid waste. Condensate collected from atmosphere was recycled into potable water through granular activated carbon adsorption, iodine sterilization, and trace element supplementation. All grey water was also purified though multifiltration and ultraviolet sterilization. Plant residue, human excrement, silkworm feces, etc. were decomposed into inorganic substances which were finally absorbed by higher plants. Some meat, ingredients, as well as nitrogen fertilizer were prestored and resupplied periodically. Meanwhile, the same amount and chemical composition of organic waste was dumped to maintain the steady state of the system. A nutritional balanced diet was developed by means of the linear programming method. It could provide 2721 kcal of energy, 375.5 g of carbohydrate, 99.47 g of protein, and 91.19 g of fat per capita per day. Silkworm powder covered 12.54% of total animal protein intakes. The balance of material flows between compartments was described by the system of stoichiometric equations. Basic life support requirements for crews including oxygen, food, potable and hygiene water summed up to 29.68 kg per capita per day. The coefficient of system material closure reached 99.40%.     

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.     

可靠性设计优化的球空间设计法

可靠性设计优化（RBDO）在航空航天等领域已经被广泛应用,具有显著提高可靠性的效果;然而它包含两个迭代循环-总体优化循环和可靠性分析循环,双循环求解方法效率低下甚至难以承受。本文提出一种可以提高可靠性设计优化求解效率的方法-球空间设计法,该方法可以方便地表达搜索区域,最大可能失效点可以从极值点处精确获取;同时,该方法可以将总体优化以及可靠性分析同步进行。本文所提出的球空间法的有效性将通过2个算例进行测试,测试结果表明该方法不仅精度与同类方法持平,求解效率有明显提升,它将会对提高航空航天装备如卫星、火箭、飞行器等产品的可靠性提供更为有效的方法和技术支持。     

低压断路器灭弧室温度检测

设计了基于光纤光栅传感系统的低压断路器灭弧室温度检测装置,实验测量出灭弧室温度数据,进行了数据的有限元分析,绘制出灭弧室内温度场分布图.     

超声速燃烧凹槽火焰稳定的研究动态

高超声速气流在燃烧室的停留时间非常短，使得超燃冲压发动机燃烧室内燃料与气流的混合及其燃烧变得非常困难。目前集燃料喷射、混合及火焰稳定为一体的凹槽有望改进这一情况而受到了普遍关注。介绍了超声速气流流过凹槽的自激振荡及其控制、停留时间和阻力等特性，总结、分析了近几年凹槽在超声速气流中增强混合及燃烧的实验与数值研究，指出了在把凹槽用于提高超燃冲压发动机性能方面存在的问题和进一步研究的方向。     

基于SFEM的SRM纤维缠绕结构的可靠性分析

采用纽曼级数展开的蒙特卡罗随机有限元方法(SFEM),分析了固体火箭发动机(SRM)复合材料缠绕的燃烧室在内压正态变化下的应力响应,然后利用应力强度干涉原理分析计算其可靠性.     

超燃冲压发动机缩比燃烧室流场数值模拟

为了采用二维N-S方程来研究带有垂直喷射的三维问题,即拓展二维模型的适用范围,提出了一种针对喷射的简化模型,即采用源项加质来近似模拟喷射的质量添加。为了验证这种简化的可行性,针对文献中的实验条件进行了对比计算。结果表明,数值模拟与实验点符合得较好。运用以上简化模型,对放置在自由射流实验台上的缩比超燃冲压发动机燃烧室流场,采用五组元单步反应模型进行了数值模拟,得到了各主要气动参数及组分质量分数的分布,表明,根据数值模拟所得到的壁面静压值与实验壁面压力符合得较好。      

冷却剂不同流动方式对膨胀循环推力室再生冷却换热的影响

为了解液体火箭发动机膨胀循环推力室再生冷却换热特性,对某一参考发动机推力室和另外两种面积比的膨胀循环推力室建立三维计算模型,采用数值模拟的方法,考察冷却剂的温升、冷却通道压降以及推力室内壁面温度和热流密度的分布情况.重点比较了不同燃烧室圆柱段长度、冷却剂不同流动方式以及不同面积比对以上结果的影响.计算过程中采用二阶迎风格式离散控制方程.计算结果表明:采用逆流冷却时,通过加长推力室圆柱段长度使推力室受热面积增加70%后,冷却剂温升提高了一倍左右;对膨胀循环推力室进行再生冷却时,采用顺流冷却要比逆流冷却的冷却通道压降低,但同时冷却剂温升也较低,并且对喉部壁面的冷却效果较差.     

流线追踪Busemann进气道设计参数的选择

为了研究型面设计马赫数、唇口偏移量对流线追踪Busemann进气道设计点性能的影响规律,寻求最佳性能的进气道,对设计马赫数为6,具有不同型面设计马赫数和唇口偏移量的流线追踪进气道进行了数值模拟。研究表明:选取低于马赫数6的型面设计马赫数,可获得较高的流量系数和增压比,而其压缩效率并不低;进气道唇口偏移量增大,会导致流量系数、增压比变小,但却有利于减小进气道内的分离程度,还会影响隔离段内的流动,因此唇口偏移量的选取需要综合考虑。     

非线性主轴降维映射法在固体火箭发动机设计优化中的应用

为在二维或三维空间中表达固体火箭发动机高维设计空间,引入非线性主轴降维映射法对多维非线性设计优化问题进行降维处理。以某大型固体火箭发动机设计问题为例,将10变量4有效约束优化问题降维映射到二维空间进行研究,拟合的非线性主轴降维映射模型中,目标函数和约束函数的相对误差控制在1.5%以内。研究表明,非线性主轴降维映射法具有发现多变量非线性优化数学模型本征特性的特点,能对设计变量重要性排序;通过降维展示设计空间全景,为优化算法和优化初始点优选提供了直观、有力的工具;优化轨迹实时展示为优化算法性质研究及算法切换提供了依据;根据优化轨迹从优化结果在降维空间中的位置能够判断优化结果是否具有全局最优解特性。