Investigation of nuclear electric powered interstellar precursor missions

Nuclear Electric Propulsion (NEP) is a technology conceptually proposed since the 1940s by E. Stuhlinger in Germany. The JIMO mission originally planned by NASA in the early 2000s produced at least two designs of ion thrusters fed by a 20–30 kW nuclear powerplant. When compared to conventional (chemical) propulsion, the major advantage of NEP in the JIMO context was recognized to be the much higher I_sp (lab-tested at up to 15,000 s) and the capability for sustained power generation, up to 8–10 years when derated to I_sp about 8000 s.The goal of this paper is to show that current or near term NEP technology enables missions far beyond our immediate interplanetary backyard. In fact, by extending the semi-analytical approach used by Stuhlinger, with reasonable ratios α≡power/mass of the propulsion system (i.e., 0.1– 0.4 kW/kg), missions to the Kuiper Belt (40 AU and beyond) and even the so-called FOCAL mission (at 540 AU) become feasible with an attractive payload fraction and in times of order 10–15 years.Further results regarding missions to Sedna’s perihelion/aphelion, and to Oort’s cloud will also be presented, showing the constraints affecting their feasibility and mass budget.     

Crater detection via genetic search methods to reduce image features

Recent approaches to crater detection have been inspired by face detection’s use of gray-scale texture features. Using gray-scale texture features for supervised machine learning crater detection algorithms provides better classification of craters in planetary images than previous methods. When using Haar features it is typical to generate thousands of numerical values from each candidate crater image. This magnitude of image features to extract and consider can spell disaster when the application is an entire planetary surface. One solution is to reduce the number of features extracted and considered in order to increase accuracy as well as speed. Feature subset selection provides the operational classifiers with a concise and denoised set of features by reducing irrelevant and redundant features. Feature subset selection is known to be NP-hard. To provide an efficient suboptimal solution, four genetic algorithms are proposed to use greedy selection, weighted random selection, and simulated annealing to distinguish discriminate features from indiscriminate features. Inspired by analysis regarding the relationship between subset size and accuracy, a squeezing algorithm is presented to shrink the genetic algorithm’s chromosome cardinality during the genetic iterations. A significant increase in the classification performance of a Bayesian classifier in crater detection using image texture features is observed.     

先进机身结构和材料设计

由于大型商用飞机机身结构的复杂性,其碳纤维复合材料部件的设计、制造和取证都不能借用现有的制造维修基本经验.碳纤维复合材料机身壁板超越了现代化金属技术,对应力应变的保守限制要求必须保证将具有损伤容限的机身结构交付到航空公司.这样,碳纤维复合材料壁板技术的应用至少限制了新飞机家族第一代成员的重量.     

Talking space: The European Commission's changing frames in defining Galileo

This paper traces the way in which the European Commission has framed and reframed the issue of EU satellite navigation over 20 years. It investigates how the EU's agenda-setter has ‘talked about’ space policy, with a particular focus on Galileo, and how its own institutional discourse – as revealed in its communications throughout the agenda-setting stage of Galileo's ‘definition’ phase – evolved in the 1990s through the use of ‘frame sets’. In so doing, it illustrates the ways in which, over time, the EU's executive has ‘projected’ the issue of independent satellite navigation capabilities as being politically and economically desirable for Europe, and has sought to persuade decision makers of its cross-policy relevance and potential economic, social and security benefits. The article deconstructs official documents and engages in a close-up analysis of policy formulation, to identify nascent, evolving and mature frames in the definition of Galileo.     

Smart Sensor Web: Web-based exploitation of sensor fusion forvisualization of the tactical battlefield

Smart Sensor Web (SSW) is a recent DUSD (S&T) initiative inspired by extraordinary technological advances in sensors and microelectronics and by the emergence of the Internet as a real time communication tool. The overall vision for SSW is an intelligent, Web-centric distribution and fusion of sensor information that provides greatly enhanced situational awareness, on demand, to warfighters at lower echelons. Emphasis is on multi-sensor fusion of large arrays of local sensors, joined with other assets, to provide real-time imagery, weather, targeting information, mission planning, and simulations for military operations on land, sea, and air. This paper gives an overview of this new initiative, highlights some of the technology challenges in sensor/information Fusion, and presents a program approach for near-term demonstrations and long-term solutions, involving the DoD, National Labs, commercial industry, and academia