Energy Dynamics (Norway)

A graph-based network flow approach to constellation planning is presented that respects spacecraft resources and mission constraints to arrive at a preliminary operational schedule. The method discretizes task fulfillment opportunity windows into graph nodes and then adds edges based on feasibility of transition between these opportunities, either by slew maneuvers or extended-time task fulfillment during downlink operations. Intelligent graph pruning is applied to improve computation performance and provide a versatile planning capability with a minimal impact on the resulting solution. A network flow formulation allows for a simultaneous search for spacecraft plans using a Mixed Integer Linear Program (MILP). The framework enables the definition of appropriate mission constraints to ensure viability and mission efficiency among the constellation of satellites. The planning technique is demonstrated for a mission of 100 satellites to illustrate its capability and performance within this proliferated regime.

Comparisons between machine learning and optimal transport-based approaches in classifying images are made in underwater orbital angular momentum (OAM) communications. A model is derived that justifies optimal transport for use in attenuated water environments. OAM pattern demultiplexing is performed using optimal transport and deep neural networks and compared to each other. Additionally, some of the complications introduced by signal attenuation are highlighted. The Radon cumulative distribution transform (R-CDT) is applied to OAM patterns to transform them to a linear subspace. The original OAM images and the R-CDT transformed patterns are used in several classification algorithms, and results are compared. The selected classification algorithms are the nearest subspace algorithm, a shallow convolutional neural network (CNN), and a deep neural network. It is shown that the R-CDT transformed images are more accurate than the original OAM images in pattern classification. Also, the nearest subspace algorithm performs better than the selected CNNs in OAM pattern classification in underwater environments.

In general, wind farms are constructed in flat terrain. However, in japan, the suitable sites are decreasing, wind farms come to be constructed in complex terrain in recent years. Accordingly, the importance of wind analysis is increasing, because of predicting turbulence intensity depending on complex terrain. In this paper, we performed validation of CFD wind analysis by comparison of measured value in real wind farm and calculated value for the wind farm. For measurement, we use "WINDCUBE", and for numerical simulation, we use "RIAM-COMPACT". The measurement is performed in Nagashima-Kuronoseto wind farm in Nagashima island, Kagoshima prefecture. CFD results appear reproduce the topographic effects, and it is suggested that "RIAM-COMPACT" is able to predict the actual wind affected by complex terrain.

We have studied the effect of sodium on the electrical properties of Cu2ZnSnS4 (CZTS) single crystal by using temperature dependence of Hall effect measurement. The sodium substitution on the cation site in CZTS is observed from the increasing of unit-cell size by powder X-ray diffraction. Sodium increases the effective hole concentration and makes the thermal activation energy smaller. The degree of compensation decreases with sodium incorporation, thus the hole mobility is enhanced. We revealed that sodium is important dopant in CZTS to control the electrical properties.

First-principles calculations of GaAsN surface with low nitrogen (N) content grown by chemical beam epitaxy were performed to theoretically analyze the incorporation process of nitrogen and impurities at the atomic scale. As a result, stable surface structures of GaAsN(001) under hydrogen (H) atmosphere were determined. In these structures, N is suggested to readily substitute into surface sites, especially those that bond with H, compared with in the bulk. This indicates that N is incorporated into a thin film together with H. This may generate H-related defects, which may lead to the degradation of its electric properties. These defects are difficult to minimize by post-annealing processes. Therefore, the amount of H attached to the growth surface should be reduced in order to obtain high-quality crystals. The calculated surface phase diagram suggests that a condition in which the extent of the incorporation of H-related defects can be reduced exists.

As a countermeasure against global warming, a substantial reduction in CO2 emissions has become an urgent issue. Accordingly, the effective use of wind power energy is attracting attention as a clean and environmentally friendly solution. Given this background, we have developed RIAM-COMPACT【○!R】 (Research Institute for Applied Mechanics, Kyushu University, COMputational Prediction of Airflow over Complex Terrain, a non-stationary, non-linear wind synopsis simulator that is capable of predicting the optimum sites for wind turbine construction to the pin-point level within a target area of a few km or less. In this study, a high resolution micro-siting of 100kW wind-lens turbines, considering the land preparation, was performed in the new campus of Kyushu University.

The Satellite Data Model (SDM) developed at Utah State University (USU) is a plugand-play system for satellites. An xTEDS must be written for each sensor device that participates with the SDM. An interface module called an Appliqu e Sensor Interface Module (ASIM) must be developed to interface between the SDM and the sensor device. The program code that runs on an ASIM can be di cult to develop. This paper presents a technique for automatically generating ASIM program code by extrapolating the needed information from the sensor device’s xTEDS. This technique has been implemented in a tool called the ASIM Wizard. The ASIM Wizard reduces the time and e ort required to develop an ASIM.

New research initiatives are being dedicated to the task of developing the procedures and technologies necessary to apply structural health monitoring methods to space structures for pre-launch assessment for the goal of truncating assembly, integration and testing times from months to days. One of the most time consuming tasks is structural flight qualification testing. Traditionally, this testing provides an excellent stress test for the structure but, in addition to being lengthy, it has poor localization of abnormalities. The most common sources for structural inadequacy develop at fastener interfaces, such as bolted connections. To manage these issues, structural health monitoring is being considered as a means of locating potential problems and to verify the structure through self-diagnostic techniques during assembly intervals. It is envisioned that this option could allow traditional tests to be omitted or significantly reduced. Piezoelectric wafer active sensors are utilized on a satellite panel where off-nominal clamping force is simulated by insufficiently loaded bolts. The method is also inspected for reliability, limitations, and hardware requirements to validate the techniques capability. Preliminary experimental results show that loose bolts can be detected and localized.