فهرست مطالب علی حکیمی

The present studt deals with presenting a new method for developing an efficient vision and mission for the aerospace industry. This method is based on the knowledge of future research. Moreover, the advantages of creating a vision and an efficient mission are discussed. After that, the definition of the infrastructure of the mission is stated and a four-fold strategy is stated in this field for the aerospace industry. In addition, the new method of resistant cycle and aerospace industry corridor is proposed based on future research. The above method has proposed a resistant cycle for the ecosystem of the aerospace industry in the face of structural uncertainties. Economic, political and social uncertainties are effective in not realizing the missions of the vision. The present article has pointed out that the upgraded structure for defining the vision and mission is not a one-sided structure of macro-to-micro policies, however it should constantly adapt to the changes in the environment around each of the sub-sectors such as economy, politics, society, knowledge and technology that they have a feedback loop and can constantly receive feedback from the surrounding environment and lead to the improvement of the definition of vision and mission. Along with identifying the needs of the society, it is necessary to create the needs for the future and this issue depends on the science of future research and a cycle resistant to uncertainties. Therefore, this article has overcome the management problems of the aerospace industry by explaining the corridor of the aerospace industry based on future research and designing a cycle resistant to uncertainties

Each warrior and leader tries to anticipate is what the future war will be like. With such knowledge or anticipation of what is the next, leaders can shape and plan for success in the next conflict. Bearing this fact in mind that the future warfare, there is two types of threats for every single country: 1- confronting regional countries threat 2- confronting non-state actors. In this study, researchers want to propose the requirements of ground to ground short range missile systems of Army to confronting both types of threats mentioned above.In this study, were used in order to analyze and prioritize cure methods, statistical methods and Analytic Hierarchical Process (AHP). For solving MCDM in fuzzy environment, in this paper, researchers will use AHP for prioritization missile systems by the fuzzy analytic hierarchy process based on grade value of membership function. Generally, we are given scores by experience of experts to represent judgmental objects. In this paper, from view point of many experts, we will build membership functions of judgment criteria for all sub-items. When the membership function is built, we can calculate the grade value by data of missile performance. From the results of first step, we reached sub-items priorities of requirements of ground-to-ground short-range missile system to confronting both regional countries and non-state actors by analytic hierarchy process method. In the next step we used statistical method to technical analysis and propose ways of developing missile systems by each sub-item.

The Mean Dynamic Topography (MDT) of the seas is a quantity which comes from subtracting the Geoid Height (GH) from the Mean Sea Surface (MSS) at every point on the sea. The direction of geostrophic currents is obtained through the calculation of the MDT slope relative to the Geoid. In this research, a series of GOCE geopotential coefficients resulted from the 4 year collection of GOCE observations was used to estimate the reference geoid height in the Persian Gulf, the Oman Sea and the Indian Ocean, i.e., in the area of interest. Two MDT models data were available at the time of performing this research: Denmark Technical University’s model, named ‘Mean Dynamic Topography of Denmark Technical University 2010’ (MDT_DTU_2010) which has been available on a geographical grid of 2 arc minutes spacing (Knudsen & Andersen, 2010). This model is based on the mean sea surface topography model MSS_DTU_2010 and the 2 month of GOCE geopotential data for the Geoid as the reference surface. The second model is the Mean Dynamic Topography Centre National dEtudes Spatiales collecte localisation satellites 2009 (MDT_CNES_CLS09) with 15 minutes resolution (Rio et al, 2011). This model contains the east-west and north-south geostrophic current components with itself as well. It is based on MSS_CLS01 (Hernandez and Schaeffer, 2001) and 4.5 years of GRACE geopotential data used for the reference geoid.
In this research a new Mean Dynamic Topography (MDT) model with the name of MDT_IAU_TN_2014 is presented. Also, the surface permanent current vectors in a grid with 2 minutes resolutions is computed in the Persian Gulf, the Oman Sea and the north of Indian Ocean. This MDT is formed by a Mean Sea Surface (MSS) model computed from 6 altimetry satellites data (Topex/Poseidon, Jason 1 and 2, ERS 1 and 2 and Geosat Follow-On) and GOCE satellite data with 21 and 4 years ranges in 1992-2013 are calculated. The first step for the Mean Sea Surface (MSS) computation is to calculate the mean of Sea Surface Heights (SSH) along the repeated (in time) sub-tracks of altimetry satellites over the years available in the area of interest. The mean value of SSHs over time in a same track is then called Mean Height (MH). The Basic Radar Altimetry Toolbox (BRAT) version 3.1.0 was used for the MH computation. The correction term includes the tidal periodic variations, physical earth corrections such as troposphere, ionosphere, and sea state biases. All of these corrections are considered from the satellite handbooks T/P (AVISO/ALTIMETRY, 1996), J1 (AVISO and PODAAC USER HANDBOOK, 2012), J2 (OSTM/Jason-2 Products Handbook, 2001), ERS (RA/ATSR products - User Manual, 2001), GFO (GEOSAT Follow-On GDR User's Handbook, 2002). Among altimetry satellites, T/P (J1 and J2) has the highest orbit and longest data sets so it has been selected as a reference for corrections.
To homogenize the spectral of MSS and the Geoid, a truncated Gaussian filter with 1.386 degree radius has been used. MDT results have been compared with two global model and have 0.033 and 0.051 RMS of differences in order. Among altimetry satellites used in this research, J2 and GFO satellites have the ability to measure shallow waters. Hence, the data provided by these satellites in shallow waters, i.e. Persian Gulf are valuable. MHS differences between E1 and T/P are larger than the MHS of other satellites, because there are differences between the two missions, i.e., there are 8 km distances between E1 sub-tracks at equator but long repeatability period of 35 days of data acquisition time and T/P sub-tracks spacing are 315 km at equator and short repeatability period of 9.9 days. Also, the orbit elevations are different: T/P at altitude of 1336 km and E1 at altitude of 785 km. Inclusion of E1 data in the MSS_IAU_TN_2014 solution would globally decrease the RMS difference of the solution relative to the MSS_CNES_CLS_2011 model from 0.4 m (without E1 data) to 0.1 m. This improvement by the E1 data is probably due to the higher resolution of the data in the region of interest.
Changing the filtering radius of 1.386 degree down to lower degrees until 1 degree would increase the MDT_IAU_TN_2014 differences (relative to the MDT_DTU_2010) and MDT_CNES_CLS09 from 0.033m and 0.051m RMS up to larger values. At the 1.386 degree, the differences are minimum. For filtering radiuses of more than 1.386 degree the MDT surface would become unreasonably much smoother and the RMS difference would increase. Geostrophic and Ekman velocity currents using 22 years data of surface wind has been calculated. Total currents of the released model in this research have been compared with OSCAR in-situ data and have 0.047 and 0.031 meter RMS of differences in North-South and East-West current components. The total currents from MDT_IAU_TN-2014 model vary between 0 to 0.61 m/s in the north Indian ocean region. The comparison shows that all three models show almost the same range of variations in the region of interest. SLA an In-Situ data could be used to make the MDT_IAU_TN_2014 independent from any other models. The lack of In-Situ data in the region of interest forced MDT_IAU_TN_2014 to use MDT_DTU_2010 to cover filtered parts. Also using other gravity models with higher Spherical harmonic coefficients degree and orders such as EIGEN-6c and EGM08, would make filtering not needed in the dynamic modeling.