Unmanned Space Vehicle Research Articles

Projectile fragmentation and debris cloud formation behaviour of wavy plates in hypervelocity impact

Continuously increasing micro meteorite and orbital debris (MMOD) in space poses a threat to any manned or unmanned space vehicle with increasing probability of damaging object impact. To address the sufficient level of protection of space vessels, many Whipple shield configurations has been studied for over half a century. Bumper plate of Whipple shields studied in existing literature are flat surfaced plates. In contrast to earlier studies, this paper investigates the reaction of bumper plates with wavy surfaces against hypervelocity impact by analysing how they contribute to projectile fragmentation, formation of debris cloud, and how they dissipate the impact energy. Aluminium plates with four different surface wave profiles (WPs) were numerically investigated under hypervelocity impact conditions to assess their performance on disintegration of the impacting projectile. Fragmentation patterns of spherical aluminium projectile and debris cloud generated by projectile-wavy plate couples were examined and compared with the equivalents observed in flat-surfaced plate impact. A hybrid Smoothed Particle Hydrodynamics (SPH) combined with finite element modelling (FEM) approach was adopted using ANSYS software to simulate hypervelocity impact phenomenon at 3 km/s. Results of the numerical work carried out in this study revealed the distinctive debris cloud generation that has never been reported before in the existing literature. Furthermore, compared to the flat plate, wavy plates are found to be more effective in decreasing the impact energy.

Global/local finite element analyses supporting the design of a ceramic matrix composite wing leading edge of a re-entry vehicle

The thermo-structural design of critical components for re-entry vehicles (e.g. nose and wing leading edge) requires the adoption of very detailed and complex finite element thermal and mechanical analyses. Indeed, since very high heat fluxes are expected during the atmospheric re-entry, Ceramic Matrix Composites (CMC) are usually employed because they can guarantee lightness, high damage tolerance, crack/fracture resistance, high tensile, bending and compression strength aside from high temperature stability (1900 °C) and excellent thermal shock resistance. However, such materials, characterized by a complex micro-structure, require demanding numerical tools involving very high computational costs. For this reason, embedded Global/Local and sub-modelling approaches need usually to be employed in order to obtain high level of accuracy, especially in the most critical areas of the components, with a significant saving of the computational cost. These efficient numerical tools allow to perform detailed numerical analyses even in a preliminary design phase where very coarse global models are usually adopted. In the present work, embedded Global/Local finite element models and sub-models are defined with the aim to improve the design of the Wing Leading Edge of an hypersonic vehicle. The aerodynamic heating, experienced along the re-entry trajectory of the CIRA Unmanned Space Vehicle FTB-X has been used as loading condition for the wing leading edge design. Local models have been defined at the interfaces between the internal and the external structure, where structural criticalities are expected, and the corresponding numerical results have been assessed and compared. Finite element commercial environments have been adopted for the numerical computations.

Conceptual Design of a Reusable Unmanned Space Vehicle Using Multidisciplinary Optimization

In this paper, a conceptual design for a reusable unmanned space vehicle was studied with multiple objective functions. To achieve this goal, a multi-objective genetic algorithm was used, and the performance of the space vehicle was evaluated based on weight, propulsion, aerothermodynamics, and trajectory analysis. Minimization of weight and landing speed and maximization of the highest CL in the supersonic flight regime were selected as the objective functions. The maximum limits in the dynamic pressure and the heat flux were applied as constraints. All objective functions are in trade-off relationships with each other. The geometry that produced the smallest weight had a very small wing size. Also, the vehicle that had the maximum CL in the supersonic flight regime had a closer angle between the flow and the lower surface of the wing, which showed the highest CL on the flat surface. The vehicle design with the lowest landing speed had the largest wing, which generated sufficient lift.

Advanced Flight Management System for an Unmanned Reusable Space Vehicle

Sangam M, Sabatini R, Ramasamy S and Gardi A. (2013). Advanced flight management system for an unmanned reusable space vehicle. International Journal of Unmanned Systems Engineering. 1(3): 48-67. The innovative architecture of an advanced Flight Management System (FMS) for Unmanned Reusable Space Vehicle (URSV) applications is presented with the associated re-entry trajectory computation algorithm. The SL-12 unmanned space vehicle, developed by Cranfield University as a part of the 2012-2013 Aerospace Vehicle Design (AVD) Group Design Project (GDP) is used as the reference platform. The overall avionics architecture of the future space transportation vehicle is described. A detailed architecture is developed for the FMS and the core functions of such an FMS are described. A dedicated computation algorithm is presented for re-entry trajectory planning, which involves determination of the path of re-entry vehicle by means of angle of attack and bank angle modulation. Simulation case studies are performed in a realistic re-entry operational scenario resulting in the generation of efficient and feasible trajectories, without violating any of the defined constraints. © Marques Engineering Ltd.

Robust Design of a Reentry Unmanned Space Vehicle by Multifidelity Evolution Control

This paper addresses the preliminary robust design of a small/medium–scale reentry unmanned space vehicle. A hybrid optimization technique is proposed that couples an evolutionary multi-objective algorithm with a direct-transcription method for optimal control problems. Uncertainties on the aerodynamic forces and vehicle mass are integrated in the design process, and the hybrid algorithm searches for geometries that 1) minimize the mean value of the maximum heat flux, 2) maximize the mean value of the maximum achievable distance, and 3) minimize the variance of the maximum heat flux. The evolutionary part handles the system-design parameters of the vehicle and the uncertain functions, while the direct-transcription method generates optimal control profiles for the reentry trajectory of each individual of the population. During the optimization process, artificial neural networks are used to approximate the aerodynamic forces required by the direct-transcription method. The artificial neural networks are trained and updated by means of a multifidelity, evolution-control approach.

Identification from Flight Data of the Italian Unmanned Space Vehicle

Identification methodologies for processing flight data are frequently used to validate and improve a pre-flight aerodynamic data-base and, specifically, to reduce the associated uncertainties. This paper describes the process applied for the identification of the aerodynamic model of the Italian Unmanned Space Vehicle. The identification problem is solved through a multi-step approach, where the aerodynamic coefficients are identified first and, in a following phase, a set of model parameters are updated. The methodology was applied to actual flight data, gathered during the second flight test performed by the Italian Aerospace Research Centre.

Robust multi-fidelity design of a micro re-entry unmanned space vehicle

This article addresses the preliminary robust design of a small-scale re-entry unmanned space vehicle by means of a hybrid optimization technique. The approach, developed in this article, closely couples an evolutionary multi-objective algorithm with a direct transcription method for optimal control problems. The evolutionary part handles the shape parameters of the vehicle and the uncertain objective functions, while the direct transcription method generates an optimal control profile for the re-entry trajectory. Uncertainties on the aerodynamic forces and characteristics of the thermal protection material are incorporated into the vehicle model, and a Monte-Carlo sampling procedure is used to compute relevant statistical characteristics of the maximum heat flux and internal temperature. Then, the hybrid algorithm searches for geometries that minimize the mean value of the maximum heat flux, the mean value of the maximum internal temperature, and the weighted sum of their variance: the evolutionary part handles the shape parameters of the vehicle and the uncertain functions, while the direct transcription method generates the optimal control profile for the re-entry trajectory of each individual of the population. During the optimization process, artificial neural networks are utilized to approximate the aerodynamic forces required by the optimal control solver. The artificial neural networks are trained and updated by means of a multi-fidelity approach: initially a low-fidelity analytical model, fitted on a waverider type of vehicle, is used to train the neural networks, and through the evolution a mix of analytical and computational fluid dynamic, high-fidelity computations are used to update it. The data obtained by the high-fidelity model progressively become the main source of updates for the neural networks till, near the end of the optimization process, the influence of the data obtained by the analytical model is practically nullified. On the basis of preliminary results, the adopted technique is able to predict achievable performance of the small spacecraft and the requirements in terms of thermal protection materials.

On-line guidance with trajectory constraints for terminal area energy management of re-entry vehicles

In this article, an on-line guidance strategy for terminal area energy management phase of a re-entry flight is proposed. In order to fulfil the objectives of this flight phase, the algorithm continuously performs long- and short-term on-line trajectory generation, also accounting for the most relevant vehicle and trajectory constraints. Long-term guidance computes a reference trajectory which minimizes the distance from the final target. Short-term guidance generates the control commands by computing a trajectory that minimizes the displacement from the reference one, thus compensating for the errors due to the environmental disturbances and to the uncertainties of the vehicle model. In the proposed guidance strategy, the main vehicle performance constraints are appropriately accounted for, thus guaranteeing adaptivity in the failure situations where the manoeuvring capabilities are reduced. The proposed guidance strategy has been developed in the framework of the unmanned space vehicle program of the Italian Aerospace Research Centre for the execution of Dropped Transonic Flight Test second mission. In this article, the algorithm performances and robustness to the vehicle initial state have been assessed through a preliminary Monte Carlo analysis. Furthermore, several simulations with bank angle and angle of attack limitations have shown the effectiveness of the algorithm in the presence of reduced manoeuvring capabilities.

Analysis of Aerodynamic Performances of Experimental Flying Test Bed in High-Altitude Flight

An aerodynamic, computational study has been performed on the 3.9.2_FW50 configuration of the winged experimental flying test bed (FTB-X) of an experimental unmanned space vehicle in the altitude interval 90—110 km, where the vehicle is in transitional regime. The range of the angle of attack was 0—40° and the side slip angle was 15°. The flow field has been solved by the three-dimensional (3D) direct simulation Monte Carlo (DSMC) code: DS3V. The results showed better aerodynamic behaviour both in symmetric and in side-slip flights, but worst longitudinal stability in symmetric flight with respect to the previous version of FTB-X (1.1.2). In fact, both the aerodynamic efficiency and the derivative of pitching moment coefficient in symmetric flight increased. Furthermore, a preliminary analysis about the possibility of an aerodynamic control of the vehicle by deflection of a trailing edge flap has been fulfilled. This analysis has been carried out in terms of the lift and drag forces and pitching moment at the altitude of 70 km in the range of the angle of attack 0—30° and flap deflection 0—30°. The flow field has been solved by a 2D DSMC code (DS2V) and computational fluid dynamic code (H3NS). A thermal analysis has been also carried out for evaluating the heat flux on the flap. This heat flux is comparable with that at the nose stagnation point, and therefore a thermal protection system should be necessary also on the flap. The effect of the flap deflection on the flow separation has been also evaluated. In particular, at high flap deflection angle, the shock wave boundary layer interaction produces a decrease of the airfoil aerodynamic efficiency. Therefore, the increases of lift and drag of the aerodynamic force, as functions of the flap deflection angle, encourage performing similar tests considering the whole vehicle.

CFD rebuilding of USV-DTFT1 vehicle in-flight experiment

The aim of this paper is to present some numerical rebuilding results of the in-flight aerodynamic experiment carried out during the first mission Dropped Transonic Flight Test (DTFT) of the Italian Aerospace Research Centre (CIRA) Unmanned Space Vehicle (USV). USV is a multi-mission, re-usable vehicle developed at CIRA and it is funded by the Italian National Aerospace Research Program (PRO.R.A.). The first mission was performed at the end of February 2007, and it was aimed at experimenting the transonic flight of a re-entry vehicle. One of the aims of the aerodynamic experiment is the validation and improvement of the prediction tools (CFD, extrapolation to flight) through the comparison between pre-flight predictions and in-flight measured data. Some selected flight conditions occurred during the DTFT mission have been numerically rebuilt aimed at reproducing the most relevant fluid dynamic phenomena characterizing the USV vehicle aerodynamics. The analysis of numerically rebuilt flight conditions has allowed the assessment of local non-linear phenomenologies and, depending on both the analysis of the numerical results and the comparison with the flight data, an assessment of the entire CFD methodology.

New Algorithm for Probabilistic Robustness Analysis in Parameter Space

In this paper a new algorithm for robustness analysis of uncertain parametric systems is proposed. The algorithm adopts a probabilistic approach to find a multidimensional region in the uncertainty parameter space where a system satisfies a given property. In particular it finds a (suboptimal) maximum volume hyper-rectangle in which the given system’s property is satisfied with a pre-assigned confidence. The algorithm has been applied for the robustness analysis of the Italian Aerospace Research Centre’s unmanned space vehicle demonstrator’s maneuverability. The use of the algorithm during the design phase of the project lowered the effort spent in aerodynamic wind tunnel testing on specific coefficients that did not require the reduction of the uncertainty ranges. Moreover the algorithm has been used for estimating the flying test bed’s initial state displacement compatible with a safe mission execution to support online launch decisions. Effectiveness of the proposed method in terms of computational efficiency and reliability has been demonstrated by comparing the results with a deterministic method that finds the actual region in the uncertainty space where the system properties are verified. The proposed algorithm allows the computational burden of robustness analysis to be drastically reduced, particularly when the number of uncertain parameters is greater than three.

Unmanned space vehicle technology demonstrator

The unmanned space vehicle (USV) program has been undertaken by the Italian Center for Aerospace Research with the aim of developing flying test beds of next generation reentry launch vehicles. In this framework, the development of small demonstrators is also foreseen to validate technological and operational aspects of full-scale vehicles and missions. In this paper, a small-scale demonstrator of the sub-orbital re-entry test mission of the USV program is described. Both mission profile and objectives are very challenging in terms of demonstrator guidance, navigation and control. After a short description of the mission and demonstrator architectures, particular emphasis is given to the guidance and navigation analysis. To this end, mission objectives and reduced-scale system constaints are integrated and translated into innovative guidance solutions relying on optimization techniques. Then, performance of a commercial-off-the-shelf GPS-aided, miniature inertial navigation system over the proposed trajectories is evaluated by Monte Carlo analysis. Standalone inertial and GPS-aided inertial navigation performance is also compared considering GPS loss conditions due to antenna plasma effects.

Numerical and Experimental Investigation of PRORA USV Subsonic and Transonic Aerodynamics

The Italian unmanned space program PRORA USV (Programma di Ricerca Aerospaziale Unmanned Space Vehicle) is a technological program focused on the realization of flying test beds to demonstrate key vehicle and operational technologies applicable to future reusable launch vehicles. In this framework, the dropped transonic flight test is the first in a series of flight experiments the objective of which is the investigation of the final transonic part of the orbital return phase of a winged reentry vehicle. To prepare this mission, the development of the aerodynamic database is in progress, using both extensive wind tunnel tests and computational fluid dynamics. This study deals with investigations focused on the aerodynamic characterization of vehicle rudders in subsonic and transonic regimes for different angles of attack and rudder deflections. The aerodynamic characteristics of the vehicle are computed and discussed. Comparisons between numerical and available experimental data show a satisfactory agreement.

USV test flight by stratospheric balloon: Preliminary mission analysis

The Unmanned Space Vehicle test flights will use a 7 m 1300 kg aircraft. The first three launches will take place at the Italian Space Agency ASI base in Trapani–Milo, Sicily, through a stratospheric balloon that will drop the aircraft at a predefined height. After free fall acceleration to transonic velocities, the parachute deployment will allow a safe splash down in the central Mediterranean Sea. The goal of this article is to show the preliminary analysis results for the first USV flight. We carried out a statistical study for the year 2000–2003, evaluating the typical summer and winter launch windows of the Trapani–Milo base. First, in the center Mediterranean, we define safe recovery areas. They cannot be reached during the balloon ascending phase so, after a sufficiently long floating part able to catch the open sea, the balloon will go down to the release height (24 km). The simulation foresees a 400,000 m 3 balloon and 3 valves for the altitude transfer. A safe splash down must occur far enough from the nearest coast: the minimum distance is considered around 25 km. The vehicle should be released at a distance, from the nearest coast, greater than this minimum amount plus the USV model maximum horizontal translation, during its own trajectory from balloon separation to splash down. In this way we define safe release areas for some possible translations. Winter stratospheric winds are less stable. The winter average flight duration is 7 h and it is probably too long for the diurnal recovery requirement and its scheduled procedures. Comparing past stratospheric balloons flights and trajectories computed using measured meteorological data (analysis), with their predictions made using forecast models and soundings, we obtain the standard deviation of the trajectory forecast uncertainty at the balloon–aircraft separation. Two cases are taken into account: predictions made 24 and 6 h before the launch. Assuming a Gaussian latitudinal uncertainty distribution for the prediction 6 h before the launch, we are able to identify the forecast trajectories that have a probability greater than 97% to reach the safe release areas. Simulating the summer windows trajectories for the years from 2000 to 2003 and for the favorable ground wind days, we obtain the number of trajectories with the desired forecast probabilities.

Flight Control Design of an Unmanned Space Vehicle Using Gain Scheduling

A flight control design of an unmanned space vehicle using an interpolative gain-scheduling technique is presented. The ν-gap metric is used to evaluate the interpolative errors between linear models at operating points. The linear-parameter-varying models for the space vehicle are then constructed by minimizing a criterion using the ν-gap metric. Furthermore, multi-objective constraints are locally imposed on the specified operating points to improve the control performance. In the numerical simulations, the gain-scheduling control laws whose number of operating points was greater than two stabilized the space vehicle over the entire region. Furthermore, the input-saturation constraint was effective in suppressing the magnitude of the input and extending the stability region of the design parameter.

ゲインスケジューリングを用いた無人宇宙往還機の飛行制御系設計（ν‐ｇａｐを用いた動作点選択と局所多目的ゲインスケジューリングの提案）

This paper presents flight control designs of an unmanned space vehicle, HOPE-X vehicle using an interpolation gain scheduling technique. The ν-gap metric is used to evaluate the errors between linear models at operating points. The linear parameter varying models for the HOPE-X vehicle were then constructed by minimizing two types of indices defined with the ν-gap metric. On the other hand, the magnitude of the input is locally constrained to avoid the saturation of the control surfaces. In the numerical simulations of the HOPE-X, the gain scheduling control laws whose number of operating points was greater than two could be applicable to the whole region of the terminal area energy management phase of the HOPE-X. Furthermore, the input constraint was effective to suppress the magnitude of the input and to extend the stability region of the design parameter.

線形補間ゲインスケジューリングを用いた無人宇宙往還機の飛行制御系設計

This paper presents flight control designs of an unmanned space vehicle, HOPE-X, vehicle using interpolation gain scheduling techniques. There are three flight phases from deorbit to landing in HOPE-X; reentry, terminal area energy management (TAEM), and approach and landing. This paper is addressed to the TAEM phase in which an amount of lateral maneuvers are required. Two interpolation gain scheduled state feedback laws were designed with respect to the Lyapunov functions used for guaranteeing the global stability of the closed-loop system, and were applied to the numerical simulations of the HOPE-X. As a result, the gain scheduled control law showed better control performance in the entire of TAEM phase than fixed state feedback laws. The gain scheduling using a parameter-dependent Lyapunov function was superior to the one using a conventional Lyapunov function.

ETS-VII 自動ランデブ接近軌道の設計

Engineering Test Satellite-VII (ETS-VII) is a test satellite to perform in-orbit demonstration of autonomous rendezvous docking (RVD) technology, which will be necessary for advanced space activities in the early 21st century. ETS-VII successfully performed the autonomous RVD by unmanned space vehicle for the first time in the world. For an unmanned space vehicle to perform rendezvous to a manned spacecraft, safe approach is needed. So we paid special attention to designing safe approach trajectory. There are other important points for approach trajectory design, for instance, coordination with guidance and control accuracy, performance of navigation sensors, and operability, etc. In this paper, we introduce the points, and show the result of ETS-VII RVD trajectory design.

General-Error Regression for Deriving Cost-Estimating Relationships

Abstract Development of cost-estimating relationships (CERs) in most cost models involving historical data is based on explicit solutions of the classical least-squares linear regression equation Y = a + bX + E, where Y is cost, X is the numerical value of a cost driver, E is a Gaussian error term whose variance does not depend on the numerical value of X, and a and b are numerical coefficients derived from the historical data. The coefficients of nonlinear forms such as Y = aXb E are derived by taking logarithms of both sides and reducing the formulation to log(Y) = log(a) + b log(X) + log(E). This approach has a number of well-documented weaknesses in addition to the fact that the error of estimation is expressed in meaningless units (“log dollars”). A second weakness is that the analyst is forced to assume an additive-error (uniform dollar value across the board) model when historical data indicate a linear relationship between cost driver and cost, but a multiplicative-error (a percentage of the estimate) model when a nonlinear relationship is indicated. A further weakness a priori excludes from consideration certain potentially attractive nonlinear forms, such as Y = a + bXc , because a logarithmic (or any other reasonable) transformation fails to reduce the problem to the classical linear-regression format. All known weaknesses are circumvented by applying “general-error” regression, which allows the analyst to determine the optimal coefficients for any curve shape and to choose the error model independently of the CER's shape. The optimal (error-minimizing) solution is found by sequential computer search rather than by explicit solution of simultaneous equations, as in the classical regression methods. CERs that comprise Version 7 (August 1994) of the U.S. Air Force's Unmanned Space Vehicle Cost Model (USCM-7) have been statistically derived from historical cost data using general-error least-squares regression. In the case of USCM-7 CER development, the multiplicative-error model was selected for all CERs, whether their shape be linear or one of several nonlinear types. The optimality criterion for CER selection is minimization of percentage standard error of the estimate.

Unmanned space vehicle navigation by GPS

In this paper, flight-path deviation in the navigation of unmanned space vehicles by global positioning system (GPS) is analyzed. A new method to calculate flight-path deviation by means of coordinate transforming is presented and the software of navigation and control is designed. This software is practical and effective for navigation by GPS with some characteristics including high-speed, high accuracy, real-time positioning and the use of digital mapping technique.