Methods for the Calculation and Control of Launch Vehicle Drop Regions
Abstract
:1. Introduction
2. DRs and Methods for Their Determination
2.1. A Brief History of the Methods’ Development for Determining DRs
2.2. Methods for the Risk Assessment of the LVs’ SPs
2.3. Monte Carlo Method and Alternative Options
3. Ways of Controlling and Changing the SPs’ DRs
3.1. Methods to Reduce the Technogenic Impact of the LVs on the DR
3.2. Engineering and Mathematical Ways to Reduce DRs
3.3. Soft-Landing Techniques
4. Discussion
5. Conclusions
- Engineering, aimed at constructive changes in the LV’s appearance. This includes adding cables for the connection of the LVs’ SPs, using parachute rescue systems, etc.;
- Mathematical, based on a detailed elaboration or modification of LV trajectories and control programs;
- The “soft-landing” method, designed to eliminate DRs. These include various techniques for returning the SR to the spaceport without being destroyed.
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
Abbreviations
DR(s) | Drop region(s) |
LV(s) | Launch vehicle(s) |
SP(s) | Separating part(s) |
GFR(s) | Guaranteed fuel reserves |
CD | Coasting descent |
IS | Importance sampling |
CM | Center of mass |
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Method | Brief Description | Advantages | Disadvantages |
---|---|---|---|
Defining DRs as circular ones: [16]. | Used for preliminary risk assessment of the Black Brant XII sounding rocket. The probability of particular SPs falling from a predicted location was assumed as constant in all directions, thus the circular shape of the DR. | (1) Simple. (2) Does not require many computing resources. | (1) Outdated. (2) Resulting DRs are seriously overestimated. |
Crude Monte Carlo simulation: [17,18,24,28]. | Simulates the flight hundreds of times. For each iteration, flight parameters are varied with the selected probability distribution. This provides a number of impact points. When combined, they lead to a DR creation. It is usually subdivided into 3 ellipses with a fixed percentage of drop points included: 3σ ellipse contains 99%, 2σ ellipse—95%, and 1σ ellipse—68%. | (1) Precise. (2) Widely used. (3) Can be completed using a personal computer with adequate accuracy. (4) Can be adjusted for specific tasks. | (1) Calculation time increases drastically with a negligible increase in accuracy. (2) Inapplicable to very rare events or impact points far out of 3σ ellipse borders. |
Significance sampling: [25,28]. | IS is closely related to the Monte Carlo simulation. However, this approach focuses on rare events, which makes the DR estimation more accurate in some cases. | (1) Requires less calculations than the crude Monte Carlo simulation. (2) It is adapted for situations when a limited number of simulations is available. (3) Can be completed using a personal computer. | Choosing the right probability density function is crucial for this method. |
Modified IS with cross-entropy and non-parametric IS: [26]. | A complementary approach of classical cross-entropy and nonparametric adaptive IS methods. Both are used to enhance the results achieved by the classical IS method. | Decreases the number of required samples without increasing the relative error. | Choosing the right probability density function is crucial for this method. |
Reliability analysis in the presence of aleatory and epistemic uncertainties: [29]. | The method consists of two recurring steps—combining interval and probabilistic analysis models and an improved Kriging model. The resulting system makes it possible to obtain accurate data precisely near the boundary of the estimated DR. | (1) Shows great results in the DR boundary area. (2) Includes both aleatory and epistemic uncertainties in calculations. | (1) Computational costs are quite high. (2) Not suitable for determining impact points closer to the center of DRs. |
Sequential Monte Carlo square algorithm: [30]. | The discussed algorithm is adapted for rare-event analyses in order to sample the target distribution. Two sets of particles are defined, one in the parameter space; another in the state space, and it is used to produce unbiased estimates of calculated probabilities. | (1) Bypasses the long time-convergence issue of its predecessors. (2) Takes very rare events into account during calculations, enhancing the results. | Computational costs significantly increase with each iteration. |
Pontryagin maximum principle: [31,32,33]. | This implementation of the Pontryagin maximum principle focuses on “branches” of LVs. “Branch” here means trajectory. The main branch represents an exit path and the side branches are used to describe the route of passive separable parts of the LV. | (1) Provides data on optimal branching trajectories for LVs. (2) Significantly decreases the number of operations, compared to crude the Monte Carlo method. | The resulting DR is slightly overestimated. |
Dispersion ellipses’ envelopes for the impact points: [34]. | Mathematical approach that involves two similar methods. The first involves the use of polygons—a small polygon is circumscribed to each scattering ellipse, then all the small polygons are inscribed into the large one. This results in the DR. The second method is similar to the first, but instead of polygons all smaller scattering ellipses are inscribed into a larger one. | (1) Simple. (2) Takes destruction of SPs into consideration. (3) Does not require many computing resources. | (1) Easily outmatched by more complex approaches. (2) It is not suitable for precise DR calculations. |
DR calculations with actual atmospheric parameters: [35,36]. | The method focuses on the fact that most of the DR calculations’ techniques lack the real atmospheric parameters and focus on average ones. If applied, the systematic deviations of the calculated impact points from the real ones can be diminished. | Significantly decreases possible deviations of calculated impact points from real ones. | (1) Actual atmospheric data have to be updated for each launch. (2) DR calculations should be completed close to the launch day, which is not always possible. |
Statistical approach to the determination of the DR: [37,38]. | A number of previously registered impact points from real LVs is taken into consideration for future calculations and comparisons. | Can result in a significant reduction in time required to find the SP in a real situation. | Requires a large number of real impact points, which are not available for new LVs. |
DR calculations with SP fracture taken into account: [39,40,41]. | SPs and their possible fractured combinations are analyzed in order to decrease the size of the actual DR. Both aerothermodynamic and mass characteristics are taken into account during calculations. | Can result in a decrease in the DR’s size. | (1) Requires specific mathematical models for each LV and SP. (2) Requires statistical data, which are not available for new LVs. |
Method | Brief Description | Advantages | Disadvantages |
---|---|---|---|
Relocation of the DR to more suitable regions: [11,44,45]. | The method includes a number of criteria for choosing the optimal areas for DRs based on their resistance to technogenic impacts, the minimum cost of environmental rehabilitation work, and how difficult it is to access them via land or water, etc. | (1) Decreases the price of maintaining the DR. (2) Decreases the number of possible negative outcomes for the environment and people. (3) Does not require any changes to be made to the LV. | (1) The size of the DR rarely decreases. (2) The criteria for choosing the DR vary drastically for each country and are difficult to unify. |
Parachute rescue systems: [46,47,48,49,50,51]. | The usage of parachute systems makes it possible to slow down the SPs’ descent, which not only leads to a smaller DR, but also allows the SP itself to be preserved and recovered. Recovery is conducted by ships and helicopters, both during descent or after the SP falls into the water or onto the ground. | (1) High reliability. (2) Cheap to produce and maintain. (3) Easy to use. (4) Can be modified for any kind of space- or aircraft. (5) Mitigates some of the damage to the SP. | (1) Increases the mass of the craft. (2) Depending on the SP’s size, the maximum carrying capacity of a rescue helicopter can be a limiting factor, especially during descent capture. |
Connection of the SPs together: [52]. | The LV’s side blocks are equipped with a flexible mechanical tether and a parachute system. After the separation from the main stage, the SP, composed of a number of side blocks, launches a parachute, stabilizes, and gradually descends into a predetermined DR. | Decreases the number of DRs, simplifying the rescue procedures. | Significantly increases the spacecraft’s mass. |
Incineration of the SPs during descent: [53,54]. | The method focuses on burning the SPs composed of polymeric composites with an autonomous combustion system implemented in them. During the descent, the specified system receives the command to release heat, which results in the SPs being incinerated mid-flight. | (1) Decreases the DR’s size by minimizing the number of components that reach Earth. (2) Decreases the search and rescue costs for SPs. | (1) Leads to an increase in the number of impact points inside the DR, as large SPs may turn into a number of unburnable small ones. (2) Burning of polymeric composites can lead to unknown environmental issues. (3) Requires additional flammable weight to be carried by LVs. |
Control of the SPs’ positions during descent: [56]. | If the SP does not have a rotating propulsion system, any aerodynamic rudders, the size, and coordinates of the DR can only be controlled by setting the necessary launch parameters, the direction of the second stage, and its launch time. A combination of these factors leads to a decrease in DRs. | (1) Allows a decrease in the size of the DR, even without involving the SP directly. (2) Does not require any changes to be made to the LV. | (1) Does not show significant changes in a negative downrange direction. (2) Requires data to be transmitted at a specific time and place of flight, which may not always be possible. |
Change in the directory for best DR possible: [58]. | The method focuses on taking into account the initial parameters for the LV’s launch, SPs’ detachment, the operational parameters of the atmosphere, etc., in order to calculate a trajectory that is optimal in terms of the DR, mostly by changing the pitch angle of the LV during its ascent. | (1) Simple. (2) Does not require any changes to be made to the LV. | (1) Inevitably decreases the maximum payload weight of the LV, which needs to be economically justified. (2) Political factor can be of importance when any changes in the trajectory are made. |
Gasification of GFRs and their usage in descent maneuvers: [59,60,61,62]. | An onboard descent system is implemented in the LV’s design. It focuses on gasifying the GFRs and then using them during the SPs’ descent phase for maneuvers, which aim at decreasing the DR’s size. | (1) Significantly lowers the chance of an explosion or fuel leakage if the SP is damaged during impact. (2) Allows the SP to be adjusted during descent in a way that results in a smaller DR size. | (1) Increases the LV’s weight. (2) Might have a negative impact on the DR environment, as GFRs are burned rather close to the ground. |
SP-guided return (in-air-capturing method): [63,64,65,66,67,68,79,80,81]. | During the descent phase, the SP gradually enters the planning phase. At this time, a prepared cargo plane approaches from below the SP and captures it with a special harpoon system. The cargo plane then guides the SP to the nearby landing position, where it glides down and lands. | (1) Allows the SP to return safely, possibly allowing it to be reused. (2) Completely excludes the need for the DR. | (1) Involves some changes in both the LV’s and rescue aircraft’s designs; (2) Requires heavy-cargo planes, which may be a limiting factor. (3) Only suitable for SPs that can glide during descent and do not simply fall down. |
SP self-return: [70,79,80,81]. | Following the separation phase, the reusable first stage reaches its maximum altitude, re-enters the atmosphere, turns to the direction of the launch site, and begins a powered flight towards it using air-breathing engines. | (1) Allows the safe return of the SP, possibly allowing it to be reused. (2) Completely excludes the need for the DR. (3) Does not require any additional aircraft to be involved. | (1) Requires significant changes in the design of the LV, which increases its weight. (2) Only suitable for SPs that can glide during descent and do not simply fall down. |
Soft-landing methods: [72,73,75,76,77,79,80,81,82,83,84]. | Although some techniques involve different approaches, they mostly follow the same algorithm. The first-stage engines re-ignite after separation, the SP makes a turn in the pitching plane, and after aerodynamic deceleration, the steering engines are activated at the specified altitude. As a result, the stage approaches the landing point with practically zero speed. | (1) Allows the safe return of the SP, possibly allowing it to be reused. (2) Completely excludes the need for the DR. (3) Many space agencies are interested in evolving this technique. | (1) Requires some changes in the LV’s design, plus some additional fuel. (2) It is not always justified from an economical point of view. (3) It is not always justified from an economical point of view. |
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Kapelyushin, Y.; Lazorak, R.; Peshkov, R.; Trofimov, E. Methods for the Calculation and Control of Launch Vehicle Drop Regions. Aerospace 2023, 10, 424. https://doi.org/10.3390/aerospace10050424
Kapelyushin Y, Lazorak R, Peshkov R, Trofimov E. Methods for the Calculation and Control of Launch Vehicle Drop Regions. Aerospace. 2023; 10(5):424. https://doi.org/10.3390/aerospace10050424
Chicago/Turabian StyleKapelyushin, Yury, Roman Lazorak, Ruslan Peshkov, and Evgeny Trofimov. 2023. "Methods for the Calculation and Control of Launch Vehicle Drop Regions" Aerospace 10, no. 5: 424. https://doi.org/10.3390/aerospace10050424
APA StyleKapelyushin, Y., Lazorak, R., Peshkov, R., & Trofimov, E. (2023). Methods for the Calculation and Control of Launch Vehicle Drop Regions. Aerospace, 10(5), 424. https://doi.org/10.3390/aerospace10050424