Organizational Unit:

Space Systems Design Laboratory (SSDL)

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https://hdl.handle.net/1853/70747

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Organizational Unit

Daniel Guggenheim School of Aerospace Engineering

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https://finding-aids.library.gatech.edu/agents/corporate_entities/1138

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Publication Search Results

Now showing 1 - 9 of 9

A Design of Experiments-Based Method for Point Selection in Approximating Output Distributions

(Georgia Institute of Technology, 2002-09) McCormick, David Jeremy ; Olds, John R.

The goal of this research is to find a computationally efficient and easy-to-use alternative to current approximation or direct Monte Carlo methods for robust design. More specifically, a technique is sought to use selected deterministic analyses to obtain probability distributions for analyses with large inherent uncertainties. Previous research by the authors has presented a promising class of methods known as Discrete Probability Matching Distributions (DPOMD). This paper introduces a new type of DPOMD better suited to problems with larger numbers of random variables. This new type utilizes a fractional factorial design of experiments array in combination with an inverse Hasofer-Lind standard normal space transform. The method defines points in the problem space that represent the moment characteristics of the input random variables. This new method is compared to two other approximation techniques, Descriptive Sampling and Response Surface/Monte Carlo Simulation, for three common aerospace analyses (Mass Properties and Sizing, Propulsion Analysis and Trajectory Simulation). A Monte Carlo analysis with corresponding error bands is used for reference. Preferences for probabilistic analysis each of these problems are determined based on the speed and accuracy of analysis. These results are presented here. The new DPOMD technique is shown to be advantageous in terms of speed and accuracy for two of the three problems tested.
A Distributed Framework for Probabilistic Analysis

(Georgia Institute of Technology, 2002-09) McCormick, David Jeremy ; Olds, John R.

Probabilistic multidisciplinary design optimization promises to incorporate critical design uncertainty in order to create optimal products with a high probability of meeting design constraints under a wide variety of circumstances. Several methods of accelerated probability analysis are available to designers. What is not available is a formal method for tying contributing analysis-level probability analysis into an integrated design framework capable of optimization. This would allow probability methods to be tailored to the characteristics of a particular contributing analysis as well as potentially reduce the dimensionality of the problems considered. This research presents such a method, and then tests it on a conceptual launch vehicle design problem. This probabilistic optimization problem consisted of 84 noise variables and four design variables. This problem setup consistently found system optimums in 6-8 hrs. It utilized several probability approximation methods run in an iterative manner to generate probabilistic vehicle sizing information. Once the probabilistic optimum was identified and confirmed using this process, a system-level Monte Carlo random simulation of the vehicle design was conducted around the optimum point to confirm the accuracy of the distributed approximation method. Because this simulation was prohibitively expensive, it was only conducted at the single optimum point. Following this accuracy confirmation, a comparison to a deterministic optimization of the same problem illustrated the difference between probabilistic and deterministic optimums.
Space Tourism: Making it Work for Fun and Profit

(Georgia Institute of Technology, 2000-10) Olds, John R. ; McCormick, David Jeremy ; Charania, Ashraf ; Marcus, Leland R.

This paper summarizes the findings of a recent study of space tourism markets and vehicles conducted by the Space Systems Design Laboratory at Georgia Tech under sponsorship of the NASA Langley Research Center. The purpose of the study was to investigate and quantitatively model the driving economic factors and launch vehicle characteristics that affect businesses entering the space tourism industry. If the growing public interest in space tourism can be combined with an economically sound business plan, the opportunity to create a new and profitable era for space flight is possible. This new era will be one in which human space flight is routine and affordable for many more people. The results of the current study will hopefully serve as a guide to commercial businesses wishing to enter this potentially profitable emerging market.
Comparison of Collaborative Optimization to Conventional Design Techniques for a Conceptual RLV

(Georgia Institute of Technology, 2000-09) Cormier, Timothy A. ; Scott, Andrew ; Ledsinger, Laura Anne ; McCormick, David Jeremy ; Way, David Wesley ; Olds, John R.

Initial results are reported from an ongoing investigation into optimization techniques applicable to multidisciplinary reusable launch vehicle (RLV) design. The test problem chosen for investigation is neither particularly large in scale nor complex in implementation. However, it does have a number of characteristics relevant to more general problems from this class including (1) the use of legacy analysis codes as contributing analyses and (2) non-hierarchical variable coupling between disciplines. Propulsion, trajectory optimization, and mass properties analyses are included in the RLV problem formulation. A commercial design framework is used to assist data exchange and legacy code integration. The need for a formal multidisciplinary design optimization (MDO) approach is introduced by first investigating two or more conventional approaches to solving the sample problem. A rather naive approach using iterative sublevel optimizations is clearly shown to produce non-optimal results for the overall RLV. The second approach using a system-level response surface equation constructed from a small number of RLV point designs is shown to produce better results when the independent variables are judiciously chosen. However, the response surface method approach cannot produce a truly optimum solution due to the presence of uncoordinated sublevel optimizers in the three contributing analyses. Collaborative optimization (CO) appears to be an attractive MDO approach to solving this problem. Initial implementation attempts using CO have exhibited noisy gradients and other numerical problems. Work to overcome these issues is currently in progress.
Approximation of Probabilistic Distributions Using Selected Discrete Simulations

(Georgia Institute of Technology, 2000-09) McCormick, David Jeremy ; Olds, John R.

The goal of this research is to find a computationally efficient and easy to use alternative to current approximation of direct Monte Carlo methods for robust design. More specifically, a new technique is sought to use selected deterministic analyses to obtain probability distributions for analyses with large inherent uncertainties. Two techniques for this task are investigated. The first uses a design of experiments array to find key points in the algorithm space upon which deterministic analyses will be performed. An expectation value error minimization routine is then used to assign discrete probabilities to the individual runs in the array based on the joint probability distribution of the inputs. This creates a representative distribution that can be used to estimate expectation values for the output distribution. The second technique uses a similar error minimization algorithm, but this time alters the location of the points to be sampled from the function space. This means that for every change in input variable distribution, the algorithm will generate a table of runs at input locations that minimize the error in expectation values. The advantages of these techniques include a small time savings over approximation or direct Monte Carlo methods as well as elimination of numerical noise due to random number generation. This noise will be shown to be a hindrance when converging multiple Monte Carlo analyses. In additional, when the variable location sampling point algorithm is used, this takes away the arbitrary task of defining levels for the input variables and provides enhanced accuracy.
Hyperion: An SSTO Vision Vehicle Concept Utilizing Rocket-Based Combined Cycle Propulsion

(Georgia Institute of Technology, 1999-11) Olds, John R. ; Bradford, John Edward ; Charania, Ashraf ; Ledsinger, Laura Anne ; McCormick, David Jeremy ; Sorensen, Kirk

This paper reports the findings of a conceptual launch vehicle design study performed by members of the Space Systems Design Laboratory at Georgia Tech. Hyperion is a conceptual design for an advanced reusable launch vehicle in the Vision Vehicle class. It is a horizontal takeoff, horizontal landing SSTO vehicle utilizing LOX/LH2 ejector scramjet rocket-based combined cycle (RBCC) propulsion. Hyperion is designed to deliver 20,000 lb. to LEO from the Kennedy Space Center. Gross weight is estimated to be 800,700 lb. and dry weight is estimated to be 123,250 lb. for this mission. Preliminary analysis suggests that, with sufficient launch traffic, Hyperion recurring launch costs will be under 200 dollars per lb. of payload delivered to LEO. However, nonrecurring costs, including development cost and acquisition of three airframes, is expected to be nearly 10.7B dollars. The internal rate of return is only expected to be 8.24 percent. Details of the concept design including external and internal configuration, mass properties, engine performance, trajectory analysis, aeroheating results, and concept cost assessment are given. Highlights of the distributed, collaborative design approach and a summary of trade study results are also provided.
Stargazer: A TSTO Bantam-X Vehicle Concept Utilizing Rocket-Based Combined Cycle Propulsion

(Georgia Institute of Technology, 1999-11) Olds, John R. ; Ledsinger, Laura Anne ; Bradford, John Edward ; Charania, Ashraf ; McCormick, David Jeremy ; Komar, D. R.

This paper presents a new conceptual launch vehicle design in the Bantam-X payload class. The new design is called Stargazer. Stargazer is a two-stage-to-orbit (TSTO) vehicle with a reusable flyback booster and an expendable LOX/RP upper stage. Its payload is 300 lbs. to low earth orbit. The Hankey wedge- shaped booster is powered by four LOX/LH2 ejector scramjet rocket-based combined-cycle engines. Advanced technologies are also used in the booster structures, thermal protection system, and other subsystems. Details of the concept design are given including external and internal configuration, mass properties, engine performance, trajectory analysis, aeroheating results, and a concept cost assessment. The final design was determined to have a gross mass of 115,450 lb. with a booster length of 99 ft. Recurring price per flight was estimated to be $3.49M. The overall conceptual design process and the individual tools and processes used for each discipline are outlined. A summary of trade study results is also given.
System Robustness Comparison of Advanced Space Launch Concepts

(Georgia Institute of Technology, 1998-10) McCormick, David Jeremy ; Olds, John R.

This research proposes two methods to investigate the robustness differences between competing types of advanced space launch systems. These methods encompass two different phases of the advanced design process and are used to compare the relative advantages of two concepts in these phases. The first is a Monte Carlo simulation during the conceptual phase of design, where mold lines can be changed to account for uncertainty in weight assumptions. This tests the vehicle weight growth for a fixed mission. Here, the all-rocket single stage to orbit (SSTO) shows a more narrow distribution of dry weight, suggesting higher concept robustness. A study of vehicle mass ratio and mixture ratio combinations for both vehicles show the relative location of the results. The second phase represents the transition to detailed design. An optimization based on length determines the appropriate size for detailed design. This optimization takes into account uncertainties placed on both weight relationships and performance requirements. Both of these analyses utilize Crystal Ball Pro in conjunction with Microsoft Excel. This gives the technique compatibility with commonly used computer platforms. While the all-rocket SSTO does show an advantage in the area of system weight growth, several other factors are important in determining the viability of a reusable launch system, not the least of which is mission flexibility. Here the runway-operated RBCC SSTO has a distinct advantage.
Component-Level Weight Analysis for RBCC Engines

(Georgia Institute of Technology, 1997-09) Olds, John R. ; McCormick, David Jeremy

Rocket-based combined-cycle engines (RBCC) engines have recently received increased attention for use on advanced, reusable space launch vehicles. By combining convention rocket and airbreathing operating modes into an integrated unit, they have given designers a middle ground between the high-thrust, low-Isp characteristics for a pure rocket and the low-thrust, high-Isp of pure airbreathers. Engine weight (or thrust-to-weight ratio) is a highly sensitive parameter in the design of advanced reusable launch vehicles. While substantial experience exists with ground-test engines from the 1960’s, little parametric data exists to help conceptual designers predict weight for today’s advanced technology, flight-weight RBCC engines. This paper reports a new set of component-level paramedic weight estimating equations for advanced rocket-based combined-cycle (RBCC) engines. These equations are derived from top-down regression analysis of historical data and include variables to account for advanced technologies and materials. Component weight equations are given as functions of engine geometry, internal pressure, flight modes, etc. Taken together, the equations are used to build up an overall RBCC weight estimation model - WATES. This spreadsheet-based model is not intended to replace a more detailed weight analysis, but rather to assist conceptual vehicle designers in assessing the relative advantages of various engine concepts. Sample RBCC engine weight predictions are given.