Person:

Mavris, Dimitri N.

Permanent Link

https://hdl.handle.net/1853/71501

Associated Organization(s)

Organizational Unit

Daniel Guggenheim School of Aerospace Engineering

Organizational Unit

Aerospace Systems Design Laboratory (ASDL)

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Publication Search Results

Now showing 1 - 10 of 19

A Methodology for Assessing Business Models of Future Air Transportation in the Atlanta Regional Transportation System

(Georgia Institute of Technology, 2004-09) Lim, Choon Giap ; Lewe, Jung-Ho ; DeLaurentis, Daniel A. ; Mavris, Dimitri N.

A methodology employing physics-based and economics-based tools in conjunction with probabilistic treatment is developed to study Personal Air Vehicle business model. In the context of the paper, a business model is a mathematical representation of a service provider business operation. Vehicle concepts and hypothesized metrics such as mobility freedom and 'value of time'are embedded in the methodology. Market behavior of the complex transportation environment is captured as part of the equation through Agent-based Modeling and Monte Carlo Simulation techniques. This simulation platform for the transportation environment facilitates the case study of the Atlanta Regional Transportation System. The establishment of this model lays the foundation for creating a robust and adaptive design methodology that allows experts in fields other than aerospace engineering to contribute their expertise towards the realization of this very diverse and dynamic future air transportation system.
An Integrated Decision-making Method to Identify Design Requirements Through Agent-based Simulation for Personal Air Vehicle System

(Georgia Institute of Technology, 2002-10) Lewe, Jung-Ho ; Ahn, Byung-Ho ; DeLaurentis, Daniel A. ; Mavris, Dimitri N. ; Schrage, Daniel P.

A product?s design requirements guide the next development efforts. Thus, correct decision-making is critical in generating design requirements as vehicle concepts are being formulated. A new method is proposed to account for system-of-systems aspects and to aid a decision-making process in synthesizing design requirements for a personal air vehicle system. The use of an agent-based modeling technique facilitates the abstraction of the key elements in the whole system. A traveling party is treated as an agent, and the infrastructure environment in the national transportation system is easily represented in the model. A number of simulations are performed to demonstrate the capability of this new approach. The method not only measures the effect of design requirements of a personal air vehicle system through sensitivity analyses, but also evaluates the effect of system technologies quantitatively, while maintaining the system-of-systems perspective. With this powerful method, designers can extract essential technical requirements that allow polishing of concept vehicles; policy makers can investigate the infrastructure and technology impact of new systems; and business planners can perform an analysis based on their own market assumptions.
A Bi-Level optimization approach for technology selection

(Georgia Institute of Technology, 2002-09) Utturwar, Aditya S. ; Rallabhandi, Sriram Kishore ; DeLaurentis, Daniel A. ; Mavris, Dimitri N.

Technology selection is a crucial step in the process of aircraft design. If the performance and economic requirements are not fulfilled for any combination of the design variables, new technologies need to be infused in the design. Typically, the designer has a pool of technology options. The technologies to be infused in the new design are to be selected from this pool so as to achieve improvements such as increased performance, reduced risk, reduced cost etc. Thus, it is critical to be able to perform a quick and accurate assessment of the available technologies in the early stages of the design process. However, if the set of available technologies is large, the designer runs into a huge combinatorial optimization problem. To tackle the problem, a systematic approach called Technology Identification, Evaluation and Selection (TIES) has been developed to choose the best set of technologies and arrive at a feasible and viable design solution. However, the issue of dealing with large combinatorial problems still remains. A new approach for tackling the same problem of technology selection was inspired from the TIES methodology and is discussed in this paper. This approach is based on identifying an optimal point in an intermediate variable space, that later on serves as the target point for technology selection. The new approach, called ?Bi-level approach? provides additional insights and expedites technology selection, thus rendering efficiency to the preliminary design process. After describing the bi-level approach, its application to an aircraft design problem is presented.
System-of-Systems Modeling for Personal Air Vehicles

(Georgia Institute of Technology, 2002-09) DeLaurentis, Daniel A. ; Lim, Choon Giap ; Kang, Taewoo ; Mavris, Dimitri N. ; Schrage, Daniel P.

On-going research is described in this paper concerning the development of a methodology for adaptable system studies of future transportation solutions based upon personal air vehicles. Two challenges in this research are presented. The challenge of deriving requirements for revolutionary transportation concepts is a difficult one, due to the fact that future transportation system infrastructure and market economics are inter-related (and uncertain) parts of the equation. Thus, there is a need for a macroscopic transportation model, and such a task is well suited for the field of techniques known as system dynamics. The determination and visualization of the benefits of proposed personal air vehicle concepts for individuals presents a second challenge. In this paper, the primary benefit metrics that serve as system requirements for personal transportation applications are the Doorstep-to-Destination travel time-savings and net present value of utilizing the new transportation option as compared to a conventional transportation mode. The modeling and determination of these metrics, the synthesis of vehicle characteristics, as well as existing travel statistical data are integrated into the system model to enable visualization of the design space and to guide the design space evolution through sensitivity assessment. This individual traveler-based analysis is referred to as a microscopic model, and interesting results from its execution are reported. The results indicate the level and direction of technology progress required to create economically viable personal air transportation architectures.
A New Model for the Aerospace Design Process Based on a Control System Analogy

(Georgia Institute of Technology, 2000-09) DeLaurentis, Daniel A. ; Mavris, Dimitri N.

A novel approach to the modeling and control of aerospace system design problems is presented. By integrating recent advances in probabilistic robust design and technology assessment methods with a traditional control system feedback architecture, the approach is intended to establish a unified structure for managing complex design problems under uncertainty. The notions of plant, state variables, feedback, and compensation are adapted from the realm of control theory to this new setting. A specific aspect of the paper addresses methods for categorizing and computing the plant? sensitivity to modeled uncertainty in the feedback system. An example problem is executed and described to illustrate probabilistic sensitivity analysis as well as one possible avenue for arriving at an optimal compensator. Since this topic is in the initial research stages, the near term challenges with regards to refining and improving the approach are identified throughout the paper. Two such challenges include constructing a valid plant model and the optimal selection of a compensator.
Methodology for Examining the Simultaneous Impact of Requirements, Vehicle Characteristics, and Technologies on Military Aircraft Design

(Georgia Institute of Technology, 2000-08) Mavris, Dimitri N. ; DeLaurentis, Daniel A.

The process of system engineering has always emphasized the definition of requirements as the first step toward product development. Typically, however, these requirements were examined in isolation from the potential systems and technologies they would likely impact. Further, requirements during design were treated deterministically, which sometimes led to non-robust and poor performing actual systems which encountered different requirements. Thus, there is a need to examine requirements early on and in a new way. This "new way" must include an environment for the simultaneous examination of requirements, design variables, and technologies. Further, this environment must be built in a probabilistic way since the requirements may be ambiguous and/or uncertain, the eventual cost and performance of critical technologies are highly uncertain, and the possibility of system The ultimate goal of the probabilistic approach is finding solutions robust to these uncertainties. A methodology for the creation of just such an environment is described in this paper. Subsequently, the implementation of the methodology is demonstrated on an example study of a notional, multi-role fighter aircraft. Important visualization and probabilistic analysis techniques are highlighted. The approach is found to be extremely valuable, especially in light of the recent initiation of several major programs in the aerospace sector which exhibit the challenges of joint service requirements, the need for advanced technologies, and an increasing emphasis on affordability.
Capturing Corporate Philosophy: The Future of IT

(Georgia Institute of Technology, 2000-02) Hale, Mark A. ; Daberkow, Debora Daniela ; DeLaurentis, Daniel A. ; Mavris, Dimitri N. ; Schrage, Daniel P. ; Craig, James I.

Context is proposed as a mechanism for organizing Information Technology practices in the future through its role in interpretation. An enterprise organization model based on decision-flow is presented here that is applicable to a variety of domains. It contains elements that mark the information content with respect to a full consideration of its environment. These elements are, in order of increasing superiority, data, information, knowledge, judgement, and philosophy. There are four marked stages where contextual derivation occurs among these elements, including definition, refinement, improvement, and realization. Discovery occurs during the derivation of context and it is at this time that higher-level processes influence subordinate processes. For this reason, it is believed that corporate philosophy can be infused explicitly throughout enterprise practices. The resulting organizational model can be used by an enterprise to strategically allocate resources and maintain competitive advantage.
Uncertainty Modeling and Management in Multidisciplinary Analysis and Synthesis

(Georgia Institute of Technology, 2000-01) DeLaurentis, Daniel A. ; Mavris, Dimitri N.

The complex, multidisciplinary nature of aerospace design problems, as well as the requirement to examine life-cycle characteristics, have exposed a need to model and manage uncertainty. In this paper, a formal approach for modeling uncertainty in such design problems is presented. The approach includes uncertainties associated with mathematical models, operation environment, response measurement, and input requirements. In addition, a new method for propagating this uncertainty (in an efficient manner) to find robust design solutions is developed and described. The uncertainty model combined with the probabilistic robust design technique is a critical advancement in multidisciplinary system design, in that it identifies solutions that have a maximum probability of success. Continued research in both uncertainty modeling and efficient robust design methods appears essential. Both the uncertainty model and robust design technique are demonstrated on an example problem involving the design of a supersonic transport aircraft using the relaxed static stability technology. At each step, validation studies are performed and initial results indicate that the robust design method represents an accurate depiction of the problem. This depiction provides critical insight into where and why uncertainty affects the family of design solutions.
Viable Designs Through a Joint Probabilistic Estimation Technique

(Georgia Institute of Technology, 1999-10) Bandte, Oliver ; Mavris, Dimitri N. ; DeLaurentis, Daniel A.

A key issue in complex systems design is measuring the 'goodness' of a design, i.e. finding a criterion through which a particular design is determined to be the 'best.' Traditional choices in aerospace systems design, such as performance, cost, revenue, reliability, and safety, individually fail to fully capture the life cycle characteristics of the system. Furthermore, current multi-criteria optimization approaches, addressing this problem, rely on deterministic, thus, complete and known information about the system and the environment it is exposed to. In many cases, this information is not be available at the conceptual or preliminary design phases. Hence, critical decisions made in these phases have to draw from only incomplete or uncertain knowledge. One modeling option is to treat this incomplete information probabilistically, accounting for the fact that certain values may be prominent, while the actual value during operation is unknown. Hence, to account for a multi-criteria as well as a probabilistic approach to systems design, a joint-probabilistic formulation is needed to accurately estimate the probability of satisfying the criteria concurrently. When criteria represent objective/ aspiration functions with corresponding goals, this ?int probability?can also be called viability. The proposed approach to probabilistic, multi-criteria aircraft design, called the Joint Probabilistic Decision Making (JPDM) technique, will facilitate precisely this estimate.
Elements of an Emerging Virtual Stochastic life Cycle Design Environment

(Georgia Institute of Technology, 1999-10) Mavris, Dimitri N. ; DeLaurentis, Daniel A. ; Hale, Mark A. ; Tai, Jimmy C. M.

The challenge of designing next-generation systems that meet goals for system effectiveness, environmental compatibility, and cost has grown to the point that traditional design methodologies are becoming ineffective. Increases in the analysis complexity required, the number of objectives and constraints to be evaluated, and the multitude of uncertainties in today? design problems are primary drivers of this situation. A new environment for design has been formulated to treat this situation. It is viewed as a testbed, in which new techniques in such areas as design-oriented/physics-based analysis, uncertainty modeling, technology forecasting, system synthesis, and decision-making can be posed as hypotheses. Several recent advances in elements of this multidisciplinary environment, termed the Virtual Stochastic Life Cycle Design Environment, are summarized in this paper.