Yongchang Li

Towards a method for assessing resilience of complex dynamical systems

System survivability is one of the key requirements for the conceptual design of an Integrated Reconfigurable Intelligent (IRIS) system. Current approaches in survivability engineering may not effectively address the challenges in designing revolutionary, large scale complex and multi-capable systems. The main objective of this study is to investigate the concept of resilience in the context of system safety and survivability and suggest a technique for assessing resilience in systems engineering. Resilience is expected to be the enabler for integrating safety and survivability in the early conceptual design. For this purpose, a small scale cooling network system architecture has been utilized to demonstrate the technique, both for a 32-valve baseline, as well as for six other configurations. The application of the technique allowed for the comparative assessment and tradeoff investigation of resilience function capacities, as well for the identification of solution feasibility, under adaptability and robustness constraints.

The Investigation of a Decision-Making Technique Using the Loss Function

In aircraft design, the decisions made during the conceptual or preliminary design phases play a large role in determining the success of the design. Supporting decision makers in these early design phases require a decision making technique with the capability of managing multiple conflicting criteria and capturing the associated uncertainties. The Joint Probability Decision making technique, which incorporates a multi-criteria and a probabilistic approach to systems design, is such a technique. This technique uses Probability of Success as the objective function, which is obtained by integrating the Joint Probability Density Function of the criteria over the area of criterion values that are of interest to the customer. However, the calculation of probability of success does not take the deviation of the solutions from the target values into account, which may be often important for concept selection. Also, this technique employs weighting coefficients to indicate the importance of each criterion when calculating the probability of success. However, representing the decision makers preference by using the numerical weights is considered ineffective and usually involves a largely undefined trial-and-error weight-tweaking process. The study presented in this paper was done with the intention of enhancing the joint probability decision making technique so as to make it useful for concept selection through the utilization of Loss Function. The impact of the loss function in the decision making process is investigated in this paper, and an advanced rotorcraft concept selection problem employing the joint probability decision making technique with and without the loss function is performed in order to demonstrate the improved technique.

Towards a Data Calibrated, Simulation-Based Campus Energy Analysis Environment for Situational Awareness and Future Energy System Planning

Researchers at Georgia Tech (GT) have recently begun the GT Smart Energy Campus initiative, which combines campus energy metering data with physics-based modeling and simulation to create an integrated analysis environment for campus energy. The environment consists of a digital representation of campus, which supports situational awareness, as well as a virtual test bed for analyzing emerging energy technologies and future scenarios. The first year of the initiative has focused on evaluating campus energy metering data using visual analytics and statistical analysis techniques. Data analysis is presented as having value for two main uses: (1) as attention-directing information to help system operators diagnose anomalies and (2) as a precursor to modeling and simulation (M&S) in future phases of the Smart Energy Campus initiative. The environment is explained using the initial study scoping of the campus thermal energy generation and distribution systems. Furthermore, a modeling and simulation approach leveraging the Modelica M&S language is described, and preliminary results in using it to represent the campus chilled water system are presented.Copyright

Modeling and simulation of integrated intelligent systems

Complex systems consist of a large number of entities with their independent local rules and goals, along with their interactions. The effect of these properties tends to produce complex behaviors that are required to be understood in order to analyze and design the systems. However, these behaviors are difficult to be predicted a priori, and can only be studied through simulation. The study presented in this paper proposes a process for developing an integrated dynamic modeling and simulation environment designed for understanding the behavior of the next generation naval ship which is envisioned to be self-sensing, self-assessing and self-reacting. Various models, including power model, fluid model and control model, are developed to investigate the functionalities of the naval ship systems. An object oriented approach is employed to validate the architectural design of the integrated simulation environment and a surrogate modeling technique is utilized to accelerate the simulation speed.

Evaluation of control system performance using Multiple Criteria Decision Making techniques

In control system design, the evaluation of the control system performance usually involves the tradeoff between multiple, potential conflicting criteria. Multi-Criteria Decision Making (MCDM) techniques can be used to effectively deal with such problem and facilitate the decision making in the evaluation process. In this study, an intelligent knowledge-based decision support system is developed to choose the most appropriate MCDM method for the problem of product selection and then provide a step by step problem solving procedure for identifying the best alternative for the given problem. A control system evaluation problem is conducted as a proof of implementation to demonstrate the functionality and effectiveness of the integrated evaluation approach with the use of MCDM techniques.

Development of a Building-Specific, Multi-Criteria Energy Technology Portfolio Evaluation Approach

An accurate building energy technology portfolio evaluation approach is needed that integrates physics-based models and business case analysis. Open source, parametric building modeling tools have recently matured to enable system-level building energy analysis at high fidelities. It is observed that these modeling tools usually only analyze energy savings and are not concerned with other criteria often factored into the choice of an energy technology portfolio. This paper presents an approach to constructing a parametric, physics-based, building-specific, business case analysis tool for quantifying multi-criteria performance of building energy technology portfolios. The resulting environment, which is used to build up a portfolio step-by-step and analyze performance trades, is explained through a case study. The application presented is for a building energy retrofit, comparing building energy consumption before and after application of technologies from a set of contenders, but it can be extended to the design of new buildings.© 2014 ASME

A hierarchical control architecture for resource allocation

Complex systems consist of a large number of entities with their independent local rules and goals, along with their interactions. In the operations of complex system, such as naval ship, proper decisions and controls are required to keep the system working functionally and effectively. An Integrated Reconfigurable Intelligent System (IRIS) framework is proposed for facilitating the design and operation of such naval complex systems through increased automation and reconfigurability. With the reconfigurable systems, the IRIS designed ship will assess the incoming information and then configure itself into the mode most adequate to deal with the situation under consideration. The study in this paper presents a hierarchical control architecture to deal with ever-evolving real time information and making autonomous control for achieving the reconfigurability of naval ship. The control architecture consists of three levels working together to achieve the overall operational goal. It is implemented on a resource allocation problem for a chilled water system. The successful resource allocation leads to a reconfiguration of the system which is the most suitable to handle the situation at hand.

A Concept Selection Method Developed from a Probabilistic Multi-Criteria Decision Making Technique Using Utility Theory

In todays aircraft design, more and more attention is paid to the conceptual and preliminary design stages in order to increase the capability of choosing a design that will be successful. Therefore, the decisions made during these design phases play a central role in determining the success of a design. Decision making techniques at these stages, must manage multiple, conflicting criteria and capture associated uncertainties. The method presented in this study was developed from Joint Probability Decision Making (JPDM), a probabilistic multiple criteria decision making technique. The proposed method eliminated the limitations that JPDM has by utilizing Utility Functions to represent the decision makers preference. An advanced rotorcraft concept selection problem is performed in order to demonstrate the improvements, and the results obtained from the proposed method and the JPDM technique are compared with each other.

Creation of a decision-support methodology for selecting more-electric aircraft subsystem technologies

Ambitious aircraft emission goals combined with airline fuel costs are driving an increasing focus on energy efficiency for the aircraft industry. Aircraft Equipment Systems (AES) perform key aircraft functions, such as pressurization or control surface actuation, but they are also energy consumers. Selecting the AES technologies of the future is inherently a multi-criteria problem if all stakeholders are to be satisfied. The problem is further complicated because technologies cannot be considered to be completely independent and must be considered from a subsystem architecture perspective. This paper proposes an evolution of the Strategic Prioritization and Planning (SP2) method including a two-level approach that considers both independent technologies and integrated architectures. These are then linked to technology attributes and high-level objectives through qualitative subject matter expert driven relationships. The information is finally displayed in an interactive environment that ranks technologies and architectures, while also allowing the decision maker to define and explore the scenarios driving the rankings.

Development and Implementation of A Hybrid Multi- Criteria Decision Making Technique

n modern aircraft design, increased attention is being paid to the conceptual and preliminary design phases so as to increase the odds of creating a design that will ultimately be successful at the completion of the design process. Since aerospace systems are complex systems with interacting disciplines and technologies, the decision makers dealing with such design problems are involved in balancing multiple, potentially conflicting attributes/criteria, transforming a large amount of customer supplied guidelines into a solidly defined set of requirement definitions. As a result, the criteria have to be all simultaneously taken into account and a compromise essentially becomes part of the decision making process. Various methods and techniques are available to deal with such sort of multi-criteria decision making (MCDM) problems. In the 1970’s, Saaty proposed the Analytic Hierarchy Process (AHP), which facilitates the MCDM problems that have a hierarchical structure of attributes by reducing complex decisions to a series of pair-wise comparisons. In this method, the preference information is elicited as the pair-wise comparisons between attributes or alternatives and treated using the eigenvector method. The other straightforward method to handle the MCDM problem is the Overall Evaluation Criterion (OEC) technique, presented in Ref 3. The OEC is a single metric and is obtained by summing multiple non-dimensional attribute metrics normalized by the metric values of a relevant baseline. Another commonly used MCDM technique is the Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS). The “best” solution chosen by TOPSIS is the alternative that is the closest to the positive ideal solution and the furthest from the negative ideal solution. The separation between each alternative solution and the ideal solution, which is determined by the weighted criteria, is rather sensitive to criterion weights, so typically several weighting scenarios are investigated to determine the final solution. Among these developed MCDM methods, different methods have different underlying assumptions, information requirements, analysis models, and decision rules that are designed for solving a certain class of decision making problems. This implies that it is critical to use the most appropriate method to solve the problem under consideration since the use of unsuitable method always leads to misleading design decisions. Consequently, bad design decisions will result in big loss to the society, such as property damage or personal injury. Thus, it is necessary to review the existing MCDM methods, discuss in depth their advantages, disadvantages, applicability, computational complexity, etc. in order to make right decision when choosing the right method for the given problem. In this paper a hybrid MCDM method is developed to deal with the problem under consideration. Relative weights of the evaluation criteria are elicited by using the eigenvector method to describe the decision maker’s preference information. The TOPSIS method is used to analyze the qualitative and quantitative data of input parameters and find the solution to the given problem. An aircraft technology selection problem is conducted as a proof of implementation to demonstrate the functionality and effectiveness of the proposed methodology.