An Integrated Risk Analysis Methodology in a Multidisciplinary Design Environment

Design of complex, one-of-a-kind systems, such as space transportation systems, is characterized by high uncertainty and, consequently, high risk. It is necessary to account for these uncertainties in the design process to produce systems that are more reliable. Systems designed by including uncertainties and managing them, as well, are more robust and less prone to poor operations as a result of parameter variability. The quantification, analysis and mitigation of uncertainties are challenging tasks as many systems lack historical data. In such an environment, risk or uncertainty quantification becomes subjective because input data is based on professional judgment. Additionally, there are uncertainties associated with the analysis tools and models. Both the input data and the model uncertainties must be considered for a multi disciplinary systems level risk analysis. This research synthesizes an integrated approach for developing a method for risk analysis. Expert judgment methodology is employed to quantify external risk. This methodology is then combined with a Latin Hypercube Sampling - Monte Carlo simulation to propagate uncertainties across a multidisciplinary environment for the overall system. Finally, a robust design strategy is employed to mitigate risk during the optimization process. This type of approach to risk analysis is conducive to the examination of quantitative risk factors. The core of this research methodology is the theoretical framework for uncertainty propagation. The research is divided into three stages or modules. The first two modules include the identification/quantification and propagation of uncertainties. The third module involves the management of uncertainties or response optimization. This final module also incorporates the integration of risk into program decision-making. The risk analysis methodology, is applied to a launch vehicle conceptual design study at NASA Langley Research Center. The launch vehicle multidisciplinary environment consists of the interface between configuration and sizing analysis outputs and aerodynamic parameter computations. Uncertainties are analyzed for both simulation tools and their associated input parameters. Uncertainties are then propagated across the design environment and a robust design optimization is performed over the range of a critical input parameter. The results of this research indicate that including uncertainties into design processes may require modification of design constraints previously considered acceptable in deterministic analyses

Lessons learned from the financial crisis for financial stability and banking supervision

The financial crisis that began in 2007 has revealed a need for a new supervisory and regulatory approach aimed at strengthening the system and containing the risk of future financial and economic disruptions. Three ingredients are needed to ensure financial stability: robust analysis, better regulation, and international cooperation. First, financial stability analysis must be improved to take full account of the different sources of systemic risk. Data coverage of the balance sheets of both non-bank financial institutions and the non-financial sectors should be increased. Moreover, to address the problems raised by the interconnections among financial institutions more granular and timely information on their exposures is needed. There must be further integration of macro- and micro-information and an upgrading of financial stability models. The second ingredient is the design of robust regulatory measures. Under the auspices of the G20 and the Financial Stability Board, the Basel Committee on Banking Supervision recently put forward substantial proposals on capital and liquidity. They will result in more robust capital base, lower leverage, less cyclical capital rules and better control of liquidity risk. Finally, the third ingredient is strong international cooperation. Ensuring more effective exchanges of information among supervisors in different jurisdictions and successful common actions is key in preserving financial integration, while avoiding negative cross-border spill-overs. Better resolution regimes are part of the efforts to ensure that the crisis of one institution does not impair the ability of the financial markets to provide essential services to the economy.financial crisis, international cooperation, macroprudential analysis, procyclicality, prudential regulation, stress tests

Geometric robustness and dynamic response management by structural topometry optimisation to reduce the risk for squeak and rattle

Historically, squeak and rattle (S&R) sounds have been among the top quality problems and a major contributor to the warranty costs in passenger cars. Geometric variation is among the main causes of S&R. Though, geometric variation analysis and robust design techniques have been passively involved in the open-loop design activities in the predesign-freeze phases of car development. Despite the successful application of topometry optimisation to enhance attributes such as weight, durability, noise and vibration and crashworthiness in passenger cars, the implementation of closed-loop structural optimisation in the robust design context to reduce the risk for S&R has been limited. In this respect, the main obstacles have been the demanding computational resources and the absence of quantified S&R risk evaluation methods. In this work, a topometry optimisation approach is proposed to involve the geometric variation analysis in an attribute balancing problem together with the dynamic response of the system. The proposed method was used to identify the potential areas of a door component that needed structural reinforcement. The main objective was to enhance the design robustness to minimise the risk for S&R by improving the system response to static geometrical uncertainties and dynamic excitation

Lessons for Asian Countries from Pension Reforms in Chile

Chile's 1981 reform revolutionized pension design and created a system that was lauded and emulated widely. The main feature of the system was the creation of state-mandated, privately managed individual pension capitalization accounts based on contributions of employees. After nearly three decades of experience, there is a reassessment of the extent to which the pension system has achieved its objectives, particularly with respect to coverage and adequacy. In March 2006, the newly elected President Bachelet set up a Presidential Advisory Council on Pension Reform under the chairmanship of Mario Marcel to evaluate the existing pension system. This paper examines the rationale and the nature of the recommendations made by the Council. The analysis focuses on the structure of the proposed new pension system and risk-sharing implications of different pillars of the system, the accessibility of the existing pension system in terms of coverage, particularly for women and self-employed persons, the impact of reform on transaction costs; investment policies and management and their implications for rates of return and financial market development. The implications of the new system on pension design and policy debate in Asian countries are addressed. The paper suggests that must imbibe lessons from countries such as Chile and urgently undertake the task of constructing sustainable, robust and adequate pension systems and social safety nets.Chile, Asia, Pension Reform

Conformance Testing for Stochastic Cyber-Physical Systems

Conformance is defined as a measure of distance between the behaviors of two dynamical systems. The notion of conformance can accelerate system design when models of varying fidelities are available on which analysis and control design can be done more efficiently. Ultimately, conformance can capture distance between design models and their real implementations and thus aid in robust system design. In this paper, we are interested in the conformance of stochastic dynamical systems. We argue that probabilistic reasoning over the distribution of distances between model trajectories is a good measure for stochastic conformance. Additionally, we propose the non-conformance risk to reason about the risk of stochastic systems not being conformant. We show that both notions have the desirable transference property, meaning that conformant systems satisfy similar system specifications, i.e., if the first model satisfies a desirable specification, the second model will satisfy (nearly) the same specification. Lastly, we propose how stochastic conformance and the non-conformance risk can be estimated from data using statistical tools such as conformal prediction. We present empirical evaluations of our method on an F-16 aircraft, an autonomous vehicle, a spacecraft, and Dubin's vehicle

Optimizing surveillance for livestock disease spreading through animal movements

The spatial propagation of many livestock infectious diseases critically depends on the animal movements among premises; so the knowledge of movement data may help us to detect, manage and control an outbreak. The identification of robust spreading features of the system is however hampered by the temporal dimension characterizing population interactions through movements. Traditional centrality measures do not provide relevant information as results strongly fluctuate in time and outbreak properties heavily depend on geotemporal initial conditions. By focusing on the case study of cattle displacements in Italy, we aim at characterizing livestock epidemics in terms of robust features useful for planning and control, to deal with temporal fluctuations, sensitivity to initial conditions and missing information during an outbreak. Through spatial disease simulations, we detect spreading paths that are stable across different initial conditions, allowing the clustering of the seeds and reducing the epidemic variability. Paths also allow us to identify premises, called sentinels, having a large probability of being infected and providing critical information on the outbreak origin, as encoded in the clusters. This novel procedure provides a general framework that can be applied to specific diseases, for aiding risk assessment analysis and informing the design of optimal surveillance systems.Comment: Supplementary Information at https://sites.google.com/site/paolobajardi/Home/archive/optimizing_surveillance_ESM_l.pdf?attredirects=

Electrical load-sizing methodology to aid conceptual and preliminary design of large commercial aircraft

The importance of the more electric aircraft has been highlighted in many publications, projects and industrial presentations. By definition, the more electric aircraft concept achieves the majority of the required system functionality by using electrically powered sub-systems and components. This manifests itself in much higher electrical power demands on-board aircraft, compared to conventional architectures. This presents many challenges in the design process. To alleviate the risk and choose the optimum architectures for the systems on the aircraft, it is essential to incorporate the characteristics and possible configurations of the electrical network in the conceptual and preliminary design stages. Hence the current practice of performing an electrical load analysis at the detailed design stage is not adequate. To address this gap, this paper presents a viable and robust methodology to define requirements, size components and systems and calculates the electric power requirements at the preliminary design stages. The methodology uses the conventional aircraft, systems and components as the baseline and uses mathematical techniques and logical sequences of component operation, developed through the research, to size electrical load profiles for conventional aircraft. It then adapts this result to the more electric aircraft concept by adding key components that would account for the difference between a conventional system and a more electric system. The methodology presented here makes the design process more robust and aids the choice of the optimum design for the aircraft

Systemic Analysis of the use of Artificial Intelligence (AI) In Regulating Terrorist Content on Social Media Ecosystem Using Functional Dependency Network Analysis (FDNA)

This research is a systemic analysis of emerging risks to the use Artificial Intelligence (AI) in regulating terrorist content on social media ecosystems using Functional Dependency Network Analysis (FDNA), a proven system-design-and-analysis tool). The research has three phases: 1) framing the problem by identifying and describing AI ecosystem elements as intended, implied and explicit objectives, discernible attributes, and performance indictors; 2) describing the idealized problem-solved scenario, which includes detailing ‘success’ states of the ecosystem; and 3) systemic risk analysis including identifying failure scenarios for each element and establishing causalities among elemental attributes leading to failure scenarios. This research contributes toward a sustainable and more robust solution to the issue of regulating one particular form of malicious content on social media platforms (i.e., terrorist content) based not on one perspective but on the entire ‘ecosystem’ using FDNA

COMPARING THE PERFORMANCE OF REGRESSION AND NEURAL NETWORKS AS DATA QUALITY VARIES: A BUSINESS VALUE APPROACH

Under circumstances where data quality may vary (due to inaccuracies or lack of timeliness, for example), knowledge about the potential performance of alternate predictive models can help a decision maker to design a business value-maximizing information system. This paper examines a real-world example from the field of finance to illustrate a comparison of alternative modeling tools. Two modeling alternatives are used in this example: regression analysis and neural network analysis. There are two main results: (1) Linear regression outperformed neural nets in terms of forecasting accuracy, but the opposite was true when we considered the business value of the forecast. (2) Neural net-based forecasts tended to be more robust than linear regression forecasts as data accuracy degraded. Managerial implications for financial risk management of MBS portfolios are drawn from the results.Information Systems Working Papers Serie