Gaussian Process Model-Based Performance Uncertainty Quantification of a Typical Turboshaft Engine

The gas turbine engine is a widely used thermodynamic system for aircraft. The demand for quantifying the uncertainty of engine performance is increasing due to the expectation of reliable engine performance design. In this paper, a fast, accurate, and robust uncertainty quantification method is proposed to investigate the impact of component performance uncertainty on the performance of a classical turboshaft engine. The Gaussian process model is firstly utilized to accurately approximate the relationships between inputs and outputs of the engine performance simulation model. Latin hypercube sampling is subsequently employed to perform uncertainty analysis of the engine performance. The accuracy, robustness, and convergence rate of the proposed method are validated by comparing with the Monte Carlo sampling method. Two main scenarios are investigated, where uncertain parameters are considered to be mutually independent and partially correlated, respectively. Finally, the variance-based sensitivity analysis is used to determine the main contributors to the engine performance uncertainty. Both approximation and sampling errors are explained in the uncertainty quantification to give more accurate results. The final results yield new insights about the engine performance uncertainty and the important component performance parameters.

First impression biases in the performing arts: taste-based discrimination and the value of blind auditioning

I develop a game-theoretic framework to study the repercussions of an evaluator’s bias against a specific group of applicants. The evaluator decides upfront between holding an informed or a blind audition. In the latter, the evaluator learns neither the applicant’s ability nor the gender. I show that, above a threshold bias, the evaluator prefers a blind audition to provide high effort incentives exclusively for high-ability applicants. Consequently, committing to no information can be beneficial for the evaluator. I also show that a highly biased evaluator’s preferences align with those of a highly able female. I extend the framework to performance uncertainty and gender-blind CVs and compare blind auditions to affirmative action. The framework is relevant for auditory-based applications: my results can explain why blind auditions have increased the probability of a female orchestra musician being hired via taste-based discrimination and challenge explanations grounded in statistical discrimination.

Design of H∞Control and Simplified Instrument Fault Detection on DC Motor

In the presence of uncertainty, a closed-loop system must be able to maintain its stability and performance. Uncertainty can be categorized into two meanings, disturbance from external systems and perturbation in a dynamical system. In this paper, we will present a robust control design by considering a disturbance from external factors, and analyze its robustness using Structured Singular Value respect to parametric uncertainty and external disturbance. Beside that, every control system has their own region to operate, outside that region a performance degradation will occur, and led into unstability. One factor to that catastrophic is a fault in instrument reading, to anticipate it, this paper also implement Simplified Instrument Fault Detection method to detect a sensor fault in order to give an alarm for further action.

Design of H∞Control and Simplified Instrument Fault Detection on DC Motor

In the presence of uncertainty, a closed-loop system must be able to maintain its stability and performance. Uncertainty can be categorized into two meanings, disturbance from external systems and perturbation in a dynamical system. In this paper, we will present a robust control design by considering a disturbance from external factors, and analyze its robustness using Structured Singular Value respect to parametric uncertainty and external disturbance. Beside that, every control system has their own region to operate, outside that region a performance degradation will occur, and led into unstability. One factor to that catastrophic is a fault in instrument reading, to anticipate it, this paper also implement Simplified Instrument Fault Detection method to detect a sensor fault in order to give an alarm for further action.

Effect of Alliance Network Asymmetry on Firm Performance and Risk

Persistent high failure rates of new product alliances call for identification of factors that might improve alliance outcomes. In this research, the authors identify two attributes of alliance network asymmetry that affect alliance performance and performance uncertainty: differences in the number of prealliance direct ties, which can create asymmetry in the volume of resources of the two firms, and differences in the interconnectivity among prealliance indirect ties, which leads the firms to possess different types of resources. The authors theorize that absolute levels of such asymmetries have curvilinear effects on alliance performance and performance uncertainty, which materialize as a focal firm’s abnormal returns and risk, respectively. They demonstrate that direct tie asymmetry has an inverted U-shaped effect on the focal firm’s abnormal returns and a U-shaped effect on its risk. Indirect tie asymmetry also has a U-shaped effect on the focal firm’s risk. However, the focal firm’s innovation quality and preexisting ties with its partner flatten these curvilinear effects. The findings have implications for partner selection in new product alliances.

Why technology adoption succeeds or fails: an exploration from the perspective of intra-organizational legitimacy

This paper constructs an intra-organizational legitimacy analysis framework to reveal the conditional mechanisms of technology adoption at the organization level. A retrospective look on a 9-year application process of ERP (Enterprise Resource Planning) in a Chinese state-owned enterprise shows how the application effects of an adopted technology fluctuate with changes to intra-organizational legitimacy, which itself is composed of performance legitimacy, task legitimacy, and value legitimacy. This research indicates that gaining sufficient legitimacy is one necessity for the success of technology adoption in organizations. Basically, performance legitimacy determines how far technologies can be transferred into the corporate sector. When a new technology adoption starts with performance uncertainty, task legitimacy ensures organizational resource investments that serve to initiate and accelerate technology adoption. Value legitimacy, on the other hand, ensures informal resource input, which preserves the technology during crises for future possible reuse and advances the application when used.