New approaches to improve the performance of the PEM based fuel cell power systems

Fuel cells are expected to play an important role in future power generation. However, significant technical challenges remain and the commercial breakthrough of fuel cells is hindered by the high price of fuel cell components. As is well known, the fuel cells do not provide the robust source characteristics required to effectively follow the load during significant load steps and they have limited overload-handling capability. Further, the performance of the fuel cell is significantly degraded when the CO (Carbon Monoxide) is contained in the hydrogen fuel. In this thesis several new approaches to improve the performance of PEM based fuel cell power systems are discussed. In the first section an impedance model of the Proton Exchange Membrane Fuel Cell Stack (PEMFCS) is first proposed. This equivalent circuit model of the fuel cell stack is derived by a frequency response analysis (FRA) technique to evaluate the effects of the ripple current generated by the power-conditioning unit. Experimental results are presented to show the effects of the ripple currents. In the second section, a fuel cell powered UPS (Uninterruptible Power Supply) system is proposed. In this approach, two PEM Fuel Cell modules along with suitable DC/DC and DC/AC power electronic converter modules are employed. A Supercapacitor module is also employed to compensate for instantaneous power fluctuations including overload and to overcome the slow dynamics of the fuel processor such as reformers. A complete design example for a 1-kVA system is presented. In the third section, an advanced power converter topology is proposed to significantly improve the CO tolerance on PEM based fuel cell power systems. An additional two-stage dc-dc converter with a supercapacitor module is connected to the fuel cell to draw a low frequency (0.5Hz) pulsating current of the specific amplitude (20-30[A]) from the fuel cell stack. CO on the catalyst surface can be electro-oxidized by using this technique, and thereby the CO tolerance of the system can be significantly improved. Simulation and experimental results show the validity and feasibility of the proposed scheme

Effects of US Monetary Policy on Gross Capital Flows: Cases in Korea

U.S. monetary policy has been claimed to generate global spillover and to destabilize other small open economies. We analyze the effects of certain identified U.S. monetary shocks on gross capital flows in the Korean economy using the local projection method. Consistent with previous results on other small open economies, we initially confirm that U.S. interest rate hikes are dynamically correlated with foreign outflows and residents’ inflows. That is, not only are they correlated with withdrawals by foreigners but they are also correlated with those by domestic (Korean) investors. The results are mostly driven by portfolio flows. Second, however, the marginal response to a U.S. monetary policy shock is, on average, subdued if we focus on the sample periods after the Global financial crisis of 2007-2008 (henceforth, global financial crisis). We conjecture a possible reason behind the change, an institutional change related to financial friction. If the degree of pledgeability of the value of net worth increases, the marginal responses by both investors would drop with a U.S. monetary policy shock, consistent with our findings

Scenario-Based Strategic Planning for Future Civil Vertical Take-off and Landing (VTOL) Transport

Rapid evolvement of the vertical take-off and landing (VTOL) technology in conjunction with recent robust R&D has demonstrated the technical feasibility of the civil VTOL system as a short-haul mass transit mode. Its combined benefits of a helicopter and a turboprop into one aircraft is expected to become an effective remedy for congested air traffic and difficulties with airport expansions in the metropolitan areas along with the potential benefit to improve accessibility to population centers and remote areas where conventional aircraft cannot access. In this study, based on a the Political, Economic, Social, Technological, Environmental, and Legal (PESTEL) factors and Technology Readiness Level (TRL) analysis, a scenario-based strategic plan for the civil VTOL transport mode was proposed on a 20-year timeframe and three key strategic factors were identified: 1) sustainable VTOL technology as an enabler, 2) VTOL infrastructure and procedure as an operation platform, and 3) integration of the VTOL technology into the existing air transportation system as a differentiator. While many socio-economic and regulatory gaps were found from this study to integrate civil VTOL aircraft into the current commercial aviation system, the integrative mode of the civil VTOL transport exhibits potentials to tackle the current challenges of the aviation industry to enhance air-mobility between the intra- and inter-city transport and provide passengers with significant benefits to reduce transportation costs and travel time

Learning Delaunay Triangulation using Self-attention and Domain Knowledge

Delaunay triangulation is a well-known geometric combinatorial optimization problem with various applications. Many algorithms can generate Delaunay triangulation given an input point set, but most are nontrivial algorithms requiring an understanding of geometry or the performance of additional geometric operations, such as the edge flip. Deep learning has been used to solve various combinatorial optimization problems; however, generating Delaunay triangulation based on deep learning remains a difficult problem, and very few research has been conducted due to its complexity. In this paper, we propose a novel deep-learning-based approach for learning Delaunay triangulation using a new attention mechanism based on self-attention and domain knowledge. The proposed model is designed such that the model efficiently learns point-to-point relationships using self-attention in the encoder. In the decoder, a new attention score function using domain knowledge is proposed to provide a high penalty when the geometric requirement is not satisfied. The strength of the proposed attention score function lies in its ability to extend its application to solving other combinatorial optimization problems involving geometry. When the proposed neural net model is well trained, it is simple and efficient because it automatically predicts the Delaunay triangulation for an input point set without requiring any additional geometric operations. We conduct experiments to demonstrate the effectiveness of the proposed model and conclude that it exhibits better performance compared with other deep-learning-based approaches

New approaches to improve the performance of the PEM based fuel cell power systems

Fuel cells are expected to play an important role in future power generation. However, significant technical challenges remain and the commercial breakthrough of fuel cells is hindered by the high price of fuel cell components. As is well known, the fuel cells do not provide the robust source characteristics required to effectively follow the load during significant load steps and they have limited overload-handling capability. Further, the performance of the fuel cell is significantly degraded when the CO (Carbon Monoxide) is contained in the hydrogen fuel. In this thesis several new approaches to improve the performance of PEM based fuel cell power systems are discussed. In the first section an impedance model of the Proton Exchange Membrane Fuel Cell Stack (PEMFCS) is first proposed. This equivalent circuit model of the fuel cell stack is derived by a frequency response analysis (FRA) technique to evaluate the effects of the ripple current generated by the power-conditioning unit. Experimental results are presented to show the effects of the ripple currents. In the second section, a fuel cell powered UPS (Uninterruptible Power Supply) system is proposed. In this approach, two PEM Fuel Cell modules along with suitable DC/DC and DC/AC power electronic converter modules are employed. A Supercapacitor module is also employed to compensate for instantaneous power fluctuations including overload and to overcome the slow dynamics of the fuel processor such as reformers. A complete design example for a 1-kVA system is presented. In the third section, an advanced power converter topology is proposed to significantly improve the CO tolerance on PEM based fuel cell power systems. An additional two-stage dc-dc converter with a supercapacitor module is connected to the fuel cell to draw a low frequency (0.5Hz) pulsating current of the specific amplitude (20-30[A]) from the fuel cell stack. CO on the catalyst surface can be electro-oxidized by using this technique, and thereby the CO tolerance of the system can be significantly improved. Simulation and experimental results show the validity and feasibility of the proposed scheme

Predicting the U.S. Airline Operating Profitability using Machine Learning Algorithms

With the increasing competition and cost pressures, the U.S. airline industry has explored methods to reduce operating costs and diversify revenue sources for improving financial performance. Understanding the influence of operating revenues and expenses on airline profitability is imperative for the long term growth of the airlines and continued generation of profits. This study examined the cost and revenue data of the U.S. major airlines from the Department of Transportation’s Bureau of Transportation Statistics Form 41 reports between 2009 and 2018. Using SAS Enterprise Miner software, researchers used variables representing revenue and expenses from these data to develop and test predictive models for airline profit generation. Decision trees and linear regression methods were used for two identical datasets one with monetary values and the other with percentage values to identify the best predictor of airline profitability. From this study, decision tree models appeared to be better predictors of profitability for major airlines. Using the decision model, transport-related revenue and expenses which are incidentals to the air transportation services performed by airlines were found to be the two most influential factors in predicting the U. S. airlines’ profitability

The boundary of Rauzy fractal and discrete tilings

The Rauzy fractal is a domain in the two-dimensional plane constructed by the Rauzy substitution, a substitution rule on three letters. The Rauzy fractal has a fractal-like boundary, and the currently known its constructions is not only for its boundary but also for the entire domain. In this paper, we show that all points in the Rauzy fractal have a layered structure. We propose two methods of constructing the Rauzy fractal using layered structures. We show how such layered structures can be used to construct the boundary of the Rauzy fractal with less computation than conventional methods. There is a self-replicating pattern in one of the layered structure in the Rauzy fractal. We introduce a notion of self-replicating word and visualize how some self-replicating words on three letters creates discrete tiling of the two dimensional plane

Assessing Trust in Air Traffic Controllers: A Pilot Study

The safety of the National Airspace System is reliant upon the partnership between pilots and air traffic controllers facilitated through verbal communications. When the partnership based on trust is strong, the pilot is able to better manage the complexities associated with flying in congested airspace and reduce the possibility of certain errors. Studying barriers to communication is important in understanding how trust is built and maintained. Bias has been shown to be a barrier to trust in communications and aviation. Previous studies have researched trust in air traffic automation and trust based on confidence in the controller’s speech. However, a search of the literature revealed no discussions of trust based on the accent of the controller. Being able to detect accent bias is an important first step in being able to address issues and reduce the risk associated with communications problems. The purpose of the current project is to assess a pilot’s trust in controllers based on the controller’s accent as a first step in creating a model to predict trust in controllers. Participants will be presented audio recordings of various air traffic controllers and then rate their perceived trust in the controller. Results of the study will be presented. Keywords: trust, accent bias, air traffic contro

Comparative Analysis of Tongue Indices between Patients with and without a Self-Reported Yin Deficiency: A Cross-Sectional Study

We investigated the hypothesis that Yin-deficient patients have a reddened tongue with less coating. We screened 189 participants aged 20 to 49 years, complaining of headache. To classify patients in terms of Yin deficiency, we used two self-reporting Yin-deficiency questionnaires (Yin-Deficiency Questionnaire and Yin-Deficiency Scale) and diagnosis by a doctor. Based on the tests, a total of 33 subjects were assigned to a Yin-deficient group and 33 subjects were assigned to a nondeficient control group. Tongue images were acquired using a computerized tongue diagnostic system, for evaluating tongue indices. The tongue coating percentage and tongue redness were calculated as the mean a⁎ value of both the whole tongue area (WT a⁎) and the tongue body area (TB a⁎). The tongue coating percentage of the Yin-deficient group (34.79 ± 10.76) was lower than that of the nondeficient group (44.13 ± 14.08). The WT a⁎ value of the Yin-deficient group (19.39 ± 1.52) was significantly higher than that of the nondeficient group (18.21 ± 2.06). However, the difference in the TB a⁎ value between the two groups was not significant. In conclusion, we verified that Yin-deficient patients had less tongue coating and tended to have a more reddish tongue than nondeficient patients