The Experts below are selected from a list of 114594 Experts worldwide ranked by ideXlab platform
B. Herrazti - One of the best experts on this subject based on the ideXlab platform.
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Sensitivity analysis of supercritical CO2 power Cycle energy and exergy efficiencies regarding Cycle Component efficiencies for concentrating solar power
Energy Conversion and Management, 2019Co-Authors: D. Novales, Aitor Erkoreka, V. De La Peña, B. HerraztiAbstract:Abstract Supercritical CO2 Cycles have been said to be a good alternative to the Rankine Cycles for Concentrating Solar Power plants of the future. The next generation molten salts will be able to achieve 700 °C, which is a suitable temperature for Supercritical CO2 Cycles. However, there is a big uncertainty about the efficiencies of the Cycle Components, which could make these Cycles unviable. A sensitivity analysis of the energy efficiency of the Recompression Cycle and Partial Cooling Cycle, regarding turbomachinery isentropic efficiencies and Recuperator effectiveness variations, has been carried out to show that the Recompression Cycle’s energy efficiency is considerably more sensitive than the Partial Cooling Cycle’s. From the sensitivity analysis, it can also be concluded that the Recompression Cycle is the best performing Cycle for most of the studied cases, with energy efficiencies in the range between 32.97% and 51.91%. Exergetically, the Recompression Cycle is also more suitable in most situations, and the exergy analysis on Cycle Components shows that irreversibilities occur mainly in the Recuperators, which means that future research should focus on methods to reduce irreversibilities in these Components. The state-of-the-art of Supercritical Rankine Cycle plant net energy efficiencies currently reach 45.60% for fossil fuel plants. Although Supercritical CO2 Cycles are a simpler and more compact alternative, this work concludes that only the optimized Recompression Cycle with turbomachinery isentropic efficiencies over 92% and Recuperator effectiveness over 95% are able to obtain similar or higher efficiencies than actual Supercritical Rankine Cycles. Furthermore, the sensitivity analysis plots permit the areas to be mapped where each of the optimized two-Cycle efficiencies can compete with the Supercritical Rankine Cycles regarding the turbomachinery isentropic efficiencies and Recuperator effectiveness.
Robert G. King - One of the best experts on this subject based on the ideXlab platform.
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Measuring Business Cycles: Approximate Band-Pass Filters for Economic Time Series
Review of Economics and Statistics, 1999Co-Authors: Marianne Baxter, Robert G. KingAbstract:Band-pass filters are useful in a wide range of economic contexts. This paper develops a set of approximate band-pass filters and illustrates their application to measuring the business-Cycle Component of macroeconomic activity. Detailed comparisons are made with several alternative filters commonly used for extracting business-Cycle Components. © 2000 by the President and Fellows of Harvard College and the Massachusetts Institute of Technology
Greg Nellis - One of the best experts on this subject based on the ideXlab platform.
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mass optimization of a supercritical co2 brayton Cycle with a direct cooled nuclear reactor for space surface power
Applied Thermal Engineering, 2019Co-Authors: Becky Sondelski, Greg NellisAbstract:Abstract A long life, reliable, and compact surface power system will be necessary to achieve future goals in space exploration. This application uniquely requires the system to be optimized with respect to mass because system mass directly drives the space launch cost associated with transporting the system to its desired location. In this study, a supercritical CO2 Brayton Cycle coupled to a direct-cooled nuclear reactor was designed and optimized for mass. Robust models were developed for each Brayton Cycle Component in order to model the Cycle performance. The three most massive Components of this Cycle are the radiator-based heat rejection system (subsequently referred to as the “radiator”), recuperator, and reactor. Mass correlations for the recuperator and radiator were established through interactions with Component experts from industry and national labs. A reactor model was developed to predict the minimum mass reactor that satisfies neutronic and thermal limitations for given Cycle conditions. The system optimization explores tradeoffs between the reactor, recuperator, and radiator sizes in order to identify the least massive system that will satisfy the power (40 kWe) and life (10 yr) requirements. To explore the effects of turbine inlet temperature on system mass, three types of microtube and shell recuperator technologies were considered: baseline stainless steel (which is consistent with the industry partner’s current designs), stainless steel with non-heritage tube sizes (which requires further development of manufacturing techniques), and Inconel (which is not a current/legacy design). Both stainless steel designs have a temperature limit of 823 K, which limits the turbine inlet temperature to 900 K. The baseline stainless steel design results in a combined mass of 738 kg. The stainless steel design allowing for non-heritage tube sizes reduces the combined mass to 674 kg (a 9% improvement). The Inconel design leads to an optimal turbine inlet temperature of 1120 K and reduces the combined mass to 391 kg (a 47% improvement). Interesting conclusion from this study include: (1) radiator mass dominates the total mass, and this drives the Cycle to relatively high heat rejection temperatures resulting in a compressor inlet state point that is not close to the vapor dome; thus, the typical advantages of an sCO2 system are not realized, and a working fluid with a higher critical temperature may be more suitable, and (2) neutronic limitations cause the reactor size to be relatively unaffected by the power level.
Kai Ming Lee - One of the best experts on this subject based on the ideXlab platform.
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Measuring Asymmetric Stochastic Cycle Components in U.S. Macroeconomic Time Series
2005Co-Authors: Siem Jan Koopman, Kai Ming LeeAbstract:To gain insights in the current status of the economy, macroeconomic time series are often decomposed into trend, Cycle and irregular Components. This can be done by nonparametric band-pass filtering methods in the frequency domain or by model-based decompositions based on autoregressive moving average models or unobserved Components time series models. In this paper we consider the latter and extend the model to allow for asymmetric Cycles. In theoretical and empirical studies, the asymmetry of cyclical behavior is often discussed and considered for series such as unemployment and gross domestic product (GDP). The number of attempts to model asymmetric Cycles is limited and it is regarded as intricate and nonstandard. In this paper we show that a limited modification of the standard Cycle Component leads to a flexible device for asymmetric Cycles. The presence of asymmetry can be tested using classical likelihood based test statistics. The trend-Cycle de! composition model is applied to three key U.S. macroeconomic time series. It is found that cyclical asymmetry is a prominent salient feature in the U.S. economy.
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Measuring Asymmetric Stochastic Cycle Components
SSRN Electronic Journal, 2005Co-Authors: Siem Jan Koopman, Kai Ming LeeAbstract:To gain insights in the current status of the economy, macroeconomic time series are often decomposed into trend, Cycle and irregular Components. This can be done by nonparametric band-pass filtering methods in the frequency domain or by model-based decompositions based on autoregressive moving average models or unobserved Components time series models. In this paper we consider the latter and extend the model to allow for asymmetric Cycles. In theoretical and empirical studies, the asymmetry of cyclical behavior is often discussed and considered for series such as unemployment and gross domestic product (GDP). The number of attempts to model asymmetric Cycles is limited and it is regarded as intricate and nonstandard. In this paper we show that a limited modification of the standard Cycle Component leads to a flexible device for asymmetric Cycles. The presence of asymmetry can be tested using classical likelihood based test statistics. The trend-Cycle decomposition model is applied to three key U.S. macroeconomic time series. It is found that cyclical asymmetry is a prominent salient feature in the U.S. economy.
Mototsugu Shintani - One of the best experts on this subject based on the ideXlab platform.
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Measuring International Business Cycles by Saving for a Rainy Day
Canadian Journal of Economics, 2015Co-Authors: Mario J. Crucini, Mototsugu ShintaniAbstract:Macroeconomics inevitably begins with a trend-Cycle decomposition of a nation's output. We propose a decomposition in which consumption is the trend Component and savings is the Cycle Component. Using data from the G-7 plus Australia, we show that this decomposition identifies international business Cycles that are: (i) more volatile, (ii) of longer mean duration and (iii) less correlated across countries than the Cycle Component from the Hodrick-Prescott filter. We argue that this difference stems from the fact that our method imposes a basic theoretical restriction arising from the permanent income hypothesis similar to the restriction used in Cochrane's ( ) decomposition.
