Energy Exchange Rate Research Articles

Novel energy exchange behaviors and mechanisms in nonlinear acoustic metamaterials with multiple nonlinear resonators

Wave-wave interactions in a nonlinear metamaterial or structure with two propagating waves can induce energy exchange within the nonlinear systems. The effects of nonlinear resonators on these interactions and energy exchanges in a nonlinear acoustic metamaterial have not been extensively studied in the literature. In this paper, a nonlinear monatomic acoustic metamaterial with multiple nonlinear resonators (NMAM-MNR) is constructed to investigate the new behaviors and mechanisms introduced by these nonlinear resonators. Stability analyses reveal that stability can be tuned by adjusting the number of nonlinear resonators and by selecting different intensities or masses of the resonators and the chain. Additionally, direct numerical simulations are performed to study the novel energy exchange behaviors and mechanisms in NMAM-MNR systems. The results demonstrate that the degree and frequency of energy exchange can be tuned by altering the mass ratios, stiffness ratios, intensities, and natural frequencies of the nonlinear resonators and the chain. The influence of mass and stiffness ratios on the time taken for the B-wave magnitude to first reach its maximum value in NMAM-MNR systems is also studied, showing that the rate of energy exchange induced by wave-wave interactions can be tuned by changing the stiffness and mass ratios of multiple nonlinear resonators. These properties have potential applications in the fields of energy harvesters, waveguides, and resonant energy transfer mechanisms.

NMR-Based Analysis of Cellular Central Energy Metabolism and Exchange Rates.

Cell cultures are widely used in studies to gain mechanistic insights of metabolic processes. The foundation of these studies lies on the quantification of intracellular and extracellular metabolites, and nuclear magnetic resonance (NMR) is one of the key analytical platforms used to this aim. Among the factors influencing the quality of the produced data are the sampling procedures as well as the acquisition and processing of spectroscopic data. Here we provide our workflow for obtaining quantitative metabolic data from adherent mammalian cells using NMR spectroscopy. The described protocol is compatible with other analytical methods like LC- or GC-MS-based lipidomics and untargeted metabolomics from the same sample. We also show how the collected extracellular data can be used to extract exchange flux rates, particularly useful for flux analysis studies and metabolic engineering of human-induced pluripotent stem cells.

Irreversible mechanism and thermal cross-radiative flow in nanofluids driven along a stretching/shrinking sheet with the existence of possible turning/critical points

The significant increase in thermal efficiency and the rate of energy exchange used in fuel dynamics and automobile coolants are leading to a better understanding of nanofluids. This computational analysis explores the thermal conductivity performance for radiative cross-flow of a nanofluid across an expanding/constricting sheet with a suction effect as a result of its application. To compute or calculate the magnificent point of nanofluid flow, the entropy, and asymmetrical heat source/sink effects are also elicited. The boundary layers traverse a stream-wise procedure for expanding and contracting sheets. Additionally, the study examines the features of heat transfer and cross-flow of nanofluids using numerical simulations. By employing similarity variables, the basic PDE equations of the current model are transformed into ODEs, and they are subsequently evaluated using the bvp4c method. Therefore, the effects of embedded flow variables on drag force, heat transfer rate, and entropy generation profiles have been framed using parametric research. Multiple solutions are offered for a specific range of the contracting parameter as well as the mass suction parameter. In addition, the heat transfer rate accelerates due to the heat source and decelerates due to the heat sink. The literature that is already published has been compared favorably, and it reveals many commonalities.

Energy market uncertainties and exchange rate volatility: A GARCH-MIDAS approach

In this paper, we employ the generalized autoregressive conditional heteroscedasticity-mixed data sampling (GARCH-MIDAS) framework to forecast the daily volatility of 19 dollar-based exchange rate returns based on monthly metrics of oil price uncertainty (OPU), and relatively broader global and country-specific energy market-related uncertainty indexes (EUI). We find that the global EUIs tend to perform better than the OPU, highlighting the need to look beyond the oil market to capture energy related uncertainties. The country-specific EUIs outperform the benchmark in a statistically significant manner for at least 14 currencies across the short-, medium-, and long-term forecasting horizons.

Numerical simulation and dynamic experimental investigation on vibration control of a structural system with a stacked single particle‐inerter damper

AbstractTo overcome the deficiencies of large particle radius, strict vibration conditions, and low kinetic energy exchange rate of traditional particle dampers, it is proposed to organically combine the rack and pinion inerter device with a stacked single particle damper (SSPD) to form a novel stacked single particle‐inerter damping system (SSPIS). Based on a detailed analysis of the force state of particles at various stages, the vibration damping mechanism of SSPIS is analyzed, and a mechanical model of a single‐degree‐of‐freedom (SDOF) structure equipped with an SSPIS is established. The numerical simulation and analysis process of SSPIS is provided, and a parametric design method of inerter device based on the structural performance requirements is proposed. The accuracy of the theoretical mechanical model and numerical simulation analysis process of SSPIS is verified through shaking table tests of a single‐story steel frame, and the actual damping control effect of SSPIS on the controlled structure is investigated. Both test and theoretical results show that the numerical simulation analysis process of SSPIS is clear and accurate, and the mechanical model of the SSPIS‐SDOF structural system is highly accurate. The inerter device in SSPIS can significantly improve the momentum exchange efficiency between particles and structures, and SSPIS could adaptively adjust the particle radius size on demand compared with the traditional particle dampers, with a high damping frequency band, and can realize good damping control effect under the earthquake with various types of sites, which has expansive engineering application scenarios.

Submesoscale Processes in the Kuroshio Loop Current: Roles in Energy Cascade and Salt and Heat Transports

AbstractThe Kuroshio Loop Current (KLC) is an important form of Kuroshio intrusion into the northeastern South China Sea (NESCS), which has significant influences on dynamical and biogeochemical processes in the NESCS. Recent studies suggested that the KLC is a hot spot of submesoscale processes (submesoscales) with spatiotemporal scales of O(1–10) km and O(1–10) days, but submesoscales' roles in energy cascade and salt and heat transports remain obscure. Here, we investigate this issue through analyzing outputs from a 1/48° simulation. The kinetic energy exchange rate between submesoscale and larger‐scale processes (KER) is overall positive in the KLC region, which suggests the dominance of forward cascade. The magnitude of KER is comparable with the temporal change rate of larger‐scale kinetic energy in the upper 200 m. We also find that magnitude and direction of KER are closely associated with strain rate and horizontal divergence of background flows, respectively. In addition, the KLC region shows elevated submesoscale salinity and heat diffusivities with magnitudes reaching O(102) m2 s−1. During the KLC period, horizontal mixing by submesoscales can transport 0.90 × 1013 kg salt and 0.71 × 1020 J heat westward into the NESCS interior, which are an order of magnitude larger than those caused by the mesoscale eddy shedding from the KLC. These results suggest that submesoscales play important roles not only in energy cascade but also in salt and heat transports in the KLC region. Therefore, the roles of submesoscales should be taken into account when studying energy, salt, and heat budgets in the NESCS.

Hydrodynamic simulations of cool stellar atmospheres with MANCHA

Three-dimensional time-dependent simulations of stellar atmospheres are essential to study the surface of stars other than the Sun. These simulations require the opacity binning method to reduce the computational cost of solving the radiative transfer equation down to viable limits. The method depends on a series of free parameters, among which the location and number of bins are key to set the accuracy of the resulting opacity. Our aim is to test how different binning strategies previously studied in one-dimensional models perform in three-dimensional radiative hydrodynamic simulations of stellar atmospheres. Realistic box-in-a-star simulations of the near-surface convection and photosphere of three spectral types (G2V, K0V, and M2V) were run with the MANCHA $-bins. These rates were compared with the ones computed with opacity distribution functions. Then, stellar simulations were run with grey, four-bin, and 18-bin opacities to see the impact of the opacity setup on the mean stratification of the temperature and its gradient after time evolution. The simulations of main sequence cool stars with the MANCHA code are consistent with those in the literature. For the three stars, the radiative energy exchange rates computed with 18 bins are remarkably close to the ones computed with the opacity distribution functions. The rates computed with four bins are similar to the rates computed with 18 bins, and present a significant improvement with respect to the rates computed with the Rosseland opacity, especially above the stellar surface. The Rosseland mean can reproduce the proper rates in sub-surface layers, but produces large errors for the atmospheric layers of the G2V and K0V stars. In the case of the M2V star, the Rosseland mean fails even in sub-surface layers, owing to the importance of the contribution from molecular lines in the opacity, underestimated by the harmonic mean. Similar conclusions are reached studying the mean stratification of the temperature and its gradient after time evolution.

Generalized Optical Sum Rules for Light-Dressed Matter.

Light-driven matter can exhibit qualitatively distinct electronic and optical properties from those observed at equilibrium. We introduce generalized sum rules for the optical properties of light-driven molecules. Both classical and quantum light are considered. For classical light, the Floquet sum rules show that the sum of all Fourier components, indexed by n = -∞ to ∞, of the time-dependent dipole matrix elements between Floquet modes weighted by the corresponding quasienergy difference in the first Floquet Brillouin zone plus n driving frequency is a constant. Surprisingly, it is impossible to alter the energy exchange rate between matter and a perturbative external probe laser by a strong driving, even though the spectra can differ significantly from the bare ones. These developments provide guidance for the control of effective optical properties of matter by light fields.

Regression Models for Calculating State-to-State Coefficients of the Rate of Vibrational Energy Exchanges

Regression Models for Calculating State-to-State Coefficients of the Rate of Vibrational Energy Exchanges

Experimental investigation on the stability and heat transfer enhancement of phase change materials composited with nanoparticles and metal foams

Conventional phase change materials (PCMs) possess the challenge of low thermal conductivity, which hinders the energy exchange rate and storage efficiency. PCMs composited nanoparticles and metal foams have been a proven solution to enhance the thermal characteristics of PCMs. In this work, three enhanced PCM composites including nanoparticle/paraffin, metal-foam/paraffin and nanoparticle/metal-foam/paraffin were prepared using fusion blending and vacuum impregnation method. The effects of different nanoparticles with different mass fractions on the stability and heat storage and release characteristics of nanoparticle/paraffin were investigated. Compared with paraffin, the melting time and solidification time of nano-metal/paraffin are reduced by a maximum of 30.18 % and 43.15 %, respectively. In addition, the effect of pore density of metal foam on natural convective heat transfer process was evaluated. The results showed that the stability in descending order is as follows: nano‑aluminum, nano‑copper and nano‑silver. The optimal mass fraction of nanoparticles with good stability was 1.5 wt% (copper), 1.0 wt% (silver), 1.5 wt% (aluminum), respectively. The metal foam makes the internal temperature distribution of PCMs more uniform in the heat transfer process, while inhibiting the convective heat transfer process. With the increase of pore density, the effect on natural convection heat transfer process rises. When the PPI (pores per linear inch) of foamed metal is greater than 40, the natural convection process can be inhibited, obviously. The foam metal has a more significant effect on the heat transfer performance of nanoparticle/metal-foam/paraffin than that of the nanoparticles. The economic benefits of nanoparticle/paraffin, metal-foam/paraffin and nanoparticle and metal foam composite phase change materials are progressively decrease, with MFP being suitable for applications with high economic budgets.

Energy prices and exchange rates in the Eurasian Economic Union: evidence from Fourier Toda-Yamamoto approach

ABSTRACT Even though there is a growing literature on the co-movement between energy and currency markets, this issue is still unclear for the Eurasian Economic Union (EEU) countries. Based on this gap in the literature, the purpose of this study is to analyse the dynamic relationships between energy prices (crude oil and natural gas) and exchange rates for the EEU countries (Armenia, Belarus, Kazakhstan, Kyrgyzstan, and Russia) for the 2015–2022 period by means of cointegration and causality approaches without and with structural shifts. While the cointegration test without structural change does not find uniform steady-state equilibrium, considering structural change in the cointegration model reveals the existence of the long-run relationship between exchange rates and energy prices. The causality analysis uncovers predictive information between energy and currency markets in the EEU countries driven by the oil market; and accounting for smooth structural breaks in causality analysis based on the Fourier Toda-Yamamoto approach reinforces these findings. The empirical findings hence imply a strong co-movement between energy and currency markets in the EEU countries shaped by the oil market.

Unravelling the nexus between energy prices and exchange rate in Malaysia: Fresh insights from a non-linear perspective using threshold cointegration analysis

This paper proposes a nonlinear threshold cointegration framework to study how energy prices affect Malaysia's nominal exchange rate, considering the money supply, income, and interest rate. The study employs a threshold cointegration approach utilizing threshold autoregressive and momentum threshold autoregressive models. The momentum threshold vector error correction model determines the short-run adjustment of exchange rate deviation from the long-run equilibrium level. The findings reveal that the nonlinear adjustment process to capture the short-run deviation in the long-run equilibrium path is primarily influenced by energy prices, money supply, and interest rates. These results highlight the importance of considering the impact of energy prices on exchange rate policies when formulating and implementing economic policies in Malaysia. The findings can also be valuable for decision-makers to comprehend the future dynamics of exchange rates and make well-informed decisions.

Regression models for calculating state-to-state coefficients of the rate of vibrational energy exchanges

The paper proposes an effective algorithm for solving problems of nonequilibrium gas dynamics taking into account detailed state-to-state vibrational kinetics. One of the problems of traditional methods is their high computational complexity, which requires a lot of time and memory. The work explored the possibilities of using relaxation rate prediction to improve the performance of numerical simulations of nonequilibrium oxygen flows instead of direct calculations. For this purpose, an approach based on nonlinear regression analysis was used, which made it possible to obtain computationally efficient approximation formulas for the energy exchange rate coefficients in the model of a forced harmonic oscillator, taking into account free rotations (FHO-FR), to significantly increase the calculation speed while maintaining accuracy, and to construct an optimized model FHO-FR-reg. Using the obtained regression formulas, numerical modeling was carried out, which made it possible to validate the model for the problem of oxygen flow behind an incident and reflected shock wave. A comparison between the forced harmonic oscillator (FHO) and FHO-FR models is not possible due to the high computational complexity of the second model. With the advent of a common approximation model, it became possible to compare simulation results for these models. Numerical calculations have shown that the FHO-FR-reg model gives values of gas-dynamic parameters close to the FHO model. The developed regression models make it possible to speed up the solution of the problem of modeling oxygen relaxation several times compared to other models of similar accuracy.

The Relationship between Energy Inflation and Exchange Rate: A Study on Türkiye

Energy is among the indicators that are taken into consideration in increasing the production levels of countries and increasing their welfare. Energy has become an indispensable resource for the industrialization of countries, increasing their industrial production and ensuring their development and growth in this direction. Today, the development and growth of countries have become linked to their energy consumption. However, countries that lack energy resources need to import the energy resources they need in order to realize their development and growth, and their economic activities for this purpose are closely related to other economic indicators, especially the exchange rate, and bring about a series of economic results. This study examines the existence of the relationship between energy inflation and the real exchange rate in Türkiye in light of the fact that Türkiye is heavily dependent on foreign energy consumption. Accordingly, the study utilizes monthly series of energy inflation and real exchange rate variables for the period 2012:M01-2021:M12 for Türkiye. In the study, firstly, the series of the variables are seasonally adjusted with the help of a computer package program, then the variables are logarithmically transformed and the stationarity of the series of the variables is analyzed. According to the results of ADF and PP unit root tests, it is concluded that the series of energy inflation and real exchange rate variables are not stationary at level, but both series become stationary after first differences are taken. In the study, Engle-Granger cointegration analysis was conducted in accordance with the unit root test results. According to the results of cointegration analysis, energy inflation and real exchange rate variables are found to move together in the long run. Finally, Granger causality test analysis was conducted and according to the results of this analysis, the existence of bidirectional causality in the Granger sense between energy inflation and real exchange rate was determined.

Unraveling the Nexus of Economic Factors: Analyzing the Impact of Trade, Energy Consumption, Electricity Generation, Exchange Rate, and Urban Population on Consumer Price Index in European countries

The dynamics of consumer price index (CPI) and its influencing factors lie at the heart of economic stability and growth. In this comprehensive research paper, we investigate the multifaceted relationship between consumer price index (CPI) and a set of critical independent variables, including trade (T), primary energy consumption (PEC), electricity generation (EG), exchange rate (ER), and urban population (UP). This research examines a cross-sectional sample of 20 European countries using panel ordinary OLS regression and fixed- and random-effects models for the period of 2000–2020. The findings of this research suggest that there is a notable inverse relationship between Primary Energy Consumption and CPI. The coefficient associated with Primary Energy Consumption carries a negative sign and demonstrates statistical significance at the 5% level and urban population, exchange rate and Electricity generation show positive significant impact on Inflation, while trade does not have any significant impact on inflation.

Nexus between environmental sustainability, energy intensity and food security: evidence from emerging economies

PurposeGrowing food insecurity is a leading cause of fatalities, particularly in developing nations like Sub-Saharan Africa and Southeast Asia. However, the rising energy consumption and carbon dioxide (CO2) emissions are mostly associated with food production. Balancing the trade-offs between energy intensity and food security remains a top priority for environmentalists. Despite the critical role of the environment in food security, there is a scarcity of substantial studies that explore the statistical connections among food security, CO2 emissions, energy intensity, foreign direct investment (FDI) and per capita income. Therefore, this study aims to provide more precise and consistent estimates of per capita CO2 emissions by considering the interplay of food security and energy intensity within the context of emerging economies.Design/methodology/approachTo examine the long-term relationships between CO2 emissions, food security, energy efficiency, FDI and economic development in emerging economies, this study employs correlated panel-corrected standard error, regression with Newey–West standard error and regression with Driscoll–Kraay standard error models (XTSCC). The analysis utilizes data spanning from 1980 to 2018 and encompasses 32 emerging economies.FindingsThe study reveals that increasing food security in a developing economy has a substantial positive impact on both CO2 emissions and energy intensity. Each model, on average, demonstrates that a 1 percent improvement in food security results in a 32% increase in CO2 levels. Moreover, the data align with the Environmental Kuznets Curve (EKC) theory, as it indicates a positive correlation between gross domestic product (GDP) in developing nations and CO2 emissions. Finally, all experiments consistently demonstrate a robust correlation between the Food Security Index (FSI), energy intensity level (EIL) and exchange rate (EXR) in developing markets and CO2 emissions. This suggests that these factors significantly contribute to environmental performance in these countries.Originality/valueThis study introduces novelty by employing diverse techniques to uncover the mixed findings regarding the relationship between CO2 emissions and economic expansion. Additionally, it integrates energy intensity and food security into a new model. Moreover, the study contributes to the literature by advocating for a sustainable development goal (SDG)-oriented policy framework that considers all variables influencing economic growth.

Connectedness analysis of oil price shocks, inflation, and exchange rate for the MENA region countries

The relation among energy prices, exchange rates and inflation has been perturbed in the recent past by both the COVID-19 shock, which resulted in a sharp downturn of the economic activity at the beginning of 2020 and the Ukraine crisis, which resulted in sharp increase in energy prices and then inflation at the beginning of 2022. This is the first paper to analyze this relation for the MENA region, conducting an empirical estimation of a VARX model on monthly data from Jan 2010 to Dec 2022 for the main 11 MENA countries. The model includes asymmetric effects, a detailed contagion analysis, conducted with the methodology à la Pesaran - Pick (2007) to identify periods of high volatility, and presents a spillover analysis à la Diebold - Yılmaz (2014), used to measure the connectedness of the three main variables.The novelties of the paper are the construction of a country specific oil portfolio; the asymmetric analysis of oil shocks and contagion; the measurement of the general impulse response spillover, to ascertain the intensity and direction of volatility spillovers. The empirical results show that: (i) the specific oil prices considered for each country induce different effects; (ii) the oil price changes effect depends on the direction and period of the shock; (iii) there are asymmetric contagion effects for exchange rate and inflation only for some countries. Finally, some policy implications are presented based on the spillover connectedness analysis, especially considering the post Covid period.

Energy price shocks, exchange rates and inflation nexus

Energy price shocks, exchange rates and inflation have challenged macroeconomics stability in the recent past, during the Covid-19 crisis and the following high growth recovery post Covid. The joint relations among these three main macro-variables: exchange rate, consumer price and oil prices is modeled in this paper, in the periods of pre-Covid and of supply recovery after the Covid-19 lockdown. The estimation of an empirical VARX model on monthly data from Jan 2010 to Dec 2021 for the main 15 countries of the G20 shows asymmetric effects, offers a detailed contagion analysis, conducted with the methodology a la Pesaran and Pick (2007) to identify periods of high volatility, and presents a spillover analysis a la Diebold and Yılmaz (2014), used to measure the connectedness of the three main variables.The main innovative contributions are: i) the analysis of the country specific oil portfolio; ii) the general impulse response spillover, to ascertain the intensity and direction of volatility connectedness; iii) the disentangling of the effects on the exchange rate and price stability stemming from oil prices shocks. The empirical results show that: i) significant effects differences depend on the specific oil price considered for each country; ii) oil price changes impacts depend on the direction and period of the shock; iii) asymmetric contagion effects are relevant only for some oil importing countries and for exchange rate and inflation. Finally, based on the spillover connectedness, some policy implications are discussed.

Exploring the link between green energy, CO2 emissions, exchange rate and economic growth: Perspective from emerging South Asian countries

This paper investigates the nexus between renewable energy use, CO2 emissions, exchange rate, and economic development within emerging South Asian nations, namely Bangladesh, India, Pakistan, and Sri Lanka, employing the Autoregressive Distributed Lag (ARDL) framework. It examines annual data spanning from 1990 to 2019, examining key indicators of renewable energy consumption, CO2 emissions, exchange rate, and economic development. The ARDL bounds test results demonstrate the existence of co-integration among the variables in the long run. The empirical result finds that the renewable energy consumption, CO2 emissions, and exchange rate have a significant impact on economic growth in Bangladesh, Pakistan, and Sri Lanka in the long run. In India no significant relationship found in the long run. In short run assessment, Bangladesh, India, and Sri Lanka also found same relationship with economic growth and renewable energy consumption, CO2 emissions, and exchange rate. Interestingly, In Pakistan no significant relationship has found in short run estimation analysis. Furthermore, study tried to determine the causality direction by using the Toda Yamamoto granger causality approach, which reveals bidirectional causation between exchange rate and CO2 emission in India. In Pakistan, study also found bi-directional causality among the variables renewable energy consumption, CO2 emissions, and economic growth. Finally, this paper emphasizes developing the policy as well as making a concrete decision regarding the renewable energy consumption, CO2 emissions, exchange rate, and economic development for ensuring sustainable economic growth in South Asian region. Future research could extend this work by including different dimensional data, additional countries, or using alternative or supplementary modeling techniques.

Opacity for realistic 3D MHD simulations of cool stellar atmospheres

Context. Realistic three-dimensional time-dependent simulations of stellar near-surface convection employ the opacity binning method for the efficient and accurate computation of the radiative energy exchange. The method provides several orders of magnitude of speedup, but its implementation includes a number of free parameters. Aims. Our aim is to evaluate the accuracy of the opacity binning method as a function of the choice of these free parameters. Methods. The monochromatic opacities computed with the SYNSPEC code were used to construct opacity distribution function (ODF) that was then verified through detailed comparison with the results of the ATLAS code. The opacity binning method was implemented with the SYNSPEC opacities for four representative cool main-sequence stellar spectral types (F3V, G2V, K0V, and M2V). Results. The ODFs from SYNSPEC and ATLAS show consistent results for the opacity and bolometric radiative energy exchange rate Q in the case of the F-, G-, and K-type stars. Significant differences, coming mainly from the molecular line lists, are found for the M-type star. It is possible to optimise a small number of bins to reduce the deviation of the results coming from the opacity grouping with respect to the ODF for the F-, G-, and K-type stars. In the case of the M-type star, the inclusion of splitting in wavelength is needed in the grouping to get similar results, with a subsequent increase in computing time. In the limit of a large number of bins, the deviation for all the binning configurations tested saturates and the results do not converge to the ODF solution. Due to this saturation, the Q rate cannot be improved by increasing the number of bins to more than about 20 bins. The more effective strategy is to select the optimal location of fewer bins.