Showing papers by "Virginia Tech published in 2022"

A Multichannel High-Frequency Current Link Based Isolated Auxiliary Power Supply for Medium-Voltage Applications

Abstract: The auxiliary power supply (APS) is one of the critical components inside medium-voltage (MV) power converters. Besides high insulation capability and small footprint, low common-mode (CM) coupling capacitance and multichannel output are the desired features of APS in the emerging silicon-carbide-based MV converters due to their fast switching speed. This article presents the design and optimization procedure of a high-density isolated APS using an LCCL-LC resonant topology with an operating frequency of 1 MHz. The proposed design procedure attains consistent soft-switching operation under a random number of output channels. The galvanic isolation is realized by a current-fed single-turn 1 MHz transformer that can achieve a breakdown voltage of over 20 kV while maintaining a small size. Design optimization on the insulation system of the current transformer is proposed to obtain both high partial-discharge inception voltage (PDIV) and low coupling capacitance. Finally, two versions of APSs are developed, using air and silicone as dielectric materials, which can reach PDIV of over 5 and 16 kV, respectively. The corresponding coupling capacitances are 1.86 pF and 3.6 pF. Both designs can provide a maximum power of 20 W on the receiving side, and 120 W on the sending side.

An index of cryptocurrency environmental attention (ICEA)

Abstract: Purpose (1) A concern often expressed in relation to cryptocurrencies is the environmental impact associated with increasing energy consumption and mining pollution. Controversy remains regarding how environmental attention and public concerns adversely affect cryptocurrency prices. Therefore, the paper aims to introduce the index of cryptocurrency environmental attention (ICEA), which aims to capture the relative extent of media discussions surrounding the environmental impact of cryptocurrencies. (2) The impacts of cryptocurrency environmental attention on long-term macro-financial markets and economic development remain part of undeveloped research fields. Based on these factors, the paper will further examine the effects of the ICEA on financial markets or economic developments. Design/methodology/approach (1) The paper introduces a new index to capture cryptocurrency environmental attention in terms of the cryptocurrency response to major related events through gathering a large amount of news stories around cryptocurrency environmental concerns – i.e. >778.2 million news items from the LexisNexis News & Business database, which can be considered as Big Data – and analysing that rich dataset using variety of quantitative techniques. (2) The vector error correction model (VECM) and structural VECM (SVECM) [impulse response function (IRF), forecast error variance decomposition (FEVD) and historical decomposition (HD)] are useful for characterising the dynamic relationships between ICEA and aggregate economic activities. Findings (1) The paper has developed a new measure of attention to sustainability concerns of cryptocurrency markets' growth, ICEA. (2) ICEA has a significantly positive relationship with the UCRY indices, volatility index (VIX), Brent crude oil (BCO) and Bitcoin. (3) ICEA has a significantly negative relationship with the global economic policy uncertainty (GlobalEPU) and global temperature uncertainty (GTU). Moreover, ICEA has a significantly positive relationship with the industrial production (IP) in the short term, whilst having a significantly negative relationship in the long term. (4) The HD of the ICEA displays higher linkages between environmental attention, Bitcoin and UCRY indices around key events that significantly change the prices of digital assets. Research limitations/implications The ICEA is significant in the analysis of whether cryptocurrency markets are sustainable regarding energy consumption requirements and negative contributions to climate change. Understanding of the broader impacts of cryptocurrency environmental concerns on cryptocurrency market volatility, uncertainty and environmental sustainability should be considered and developed. Moreover, the paper aims to point out future research and policy legislation directions. Notably, the paper poses the question of how cryptocurrency can be made more sustainable and environmentally friendly and how governments' cryptocurrency policies can address the cryptocurrency markets. Practical implications (1) The paper develops a cryptocurrency environmental attention index based on news coverage that captures the extent to which environmental sustainability concerns are discussed in conjunction with cryptocurrencies. (2) The paper empirically investigates the impacts of cryptocurrency environmental attention on other financial or economic variables [cryptocurrency uncertainty (UCRY) indices, Bitcoin, VIX, GlobalEPU, BCO, GTU index and the Organisation for Economic Co-operation and Development IP index]. (3) The paper provides insights into making the most effective use of online databases in the development of new indices for financial research. Social implications Whilst blockchain technology has a number of useful implications and has great potential to transform several industries, issues of high-energy consumption and CO2 pollution regarding cryptocurrency have become some of the main areas of criticism, raising questions about the sustainability of cryptocurrencies. These results are essential for both policy-makers and for academics, since the results highlight an urgent need for research addressing the key issues, such as the growth of carbon produced in the creation of this new digital currency. The results also are important for investors concerned with the ethical implications and environmental impacts of their investment choices. Originality/value (1) The paper provides an efficient new proxy for cryptocurrency and robust empirical evidence for future research concerning the impact of environmental issues on cryptocurrency markets. (2) The study successfully links cryptocurrency environmental attention to the financial markets, economic developments and other volatility and uncertainty measures, which has certain novel implications for the cryptocurrency literature. (3) The empirical findings of the paper offer useful and up-to-date insights for investors, guiding policy-makers, regulators and media, enabling the ICEA to evolve into a barometer in the cryptocurrency era and play a role in, for example, environmental policy development and investment portfolio optimisation.

Load Detection and Power Flow Control Algorithm For an Omnidirectional Wireless Power Transfer System

Abstract: This article presents a control scheme for an omnidirectional wireless power transfer system. A system architecture is proposed to implement the current amplitude control. To focus power transfer towards targeted loads, a smart detection algorithm for identifying the positioning and orientation of receiver devices based on the input power information is presented. The system efficiency is further improved by a maximum efficiency point tracking function. A novel power flow control with a load combination strategy to charge multiple loads simultaneously is explained. Finally, the proposed control scheme is successfully applied to an example 6.78 MHz omnidirectional wireless charging bowl system. The experimental results confirm the accuracy of the load detection algorithm and validate the power flow control strategy.

Lectin-Modified Bacterial Cellulose Nanocrystals Decorated with Au Nanoparticles for Selective Detection of Bacteria Using Surface-Enhanced Raman Scattering Coupled with Machine Learning

Abstract: Bacterial cellulose nanocrystals (BCNCs) are tunable and biocompatible cellulose nanomaterials that can be easily bioconjugated and used for biosensing applications. We report the application of concanavalin A (con A) lectin-modified BCNCs (con A + BCNCs) for bacterial isolation and label-free surface-enhanced Raman spectroscopy (SERS) detection of bacterial species using Au nanoparticles (AuNPs). The aggregated AuNP + bacteria + (con A + BCNC) conjugates generated SERS hot spots that enabled the SERS detection of the strain Escherichia coli 8739 at the 103 CFU/mL level. The optimized detection assay was then used to differentiate 19 common bacterial strains. The large SERS spectral dataset for the 19 bacterial strains was analyzed using the support vector machine (SVM), an optimization-based machine-learning technique that worked as a binary classifier. The SVM classifier showed a high overall accuracy of 87.7% in correctly discriminating bacterial strains. This study illustrates the potential of combining low-cost nanocellulose-based SERS biosensors with machine-learning techniques for the analysis of large spectral datasets.

Imitation Learning With Stability and Safety Guarantees

Abstract: A method is presented to learn neural network (NN) controllers with stability and safety guarantees through imitation learning (IL). Convex stability and safety conditions are derived for linear time-invariant systems with NN controllers by merging Lyapunov theory with local quadratic constraints to bound the activation functions in the NN. These conditions are incorporated in the IL process, which minimizes the IL loss, and maximizes the volume of the region of attraction associated with the NN controller simultaneously. An alternating direction method of multipliers based algorithm is proposed to solve the IL problem. The method is illustrated on a vehicle lateral control example.

A framework for ensemble modelling of climate change impacts on lakes worldwide: the ISIMIP Lake Sector

Abstract: Abstract. Empirical evidence demonstrates that lakes and reservoirs are warming across the globe. Consequently, there is an increased need to project future changes in lake thermal structure and resulting changes in lake biogeochemistry in order to plan for the likely impacts. Previous studies of the impacts of climate change on lakes have often relied on a single model forced with limited scenario-driven projections of future climate for a relatively small number of lakes. As a result, our understanding of the effects of climate change on lakes is fragmentary, based on scattered studies using different data sources and modelling protocols, and mainly focused on individual lakes or lake regions. This has precluded identification of the main impacts of climate change on lakes at global and regional scales and has likely contributed to the lack of lake water quality considerations in policy-relevant documents, such as the Assessment Reports of the Intergovernmental Panel on Climate Change (IPCC). Here, we describe a simulation protocol developed by the Lake Sector of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) for simulating climate change impacts on lakes using an ensemble of lake models and climate change scenarios for ISIMIP phases 2 and 3. The protocol prescribes lake simulations driven by climate forcing from gridded observations and different Earth system models under various representative greenhouse gas concentration pathways (RCPs), all consistently bias-corrected on a 0.5∘ × 0.5∘ global grid. In ISIMIP phase 2, 11 lake models were forced with these data to project the thermal structure of 62 well-studied lakes where data were available for calibration under historical conditions, and using uncalibrated models for 17 500 lakes defined for all global grid cells containing lakes. In ISIMIP phase 3, this approach was expanded to consider more lakes, more models, and more processes. The ISIMIP Lake Sector is the largest international effort to project future water temperature, thermal structure, and ice phenology of lakes at local and global scales and paves the way for future simulations of the impacts of climate change on water quality and biogeochemistry in lakes.

Improved Odd-Harmonic Repetitive Control Scheme for Ćuk-Derived Inverter

Abstract: This article proposes an improved odd-harmonic repetitive controller (IORC) for a Cuk-derived inverter. The IORC is composed of a modified structure of an odd-harmonic repetitive controller (ORC) combined with a proportional-integral (PI) controller and a feedforward controller to achieve a zero steady-state error in the Cuk-derived inverter. The IORC features much larger gains at odd-harmonic frequencies by modification of an existing ORC, so both its convergence rate and transient response become much faster. The added benefit of using the IORC is that it has wider bandwidth at odd-harmonic frequencies, so it is more insensitive to the grid frequency fluctuation. The IORC also adopts a linear phase-lead compensator to compensate for the phase lag of the Cuk-derived inverter. Hence, the IORC can effectively eliminate the odd-harmonic components in the output current of the grid-connected Cuk-derived inverter while using less memory space. However, the distinctive structure of the IORC makes it difficult to guarantee the stability of the overall control system. Thus, in this article, a new stability analysis method is developed for the IORC system, and then a practical design guideline is also provided to obtain the optimal control parameters. Experimental results are presented to validate the proposed controller in the 300-W Cuk-derived inverter prototype.