System-level Studies Research Articles

Cladding-Pumped Erbium/Ytterbium Co-Doped Fiber Amplifier for C-Band Operation in Optical Networks

Space-division multiplexing (SDM) attracts attention to cladding-pumped optical amplifiers, but they suffer from a low pump power conversion efficiency. To address this issue, ytterbium (Yb3+) and erbium (Er3+) co-doping is considered as an effective approach. However, it changes the gain profile of Er3+-doped fiber amplifiers and induces the gain difference between optical wavelengths in the C-band, significantly limiting the effective band of the dense wavelength-division multiplexed (DWDM) system. This paper is devoted to a detailed study of a cladding-pumped Er3+/Yb3+ co-doped fiber amplifier (EYDFA) through numerical simulations aiming to identify a configuration, before assembling a similar EYDFA in our laboratory premises that ensures the desired performance. The simulation model is based on a commercial double cladding EYDF whose parameters are experimentally extracted and fed to the EYDFA setup for the system-level studies. We investigate the wavelength dependence of the amplifier’s characteristics (absolute gain, gain uniformity, noise figure) and bit error rate (BER) performance for several DWDM channels and their optical power. The obtained results show that a 7 m long EYDF and co-propagating pump direction is preferable for the EYDFA with a 3 W pump source at 975 nm and with the given gain medium characteristics for WDM applications. For instance, it ensures a gain of 19.7–28.3 dB and a noise figure of 3.7–4.2 dB when amplifying 40 DWDM channels with the input power of −20 dBm per channel. Besides, we study EYDFA gain bandwidth and the maximum output power when operating close to the saturation regime and perform a sensitivity analysis showing how the doped fiber’s absorption and emission cross-sections impact the amplification process through energy transfer from Yb3+ to Er3+. Finally, we quantify the power penalty introduced by the EYDFA; the results show that it is not higher than 0.1 dB when amplifying 40 × 10 Gbps non-return-to-zero on-off keying signals from −20 dBm/channel.

PHY Abstraction Techniques for V2X Enabling Technologies: Modeling and Analysis

IEEE 802.11p and LTE-V2X are the current wireless standards of interest to enable connected and autonomous driving. The specification for their follow up generations, i.e., IEEE 802.11bd and NR-V2X are being developed and expected to be completed soon. To evaluate and compare the performance of these technologies, system-level studies are required to be carried out for various channel conditions and reliability requirements. However, these studies are time-intensive and require highly complex computations, if they are performed using link-level simulators. Therefore, the physical layer performance is usually abstracted using a link quality model, also known as Physical layer abstraction (PLA). For this purpose, we present novel PLA techniques to model different fading and interference effects for considered technologies. Further, we compare the performance of PLA techniques in terms of estimation accuracy against physical layer simulations. The results show that the estimated packet error rate (PER) by proposed PLA methods are close to the results obtained through physical layer simulations. Besides, we compare the performance of all considered technologies (i.e., IEEE 802.11p, LTE-V2X, IEEE 802.11bd, and NR-V2X) in terms of data rates, latency, and reliability. The results indicate that NR-V2X is superior in terms of average data rates compared to other technologies. In contrast, IEEE 802.11bd has lower transmission latency and higher reliability compared to other technologies.

Comprehensive Modelling of Renewable Energy Based Microgrid for System Level Control Studies

Renewable energy will constitute the backbone of the future sustainable energy systems by forming onsite microgrids. This reduces the utility grid burden and outages. Besides, microgrids can address the issues of greenhouse gasses, global warming, fossil fuel evaporations, slow start-up/shutdown times, etc. However, their dependency on geography/climatic conditions lead to the exhibition of intermittent output characteristics. Moreover, a majority of microgrids must be interfaced with the utility grid through power electronic converters, which are static and do not possess any kinetic energy. Due to this nature, these systems are highly sensitive to events, and thereby, creating issues with fast detection of islanding during abnormalities. Furthermore, for superior power quality, stability, energy yield, reliability, and protection, they must be properly coordinated with the utility grid or neighbour microgrids via robust control mechanisms. To study all these factors, lead to a better system, it is desired to have a perfect model of the system. Many literary works have developed microgrid models by focusing on a very particular aspect or component of it with respect to their area of research. But, comprehensive models are much required for many different studies as mentioned above. Further, the comprehensive model helps in detailed system-level studies. So, with this intension, this paper proposes the development of comprehensive model of the microgrid which involves all its key characteristics/elements. Further, system-level control study is presented to persuade the importance of this proposed model. From results, the WJC method is recommended as the best method to design microgrid’s controller.

Power Electronics Reliability: State of the Art and Outlook

This article aims to provide an update of the reliability aspects of research on power electronic components and hardware systems. It introduces the latest advances in the understanding of failure mechanisms, testing methods, accumulated damage modeling, and mission-profile-based reliability prediction. Component-level examples (e.g., Si IGBT modules, SiC MOSFETs, GaN devices, capacitors, and magnetic components) are used for illustration purposes in addition to system-level studies. The limitations and associated open questions are discussed to identify future research opportunities in power electronics reliability.

On the expanding roles of tRNA fragments in modulating cell behavior.

The fragments that derive from transfer RNAs (tRNAs) are an emerging category of regulatory RNAs. Known as tRFs, these fragments were reported for the first time only a decade ago, making them a relatively recent addition to the ever-expanding pantheon of non-coding RNAs. tRFs are short, 16–35 nucleotides (nts) in length, and produced through cleavage of mature and precursor tRNAs at various positions. Both cleavage positions and relative tRF abundance depend strongly on context, including the tissue type, tissue state, and disease, as well as the sex, population of origin, and race/ethnicity of an individual. These dependencies increase the urgency to understand the regulatory roles of tRFs. Such efforts are gaining momentum, and comprise experimental and computational approaches. System-level studies across many tissues and thousands of samples have produced strong evidence that tRFs have important and multi-faceted roles. Here, we review the relevant literature on tRF biology in higher organisms, single cell eukaryotes, and prokaryotes.

Application of Proteomics in Sarcoidosis.

Sarcoidosis is a multisystem disease with heterogeneity in manifestations and outcomes. System-level studies leveraging "omics" technologies are expected to define mechanisms contributing to sarcoidosis heterogeneous manifestations and course. With improvements in mass spectrometry (MS) and bioinformatics, it is possible to study protein abundance for a large number of proteins simultaneously. Contemporary fast-scanning MS enables the acquisition of spectral data for deep coverage of the proteins with data-dependent or data-independent acquisition MS modes. Studies leveraging MS-based proteomics in sarcoidosis have characterized BAL fluid (BALF), alveolar macrophages, plasma, and exosomes. These studies identified several differentially expressed proteins, including protocadherin-2 precursor, annexin A2, pulmonary surfactant A2, complement factors C3, vitamin-D-binding protein, cystatin B, and amyloid P, comparing subjects with sarcoidosis with control subjects. Other studies identified ceruloplasmin, complement factors B, C3, and 1, and others with differential abundance in sarcoidosis compared with other interstitial lung diseases. Using quantitative proteomics, most recent studies found differences in PI3K/Akt/mTOR, MAP kinase, pluripotency-associated transcriptional factor, and hypoxia response pathways. Other studies identified increased clathrin-mediated endocytosis and Fcγ receptor-mediated phagocytosis pathways in sarcoidosis alveolar macrophages. Although studies in mixed BAL and blood cells or plasma are limited, some of the changes in lung compartment are detected in the blood cells and plasma. We review proteomics for sarcoidosis with a focus on the existing MS data acquisition strategies, bioinformatics for spectral data analysis to infer protein identity and quantity, unique aspects about biospecimen collection and processing for lung-related proteomics, and proteomics studies conducted to date in sarcoidosis.

Average-Value Model for a Modular Multilevel Converter With Embedded Storage

This article proposes an average-value model for a modular multilevel converter with sub-module level battery energy storage. The developed model is a computationally efficient representative of the converter in system-level studies; it is also shown to be useful in analytical characterization of circulating currents and sub-module capacitor voltage ripple both with and without circulating current suppression control. The model is then used to investigate the sizing of converter components under different operating regimes. The accuracy of the developed model is verified against detailed EMT models as well as against experimental results on a converter prototype.

Generalised average modelling of grid‐connected three‐phase VSC with closed‐loop vector control and regular‐sampled modulation

Based on the generalised averaging method, a comprehensive mathematical model for a three-phase grid-connected voltage source converter (VSC) with closed-loop vector control and symmetrical regular-sampled modulation is proposed here. The double Fourier series of switching functions is presented to construct the state average vectors in this model. To involve the conventional vector current control strategy, the coordinate transformation method of the state average vector is derived. The multiplication properties are also illustrated to calculate the product average vector for state variables. The proposed model is validated in both MATLAB simulations and hardware experiments. The results show that both the fundamental and the switching behaviours of the converter as well as the closed-loop dynamics of the controller can be accurately demonstrated by the derived model with fast simulation speed. The steady-state harmonic distribution can also be directly achieved by computing the equilibrium point of the system. The proposed model is appropriate for system-level studies of power electronic-based power systems and can provide a beneficial reference for the practical design and the performance assessment of the closed-loop VSC system, which indicates the broad prospect of the application of generalised average models in power system and power electronics fields.

High Throughput strategies Aimed at Closing the GAP in Our Knowledge of Rho GTPase Signaling

Since their discovery, Rho GTPases have emerged as key regulators of cytoskeletal dynamics. In humans, there are 20 Rho GTPases and more than 150 regulators that belong to the RhoGEF, RhoGAP, and RhoGDI families. Throughout development, Rho GTPases choregraph a plethora of cellular processes essential for cellular migration, cell–cell junctions, and cell polarity assembly. Rho GTPases are also significant mediators of cancer cell invasion. Nevertheless, to date only a few molecules from these intricate signaling networks have been studied in depth, which has prevented appreciation for the full scope of Rho GTPases’ biological functions. Given the large complexity involved, system level studies are required to fully grasp the extent of their biological roles and regulation. Recently, several groups have tackled this challenge by using proteomic approaches to map the full repertoire of Rho GTPases and Rho regulators protein interactions. These studies have provided in-depth understanding of Rho regulators specificity and have contributed to expand Rho GTPases’ effector portfolio. Additionally, new roles for understudied family members were unraveled using high throughput screening strategies using cell culture models and mouse embryos. In this review, we highlight theses latest large-scale efforts, and we discuss the emerging opportunities that may lead to the next wave of discoveries.

Stability Analysis of Power Hardware-in-the-Loop Architecture With Solar Inverter

Power hardware-in-the-loop (PHIL) simulations have been rapidly growing in recent times due to the flexibility it offers in conducting various system-level studies as well as individual device evaluation. Evaluating a power converter has been one of the major applications of PHIL at recent times in the industry. Following this trend, this article proposes a way to evaluate a photovoltaic (PV) microinverter in PHIL arrangement. The mathematical background to quantify the stability criteria for a PHIL network is presented along with theoretical and experimental verifications. The methodology in this article is based on the model of interface devices and accurate delay model to analyze the stability of a PHIL system employing Routh–Hurwitz's formulation. An extensive analysis on stability along with the compensator design to enhance the stability limit of a PHIL system is presented. The workflow developed is applied to evaluate a 250-W PV microinverter, which showed a stable performance with more than 97% efficiency during steady state and transients.

Hybrid Parametric Average-Value/Detailed Modeling of Line-Commutated Rectifiers

Simulations and analysis of power-electronic-based systems are conventionally done using detailed switching models of power-electronic converters that are available in many electromagnetic transient (EMT) simulation programs. Although being accurate, such detailed models typically require small time-steps for accurate detection and handling of switching events, which makes them computationally expensive. Recently, a parametric average-value modeling (PAVM) approach has been developed for system-level modeling and fast simulations of line-commutated rectifiers (LCRs) including several selected ac harmonics. In this paper, a new hybrid parametric methodology is presented, which has the capability of operating at large time-steps while including the details of the ac- and dc-side variables similar to the detailed switching models (but without the need for locating switching events, i.e., zero crossings), or operating as an average-value model. Extensive simulation studies demonstrate advantageous numerical efficiency and accuracy of the proposed hybrid parametric AVM/detailed model compared to the previous PAVMs as well as the detailed switching models of LCRs when using large time-steps for system-level studies.

Technical Debt and Firm Performance

Technical debt refers to the design, development, and implementation shortcuts taken by firms when deploying accounting information systems. Prior system-level studies have shown that such shortcuts decrease the reliability of systems and increase the long-term system maintenance obligations. On the one hand, technical debt may cause system disruptions that impair firm-level performance. On the other hand, incurring technical debt may aid firms to expedite their systems deployment and to implement idiosyncratic functionalities that may enhance performance. In this firm-level study, we examine the economic implications of technical debt accumulated by 26 firms in their customer relationship management (CRM) systems over an 11-year period. We find that firms operating in industries with higher “clockspeed” and higher competitive threats tend to accumulate more technical debt. After controlling for industry- and firm-level factors, our analysis reveals that technical debt embedded in the CRM systems negatively impacts firms’ performances, measured as gross profit scaled by beginning-of-year total assets (GROA). We estimate that a 10% increase in technical debt reduces GROA by 16% on average. The negative impact of technical debt on GROA increases over the lifecycle of the systems, which significantly reduces the long-term business value of those systems. Highly experienced information technology teams and the presence of a chief information officer in a firm’s top management team, however, serve to mitigate, at least partially, the negative impact of technical debt. We discuss the implications of these findings for research on the business value and governance of accounting information systems and performance evaluation. This paper was accepted by Shiva Rajgopal, accounting.

Modeling a voltage source converter assisted resonant current DC breaker for real time studies

In order to test protection performance of future multi-terminal HVDC grids where DC circuit breakers (DC CBs) play an important role, a DC CB model in real time test environment should be developed. It is well known that a DC CB needs to interrupt DC faults very quickly in order to avoid converter damages and to ensure security of supply. The total current interruption time consists of a fault detection time, which is needed for the DC protection to provide a trip command to the DC CB, and a DC CB interruption time. Thus, it is necessary to demonstrate the performance of associated protective devices through real time simulations, before these devices can be implemented and commissioned in practice. This paper presents a detailed modeling of the voltage source converter assisted resonant current DC circuit breaker (VARC DC CB) in real time simulation environment based on RTDS. The proposed model provides sufficient representation of the circuit breaker for system level studies. External current-voltage characteristics of the proposed VARC DC CB models replicate the ones of the device in the real world. The proposed model of the breaker is tested in a simple test circuit including a DC voltage source and a T-scheme HVDC cable. Additionally, a case study has been presented by making use of a protection algorithm in a multi-terminal HVDC grid with frequency dependent parameters of the HVDC cables to show both protection performance and current interruption.

Large-signal modeling of three-phase dual active bridge converters for electromagnetic transient analysis in DC grids

The three-phase dual active bridge (3p-DAB) converter is widely considered in next-generation DC grid applications. As for traditional AC grids, the successful integration of power electronic converters in DC grids requires accurate time-domain system-level studies. As demonstrated in the existing literature, the development and efficient implementation of large-signal models of 3p-DAB converters are not trivial. In this paper, a generalized average model is developed, which enables system-level simulation of DC grids with 3p-DAB converters in electromagnetic transient type (EMT-type) programs. The proposed model is rigorously compared with alternative modeling techniques: ideal-model, switching-function and state-space averaging. It is concluded that the generalized average model provides an optimal solution when accuracy of transient response, reduction in computation time, and wideband response factors are considered.

Dynamics and Stability of Meshed Multiterminal HVDC Networks

This paper investigates the existence of an equilibrium point in multiterminal HVdc grids, assesses its uniqueness, and defines conditions to ensure its stability. An offshore multiterminal HVdc system including two wind farms is selected as an application test case. At first, a generalized dynamic model of the network is proposed, using multigraph theory. Such model captures the frequency dependence of transmission lines and cables; it is nonlinear due to the constant power behavior of the converter terminals using droop regulation, and presents a suitable degree of simplifications of the modular multilevel converters, under given conditions, to allow system level studies over potentially large networks. Based on this model, the existence and uniqueness of the equilibrium point are demonstrated by returning the analysis to a load-flow problem and using the Banach fixed point theorem. Additionally, the stability of the equilibrium is analyzed by obtaining a Lyapunov function by the Krasovskii's theorem. Computational results obtained for the selected four-terminal HVdc grid corroborate the requirement for the existence and stability of the equilibrium point.

Multicolor multiscale brain imaging with chromatic multiphoton serial microscopy

Large-scale microscopy approaches are transforming brain imaging, but currently lack efficient multicolor contrast modalities. We introduce chromatic multiphoton serial (ChroMS) microscopy, a method integrating one‐shot multicolor multiphoton excitation through wavelength mixing and serial block-face image acquisition. This approach provides organ-scale micrometric imaging of spectrally distinct fluorescent proteins and label-free nonlinear signals with constant micrometer-scale resolution and sub-micron channel registration over the entire imaged volume. We demonstrate tridimensional (3D) multicolor imaging over several cubic millimeters as well as brain-wide serial 2D multichannel imaging. We illustrate the strengths of this method through color-based 3D analysis of astrocyte morphology and contacts in the mouse cerebral cortex, tracing of individual pyramidal neurons within densely Brainbow-labeled tissue, and multiplexed whole-brain mapping of axonal projections labeled with spectrally distinct tracers. ChroMS will be an asset for multiscale and system-level studies in neuroscience and beyond.

Symposium review: Intramammary infections—Major pathogens and strain-associated complexity

Intramammary infection (IMI) is one of the most costly diseases to the dairy industry. It is primarily due to bacterial infection and the major intramammary pathogens include Escherichia coli, Streptococcus uberis, and Staphylococcus aureus. The severity and outcome of IMI is dependent on several host factors including innate host resistance, energy balance, immune status, parity, and stage of lactation. Additionally, the infecting organism can influence the host immune response and progression of disease. It is increasingly recognized that not only the infecting pathogen species, but also the strain, can affect the transmission, severity, and outcome of IMI. For each of 3 major IMI-associated pathogens, S. aureus, Strep. uberis, and E. coli, specific strains have been identified that are adapted to the intramammary environment. Strain-dependent variation in the host immune response to infection has also been reported. The diversity of strains associated with IMI must be considered if vaccines effective against the full repertoire of mammary pathogenic strains are to be developed. Although important advances have been made recently in understanding the molecular mechanism underpinning strain-specific virulence, further research is required to fully elucidate the cellular and molecular pathogenesis of mammary adapted strains and the role of the strain in influencing the pathophysiology of infection. Improved understanding of molecular pathogenesis of strains associated with bovine IMI will contribute to the development of new control strategies, therapies, and vaccines. The development of enabling technologies such as pathogenomics, transcriptomics, and proteomics can facilitate system-level studies of strain-specific molecular pathogenesis and the identification of key mediators of host-pathogen interactions.

Modelling of wind power plant transmission system for harmonic propagation and small‐signal stability studies

This study presents the impact of wind power plant components modelling on harmonics propagation and harmonic small-signal stability studies. Different types of cable and transformer modelling techniques are taken into consideration, e.g. state-of-the-art standard models and latest academic developments. The models are compared based on system-level studies in a real-life large offshore wind power plant. It is shown that the use of detailed cable and transformer models increases the overall damping estimation in the system, and therefore improves the resonance characteristics and small-signal stability margins of the investigated wind power plant.

Alternate Arm Converters-Based HVDC Model Compatible With the CIGRE B4 DC Grid Test System

This paper develops an alternate arm converter (AAC)-based point-to-point high-voltage direct current (HVDC) transmission system compatible with the existing benchmark models of modular multilevel converter (MMC)-based HVDC and multiterminal dc (MTDC) grids. The developed AAC-based HVDC system expedites the future development of multi-converter, multiterminal benchmark models that enable the system level studies with detailed models of multiple topologies. The configuration and design parameters of the topology, are derived in alignment with the existing MMC-based benchmark systems. Detailed analysis and simulation studies based on real-time digital simulations verify the operation and performance of the developed AAC-based HVDC system and the associated control functions. The model developed in RTDS is also provided as supplementary material in order to enable further research and development on multiple topologies-based dc grids.

Leveraging Biologically Inspired Models for Cyber–Physical Systems Analysis

Cyber–physical systems (CPS) are systems composed of distributed sensors, physical actuators, and controlling computers that are interconnected through a computer network. Notable examples include: electric utility “smart grids” that can sense and optimize power distribution, transportation systems, and healthcare and medical systems. As CPS complexity increases, system-level trade studies become more challenging due to the combined interaction of the computing, network communications, and physical sensor and actuator elements. Although fundamentally different, complex CPS and biological systems share common attributes that suggest the use of similar modeling approaches. This research investigated if CPS multiobjective optimization methods using mathematical models of a CPS that incorporate biologically inspired CPS system performance objective functions are better than those methods that do not use biologically inspired objective functions. The research methodology employed computer modeling and simulation. A multiobjective optimization study, using a commercially available genetic algorithm-based optimizer, was conducted on four slightly different versions of a dynamic model of a simple distributed robotic sensor system to assess the effect of incorporating a biological mathematical model on the quality of the Pareto fronts generated by the optimizer. An improvement in Pareto front quality was found after incorporating a biological mathematical model.