First-order Assumption Research Articles

Acclimation dynamics of Chlorella vulgaris to sudden light change

Chlorella vulgaris photoacclimation was monitored over eight instantaneous light intensity changes. The intensities ranged between 35μmol PhotonPAR.m−2.s−1 and 600μmolPhotonPAR.m−2.s−1. Cultures were grown in ultra-thin flat panel photobioreactors under continuous light and maintained in low cell density to ensure homogeneous light availability. Photoacclimation was evaluated through spectral quantification of pigments and fluorometric assays. The former gave access to a proxy of chlorophyll and carotenoid content, the latter to the Photosystem-II cross-section (σPSII) and qualification of the photosynthetic machinery (viaOJIP assays). Both the acclimated steady-state values of pigment content and the dynamic of their evolutions after sudden light intensity change were monitored. The characteristic times of the transitions were estimated based on a first-order assumption. Results consistently showed that antenna size adjustment of Chlorella vulgaris was primarily dictated by the light availability, both regarding the acclimated steady-state values and the acclimation dynamics. An energetic limitation was highlighted by the acclimation dynamics at low light. The characteristic time of transition was estimated to be 16.6±2.17h for the transition to the lowest light intensity (35μmol PhotonPAR.m−2.s−1) and 3.55±1.01h for intensities higher than the maximal intensity of photolimitation (120μmol PhotonPAR.m−2.s−1). No hysteresis effect was observed as light intensities were shifted once and reverted to their original values. These results extend the literature regarding photoacclimation dynamics of antenna size and photosynthetic apparatus. They are well-suited to calibrate photoacclimation models and can provide valuable insight into the strategies to implement for culture scale-up, fed-batch, and semi-continuous processes.

Dynamic changes in dissolved organic matter during transport of landfill leachate in porous medium.

The dynamic changes in dissolved organic matter (DOM) during the transport of landfill leachate (LL) in porous medium should be explored, considering the high levels of DOM in the LL of municipal solid waste. Column experiments were carried out at 25°C at a Darcy's flux of 0.29cm/h for 2722h to compare the transport of Cl-, ultraviolet absorbance at 254nm (UV254), chemical oxygen demand (COD), and dissolved organic carbon (DOC) in the simulated porous medium by using the CXTFIT2.1 code. Results showed that the convection-dispersion equation (CDE) could describe Cl- transport well. The high levels of λ and D could be highly correlated with the physicochemical properties of the porous medium. The transport of the studied DOM with evident aromatic character could be described appropriately by the CDE model with the first-order reaction assumption, considering the similar variation trends of UV254, COD, and DOC in the effluent during experiments. Specifically, the values of retardation factor (R) were in the following order: DOC > UV254 > COD, whereas the low values of the first-order decay coefficient (k1) for DOC and COD were still higher than that for UV254. High contents of humic-like substances in the DOM with complex toxic components resulted in the natural low removal efficiencies of COD, DOC, and UV254 (≤ 23%), which could be confirmed by the variations of fluorescence index (FI) and humification index (HIX) in the effluent. The results should be helpful in evaluating the environmental risk induced by the LL leakage in a landfill site.

Combining α-Al2O3 Packing Material and a ZnO Nanocatalyst in an Ozonized Bubble Column Reactor to Increase the Phenol Degradation from Wastewater

The ozonation reaction in a bubble column reactor (BCR) has been widely used in the removal of phenol from wastewater, but the phenol removal efficiency in this type of reactor is limited because of low ozone solubility and reactivity in the system. In the present study, the phenol degradation in the BCR was enhanced by using α-Al2O3 as a packing material and a ZnO nanocatalyst. The reactor diameter and height were 8 cm and 180 cm, respectively. The gas distributor was designed to include 52 holes of a 0.5 mm diameter. Also, the gas holdup, pressure drop, and bubble size were measured as a function of the superficial gas velocity (i.e., 0.5, 1, 1.5, 2, 2.5, and 3 cm/s). The evaluation of the hydrodynamic parameters provided a deeper understanding of the ozonation process through which to select the optimal operating parameters in the reactor. It was found that the best superficial gas velocity was 2.5 cm/s. A complete (100%) phenol removal was achieved for phenol concentrations of 15, 20, and 25 ppm at reaction times of 80, 90, and 100 min, respectively; this was achieved by using α-Al2O3 packing material and a ZnO nanocatalyst in the BCR. Additionally, a reaction kinetics study was conducted to describe the ozonation reaction in BCR. The first-order reaction assumption clearly describes the reaction kinetics with an R2 = 0.991. Finally, the applied treatment method can be used to efficiently remove phenol from wastewater at a low cost, with a small consumption of energy and a simple operation.

IDDES simulation of hydrogen-fueled supersonic combustion based on dynamic zone flamelet model

Based on the dynamic zone flamelet model (DZFM), the turbulent combustion of the DLR supersonic combustor with a wedge-shaped flame holder is numerically studied by IDDES. The mixing-relevant flow structures, combustion characteristics, and reaction paths were analyzed. The significant variation of flame modes, turbulence-chemistry interaction modes, and correlations between species (YOH) and mixture fraction suggests that applying a single flamelet for the whole physical space may introduce remarkable errors in describing the reacting states. Dynamically partitioning the flow field based on multiple zone division indices can effectively reduce conditional fluctuations and make the first-order closure assumption more valid. The results also demonstrate the necessity of a low-Re modification to DZFM, even for supersonic combustion.

The Relative Stability of Planktic Foraminifer Thermal Preferences over the Past 3 Million Years

Stationarity of species’ ecological tolerances is a first-order assumption of paleoenvironmental reconstruction based upon analog methods. To test this and other assumptions used in quantitative analysis of foraminiferal faunas for paleoceanographic reconstruction, we analyzed paired alkenone unsaturation ratio (U37K′) sea surface temperature (SST) estimates and relative abundances of planktic foraminifera within Late Pliocene assemblages. We established Pliocene temperature preferences for nine species in the North Atlantic: Dentoglobigerina altispira, Globorotalia menardii, Globoconella puncticulata, Neogloboquadrina atlantica, Neogloboquadrina incompta, Neogloboquadrina pachyderma, Trilobatus sacculifer, Globigerinita glutinata, and Globigerina bulloides. We compared these to the temperature preferences of the same extant species, and in the three cases where the species are now extinct (Dentoglobigerina altispira, Neogloboquadrina atlantica, and Globoconella puncticulata), comparisons were made to either the descendant species or other modern species commonly used as analogs. In general, the taxa tested show similar temperature responses in both Late Pliocene and present-day (core-top) distributions. The data from these comparisons are mostly encouraging, supporting past paleoceanographic conclusions, and are otherwise valuable for testing previous taxonomic grouping decisions that are often necessary for interpreting the paleoenvironment based upon Pliocene foraminiferal assemblages.

A high-order hidden Markov model for dynamic decision analysis of multi-homing ride-sourcing drivers

Ride-sourcing drivers enjoy flexibility in scheduling work hours and choosing platforms, which generates multi-homing behavior on multiple platforms. It is challenging to observe the labor supply of multi-homing ride-sourcing drivers due to data limitations, which motivates our research on modeling drivers' dynamic decisions on labor supply in the competitive ride-sourcing market with multiple platforms. We propose a dynamic discrete choice framework by modeling drivers' high-frequency decision sequences on platform switching as high-order hidden Markov processes and considering time-varying factors. The high-order hidden Markov framework relaxes the first-order Markovian assumption and builds interdependencies of unobserved states across multiple time periods. The estimation of the proposed model takes advantage of city-scale multiple platforms datasets in Hangzhou, China, including more than 16 million records of the order payment information and more than 46 thousand records of active ride-sourcing drivers' information. The case study results indicate that the high-order hidden Markov model (HO-HMM) has superior explanatory power in fitting multiple platforms datasets than the multinomial logit model and the first-order hidden Markov model. HO-HMM performs an advantage in modeling the extended historical dependency of drivers' decisions and individual driver behavior modeling with high interpretability. The results uncover the variations of drivers' attitudes in different hidden (unobservable) states and towards different platforms. In general, ride-sourcing drivers respond actively and positively to income and working time. The findings support the platforms' decision-making on pricing, reward, and personalized management of ride-sourcing drivers, and provide beneficial suggestions for improving income in the competitive ride-sourcing market.

On the equality problem of two-variable Bajraktarević means under first-order differentiability assumptions

The equality problem of two-variable Bajraktarević means can be expressed as the functional equation fg-1(f(x)+f(y)g(x)+g(y))=hk-1(h(x)+h(y)k(x)+k(y))(x,y∈I),\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\begin{aligned} \\left( \\frac{f}{g}\\right) ^{-1}\\bigg (\\frac{f(x)+f(y)}{g(x)+g(y)}\\bigg ) =\\left( \\frac{h}{k}\\right) ^{-1}\\bigg (\\frac{h(x)+h(y)}{k(x)+k(y)}\\bigg )\\qquad (x,y\\in I), \\end{aligned}$$\\end{document}where I is a nonempty open real interval, f,g,h,k:Irightarrow {mathbb {R}} are continuous functions, g, k are positive and f/g, h/k are strictly monotone. This functional equation, for the first time, was solved by Losonczi in 1999 under 6th-order continuous differentiability assumptions. Additional and new characterizations of this equality problem have been found recently by Losonczi, Páles and Zakaria under the same regularity assumptions in 2021. In this paper it is shown that the same conclusion can be obtained under substantially weaker regularity conditions, namely, assuming only first-order differentiability.

A Longitudinal Analysis of Respiratory Illness and Tobacco Use Transitions

Among individuals with chronic respiratory conditions, transitions between patterns of tobacco product use are not well understood. This study examines how transitions, including quitting altogether, differ over time between those who do and do not have chronic respiratory conditions. Data from youth and adult participants of the longitudinal Population Assessment of Tobacco and Health Study (2013-2018) were analyzed. Youth aged 12-17 years were included if they had aged into the adult sample by Wave 4. Stratified polytomous regression models built under a first-order Markov assumption modeled the probability of transitioning between different states/patterns of tobacco product use (exclusive current E-cigarette use, exclusive current combustible tobacco product use, current dual use of combustible products and E-cigarettes, and no current tobacco product use) at each wave. Marginal transition probabilities were computed as a function of ever or past-year diagnosis of a respiratory condition (separately for asthma and a composite variable representing chronic bronchitis, emphysema, and/or chronic obstructive pulmonary disease). Analyses were conducted in 2020-2021. Most individuals, regardless of respiratory condition, maintained the same pattern of tobacco use between waves. Exclusive combustible tobacco product users, including those with or without a respiratory condition, were not likely to become exclusive E-cigarette users or to quit using tobacco entirely. Although combustible tobacco use negatively impacts the management and prognosis of respiratory illnesses, combustible tobacco users who were recently diagnosed with a chronic respiratory condition were not likely to quit using tobacco. Efforts to encourage and support cessation in this medically vulnerable population should be increased.

Increased Use of Antibiotics in the Intensive Care Unit During Coronavirus Disease (COVID-19) Pandemic in a Brazilian Hospital.

Background: Microbial drug resistance is one of the biggest public health problems. Antibiotic consumption is an essential factor for the emergence and spread of multiresistant bacteria. Therefore, we aimed to analyze the antibiotics consumption in the Intensive Care Unit (ICU), identifying trends in the antibiotics use profile and microbiological isolates throughout the COVID-19 pandemic. Methods: We performed this retrospective observational study in intensive care units of a Brazilian tertiary hospital from January 2019 to December 2020. The primary outcome was antimicrobial consumption in the ICU, measured by defined daily doses (DDDs) per 100 bed-days. As a secondary outcome, bacterial infections (microbiological isolates) were calculated in the same fashion. Outcomes trends were analyzed using Joinpoint regression models, considering constant variance (homoscedasticity) and first-order autocorrelation assumptions. A monthly percent change (MPC) was estimated for each analyzed segment. Results: Seven thousand and nine hundred fifty-three patients had data available on prescribed and received medications and were included in the analyses. Overall, the use of antibiotics increased over time in the ICU. The reserve group (World Health Organization Classification) had an increasing trend (MPC = 7.24) from February to April 2020. The azithromycin consumption (J01FA) increased rapidly, with a MPC of 5.21 from January to April 2020. Polymyxin B showed a relevant increase from March to June 2020 (MPC = 6.93). The peak of the antibiotic consumption of Reserve group did not overlap with the peak of the pathogenic agents they are intended to treat. Conclusion: Overall antimicrobial consumption in ICU has increased in the context of the COVID-19 pandemic. The peaks in the antimicrobial’s use were not associated with the rise of the pathogenic agents they intended to treat, indicating an empirical use, which is especially concerning in the context of treating multidrug-resistant (MDR) infections. This fact may contribute to the depletion of the therapeutic arsenal for MDR treatment.

Buckling Strengths of Composite Plate Using Shape Memory Alloy under In-Plane Shear

In this article, we analyze the strength and buckling response in the plane shear load fixed at the corner of the composite plate. The fem is formulated is done on the basis of first-order shear deformation theory and assumptions of von Karman. The Newton-Raphson technique is considered to analyze the non-linearity algebraic equation. The effect of shape memory alloy in shear load and buckling response is discussed. In this study we analyze the two cases in the first simple carbon/epoxy plate is analyze and then we use the shape memory wire embedded in the plate which is about 1% of the volume of the plate and studies the buckling response effect on the plate. In the second case we use Shape Memory Alloy plate and loading but a circular cutout at the middle of the plate this case we analyze for both with the use of shape memory alloy and without the use of shape memory. It is observed that the shape memory alloy increases the strength of the plate in both cases. The whole simulations are done using Ansys workbench software v 2020R2.

Kinetic insight into glucose conversion to 5-hydroxymethyl furfural and levulinic acid in LiCl⋅3H2O without additional catalyst

Conversion of glucose to 5-hydromethyl furfural (HMF) and levulinic acid (LA) was systematically investigated in LiCl·3H2O without additional catalyst. Based on the experimental investigations by using glucose, fructose and HMF as the reaction substrate separately, corresponding reaction kinetics in LiCl·3H2O were modelled by first-order assumption. Kinetic analysis demonstrates that high temperature favors the formation of LA, while low temperature facilitates to selectively form humins. To achieve high LA yield, at least a temperature of 140 °C is required. Without additional catalyst converting glucose to LA in LiCl·3H2O, humins was predominantly derived from glucose and HMF, and glucose isomerization is the reaction rate-determining step. The activation energies of the main reactions are 160.96 kJ/mol (glucose to HMF), 139.20 kJ/mol (fructose to HMF), and 71.81–76.48 kJ/mol (HMF to LA) respectively. The activation energies for humins formation were 23.45 kJ/mol from glucose, 49.54 kJ/mol from fructose, and 42.15–65.85 kJ/mol from HMF, respectively. It is verified that LiCl·3H2O, as compared to aqueous medium, is an excellent reaction medium for converting glucose to LA as it can provide the active centers for fructose to HMF reaction and HMF to LA reaction, but lack of highly efficient Lewis acid for glucose isomerization. With the addition of Lewis acid (such as AlCl3 and FeCl3), as high as 83.4% of LA yield can be obtained respectively when directly converting glucose, with the total selectivities of LA and HMF of 95%.

Mechanism and kinetics of moisture-curing process of reactive hot melt polyurethane adhesive

Reactive hot melt polyurethane adhesive (HMPUR) was prepared by polycondensation of polyesters, pentaerythritol diacrylate (PEDA) and 4,4′-Methylene diphenyl diisocyanate (MDI). The moisture-curing kinetic experiments for HMPUR film with a thickness of 2.0 mm were carried out at various temperatures (283, 293, 303 and 313 K) and 85% relative humidity, with the mass changes dynamically monitored. A diffusion-reaction assumption was proposed to describe the mechanism of the moisture-curing process, and three kinetic models were established to correlate the moisture-curing kinetic data. The results showed that the model with the first-order reaction assumption is more reasonable. Based on the model, the time-dependent concentration profiles of water in HMPUR film, as well as the depth (x*) of water-diffusion, are predicted. Also, the reaction activation energy (Ek) and the diffusion activation energy (ED) were determined.

Higher-order patterns of aquatic species spread through the global shipping network.

The introduction and establishment of nonindigenous species (NIS) through global ship movements poses a significant threat to marine ecosystems and economies. While ballast-vectored invasions have been partly addressed by some national policies and an international agreement regulating the concentrations of organisms in ballast water, biofouling-vectored invasions remain largely unaddressed. Development of additional efficient and cost-effective ship-borne NIS policies requires an accurate estimation of NIS spread risk from both ballast water and biofouling. We demonstrate that the first-order Markovian assumption limits accurate modeling of NIS spread risks through the global shipping network. In contrast, we show that higher-order patterns provide more accurate NIS spread risk estimates by revealing indirect pathways of NIS transfer using Species Flow Higher-Order Networks (SF-HON). Using the largest available datasets of non-indigenous species for Europe and the United States, we then compare SF-HON model predictions against those from networks that consider only first-order connections and those that consider all possible indirect connections without consideration of their significance. We show that not only SF-HONs yield more accurate NIS spread risk predictions, but there are important differences in NIS spread via the ballast and biofouling vectors. Our work provides information that policymakers can use to develop more efficient and targeted prevention strategies for ship-borne NIS spread management, especially as management of biofouling is of increasing concern.

Long-Prediction-Horizon Near-Optimal Model Predictive Grid Current Control for PWM-Driven VSIs With LCL Filters

This article proposed and investigated a near-optimal finite-control-set model-predictive grid current control (NOP-MPGCC) for voltage source inverters (VSIs) with actively damped LCL filters. It carries three advantages: (i) the constant-frequency pulsewidth modulator produces regular switching spectrum-which can ease the LCL filter design process in grid current control applications with medium-to-high carrier ratio; (ii) it avoids the use of the usual first-order assumption in most PI-/PR-based control and the common simplifications adopted in some existing FCS-MPC schemes. This is achieved by considering the third-order behavior using long prediction horizon; and (iii) it can operate near and across the critical frequency, defined using the established classical control definition. Moreover, it retains the intuitive enumeration structure and maximizes the dc-bus utilization through the consideration of entire hexagonal vector space at every control cycle. The theoretical derivation, simulation, and experiment results verify that NOP-MPGCC is potentially a viable direct grid current control scheme for PWM-VSIs with actively damped LCL filters.

Low threshold for nitrogen concentration saturation in headwaters increases regional and coastal delivery

River corridors store, convey, and process nutrients from terrestrial and upstream sources, regulating delivery from headwaters to estuaries. A consequence of chronic excess nitrogen loading, as supported by theory and field studies in specific watersheds, is saturation of the biogeochemically-mediated nitrogen removal processes that weakens the capacity of the river corridor to remove nitrogen. Regional nitrogen models typically assume that removal capacity exhibits first-order behavior, scaling positively and linearly with increasing concentration, which may bias the estimation of where and at what rate nitrogen is removed by river corridors. Here we estimate the nitrogen concentration saturation threshold and its effects on annual nitrogen export from the Northeastern United States, revealing an average 42% concentration-induced reduction in headwater removal capacity. The weakened capacity caused an average 10% increase in the predicted delivery of riverine nitrogen from urban and agricultural watersheds compared to estimates using first-order process assumptions. Our results suggest that nitrogen removal may fall below a first-order rate process as riverine concentration increases above a threshold of 0.5 mg N l−1. Threshold behavior indicates that even modest mitigation of nitrogen concentration in river corridors above the threshold can cause a self-reinforcing boost to nitrogen removal.

Matrix-fluid-fracture decoupled-based elastic impedance variation with angle and azimuth inversion for fluid modulus and fracture weaknesses

The ratio of normal-to-shear fracture compliances, approximate to the product of two ratios of shear-to-compressional (S-to-P) wave velocity and normal-to-tangential fracture weakness, has been treated as an indicator of fluid content for an oil-bearing reservoir with aligned fractures. However, this indicator depends on both fluid saturation and fracturing strength of rocks, while the effective fluid bulk modulus as a sensitive indicator decouples the double effects of rock porosity and pore fluid. Moreover, an incorrect value of S- and P-wave velocity ratio may have a significant effect on the estimation of normal-to-shear fracture compliances. Based on the anisotropic poroelasticity amplitude variation with offset and azimuth (AVOAz) theory, we use the Born formalism and a first-order perturbation assumption to derive a matrix-fluid-fracture decoupled-based linearized PP-wave reflection coefficient in an oil-bearing fractured porous medium. Our derived formula reveals that the combined effects of background matrix, pore fluids and fracture strength on seismic amplitudes are separated, more applicable to implement the fluid identification and fracture detection in a liquid-filled porous reservoir with aligned fractures. Following a Bayesian framework, we develop a Bayesian inversion method to reasonably obtain the fluid modulus and saturated fracture weaknesses. The implementation methodology includes two steps: a model-based least-squares inversion for azimuthal elastic impedances and an iterative Bayesian seismic inversion for model parameters. Tests on synthetic data corrupted with moderate random noise indicate that these model parameters can be estimated reasonably and accurately when the oil-saturated rock is permeated with a single fracture system. Test on a real data set validates that the reliable estimates of fluid and fracture parameters can be used to realize the fluid identification and fracture detection in an oil-bearing fractured porous reservoir in a more direct manner than previous approach.

EFFICIENT SURFACE-AWARE SEMI-GLOBAL MATCHING WITH MULTI-VIEW PLANE-SWEEP SAMPLING

Abstract. Online augmentation of an oblique aerial image sequence with structural information is an essential aspect in the process of 3D scene interpretation and analysis. One key aspect in this is the efficient dense image matching and depth estimation. Here, the Semi-Global Matching (SGM) approach has proven to be one of the most widely used algorithms for efficient depth estimation, providing a good trade-off between accuracy and computational complexity. However, SGM only models a first-order smoothness assumption, thus favoring fronto-parallel surfaces. In this work, we present a hierarchical algorithm that allows for efficient depth and normal map estimation together with confidence measures for each estimate. Our algorithm relies on a plane-sweep multi-image matching followed by an extended SGM optimization that allows to incorporate local surface orientations, thus achieving more consistent and accurate estimates in areasmade up of slanted surfaces, inherent to oblique aerial imagery. We evaluate numerous configurations of our algorithm on two different datasets using an absolute and relative accuracy measure. In our evaluation, we show that the results of our approach are comparable to the ones achieved by refined Structure-from-Motion (SfM) pipelines, such as COLMAP, which are designed for offline processing. In contrast, however, our approach only considers a confined image bundle of an input sequence, thus allowing to perform an online and incremental computation at 1Hz–2Hz.

Supersonic panel flutter of variable stiffness composite laminated skew panels subjected to yawed flow by using NURBS-based isogeometric approach

An enhanced isogeometric finite element method is developed to investigate the free vibration analysis as well as the linear flutter characteristics of finite square as well as skew laminated plates. The laminates are assumed composed of variable stiffness plies due to implementation of curvilinear fibers. The flutter analysis of the skew laminate under various flow yaw angles are also taken into account. The first-order shear deformation plate structural assumptions are utilized in conjunction with an aerodynamic loading model according to the first-order piston theory. The cubic NURBS basis functions are employed to build the plate’s geometry while are also hired as the shape functions for finite element analysis field approximations. In order to show the accuracy and effectiveness of the present formulation, some representative results are provided and compared to those available in the literature. The flutter characteristics of curvilinear skew laminates are investigated and the effects of different changing parameters including boundary condition, skewness, flow direction and layup on the dynamic stability of the panel from both free vibration as well as flutter points of view are then studied.

Modeling variation coefficient of wave-induced underwater irradiance for clear ocean and its application to find the optimal detector size.

In measuring the coefficient of variation (CV) of underwater wave-induced sunlight irradiance, the spatial integration of irradiance signals due to the finite aperture size of an irradiance detector usually causes underestimation of the measured variance. Because this spatial integration effect is strongly coupled with ocean wave features, inherent optical properties (IOPs) of water, and atmospheric radiance conditions, direct deconvolution techniques from measured irradiance signals can lead to serious signal-to-noise degradation in a noisy upper ocean. On the other hand, choosing a small detector to guarantee CV accuracy is expensive. We address the intrinsic dependence of the CV on the detector size and choice of optimal detector size for measuring irradiance variability in a turbid ocean environment. We present a new theoretical model to directly obtain the form of the CV of the wave-induced scalar irradiance as the function of the detector size, ocean surface wave parameters, and IOPs of ocean water. The model is derived under the small-angle scattering approximation and the first-order assumption of Snell's law and Fresnel transmission coefficient. We demonstrate the validity and efficacy of the model for weakly roughened Gaussian ocean surface conditions, by comparison with Monte Carlo radiative transfer simulations. The model shows that the CV of wave-induced irradiance reaches an asymptotic with decreasing the detector size, thereby providing an optimal or maximum detector size for given IOP and environmental conditions.

Real-Time Device-Level Simulation of MMC-Based MVDC Traction Power System on MPSoC

Real-time simulation of device-level power electronic converter models plays an essential role in traction power systems by allowing accurate prediction of device stresses to design improved control and protection schemes. This paper proposes the electrothermal behavioral power electronic models for the modular multilevel converter (MMC)-based medium voltage direct current (MVDC) traction power system based on the Wiener–Hammerstein configuration. The new configuration introduces the carrier charge prerequisite dynamic transients before device turn-ON or turn-OFF operation. The equivalent carrier charge circuit is also proposed, and the first-order delay assumption of turn-ON and turn-OFF delay time has been proven by the device datasheet. The power electronic device models are implemented in a Xilinx® Zynq® multiprocessing system-on-chip platform. By utilizing hardware and software codesign, both 25- $\mu \text{s}$ time-step system-level and 100-ns time-step device-level transients can be captured in real time within a single device. The three-phase unbalance issue has been resolved by introducing the three-phase to single-phase MMC topology. In the case study, the MMC-based MVDC traction power system has been utilized for the performance of the proposed electrothermal behavioral power electronic models by the off-line simulation models on SaberRD® for device-level transients and PSCAD/EMTDC® for system-level transients.