Grid Model Research Articles

Long-Duration Energy Storage—A Literature Review on the Link between Variable Renewable Energy Penetration and Market Creation

The relationship between a region’s dependency on variable renewable energy (VRE) and the viability of long-duration energy storage (LDES) technologies is recognised through various electricity grid modelling efforts in the contemporary literature. Numerous studies state a specific VRE penetration level in total electricity generation as an indicator of the emergence of an LDES market. However, there is considerable variability across studies when comparing VRE penetration levels in conjunction with LDES technology utilisation, and significant diversity exists in electricity grid modelling approaches. This review aims to highlight these inconsistencies by offering an overview of disparate findings and dissecting the influencing variables. Sixteen parameters are identified from reviewed studies, complemented by an additional five recognised through in-depth analysis. This comprehensive examination not only sheds light on critical aspects overlooked in previous reviews, requiring further investigation, but also provides novel insights into the complexity of this correlation, elevating the understanding of LDES market creation by unravelling the factors that influence the technology adoption across various contexts. Furthermore, it provides clarity in LDES research terminology by rectifying ambiguous language in the existing literature. Altogether, seven databases were explored to produce a trustworthy foundation for the study.

Skill assessment of a total water level and coastal change forecast during the landfall of a hurricane

The Total Water Level and Coastal Change Forecast (TWL&CC Forecast) provides coastal communities with 6-day notice of potential elevated water levels and coastal change (i.e., dune erosion, overwash, or inundation) on sandy beaches that threatens safety, infrastructure, or resources. This continuously operating model provides hourly information for select regions along U.S. Gulf of Mexico and Atlantic Ocean coastlines. The objective of this work is to assess the skill of forecasts during a period of elevated water levels along the coasts of North Carolina (NC) and South Carolina, USA caused by Hurricane Isaias in August 2020, using a combination of observations and model hindcasts. Water levels and waves were observed throughout the storm at three locations near Wrightsville Beach, NC, which provided information to assess forecast skill; a wave buoy offshore, a tide gage at a local pier, and a pressure sensor deployed at the pier. In addition to observations, the non-hydrostatic phase-resolving model SWASH (Simulating WAves till SHore) was forced with hourly wave energy spectra derived from a coupled Delft3D-SWAN simulation during the peak of Isaias, to complement observations by computing nearshore wave height and wave-induced setup and runup at the shoreline. During the storm peak, SWASH-simulated water levels at the sensor position were comparable to those at the maximum landward extent (bias = −0.05 m; gain = 0.26; r2 = 0.99), suggesting that observations at the USGS sensor location were a useful proxy for total water level (TWL; sum of tide, surge and wave runup) at the shoreline that are predicted by the TWL&CC Forecast. The TWL forecast at Wrightsville Beach was consistent with observations from the USGS sensor (bias = −0.38 m and −0.74 m, scatter index = 0.22 and 0.28 for the two forecast model grids considered, respectively; weighted regression considering model uncertainty explained 95 percent of variability in observed TWL). Observed TWL was within the confidence interval of the TWL&CC Forecast for the 5 h at the storm peak. Forecast mean water levels (MWL; sum of tide, surge and wave setup) and tide gage observations were also consistent (bias = 0.07 m and 0.02 m for the forecast model grids; scatter index = 0.46; r2 = 0.80). Forecast MWL at the storm peak was within 0.06 m of the observed MWL from the tide gage for both sites. In the region where Isaias made landfall, eight additional pressure sensors were compared to the peak TWL forecast (bias = 0.14 m; scatter index = 0.18). Forecast TWL explained 90 percent of observed variability in TWL when considering uncertainty of the forecast with a weighted regression. The results demonstrate that wave-driven water levels contributed a significant portion of the forecast TWL during Isaias (52 percent during the three peak hours of the storm), and that TWL were represented using the forecast model. Mean absolute error of the coastal change forecast and observed overwash is 0.4 and 0.14 for the two forecast model grids considered. The skill demonstrated by this computationally efficient method indicates that the forecasting system can provide fast and reliable predictions of TWL across hundreds of km of coastline at sub-km resolution, days to hours in advance of when storms threaten coastal regions.

Application of hydrostatic local thermodynamic equilibrium atmosphere models to interpretations of supersoft X-ray source spectra

Supersoft X-ray sources (SSSs) are accreting white dwarfs (WDs) with stable or recurrent thermonuclear burning on their surfaces. High-resolution X-ray spectra of such objects are rather complex, often consist of several components, and are difficult to interpret accurately. The main emission source is the hot surface of the WD and the emergent radiation can potentially be described by hot WD model atmospheres. We present a new set of such model atmosphere spectra computed in the effective temperature range from 100 kK to 1000 kK, for eight values of surface gravity and three different chemical compositions. These compositions correspond to the solar one as well as to the Large and Small Magellanic Clouds, with decreased heavy element abundances, at one-half and one-tenth of the solar value. The presented model grid covers a broad range of physical parameters and, thus, it can be applied to a wide range of objects. It is also publicly available in XSPEC format. As an illustration, we applied it here for the interpretation of Chandra and XMM grating spectra of two classical SSSs, namely, CAL 83 (RX J0543.5–6823) and RX J0513.9–6951. The obtained effective temperatures and surface gravities of Teff ≈ 560 kK, log g ≈ 8.6–8.7, and Teff ≈ 630 kK, log g ≈ 8.5–8.6, respectively, are in a good agreement with previous estimations for both sources. The derived WD mass estimations are within 1.1–1.4 M⊙ for CAL 83 and 1.15–1.4 M⊙ for RX J0513.9–6951. The mass of the WD in CAL 83 is consistent with the mass predicted from the respective model of recurrent thermonuclear burning.

Dynamical heterogeneity and universality of power-grids

Electric power systems during transient states are extensively investigated using variations of the Kuramoto model to analyze their dynamic behavior. However, the majority of current models fail to capture the physics of power flows and the heterogeneity of the grids under study. This study addresses this gap by comparing the levels of heterogeneity in continent-sized power grids in Europe and North America to reveal the underlying universality and heterogeneity of grid frequencies, electrical parameters, and topological structures. Empirical data analysis of grid frequencies from the Hungarian grid indicates that q-Gaussian distributions best fit simulations, with spatio-temporally correlated noise evident in the frequency spectrum. Comparing European and North American power grids reveals that employing homogeneous transmission capacities to represent power lines can lead to misleading results on stability, and nodal behavior is heterogeneous. Community structures of the continent-sized grids are detected, demonstrating that Chimera states are more likely to occur when studying only subsystems. A topographical analysis of the grids is presented to assist in selecting such subsystems. Finally, synchronization calculations are provided to illustrate the occurrence of Chimera states. The findings underscore the necessity of heterogeneous grid models for dynamic stability analysis of power systems.

Using the Multiple-Sensor-Based Frost Observation System (MFOS) for Image Object Analysis and Model Prediction Evaluation in an Orchard

Accurate frost observations are crucial for developing and validating frost prediction models. In 2022, the multi-sensor-based automatic frost observation system (MFOS), including an RGB camera, a thermal infrared camera, a leaf wetness sensor (LWS), LED lighting, and three glass plates, was developed to replace the naked-eye observation of frost. The MFOS, herein installed and operated in an apple orchard, provides temporally high-resolution frost observations that show the onset, end, duration, persistence, and discontinuity of frost more clearly than conventional naked-eye observations. This study introduces recent additions to the MFOS and presents the results of its application to frost weather analysis and forecast evaluation in an orchard in South Korea. The NCAM’s Weather Research and Forecasting (WRF) model was employed as a weather forecast model. The main findings of this study are as follows: (1) The newly added image-based object detection capabilities of the MFOS helped with the extraction and quantitative comparison of surface temperature data for apples, leaves, and the LWS. (2) The resolution matching of the RGB and thermal infrared images was made successful by resizing the images, matching them according to horizontal movement, and conducting apple-centered averaging. (3) When applied to evaluate the frost-point predictions of the numerical weather model at one-hour intervals, the results showed that the MFOS could be used as a much more objective tool to verify the accuracy and characteristics of frost predictions compared to the naked-eye view. (4) Higher-resolution and realistic land-cover and vegetation representation are necessary to improve frost forecasts using numerical grid models based on land–atmosphere physics.

Modeling the Progenitor Stars of Observed Type IIP Supernovae

Type IIP supernovae (SNe IIP) are thought to originate from the explosion of massive stars >10 M ⊙. Their luminosity is primarily powered by the explosion energy and the radioactive decay energy of 56Co, with the photosphere location regulated by hydrogen recombination. However, the physical connections between SNe IIP and their progenitor stars remain unclear. This paper presents a comprehensive study of SNe IIP and their progenitor stars by using the one-dimensional stellar evolution code, MESA. Our model grids consider the effects of stellar metallicity, mass, and rotation in the evolution of massive stars, as well as the explosion energy and 56Ni production in modeling supernovae. To elucidate the observed SNe IIP and their origins, we compare their light curves (LCs) with our models. Furthermore, we investigate the impact of stellar parameters on LCs by considering stellar mass, metallicity, rotation, explosion energy, and 56Ni production. We find that more massive stars exhibit longer plateaus due to increased photon diffusion time caused by massive ejecta. Higher metallicity leads to increased opacity and mass loss of progenitor stars. Rapid rotation affects internal stellar structures, enhancing convective mixing and mass loss, potentially affecting the plateau’s brightness and duration. Higher explosion energy results in brighter but shorter plateaus due to faster-moving ejecta. 56Ni mass affects late-time luminosity and plateau duration, with larger masses leading to slower declines.

Geoid Undulation Model as Vertical Reference in Indonesia

Indonesia released a new regional geoid model in 2020—the Indonesian Geoid 2020 (INAGEOID2020). It covers the Indonesian region with a spatial resolution of 0.01 × 0.01 degree with the unit in meters. The model was generated through a series of data and computations. Three components of gravity data, i.e., the observed free-air anomaly, the long-wave from the global geoid model, and the short-wave from the terrain model, were employed. The computation was performed using the Remove-Compute-Restore technique with the Fast Fourier Transformation approach. The output was then fitted to the geoid at tide stations by adding a fitting plane to the geoid model. The fitting plane was constructed based on the difference between the geoid model and each tide gauge benchmark. The final geoid model was evaluated by comparing the model with the reference data. Based on quality metrics, the accuracy of INAGEOID2020 varied between 6 cm to 29 cm. Any interested user can use this gridded geoid model to convert geodetic to orthometric heights and vice versa.

Aerodynamic discrepancies of high-speed trains meeting within two types noise barriers: considering modeling scale ratio

PurposeSustainable urban rail transit requires noise barriers. However, these barriers’ durability varies due to the differing aerodynamic impacts they experience. The purpose of this paper is to investigate the aerodynamic discrepancies of trains when they meet within two types of rectangular noise barriers: fully enclosed (FERNB) and semi-enclosed with vertical plates (SERNBVB). The research also considers the sensitivity of the scale ratio in these scenarios.Design/methodology/approachA 1:16 scaled moving model test analyzed spatiotemporal patterns and discrepancies in aerodynamic pressures during train meetings. Three-dimensional computational fluid dynamics models, with scale ratios of 1:1, 1:8 and 1:16, used the improved delayed detached eddy simulation turbulence model and slip grid technique. Comparing scale ratios on aerodynamic pressure discrepancies between the two types of noise barriers and revealing the flow field mechanism were done. The goal is to establish the relationship between aerodynamic pressure at scale and in full scale.FindingsThe aerodynamic pressure on SERNBVB is influenced by the train’s head and tail waves, whereas for FERNB, it is affected by pressure wave and head-tail waves. Notably, SERNBVB's aerodynamic pressure is more sensitive to changes in scale ratio. As the scale ratio decreases, the aerodynamic pressure on the noise barrier gradually increases.Originality/valueA train-meeting moving model test is conducted within the noise barrier. Comparison of aerodynamic discrepancies during train meets between two types of rectangular noise barriers and the relationship between the scale and the full scale are established considering the modeling scale ratio.

Behavior recognition of non-motorized transport at intersections using dual-channel grid model based on disordered trajectory point data

Accurately identifying the passing and waiting behavior of pedestrians and non-motorized vehicles at intersection is essential to planning management measures for non-motorized transport. Much previous study in this field has focused on methods based on continuous individual trajectory detection, which are almost ineffective under the poor detection condition in dense traffic scenarios. To address the task, this paper establish a workable framework for inferring the probabilities of passing or waiting behavior of pedestrians and non-motorized vehicles in arbitrary space using disordered trajectory point data. First, a two-channel model is proposed to perform a formalized grid-level representation of an intersection, in which the functional attributes and occupancy characteristics of grids are comprehensively defined and quantified. Then, the quantitative characteristics of the grids are used to detect the real-world occurrence space of passing and waiting behaviors, by the clustering and expanding operations on grids. Finally, through feature transfer along path, characteristics is decomposed into passing and waiting occurrence characteristics for behavior probability computation. Results indicate that the method achieves over 91% accuracy of behavior recognition, which is better than compared methods in various Multiple Object Tracking Accuracy (MOTA). Although the method is sensitive to spatial detection conditions, it obtains steady accuracy under various target detection settings.

Optimized analysis and reinforcement design model for RC/SCC box-section bridges using developed advanced design framework

In recent years, there has been a significant rise in the construction of reinforced concrete (RC) and steel-concrete composite (SCC) box-section bridges. However, design codes do not provide specific design methods for the RC plates of such bridges where the plates experience both intricate forces and moments. The current design approaches are primarily based on conventional one-dimensional beam element theory, which neglects the complex spatial force characteristics of the structural elements, potentially leading to unsafe design. Therefore, it is imperative to address this issue. To bridge this gap, a comprehensive analysis and reinforcement design procedure named as the developed advanced design framework (DADF) is proposed in this study. The spatial analysis of bridges was performed using a refined numerical model, called the spatial grid model (SGM), to consider the structural spatial effects with limited model scales. Subsequently, the internal force corresponding matrix (IFCM) was implemented through Python scripts to determine the most critical internal force combination for an RC plate element. Additionally, the three-layered sandwich model (T-LSM) was employed with limit analysis to automatically design reinforcement for all elements, serving as a practical tool for design. This research demonstrates that the implementation of the DADF can significantly reduce steel reinforcement in the RC plates of such bridges by up to 48 %, and 23 % in total, showcasing the efficiency of the developed framework. Overall, the findings emphasize that the proposed DADF offers a robust procedure for steel reinforcement design of RC/SCC box-section bridges.

Integration of two different road network models for emergency rescue pathfinding in indoor and outdoor environments

Abstract The environment of buildings and outdoor transportation in urban areas is becoming increasingly complex. This poses a challenge for rescue pathfinding once an emergency occurs, which relies on the generation of road network models. To better balance efficiency and accuracy in pathfinding, a three-dimensional integrated road network model (3D-IRNM) derived from grid and topological road network models was developed in this study. Firstly, a cross-platform data loading method from building information model to geographic information systems (GIS) is proposed, to serve as a data source for road network model generation, visual enhancement, and breaking the barriers between different spatial data format models. Then, the topological and grid road network models are generated in indoor spaces of different functions, with IRNM obtained by the integration strategy. The 3D-IRNM can be formed by extracting indoor vertical paths from the stairs and connecting them with the IRNM of each floor. To further combine the 3D-IRNM with outdoor environments, a CrossNode model is then proposed. Besides, an adaptive pathfinding algorithm is also proposed. Finally, the construction of an emergency pathfinding system based on GIS technology is achieved. The pathfinding algorithm and the structure of 3D-IRNM help the pathfinding both efficiency and accuracy. The practicability of the designed 3D-IRNM together with its pathfinding algorithm is well verified.

How Accurate Numerical Simulation of Seismic Waves in a Heterogeneous Medium Can Be?

ABSTRACT Analysis of equations of motion by Moczo et al. (2022) led to the conclusion that the discrete (grid) representation of the heterogeneous medium must be wavenumber bandlimited up to the Nyquist frequency. This is a consequence of the spatial discretization. Mittet (2021a) reported that if the discrete grid model of medium coincides with the true medium up to some wavenumber, the simulated wavefield is accurate only up to a half of this wavenumber. Here, we present results of the systematic and comprehensive analysis focused on the principal limits of accuracy of numerically simulated wavefields. First, we analyze wavenumber spectra of (1) exact wavefields in a heterogeneous elastic medium, (2) wavenumber bandlimited wavefields, and (3) spatially discretized wavefields. Then, we derive spatial dependence of the frequency spectrum of waves generated by a finite source, and perturbing wavefields due to a small perturbation of the medium and due to a small wavenumber bandlimited perturbation of the medium. We analyze an interaction of an incoming wave with the medium perturbation through a change of phase difference and through wavenumber spectra. We draw conclusions on the wavenumber limitation of wavefields in the wavenumber bandlimited heterogeneous medium. We numerically verify the fundamental finding using exact solutions. The main consequence for the finite-difference (FD) modeling based on spatial discretization of the computational domain is: Due to spatial sampling, the medium must be wavenumber limited up to the Nyquist frequency. Then, the wavefield should not be sampled by less than four spatial grid spacings per shortest wavelength to obtain sufficiently accurate results. This applies to any heterogeneous FD scheme.

Comparison of Chromatic Assimilation Effects Depending on Printing Substrate in the Munker-White Model

Understanding the influence of paper surface structures on color perception is crucial for the printing industry. This research investigates the impact of horizontal and vertical parallel lines on chromatic assimilation using the Munker-White grid model. The study employs the perceived ∆E00 metric to quantify color differences and determine whether these textures affect perceived color accuracy and consistency differently. Results reveal variations in color perception due to surface textures. The biggest color difference (ΔE00) occurred at 60% RTV coverage for cyan, where the vertical structure showed a significantly lower value than the horizontal. For the yellow primary stimulus, the greatest difference was observed at 20% RTV coverage, with both structures showing high initial values that decrease with increased coverage. These findings provide valuable insights for improving color management practices and enhancing the quality and reliability of color reproduction on various substrates, contributing to advancements in printing technology and color science.

Optimum management of microgrid generation containing distributed generation sources and energy storage devices by considering uncertainties

In recent years, the financial and energy crises have made the economical and safe operation of distribution microgrids one of the main challenges for operators. In this regard, the optimal distribution of the microgrid, considering the favorable indicators of Generation and consumption, significantly improves the quality of the development and economic operation of electricity grids. On the other hand, distribution microgrids have many problems and complications due to the presence of DG sources and the uncertainties caused by them in Generation and consumption, such as the inability to solve optimal load distribution using common and common calculation methods. Therefore, grid technical indicators such as voltage deviation and losses in solving load distribution add to the complexity of related issues. To solve the challenges raised in the distribution microgrid, this paper proposes an optimal load distribution model that models the uncertainties in the distribution microgrids using the Monte Carlo method. Using meta-heuristic algorithms, the optimal Generation function by modeling grid security constraints such as voltage deviation, losses, and a load limit of the system should be in economic operation mode, and then the power distribution equations should be solved. The battery can supply 1 kW of active power to the system at a cost of 1 unit/kW during the high cost period if it absorbs 1 kW of active power at a cost of 0.92 units/kW during the low cost period. Additionally, the active and reactive power losses have been decreased to 0.3kW and 0.2kW, respectively, by utilizing the suggested methodology. The simulation results show that the proposed method performs satisfactorily and that the modeling is simulated in MATLAB software.

Multi-period urban hydrogen refueling stations site selection and capacity planning with many-objective optimization for hydrogen supply chain

The location and quantity of hydrogen refueling stations (HRSs) play a crucial role in the development and promotion of hydrogen fuel cell vehicles (HFCVs). This study proposes a multi-period urban HRSs site selection and capacity planning with many-objective optimization framework for hydrogen supply chain (HSC). Firstly, the city's multi-period hydrogen requirement is predicted based on a generalized Bass diffusion model. Using publicly available data, including gas station network data, geographic information system (GIS) data, population data, and regional economic data, a spatially aggregated demand model is established to allocate hydrogen requirement at candidate sites in the city of the geographic grid model with a 1 km resolution. On this basis, four interrelated objective functions (total investment cost, hydrogen requirement coverage, risk coefficient, and environmental factors) are developed. The third-generation non-dominated sorting genetic algorithm (NSGA-III) and the technique for order preference by similarity to an ideal solution (TOPSIS) are employed to achieve multi-period urban HRSs site selection and capacity planning with many-objective optimization for HSC. By comparing the results of single-objective optimization focusing on minimum cost and maximum hydrogen requirement coverage, it is observed that many-objective optimization achieves a better balance among the four conflicting objectives. After comprehensive analysis, the distribution of HRSs exhibits a clustered structure, influenced by the population and economic structure of the city. In the initial stages of HFCV development, most stations serve the peripheral areas around the city center; while n the later stages of the optimization period, a few high-capacity HRSs begin to concentrate in the city center.

The Met Office Forecast Ocean Assimilation Model (FOAM) using a 1/12‐degree grid for global forecasts

AbstractThe Met Office Forecast Ocean Assimilation Model (FOAM) ocean–sea‐ice analysis and forecasting operational system has been using an ORCA tripolar grid with 1/4° horizontal grid spacing since December 2008. Surface boundary forcing is provided by numerical weather prediction fields from the operational global atmosphere Met Office Unified Model. We present results from a 2‐year simulation using a 1/12° global ocean–sea‐ice model configuration while keeping a 1/4° data assimilation (DA) set‐up. We also describe recent operational data assimilation enhancements that are included in our 1/4° control and 1/12° simulations: a new bias‐correction term for sea‐level anomaly assimilation and a revised pressure correction algorithm. The primary effect of the first is to decrease the mean and variability of sea‐level anomaly increments at high latitudes, whereas the second significantly reduces the vertical velocity standard deviation in the tropical Pacific. The level of improvement achieved with the higher resolution configuration is moderate but consistently satisfactory when measured using neighbourhood verification metrics that provide fairer quantitative comparisons between gridded model fields at different spatial resolutions than traditional root‐mean‐square metrics. A comparison of the eddy kinetic energy from each configuration and an observation‐based product highlights the regions where further system developments are most needed.

Research on the Protection System for Smart Grid Based on Phasor Information at Circuit Breakers

A smart grid protection system based on phasor information at circuit breakers is proposed in this paper. Phasor data for fault diagnosis is obtained from phasor measurement units or intelligent electronic devices installed near circuit breakers, without the need for additional measurement equipment. When a fault occurs, the protection system first locates the core protection circuit breaker closest to the fault point. It then identifies the faulty component by analyzing the current phasor differences between this breaker and adjacent ones. This scheme offers high computational efficiency, enabling rapid identification of faulty equipment and its precise location. The proposed protection system structure can be divided into two types: centralized and decentralized, and the most suitable scheme should be selected based on the actual situation. Finally, the feasibility of the proposed scheme was verified through the IEEE 39-bus system and a simulated actual area power grid model, demonstrating its applicability to practical smart grid scenarios. The simulation network validates the implementation method of the proposed protection strategy.

Impact of PLL and non-PLL vector current control techniques on grid connected inverter

In the micro-grids, all the Distributed Power Generation Systems (DPGS) and loads are interconnected across the Point of Common Coupling (PCC). The stability and harmonics of the grid connected inverters are significantly impacted by uncertainties in the renewable energy sources based DPGS. The performance of these grid connected inverters across the PCC depends on the Phase-Locked Loop (PLL) used to track the grid angle and power control structures used to control the power fed to grid. These power control structures can be either PLL based or PLL less systems. The PLL based Vector Current Control Direct Quadrature (VCC DQ) control and PLL less Non-PLL Vector Control (NPVC) techniques are compared along with their controller design and bode plots. Also, the small signal models of grid connected inverter with PLL are presented from which the converter impedance is derived to show the effect of PLL on the system using bode plots. The impact of the PLL based and PLL less control techniques on the grid connected inverter are presented with analytical equations along with simulation and hardware results. A 6 kW grid connected inverter simulation model and 150 W hardware prototype is developed using TI F28379D processor to compare the performance of both with and without PLL control techniques.

Using Parametric g-Computation for Time-to-Event Data and Distributed Lag Models to Identify Critical Exposure Windows for Preterm Birth: An Illustrative Example Using in a Retrospective Birth Cohort Based in Eastern Massachusetts (2011-2016).

Parametric g-computation is an attractive analytic framework to study the health effects of air pollution. Yet, the ability to explore biologically relevant exposure windows within this framework is underdeveloped. We outline a novel framework for how to incorporate complex lag-responses using distributed lag models (DLMs) into parametric g-computation analyses for survival data. We call this approach "g-survival-DLM" and illustrate its use examining the association between during pregnancy and the risk of preterm birth (PTB). We applied the g-survival-DLM approach to estimate the hypothetical static intervention of reducing average in each gestational week by 20% on the risk of PTB among 9,403 deliveries from Beth Israel Deaconess Medical Center, Boston, Massachusetts, 2011-2016. Daily was taken from a grid model and assigned to address at birth. Models were adjusted for sociodemographics, time trends, nitrogen dioxide, and temperature. To facilitate implementation, we provide a detailed description of the procedure and accompanying R syntax. There were 762 (8.1%) PTBs in this cohort. The gestational week-specific median concentration was relatively stable across pregnancy at . We found that our hypothetical intervention strategy changed the cumulative risk of PTB at week 36 (i.e., the end of the preterm period) by (95% confidence interval: , 0.007) in comparison with the scenario had we not intervened, which translates to about 86 fewer PTBs in this cohort. We also observed that the critical exposure window appeared to be weeks 5-20. We demonstrate that our g-survival-DLM approach produces easier-to-interpret, policy-relevant estimates (due to the g-computation); prevents immortal time bias (due to treating PTB as a time-to-event outcome); and allows for the exploration of critical exposure windows (due to the DLMs). In our illustrative example, we found that reducing fine particulate matter [particulate matter (PM) with aerodynamic diameter ()] during gestational weeks 5-20 could potentially lower the risk of PTB. https://doi.org/10.1289/EHP13891.

Evolutionary nature of puffed-up stripped star binaries and their occurrence in stellar populations

The majority of massive stars are formed in multiple systems, and at some point during their life, they interact with their companions via mass transfer. This interaction typically leads to the primary shedding its outer envelope, resulting in the formation of a “stripped star”. Classically, stripped stars are expected to quickly contract to become hot and UV-bright helium stars. Surprisingly, recent optical spectroscopic surveys have unveiled many stripped stars that are much larger and cooler, appearing “puffed up” and overlapping with the Main Sequence (MS) in the Hertzsprung–Russell diagram. Here, we study the evolutionary nature of puffed-up stripped (PS) stars and the duration of this enigmatic phase using the stellar-evolution code MESA. We computed grids of binary models at four metallicities: Solar (Z⊙ = 0.017), Large Magellanic Cloud (LMC, Z = 0.0068), Small Magellanic Cloud (SMC, Z = 0.0034), and Z = 0.1 Z⊙. Contrary to previous assumptions, we find that stripped stars regain thermal equilibrium shortly after the end of mass transfer and maintain it during most of the PS phase. Their further contraction towards hot and compact He stars is determined by the rate at which the residual H-rich envelope is depleted, with the main agents being H-shell burning (dominant for M ≲ 50 M⊙) and mass-loss in winds. The duration of the PS star phase is approximately 10% of the core-He burning lifetime (1% total lifetime) and up to 100 times more than the thermal timescale. It decreases with increasing mass and luminosity and increases with metallicity. We explored several factors influencing PS star lifetimes: orbital period, mass ratio, winds, and semiconvection. We further carried out a simple binary population synthesis estimation, finding that ∼0.5–0.7% of all the stars with log (L/L⊙) > 3.7 may, in fact, be PS stars. Our results indicate that tens to hundreds of PS stars in post-interaction binaries may be hiding in the MS population, disguised as ‘normal’ stars: ∼100 (∼280) in the SMC (LMC) and ∼1500 in the Milky Way. Their true nature may be revealed by spectroscopically measured low surface gravities, high N enrichment, and likely slow rotation rates.