Model predictive control simulations with block-hierarchical differential–algebraic process models
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We present the detection of neutral helium at 10833 Å in the atmosphere of WASP-52b and tentative evidence of helium in the atmosphere of the grazing WASP-177b, using high-resolution observations acquired with the NIRSPEC instrument on the Keck II telescope. We detect excess absorption by helium in WASP-52b's atmosphere of 3.44% ± 0.31% (11σ), or equivalently 66 ± 5 atmospheric scale heights. This absorption is centered on the planet's rest frame (Δv = 0.00 ± 1.19 km s –1 ). We model the planet's escape using a 1D Parker wind model and calculate its mass-loss rate to be ~1.4 × 10 11 g s –1 , or equivalently 0.5% of its mass per gigayear. For WASP-177b, we see evidence for redshifted (Δv = 6.02 ± 1.88 km s –1 ) helium-like absorption of 1.28% ± 0.29% (equal to 23 ± 5 atmospheric scale heights). However, due to residual systematics in the transmission spectrum of similar amplitude, we do not interpret this as significant evidence for He absorption in the planet's atmosphere. Using a 1D Parker wind model, we set a 3σ upper limit on WASP-177b's escape rate of 7.9 × 10 10 g s –1 . Our results, taken together with recent literature detections, suggest the tentative relation between XUV irradiation and He ι absorption amplitude may be shallower than previously suggested. Our results highlight how metastable helium can advance our understanding of atmospheric loss and its role in shaping the exoplanet population.
Cosmic ray (CR) muon shadows were located using muon data from the MINOS Far Detector in Northern Minnesota. The shadows were located independently across 3 time periods; near solar minimum, solar maximum, and over the entire 13 year span of the data. A muon distribution for each shadow was then sampled to simulate CR motions near the Sun using the Parker Spiral model of the Sun’s IMF and a dipole model of the Earth’s GMF. The resulting particle distributions were then compared to their position with respect to the Sun. An analytical relationship between the primary CR cutoff energy E0 and the associated shadow deflections was observed. The minimum cutoff energy of the primary CR energy spectrum consistent with the Parker Spiral model was determined to be $E_0 = 22.8 \pm 1.2$~TeV. This value is 2-3 times higher than the experimentally determined value. Complexities that can be added to the Parker Spiral Model and affect the overall shift of the the Sun’s cosmic ray shadow are discuss ed to explain discrepancies. Results show that the Parker Spiral model is most consistent with the the solar minimum shadow and least consistent with the solar maximum shadow, as expected.
Shadows cast in the cosmic ray (CR) muon sky by the Sun were located using muon data from the MINOS far detector in Northern Minnesota. The shadows were observed independently across three time periods; near solar minimum, near solar maximum, and over the entire 13 year span of the data. A distribution of muon positions for each shadow was then sampled to simulate CR motions near the Sun using the Parker spiral model of the Heliospheric Magnetic Field (HMF) and a dipole model of the Geomagnetic Field (GMF). The resulting particle distributions were then compared to their position with respect to the Sun. Results show that the Parker spiral model is most consistent with the solar minimum shadow and least consistent with the solar maximum shadow, as expected. The simple Parker spiral is more consistent with the data for a harder CR spectrum than is actually present, indicating the need for a more detailed HMF model. Plausible modifications to the Parker spiral model which would affect the overall shift of the Sun's CR shadow are discussed.
We search for escaping helium from the hot super-Earth 55 Cnc e by taking high-resolution spectra of the 1083 nm line during two transits using Keck/NIRSPEC. We detect no helium absorption down to a 90% upper limit of 250 ppm in excess absorption or 0.27 mÅ in equivalent width. This corresponds to a mass-loss rate of less than ∼10{sup 9} g s{sup −1} assuming a Parker wind model with a plausible exosphere temperature of 5000–6000 K, although the precise constraint is heavily dependent on model assumptions. We consider both hydrogen- and helium-dominated atmospheric compositions and find similar bounds on the mass-loss rate in both scenarios. Our hydrodynamical models indicate that if a lightweight atmosphere exists on 55 Cnc e, our observations would have easily detected it. Together with the nondetection of Lyα absorption by Ehrenreich et al., our helium nondetection indicates that 55 Cnc e either never accreted a primordial atmosphere in the first place or lost its primordial atmosphere shortly after the dissipation of the gas disk.
We obtained high-resolution spectra of the ultracool M-dwarf TRAPPIST-1 during the transit of its planet “b” using two high-dispersion near-infrared spectrographs, the Infrared Doppler (IRD) instrument on the Subaru 8.2m telescope, and the Habitable Zone Planet Finder (HPF) instrument on the 10 m Hobby–Eberly Telescope. These spectroscopic observations are complemented by a photometric transit observation for planet “b” using the APO/ARCTIC, which assisted us in capturing the correct transit times for our transit spectroscopy. Using the data obtained by the new IRD and HPF observations, as well as the prior transit observations of planets “b,” “e” and “f” from IRD, we attempt to constrain the atmospheric escape of the planet using the He i triplet 10830 Å absorption line. We do not detect evidence for any primordial extended H-He atmospheres in all three planets. To limit any planet-related absorption, we place an upper limit on the equivalent widths of <7.754 mÅ for planet “b,” <10.458 mÅ for planet “e,” <4.143 mÅ for planet “f” at 95% confidence from the IRD data, and <3.467 mÅ for planet “b” at 95% confidence from HPF data. Using these limits along with a solar-like composition isothermal Parker wind model, we attempt to constrain the mass-loss rates for the three planets. For TRAPPIST-1b, our models exclude the highest possible energy-limited rate for a wind temperature <5000 K. This nondetection of extended atmospheres with low mean-molecular weights in all three planets aids in further constraining their atmospheric composition by steering the focus toward the search of high-molecular-weight species in their atmospheres.
The Parker Solar Probe (PSP) aims to explore the nascent solar wind close to the Sun. Meanwhile, PSP is also expected to encounter small objects like comets and asteroids. Here, we survey the ephemerides to find the chance of a recent encounter and then model the interaction between released dusty plasmas and solar wind plasmas. On 2019 September 2, a comet-like object, the 322P/Solar and Heliosphere Observatory, just passed its perihelion flying to a heliocentric distance of 0.12 au and swept by PSP at a relative distance as close as 0.025 au. We present the dynamics of the dust particles released from 322P, forming a curved dust tail. Along the path of PSP in the simulated inner heliosphere, the states of plasma and magnetic field are sampled and illustrated, with the magnetic field sequences from simulation results being compared directly with the in situ measurements from PSP. Through the comparison, we suggest that 322P might be at a deficient activity level releasing limited dusty plasmas on its way to becoming a "rock comet." We also present images of solar wind streamers as recorded by the Wide-field Imager for Solar Probe Plus, showing an indication of dust bombardment for the images superposed with messy trails. We observe from the Large Angle and Spectrometric Coronagraph that 322P was transiting from a dimming region to a relatively bright streamer during its perihelion passage, and perform a simulation to confirm that 322P was flying from relatively faster to slower solar wind streams, modifying the local plasma states of the streams.
Observations of the time-dependent cosmic-ray Sun shadow have been proven as a valuable diagnostic for the assessment of solar magnetic field models. Here, seven years of IceCube data are compared to solar activity and solar magnetic field models. A quantitative comparison of solar magnetic field models with IceCube data on the event rate level is performed for the first time. Additionally, a first energy-dependent analysis is presented and compared to recent predictions. We use seven years of IceCube data for the moon and the Sun and compare them to simulations on data rate level. The simulations are performed for the geometrical shadow hypothesis for the moon and the Sun and for a cosmic-ray propagation model governed by the solar magnetic field for the case of the Sun. We find that a linearly decreasing relationship between Sun shadow strength and solar activity is preferred over a constant relationship at the 6.4σ level. We test two commonly used models of the coronal magnetic field, both combined with a Parker spiral, by modeling cosmic-ray propagation in the solar magnetic field. Both models predict a weakening of the shadow in times of high solar activity as it is also visible in the data. We find tensions with the data on the order of 3σ for both models, assuming only statistical uncertainties. The magnetic field model CSSS fits the data slightly better than the PFSS model. This is generally consistent with what is found previously by the Tibet AS-γ Experiment; a deviation of the data from the two models is, however, not significant at this point. Regarding the energy dependence of the Sun shadow, we find indications that the shadowing effect increases with energy during times of high solar activity, in agreement with theoretical predictions.
Nonlinear modeling and optimization is a valuable tool for aiding decisions by engineering practitioners, but programming an optimization problem based on a complex electrical, mechanical, or chemical process is a time-consuming and error-prone activity. Therefore, there is a need for model analysis and debugging tools that can detect and diagnose modeling errors. One such tool is the Dulmage–Mendelsohn decomposition, which identifies structurally under- and over-determined subsets in systems of equations and variables by partitioning the bipartite graph of the system. This work provides the necessary background to understand the Dulmage–Mendelsohn decomposition and its application to the analysis of nonlinear optimization problems, demonstrates its use in diagnosing a variety of modeling errors, and introduces software implementations for analyzing nonlinear optimization problems in the Pyomo and JuMP algebraic modeling languages.
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This dataset is the raw and processed data for the paper "Simulated plant ‑ mediated oxygen input has strong impacts on fine ‑ scale porewater biogeochemistry and weak impacts on integrated methane fluxes in coastal wetlands". This study investigated how plant-mediated oxygen input affects subsurface biogeochemical reactions of organic carbon degradation and the resulting methane emissions of coastal wetlands by model simulation. We used the subsurface geochemical simulator PFLOTRAN for the modeling, which produced the simulated changes in porewater chemical substances and methane emissions over 10 days under different scenarios of plant-mediated oxygen input.Specifically, this dataset contains: 1) the input files for PFLOTRAN of all simulation runs conducted in this study. Those files are with an extension of ".in", containing information of the biogeochemical reaction network (stoichiometry, reaction rate, Monod constants, etc), fluid flow rate and oxygen concentration in the fluid which together simulated the plant-mediated oxygen input, the configuration of artificial reactions that simulated the methane fluxes, etc. The PFLOTRAN input files are text files, which can be opened by NotePad, but running these input files will require proper installation of PFLOTRAN (instruction: https://documentation.pflotran.org/user_guide/how_to/installation/installation.html). 2) the raw and processed model output from PFLOTRAN of all simulation runs, and 3) the python scripts used to process the raw model output, including random allocation of root cells, converting raw data into organized formats, calculating the methane fluxes based on the model output, data visualization, etc. The raw and processed model output from PFLOTRAN are in .spydata format, which can be viewed with Python. and 3) the python scripts for data processing and analysis are programming scripts, which can be opened with Python.This modeling work, in particular the model parameterization of root density and initial conditions of porewater concentrations of biogeochemical substances, was based on field measurements at the salt marsh of the Upper Parker River Estuary, Massachusetts, United States.
Abstract not provided.
This dataset contains 15-minute tide height and salinity data from the Typha site along the Parker River, part of the Plum Island Ecosystems Long Term Ecological Research (PIE LTER) site in Plum Island Sound, Massachusetts (MA) 2014-2023. Tide height (in NAVD88) was compiled from measurements conducted at the mouth of Plum Island Sound and corrected for time lags. Gap-filling of missing periods were done by fitting tidal constituents to the time series. Salinity was measured (and is stored on ESS DIVE ) in 2022 and 2023 using HOBO U24-002 conductivity loggers. River discharge is the most important control on tidal river water salinity at the location (Vallino & Hopkinson, 1998). An artificial neural network was trained to predict river water salinity at the location using Parker River discharge (USGS station 01101000, Parker River at Byfield, MA) and gap-filled salinity observations from a long-term monitoring station ca. 3km downstream from the Typha site (LTER station ‘Middle Road’) as input variables to create continuous time series information. The data set was used in the spin up and simulations of a land surface model coupled to a biogeochemical reaction network (ELM PFLOTRAN) assessing impacts of hydrology and salinity input on methane fluxes in 2022 and 2023 (Sulman et al., 2024). Metadata files ELMPFLOTRAN_tide_salinity_dd.csv and ELMPFLOTRAN_tide_salinity_flmd.csv provide details on site location, data variables, and QA/QC methods .
The heat pump rooftop units (RTUs) measure replaces gas furnace and electric resistance RTUs with high-efficiency heat pump rooftop units (HP-RTUs). The HP-RTUs are intended to be top-of-the line, including high-efficiency fans and heat pump systems. The fans are variable speed, allowing the HP-RTUs to operate as single-zone variable air volume systems. The heat pumps are also variable speed, allowing for high part load performance. All schedules in the existing RTUs are transferred to the new HP-RTUs for consistency. Furthermore, any energy efficiency features in the existing baseline RTUs such as energy recovery or economizers are also transferred to the new HP-RTUs for consistency. This measure is applicable to approximately 45% of the ComStock floor area. The HP-RTU measure demonstrates 10.3% total site energy savings (449 trillion British thermal units [TBtu]) for the U.S. commercial building stock modeled in ComStock.
Abstract Through their rooting profiles and water demands, plants affect the distribution of water in the soil profile. Simultaneously, soil water content controls plant development and interactions within and between plant communities. These plant-soil water feedbacks might vary across plant communities with different rooting depths and species composition. In semiarid environments, understanding these differences will be essential to predict how ecosystems will respond to drought, which may become more frequent and severe with climate change. In this study, we tested how plant-soil water feedbacks responded to drought in two contrasting ecosystem types—grassland and shrubland—in the coastal foothills of southern California. During years 5–8 of an ongoing precipitation manipulation experiment, we measured changes in plant communities and soil moisture up to 2 m depth. We observed different water use patterns in grassland and shrubland communities with distinct plant functional types and water use strategies. Drought treatment did not affect perennial, deep-rooted shrubs because they could access deep soil water pools. However, mid-rooted shrubs were sensitive to drought and experienced decreased productivity and die-off. As a result, water content actually increased with drought at soil depths from 50–150 cm. In grassland, biomass production by annual species, including annual grasses and forbs, declined with drought, resulting in lower water uptake from the surface soil layer. An opportunistic “live fast, die young“ life strategy allowed these species to recover quickly once water availability increased. Our results show how drought interacts with plant community composition to affect the soil water balance of semiarid ecosystems, information that could be integrated into global scale models.
The software is code for analyzing, debugging, and solving optimization models. The code implements several algorithms and provides convenient APIs to apply these algorithms to optimization models. The algorithms are primarily based on graph theory. They compute well-known partitions of graphs, and use these partitions to provide the user information about their optimization model, including diagnosing certain types of structural modeling errors. Some algorithms may be used as a subroutine to solve an optimization problem, and may call an optimization solver to facilitate this. Well-known linear algebra routines are called to provide further diagnostics. The software contains no data and no models other than toy models used for testing.
Magnetic reconnection in partially ionized plasmas is a ubiquitous and important phenomenon in both laboratory and astrophysical systems. Here, simulations of partially ionized magnetic reconnection with well-matched initial conditions are performed using both multi-fluid and fully-kinetic approaches. Despite similar initial conditions, the time-dependent evolution differs between the two models. In multi-fluid models, the reconnection rate locally obeys either a decoupled Sweet–Parker scaling, where neutrals are unimportant, or a fully coupled Sweet–Parker scaling, where neutrals and ions are strongly coupled, depending on the resistivity. In contrast, kinetic models show a faster reconnection rate that is proportional to the fully-coupled, bulk Alfvén speed, $v^*_A$. In this work, these differences are interpreted as the result of operating in different collisional regimes. Multi-fluid simulations are found to maintain $ν_{ni}L/v^*_A$ ≳1, where $ν_{ni}$ is the neutral–ion collision frequency and L is the time-dependent current sheet half-length. This strongly couples neutrals to the reconnection outflow, while kinetic simulations evolve to allow $ν_{ni}L/v^*_A$ <1, decoupling neutrals from the reconnection outflow. Differences in the way reconnection is triggered may explain these discrepancies.