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At least 613 records · Page 34

Numerical and experimental analysis of precooled desiccant system

This paper presents a numerical and experimental study of four novel, desiccant air-conditioning systems based on pre-cooling of the ambient air. The purpose of the study is to: 1) establish which configuration is most profitable for the future studies through numerical and experimental methods; 2) verify the concept of precooled system and confirm that it is working in experimental conditions (for this purpose two prototypes of evaporative cooling units were developed and compared for different operation arrangements with desiccant wheel); 3) Analyze practical aspects of the systems, which includes water consumption analysis, economic analysis and establishing operational modes during a cooling season in temperate climate conditions (the proposed solution has a significant advantage during operation in a temperate climate, since it can utilize its first evaporative cooler the only source of cooling energy when the humidity of outdoor air allows to to meet the latent cooling load). Four arrangements of the system with different dew point evaporative air cooler prototypes were selected and developed for comparative analysis. The system was simulated as a whole, also, each component was individually tested on measurement station. develop the optimal arrangement of the system through numerical and experimental analysis. Four different performance indicators were considered: thermal COP (Coefficient Of Performance), the ERR (Energy Efficiency Ratio), coefficient a describing the potential in compensating indoor cooling loads, water consumption ratio. Also costs of the systems were compared through economic analysis. It was established that arrangement which is characterized by best-averaged performance in terms of all considered factors is a unit combined with two different types of evaporative coolers (marked as System B)- this is caused by the favorable arrangement of two units, where one is better suited to the pre-cooler role, while the other is better suited as the post-cooler.

42 ENGINEERING↗

Advancing Li-plating detection: Motivating a multi-signal correlation approach

Facilitating fast charging in lithium-ion batteries (LiBs) is often linked to Li-plating, which harms performance, longevity, and safety. Early detection of Li-plating is essential for rapid technological development and for preventing performance deterioration and ensuring safety during operation. Fast and real-time detection, using commonly collected measurements like voltage (V), current (I), temperature (T), and pressure (P), is highly desirable. Existing standalone methods relying on electrochemical and mechanical signatures, using half, smaller, or specially designed cells often operated at lower temperatures, fail to account for real-world fast-charging conditions. These signatures may also have inherent unreliability in aged LiBs, a phenomenon currently not-well understood. All these uncertainties have complicated practical implementation of a robust Li-plating detection technique. This study, through multiple case studies involving real-world fast-charging conditions using automotive-grade 11.6 Ah LiBs, shows that many single signal-based diagnostic techniques may be inadequate to detect Li-plating. Among various signatures, end-of-charge rest pressure, differential pressure-sensing, and end-of-charge rest voltage were identified as particularly useful in detecting Li-plating. Furthermore, A multi-signal-based detection technique is shown to be more robust in detecting Li-plating. Using both fresh and aged cells, the results and analysis highlight how detection capabilities are influenced by various factors, including battery design, size, charging speed, operating temperature, and degradation level. Adopting such a multi-signal Li-plating detection approach may be instrumental in the rapid development of battery technology in laboratories, as well as ensuring the enhanced safety of next-generation LiBs in real-world fast-charging applications.

25 ENERGY STORAGE↗

Toward practical issues: Identification and mitigation of the impurity effect in glyme solvents on the reversibility of Mg plating/stripping in Mg batteries

Reversible electrochemical magnesium plating/stripping processes are important for the development of high-energy-density Mg batteries based on Mg anodes. Ether glyme solutions such as monoglyme (G1), diglyme (G2), and triglyme (G3) with the MgTFSI 2 salt are one of the conventional and commonly used electrolytes that can obtain the reversible behavior of Mg electrodes. However, the electrolyte cathodic efficiency is argued to be limited due to the enormous parasitic reductive decomposition and passivation, which is governed by impurities. In this work, a systematic identification of the impurities in these systems and their effect on the Mg deposition–dissolution processes is reported. The mitigation methods generally used for eliminating impurities are evaluated, and their beneficial effects on the improved reactivity are also discussed. By comparing the performances, we proposed a necessary conditioning protocol that can be easy to handle and much safer toward the practical application of MgTFSI 2 /glyme electrolytes containing impurities.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Consistency and reproducibility in atomic layer deposition

Atomic layer deposition (ALD) is a thin film synthesis technique that can provide exquisite accuracy and precision in film thickness and composition even on complex, large area substrates. Based on self-limiting surface chemistry, ALD can be insensitive to process conditions and reactor designs, allowing an ALD process developed in one lab to be easily reproduced in other labs. In practice, however, ALD is sometimes difficult to reproduce or replicate, and the results can vary substantially between ALD reactors and between labs. This is exemplified by large deviations in reports on the growth of, e.g., Al2O3, FeOx, and TiO2 given the same precursors under similar conditions. Furthermore, the problem of irreproducibility seems to be growing as ALD is adopted by more researchers and integrated into new applications. In this article, the authors highlight some of the major sources of variations and errors and common misconceptions related to ALD. In particular, the authors focus on issues related to precursors, substrates, and deposition tools. The authors illustrate these problems through examples from the literature, and they present results from numerical simulations that describe how nonidealities would manifest in thickness profiles in a typical cross-flow reactor. They also describe how reproducibility in ALD is linked to consistent experimental practice and reporting between labs. The authors’ hope is that by educating newcomers to ALD and advocating for consistent reporting of deposition conditions, they can minimize irreproducibility and enable ALD practitioners to realize the full potential afforded by self-limiting surface chemistry.

36 MATERIALS SCIENCE↗

A noniterative improvement of Guyan reduction

In determining the natural modes and frequencies of a linear elastic structure, Guyan reduction is often used to reduce the size of the mass and stiffness matrices and the solution of the reduced system is obtained first. The reduced system modes are then expanded to the size of the original system by using a static transformation linking the retained degrees of freedom to the omitted degrees of freedom. In the present paper, the transformation matrix of Guyan reduction is modified to include additional terms from a series accounting for the inertial effects. However, the inertial terms are dependent on the unknown frequencies. A practical approximation is employed to compute the inertial terms without any iteration. This new transformation is implemented in NASTRAN using a DMAP sequence alter. Numerical examples using a cantilever beam illustrate the necessary condition for allowing a large number of additional terms in the proposed series correction of Guyan reduction. A practical example of a large model of the Plasma Motor Generator module to be flown on a Delta launch vehicle is also presented.

Ganesan, N.↗

A Combined CFD/Material Response Analysis of 3MDCP Arcjet Experiments

The Mars Sample Return Earth Entry System (MSR-EES) project has selected 3-D Woven Mid-Density Carbon Phenolic (3MDCP) as the baseline thermal protection system (TPS) material for the capsule that will return Martian soil samples to Earth sometime in the 2030’s. A series of experiments in the NASA Ames AHF and IHF arcjets will be used to characterize the performance of 3MDCP and to develop and refine material response models for it. The test objectives for these experiments include obtaining in-depth and surface temperature data, mass loss and surface recession measurements, and char depth measurements. To provided pre- and post-test support for the arcjet experiments, a combined CFD/material response was performed using the DPLR and Icarus code. Pre-and post-test analysis on the 3MDCP arcjet experiments was performed using the DPLR CFD and Icarus material response codes. The codes were not tightly coupled, but boundary condition data required by Icarus (e.g., heat transfer coefficients and surface pressures), were extracted from the CFD solutions. This poster shows comparisons between DPLR/Icarus and the experimental data taken during arcjet experiment AHF-348 where 4-inch diameter iso-q models made from 3MDCP were tested in the 12-inch nozzle of the AHF arcjet. This poster also includes a top-level overview of the CFD/material response arcjet simulation process. Best-practices for running CFD solutions of arcjet experiments including how to determine the inflow conditions for the CFD solution from the arc heater settings are discussed. The required inputs to the material response solver are presented, as well as a discussion of how they can be extracted from the CFD solution.

thermal protection systems↗

Condition monitoring of permanent magnet AC machines for all-electric transportation systems: State of the art

The current state of the art on emerging and efficient techniques for condition monitoring of permanent magnet (PM) alternating-current (AC) machines deployed in electric vehicle (EV) applications is presented. The discussion includes the most common and specific types of faults in PM motors, such as rotor demagnetisation and stator inter-turn faults, respectively. Fault indicators, such as voltage (v s ) and current (i s ) signals and machine signatures based on motor back electromotive force (EMF) (E B ) and magnetic flux (φ), are taken into account as a measuring quantity in diagnosing motor faults. Other signatures, including thermal analysis, acoustic noise, and vibrations, are also illustrated as some of the emerging techniques in estimating the performance of EV motors while under operations. In addition, various fault modelling methods, condition monitoring techniques, and comprehensive approaches applied in diagnosing the effect of machine faults during its incipient stages are illustrated. Since most of the fault diagnostic techniques discussed here include only machine-based quantities as fault indices/indicators, the provided solutions are therefore found to be more reliable and accurate for diagnosing the motor faults. This comprehensive review study is inclusive of the existing fault diagnostic techniques, which are currently employed in industrial and commercial practices, in addition to the new methodologies proposed by the authors. All the given condition monitoring schemes therefore seem significantly vital in estimating the state of health of PM AC machines while under operation in all-electric transportation systems.

33 ADVANCED PROPULSION SYSTEMS↗

Accelerating Climate Research and Action in Cities through Advanced Science-Policy-Practice Partnerships

Cities have become increasingly recognized as key sites for climate research and action. Recently, these efforts have been significantly advanced through science-policy-practice partnerships. The objective of this paper is to assess how these partnerships are structured, the research and action agenda that underpins them, and how this agenda is being articulated and implemented. The assessment also helps to define some of the conceptual and operational gaps faced by the science-policy-practice community and how they can be addressed. The work evaluates the critical conditions for promoting these advances including the definition and fulfillment of knowledge needs, the integration of different perspectives and approaches, establishment of pathways to finance the urban climate research and action community, and creation and promotion of new partnerships. The paper concludes with a series of strategies and recommendations for how targeted policy adjustments can accelerate and support the production of actionable knowledge and this integrated researcher-policymaker-practitioner community.

Climate research↗

Extremum seeking for optimal control problems with unknown time-varying systems and unknown objective functions

We consider the problem of optimal feedback control of an unknown, noisy, time-varying, dynamic system that is initialized repeatedly. Examples include a robotic manipulator which must perform the same motion, such as assisting a human, repeatedly and accelerating cavities in particle accelerators which are turned on for a fraction of a second with given initial conditions and vary slowly due to temperature fluctuations. In this paper, we present an approach that applies to systems of practical interest. The method presented here is model independent; does not require knowledge of the objective function; is robust to measurement noise; is applicable for any set of initial conditions; is applicable to simultaneously controlling an arbitrary number of parameters; and may be implemented with a broad range of continuous or discontinuous functions such as sine or square waves. For systems with convex cost functions we prove that our algorithm will produce controllers that approach the minimal cost. For linear systems we reproduce the cost minimizing linear quadratic regulator optimal controller that could have been designed analytically had the system and cost function been known. We demonstrate the effectiveness of the algorithm with simulation studies of noisy and time-varying systems.

42 ENGINEERING↗

Leaf water potential measurements using the pressure chamber: Synthetic testing of assumptions towards best practices for precision and accuracy

Leaf water potential (ψ leaf ), typically measured using the pressure chamber, is the most important metric of plant water status, providing high theoretical value and information content for multiple applications in quantifying critical physiological processes including drought responses. Pressure chamber measurements of ψ leaf (ψ leafPC ) are most typical, yet, the practical complexity of the technique and of the underlying theory has led to ambiguous understanding of the conditions to optimize measurements. Consequently, specific techniques and precautions diversified across the global research community, raising questions of reliability and repeatability. Here, we surveyed specific methods of ψ leafPC from multiple laboratories, and synthesized experiments testing common assumptions and practices in ψ leafPC for diverse species: (i) the need for equilibration of previously transpiring leaves; (ii) leaf storage before measurement; (iii) the equilibration of ψ leaf for leaves on bagged branches of a range of dehydration; (iv) the equilibration of ψ leaf across the lamina for bagged leaves, and the accuracy of measuring leaves with artificially ‘elongated petioles’; (v) the need in ψ leaf measurements for bagging leaves and high humidity within the chamber; (vi) the need to avoid liquid water on leaf surfaces; (vii) the use of ‘pulse’ pressurization versus gradual pressurization; and (viii) variation among experimenters in ψ leafPC determination. Based on our findings we provide a best practice protocol to maximise accuracy, and provide recommendations for ongoing species-specific tests of important assumptions in future studies.

54 ENVIRONMENTAL SCIENCES↗

The Effect of Information Feedback Upon Psychophysical Judgments

An analysis was made of the role of presentation schedules and information feedback on performance in a forced-choice signal detection task. The experimental results indicate that information feedback facilitates performance, but only for certain presentation schedules. The present study was designed to assess performance in a signal detection task under two conditions of information feedback. In the I-condition, S was told on each trial whether his detection response was correct or incorrect; in the !-condition S was given no feedback regarding the correctness of his response. The task involved a 2-response, forced-choice auditory detection problem. On each trial 2 temporal intervals were defined and S was required to report which interval he believed contained the signal; i. e., in one interval a tone burst in a background of white noise was presented, while the other interval contained only white noise. A trial will be denoted as s1 or s2, depending on whether the signal was embedded in the 1st or 2nd interval; the S's response will be denoted A1 or A2 to indicate which interval he reported contained the signal. The probability of an s1 trial will be denoted as y. In this study two values of y were used (.50 and.75) and, as indicated above, two conditions of information feedback. Thus there were 4 experimental conditions (501, · 50I, 751, 75I); each S was run under all 4 conditions. Method Gaussian noise was presented binaurally in S's headphones throughout a test session and the signal was a 1000-cps sinusoid tone; the tone was presented for 100 msec. including equal fall and rise times of 20 msec. The ratio of signal energy to noise power in a unit bandwidth was 2.9, and was constant throughout the study. The. S was seated before a stimulus display board. On each trial a red warning light was flashed for 100 msec. Two amber lights then came on successively each for 1 sec.; these lights defined the 2 observation intervals. The onset of the signal occurred 500 msec. after the onset of one of the observation intervals. After the second amber light went off, S indicated his response by pressing 1 of 2 wand switches under cards reading "1st interval" and "2nd interval." For the !-condition a green light flashed on above the correct response key after S's response; the green light was omitted in the !-condition. Each trial lasted 6 sec. The S's were 12 male college students with normal hearing. They were run for two practice sessions followed by 20 test sessions. Test sessions were run on consecutive days, 350 trials/day. Each day S ran on 1 of the 4 experimental conditions; in successive 4-day blocks S ran one day on each of the 4 experimental conditions in a random order. Thus, over 20 days each of the experimental conditions was repeated 5 times.

Atkinson, Richard C.↗

Role of Dynamic Nucleation at Moving Boundaries in Phase and Microstructure Selection

Solidification microstructures that form under steady-state growth conditions (cells, dendrites, regular eutectics, etc.) are reasonably well understood in comparison to other, more complex microstructures, which form under intrinsically non-steady-state growth conditions due to the competition between the nucleation and growth of several phases. Some important practical examples in this latter class include microstructures forming in peritectic systems in highly undercooled droplets, and in strip cast stainless steels. Prediction of phase and microstructure selection in these systems has been traditionally based on (1) heterogeneous nucleation on a static interface, and (2) comparing the relative growth rate of different phase/microstructures under steady-state growth conditions. The formation of new phases, however, occurs via nucleation on, or ahead of, a moving boundary. In addition, the actual selection process is controlled by a complex interaction between the nucleation process and the growth competition between the nuclei and the pre-existing phase under non-steady-state conditions. As a result, it is often difficult to predict which microstructure will form and which phases will be selected under prescribed processing conditions. This research addresses this critical role of nucleation at moving boundaries in the selection of phases and solidification microstructures through quantitative experiments and numerical modeling in peritectic systems. In order to create a well characterized system in which to study this problem, we focus on the directional solidification of hypo- and hyper-peritectic alloys in the two-phase region, imposing a large enough ratio of temperature gradient/growth rate (G/V(sub p)) to suppress the morphological instability of both the parent (alpha) and peritectic (Beta) phases, i.e. each phase alone would grow as a planar front. Our combined experimental and theoretical results show that, already in this simplified case, the growth competition of these two phases leads to a rich variety of microstructures that depend sensitively upon the relative importance of nucleation, diffusion, and convection.

Karma, Alain↗

Modelling the Effects of Wetland Restoration on Coastal Hydrology: A Case Study of Elkhorn Slough Watershed, California

ABSTRACT Coastal wetlands, some of the most productive ecosystems on Earth, provide critical ecosystem services, including support of biodiversity, carbon sequestration and flood protection. In recent decades, these ecosystems have experienced extensive coastal wetland loss. Coastal wetland restoration provides a beacon of hope, offering a chance to reclaim these important habitats. However, even with billions of dollars invested worldwide in restoring coastal wetlands, we still lack comprehensive knowledge about the effectiveness of these restoration efforts in recovering wetland ecosystem functions and how future climate change may affect these efforts. The ability to evaluate how these ecosystems will function in the future is vital for examining current investments and developing future protection and management plans. We selected Elkhorn Slough, a tidal estuary, in California, to investigate the impact of wetland restoration and sea level rise (SLR) on coastal hydrology using the process‐based coastal hydrologic model, Advanced Terrestrial Simulator (ATS), informed by site‐specific data. We designed a novel modelling workflow for incorporating wetland restoration features into land cover and soil properties for the model parameterization. The validation results demonstrate a strong agreement between modelled and observed data. We studied the characteristics of coastal watershed hydrology, then focused on the surface water dynamics at two wetland sites within Elkhorn Slough, a reference site and a restored site. Our simulation results indicate that the restored site successfully maintains surface elevation, resulting in reduced surface inundation. We also examined the impact of wetland restoration under expected SLR over the next few decades. The low‐lying Yampah Marsh, the reference site, is likely to be inundated due to future SLR when highest tides arrive, while a higher percentage of Hester Marsh, the restored site, would retain marsh vegetation in coming decades, regardless of tidal conditions. Our study provides important information for examining the outcome of restoration practices that include surface elevation in tidal wetlands under climate changes.

advanced terrestrial simulator↗

Dynamic data-driven multiscale modeling for predicting the degradation of a 316L stainless steel nuclear cladding material

Here, we have developed a long short-term memory stacked ensemble (LSTM-SE) surrogate modeling approach that can provide rapid predictions of microstructural evolution and the resultant mechanical properties of American Iron and Steel Institute (AISI) 316L series stainless steel (316LSS) fuel cladding under conditions of varying temperature and radiation dose rate. To acquire training data, we developed and implemented a kinetic Monte Carlo (KMC) model to simulate precipitation kinetics of M 23 C 6 , γ', and G phases within SS316L cladding. Experimentally reported precipitation kinetics of SS316L in literature were linked to the kinetic parameters of the simulated precipitation in our KMC model. The model was then used to simulate microstructure evolution under synthetically generated treatments of varying temperature and radiation dose rate, for periods of up to 3000 hours. Changes in volume fraction, number density, and particle size of precipitates were recorded, and particle area fractions were correlated using statistical methods to develop the surrogate model. Simultaneously, the mechanical properties of the simulated microstructures were evaluated using microstructure-based finite element method (FEM) analysis to determine the elastic modulus, yield stress, ultimate tensile strength, and elongation to failure of the aged microstructures. Using this approach, our surrogate model can predict precipitation behavior within 0.25% volume fraction and mechanical properties within 6% relative error from the values predicted by the KMC and FEM models using 50 training simulations as input. The trained recurrent neural network-based model can return estimations of precipitation kinetics and mechanical properties ~1000 times faster than the physics-based codes. This work demonstrates, as a proof of concept, that reactor material service lifetimes under variable service conditions can be predicted for a statistics-based model from a practicably obtainable dataset.

36 MATERIALS SCIENCE↗

Hydrodynamic modeling of plasma channel systems for laser plasma accelerators

Structured plasma channels are an essential technology for driving high-gradient, plasma-based acceleration and control of electron and positron beams for advanced concepts accelerators. Laser and gas technologies can permit the generation of long plasma columns known as hydrodynamic, optically-field-ionized (HOFI) channels, which feature low on-axis densities and steep walls. By carefully selecting the background gas and laser properties, one can generate narrow, tunable plasma channels for guiding high intensity laser pulses. Here, we present on the development of simulations of HOFI channels using the FLASH code, a publicly available radiation hydrodynamics code. We explore sensitivities of the channel evolution to laser profile, intensity, and background gas conditions, and identify relevant scalings with laser intensity through a range of practical channel delays.

Accelerators↗

Micro-structural features and material properties impact on adhesive metal joints via computational modeling and machine learning

The quality of structural bonding in practical applications depends on various factors arising from materials, pre-processing conditions, and manufacturing. Understanding how these factors influence bonding performance and determining their relative importance are of significant interest. Thus, this study evaluates the effects of microstructural features and material properties on the structural strength of adhesively-bonded metal joints at the submillimeter scale, utilizing a combination of Finite Element Modeling (FEM) and Machine Learning (ML) with Gradient Boosting Regression (GBR). The microstructural features include adhesive thickness, internal voids within the adhesive, adherend-adhesive interfacial voids, void size and volume fraction, and surface roughness. The material properties include the constitutive behavior of the adhesive, as well as the adherend-adhesive interfacial strength and fracture energy. The changes in structural strength and morphologies of the bonded metal structures with respect to different microstructural features and material properties were clarified by FEM. By further leveraging ML-GBR, the sequence of importance of these factors affecting bonding performance across various scenarios was summarized. This work provides valuable insights into the development of improved structural bonding for adhesive joints in industries such as automotive , aerospace, and beyond.

36 MATERIALS SCIENCE↗

Generalized Quantum Signal Processing

Quantum signal processing (QSP) and quantum singular value transformation (QSVT) currently stand as the most efficient techniques for implementing functions of block-encoded matrices, a central task that lies at the heart of most prominent quantum algorithms. However, current QSP approaches face several challenges, such as the restrictions imposed on the family of achievable polynomials and the difficulty of calculating the required phase angles for specific transformations. In this paper, we present a generalized quantum signal processing (GQSP) approach, employing general SU(2) rotations as our signal-processing operators, rather than relying solely on rotations in a single basis. Our approach lifts all practical restrictions on the family of achievable transformations, with the sole remaining condition being that | P | ≤ 1 , a restriction necessary due to the unitary nature of quantum computation. Furthermore, GQSP provides a straightforward recursive formula for determining the rotation angles needed to construct the polynomials in cases where P and Q are known. In cases where only P is known, we provide an efficient optimization algorithm capable of identifying in under a minute of GPU time, a corresponding Q for polynomials of degree on the order of 10 7 . We further illustrate GQSP simplifies QSP-based strategies for Hamiltonian simulation, offer an optimal solution to the ϵ -approximate fractional query problem that requires O ( ( 1 / δ ) + log ( 1 / ϵ ) ) queries to perform where O ( 1 / δ ) is a proved lower bound, and introduces novel approaches for implementing bosonic operators. Moreover, we propose a novel framework for the implementation of normal matrices, demonstrating its applicability through synthesis of diagonal matrices, as well as the development of a new algorithm for convolution through synthesis of circulant matrices using only O ( d log N + log 2 N ) 1 and 2-qubit gates for a filter of lengths d . Published by the American Physical Society 2024

Motlagh, Danial↗

Data-model files associated with the manuscript "Modeling the Effects of Wetland Restoration on Coastal Hydrology: A Case Study of Elkhorn Slough Watershed, California"

This package contains the data, simulation setups, notebooks and figures used in “Modeling the Effects of Wetland Restoration on Coastal Hydrology: A Case Study of Elkhorn Slough Watershed, California” (Xu et al., 2025). In this study, we selected Elkhorn Slough, a tidal estuary, in California, to investigate the impact of wetland restoration and sea level rise on coastal hydrology using the process-based coastal hydrologic model, Advanced Terrestrial Simulator (ATS), informed by site-specific data. We designed a novel modeling workflow for incorporating wetland restoration features into land cover and soil properties for the model parameterization. The validation results demonstrate a strong agreement between modeled and observed data. We studied the characteristics of coastal watershed hydrology, then focused on the surface water dynamics at two wetland sites within Elkhorn Slough, a reference site and a restored site. Our simulation results indicate that the restored site successfully maintains surface elevation, resulting in reduced surface inundation. We also examined the impact of wetland restoration under expected sea level rise over the next few decades. The low-lying Yampah Marsh, the reference site, is likely to be inundated due to future sea level rise when highest tides arrive; while a higher percentage of Hester Marsh, the restored site, would retain marsh vegetation in coming decades, regardless of tidal conditions. Our study provides important information for examining the outcome of restoration practices that include surface elevation in tidal wetlands under climate changes.Several files can be found from this data package.1. README.md: This file describes the title, journal, co-authors, abstract, repository structure and model version.2. Simulation_Setups.zip: The file contains the model configuration files (XML format) for ATS. 3. Notebooks.zip: The file contains the Jupyter notebooks for generating the pre- and post-restoration meshes and the meshes of future scenarios. 4. Figures.zip: The file contains the figures used in the manuscript.5. Data.zip: The file contains the data used to drive the model simulations, including watershed and wetlands boundaries, mesh files and references to additional datasets (e.g., meteorological forcing, tidal dataset, DEMs, land cover, soil properties). Also, it contains water level observations at the restored wetland.

54 ENVIRONMENTAL SCIENCES↗