Close-coupling Research Articles

Simulating the feedback between corrosive gas generation and water availability for the evaluation of radionuclide mobility in the context of radioactive waste disposal

Abstract. It has been recently recognized that the availability of liquid water may be a controlling factor in the feedback between the physical processes of variably saturated liquid and gas flow on the one hand, and various chemical processes such as metal corrosion in an underground storage facility for radioactive waste on the other hand (e.g., Huang et al., 2021, and reference therein). Iron corrosion in anoxic conditions produces hydrogen gas and consumes water, as expressed by the following stylized chemical equation (e.g., Diercks and Kassner, 1988; Senior et al., 2021): 3Fe+4H2O⟶Fe3O4+4H2 Since water is an educt the corrosion reaction may be suspended or suppressed by the scarcity of water near the corroding surfaces. At the same time, gas pressure build-up through hydrogen generation may limit further water ingress. We developed a model that focuses on the close coupling between gas generation through iron corrosion and water availability. The feedback between iron corrosion, gas generation and liquid phase flow is considered by implementing the corrosion reaction in the subsurface flow and transport simulator PFLOTRAN (Hammond et al., 2012; Lichtner et al., 2015, 2020) making use of its coding provisions to implement source/sink terms for water and gas. These source/sink terms reflect the kinetics of the iron corrosion and its dependence on the educts, where the availability of water is approximated by the local liquid saturation. The model was applied to evaluate the mobility of radionuclides in, and their release from a hypothetical geological storage facility for radioactive waste. The radionuclides are traced through the emplacement chambers and drift by means of advective and diffusive transport. Parameter variations illustrate the influence of crucial modelling parameters on the simulation results.

Knowledge Discovery by Analyzing the State of the Art of Data-Driven Fault Detection and Diagnostics of Building HVAC

The automated fault detection and diagnostics (AFDD) of heating, ventilation, and air conditioning (HVAC) using data mining and machine learning models have recently received substantial attention from researchers and practitioners. Various models have been developed over the years for AFDD of complete HVAC or its sub-systems. However, HVAC complexities, which partly have roots in its close coupling nature and interrelated dependencies, mean that understanding the relationship between faults and the suitability of the techniques remains an unanswered question. The literature analysis and interactive visualization of the data collected from the past implementation of AFDD models can provide useful insight to further explore this question by applying artificial intelligence (AI). Association rule mining (ARM) is deployed by this paper, using the frequent pattern (FP) growth algorithm to generate frequent fault sets for most common HVAC faults from the body of AFDD models developed in the literature to represent the status quo. A new model is developed for common HVAC faults and the techniques most frequently used to detect and diagnose them. A recommender system is developed using the ARM model to extract knowledge from the body of knowledge of HVAC data-driven AFDD in the form of rule-sets that reflect the associations. Findings of this review paper can significantly help civil and building engineers, as well as facility managers, in better management of building HVAC systems.

Species-specific coupling of tree-ring width and litter production in a temperate mixed forest

Tree growth is delineated into multiple processes, such as foliar growth, stem growth, and reproductive growth; however, only stem growth can store carbon in forests at a relatively long time scale. Understanding how these processes interact in response to climate change is of utmost importance for predicting the future carbon fixation ability of forests. However, it largely remains an unresolved question. To bridge this knowledge gap, we collected litter and tree-ring samples of two deciduous tree species, i.e. Larix principis-rupprechtii and Quercus liaotungensis, in a temperate mixed forest on Dongling Mountain in northern China. The influence of climate and the coupling characteristics between leaf/needle litter, fruit/cone litter, and tree-ring width (TRW) were analysed. The results highlighted that leaf/needle production was significantly and positively coupled with TRW for both species, but with one-year time lag for larch. Path analysis revealed that climate changes directly and significantly affected fruit production, which in turn indirectly affected TRW for oak trees, but such effect of cone production on TRW was not significant for larch trees. Additionally, we found that the radial growth of oak trees is more sensitive to drought stress than larch, possibly due to the close coupling between leaf biomass and TRW. Our results demonstrated that the coupling characteristics between different components of tree growth are species-specific, and understanding these relationships is of great significance for improving the tree growth model of forest ecosystems.

An overview of thermotransport in fluorite-related ionic oxides

Abstract In this overview, we summarize the phenomenon of thermotransport (the close coupling of mass transport and heat transport) in two fast ion conductors: yttria-doped zirconia and gadolinia-doped ceria. We focus on two recent molecular dynamics calculations using the Green-Kubo formalism. We show that the Onsager thermotransport cross coefficient (mass-heat coupling) is negative, meaning that oxygen ions would drift, in principle, to the hot side in a temperature gradient. Simulation results presented in this overview show reasonable agreement with available experimental data for thermal conductivity. Results of this study suggest that the coupling between mass and heat transport in oxygen ion electrolytes could have significant effect for practical applications.

Coupling between physical processes and biogeochemistry of suspended particles over the inner shelf mud in the East China Sea

This study examines how geochemical signals regarding the source and transformation in suspended particles are transported in the marine portion of the sediment dispersal system. In the source-to-sink sedimentary continuum of a world major river, the Changjiang (Yangtze) River, is used to demonstrate the close coupling between the marine physical processes and the geochemical signals carried by suspended particles. A sediment trap mooring configured with a non-sequential sediment trap, a downward-looking ADCP, CTD, LISST-100× were deployed for 29 days in the winter of 2014 off the coast of Zhejiang Province, China in water depth of 22.5 m. The mooring rendered two types of data. Physical processes included temporal changes of water depth, currents at 11 depths, temperature at two depths, and salinity at one depth. There was 15-cm accumulation of captured particles in the trap, which rendered the total mass flux of 233.3 g/cm2/day. The trap material was analyzed for grain-size composition, total 210Pb, minerals including mica/illite, kaolinite, chlorite, k-feldspar, plagioclase, quartz, and dolomite. Organic material (TOC, TN) and carbon isotope δ13C were also measured. The range of terrestrial fraction (Ft) of the trap material was between 45–60%. EOF analysis was used to examine the covariability in both data sets. For the physical data set, 37 variables were used in the analysis. For the sediment trap material, 15 variables were used. The EOF results of the physical processes indicate the tidal flow was the most important physical forcing for the transport of suspended particles and water masses that carried marine- and terrestrial-sourced particles. Wave and current combined resuspension entrained reworked sediment off the seabed, which was then transported landward or seaward. The most important covariability of the particle properties in the sediment trap was caused by hydrodynamic sorting that separated the clay from silt and sand sizes. Geochemical signals of the particles were carried by clay and the particle mass (dry weight) was associated with silt and sand. The temporal characteristics of the sorting show the spring-neap tidal cycle. The next major distinction was the contrast between terrestrial- and marine-sourced materials. The EOF analysis further distinguish contributions from the distal Changjiang River and proximal small rivers at the tertiary level of the covariability. The coverabilities in both data sets show close correspondence. Our findings give firm evidence to show marine processes dominated the transport of land-derived fluvial sediment and the incorporation of marine-sourced particles into the dispersal system. There is complexity in both physical processes and geochemical signals of suspended particles. However, our study points out the close coupling between the two.

An empirical model of electron temperatures in the Mars ionosphere based on Langmuir probe measurements in the descending phase of solar cycle 24

Mars ionospheric temperatures exhibit profound variability based on, for example, changes in solar irradiance, solar local time, season, and latitude. The close coupling between ionospheric temperatures and neutral thermospheric density is of even greater importance. To evaluate these effects and to quantify their contributions to electron temperature, we developed the Temperature of electrons Specification for the Mars Ionosphere (TeSMI). After identifying the strongest correlations between the model inputs and the observed electron temperatures, several additional corrections were examined and implemented. The primary source of climatological variability was related to neutral pressure, local solar time, and 17-22 nm irradiance. In addition to this, changes due to seasonal effects and latitude each required 5–10% of additional corrections. Evaluating the electron temperatures on which TeSMI is based provided an opportunity to study several relevant ionospheric phenomena. One of these is the solar cycle dependence of electron temperature which is found to be relatively small compared with other sources of variability. Solar minimum temperatures are on average 7–12% lower than those at solar maximum during solar cycle 24. The solar cycle dependence also appears stronger at aphelion than at other times. Furthermore, at Mars perihelion, electron temperatures seem to increase in response to a possible source of heating from the lower atmosphere. Furthermore, we identify cold and warm regions with respect to the TeSMI model that occur in specific aerographic locations. These regions of warmer and colder temperatures appear organized with respect to the crustal magnetic field locations at altitudes above 170 km. This is the first time that the effect of the crustal field is identified in the statistical electron temperature data below 200 km. Lastly, at the lowest altitudes (160–180 km) analyzed here, the equatorial ionosphere is colder than the polar regions by 5–15% which is interpreted to be a result of the atmospheric circulation pattern.

Discovery of complex oxides via automated experiments and data science

The quest to identify materials with tailored properties is increasingly expanding into high-order composition spaces, with a corresponding combinatorial explosion in the number of candidate materials. A key challenge is to discover regions in composition space where materials have novel properties. Traditional predictive models for material properties are not accurate enough to guide the search. Herein, we use high-throughput measurements of optical properties to identify novel regions in three-cation metal oxide composition spaces by identifying compositions whose optical trends cannot be explained by simple phase mixtures. We screen 376,752 distinct compositions from 108 three-cation oxide systems based on the cation elements Mg, Fe, Co, Ni, Cu, Y, In, Sn, Ce, and Ta. Data models for candidate phase diagrams and three-cation compositions with emergent optical properties guide the discovery of materials with complex phase-dependent properties, as demonstrated by the discovery of a Co-Ta-Sn substitutional alloy oxide with tunable transparency, catalytic activity, and stability in strong acid electrolytes. These results required close coupling of data validation to experiment design to generate a reliable end-to-end high-throughput workflow for accelerating scientific discovery.

Collisional excitation of methylene by molecular hydrogen

ABSTRACT Accurate estimates of the abundance of methylene (CH2) in the interstellar medium require knowledge of both the radiative and collisional rate coefficients for the transfer of population between rotational levels. In this work, time-independent quantum close coupling calculations have been carried out to compute rate coefficients for the (de-)excitation of ortho- and para-CH2 in collisions with ortho- and para-H2. These scattering calculations have employed a recently computed, high-quality potential energy surface, based on the coupled cluster level of theory [RCCSD(T)-F12a], for the interaction of CH2 in its ground $\tilde{X} ^3B_1$ electronic state with H2. The collisional rate coefficients were obtained for all fine-structure transitions among the first 22 and 24 energy levels of ortho- and para-CH2, respectively, having energies less than 277 cm−1. These rate coefficients are compared with previous calculated values, obtained by scaling data for CH2–He. In the case of ortho-CH2, whose levels display hyperfine structure, rate coefficients for transitions between hyperfine levels were also computed, by the MJ randomization approximation. Finally, some simple radiative transfer calculations are presented.

Accelerating the rate of discovery: toward high-repetition-rate HED science

As high-intensity short-pulse lasers that can operate at high-repetition-rate (HRR) (>10 Hz) come online around the world, the high energy density (HED) science they enable will experience a radical paradigm shift. The >103 increase in shot rate over today’s shot-per-hour drivers translates into dramatically faster data acquisition, more experiments, and the ability to exploit machine learning, and thus the potential to significantly accelerate the advancement of HED science. A wide range of HED experiments, from opacity investigations to secondary source generation to plasma nuclear physics, will benefit from the increased statistics, precision, and exploration of phase space. Besides increasing the rate at which scientific experiments can be performed, HRR also allows for the rapid delivery of optimal experiments supported by simulations and modeling augmented by close coupling to empirical data. To fully realize such an HRR framework, numerous subsystems must be developed and brought together, including feedback laser control loops, high-throughput targetry and diagnostics, cognitive simulation, enhanced HED codes, and advanced data analytics. This paper describes the vision for an integrated HRR laser experimental HED system and outlines some of the major considerations and challenges for realizing it.

Research on clearance model for electricity market with cascade hydropower stations

Together with power structural reform, the intended contribution target of carbon neutral and carbon peaking aims to promote the market-based consumption of renewable energy, which has become an essential task for the construction of China’s power market. Cascade hydropower is a special form of hydro-generation, the upstream and downstream power stations have a close hydraulic coupling relationship with each other. In order to ensure the fair participation of all generation entities in the market and improve the feasibility of the transaction results, the operational characteristics of the cascade hydropower should be integrated into the market clearance model. In this paper, a day-ahead market case including six generation entities is designed, and the rationality and practicality of the clearance model are verified by analyzing the results of market transaction in different operation scenarios.

Research on Data Gateway for Ship Based on Dynamic Adaptation

In view of the immature status of the old-fashioned ship information collection and data analysis system in inland rivers, after analyzing the characteristics of ship navigation information, the problem of low efficiency, inaccuracy and poor real-time information collection is solved. Starting from ship equipment (such as main engine, power station, control system, etc), a ship data acquisition gateway based on dynamic adaptation is designed. Based on the principle of making full use of the old system of marine equipment in the engine room, a multi-protocol data acquisition method based on an adaptive model is constructed, which realizes the separation of information acquisition and information use, eliminates all the close coupling relations between system equipment and applications, and realizes the integration of different data information on the ship and the dynamic display management function on the client.

Inelastic scattering of interstellar silyl cyanide (SiH3CN) by helium atoms : cross-sections and rate coefficients for A- and E-SiH3CN

ABSTRACT Rotational inelastic scattering of silyl cyanide (SiH3CN) molecule with helium (He) atoms is investigated. Three-dimensional potential energy surface (3D-PES) for the SiH3CN–He interacting system is carried out. The ab initio 3D-PES is computed using explicitly correlated coupled cluster approach with single, double, and perturbative triple excitation CCSD(T)-F12a connected to augmented-correlation consistent-polarized valence triple zeta Gaussian basis set. A global minimum at (R = 6.35 bohr; θ = 90○; ϕ = 60○) with a well depth of 52.99 cm−1 is pointed out. Inelastic rotational cross-sections are emphasized for the 22 first rotational levels for total energy up to 500 cm−1 via close coupling (CC) approach in the case of A-SiH3CN and for the 24 first rotational levels for total energy up to 100 cm−1 via CC and from 100 to 500 cm−1 via coupled states (CS) in the case of E-SiH3CN. Rate coefficients are derived for temperature until 80 K for both A- and E-SiH3CN–He systems. Propensity rules are obtained for |ΔJ| = 2 processes with broken parity for A-SiH3CN and for |ΔJ| = 2 processes with |ΔK| = 0 and unbroken parity for E-SiH3CN.

Coordination of plant hydraulic and photosynthetic traits: confronting optimality theory with field measurements.

Summary Close coupling between water loss and carbon dioxide uptake requires coordination of plant hydraulics and photosynthesis. However, there is still limited information on the quantitative relationships between hydraulic and photosynthetic traits.We propose a basis for these relationships based on optimality theory, and test its predictions by analysis of measurements on 107 species from 11 sites, distributed along a nearly 3000‐m elevation gradient.Hydraulic and leaf economic traits were less plastic, and more closely associated with phylogeny, than photosynthetic traits. The two sets of traits were linked by the sapwood to leaf area ratio (Huber value, v H). The observed coordination between v H and sapwood hydraulic conductivity (K S) and photosynthetic capacity (V cmax) conformed to the proposed quantitative theory. Substantial hydraulic diversity was related to the trade‐off between K S and v H. Leaf drought tolerance (inferred from turgor loss point, –Ψtlp) increased with wood density, but the trade‐off between hydraulic efficiency (K S) and –Ψtlp was weak. Plant trait effects on v H were dominated by variation in K S, while effects of environment were dominated by variation in temperature.This research unifies hydraulics, photosynthesis and the leaf economics spectrum in a common theoretical framework, and suggests a route towards the integration of photosynthesis and hydraulics in land‐surface models.

Wireless Signal Propagation Prediction Based on Computer Vision Sensing Technology for Forestry Security Monitoring.

In this paper, Computer Vision (CV) sensing technology based on Convolutional Neural Network (CNN) is introduced to process topographic maps for predicting wireless signal propagation models, which are applied in the field of forestry security monitoring. In this way, the terrain-related radio propagation characteristic including diffraction loss and shadow fading correlation distance can be predicted or extracted accurately and efficiently. Two data sets are generated for the two prediction tasks, respectively, and are used to train the CNN. To enhance the efficiency for the CNN to predict diffraction losses, multiple output values for different locations on the map are obtained in parallel by the CNN to greatly boost the calculation speed. The proposed scheme achieved a good performance in terms of prediction accuracy and efficiency. For the diffraction loss prediction task, 50% of the normalized prediction error was less than 0.518%, and 95% of the normalized prediction error was less than 8.238%. For the correlation distance extraction task, 50% of the normalized prediction error was less than 1.747%, and 95% of the normalized prediction error was less than 6.423%. Moreover, diffraction losses at 100 positions were predicted simultaneously in one run of CNN under the settings in this paper, for which the processing time of one map is about 6.28 ms, and the average processing time of one location point can be as low as 62.8 us. This paper shows that our proposed CV sensing technology is more efficient in processing geographic information in the target area. Combining a convolutional neural network to realize the close coupling of a prediction model and geographic information, it improves the efficiency and accuracy of prediction.

Poro-Viscoelastic Effects During Biomechanical Testing of Human Brain Tissue

Brain tissue is one of the softest tissues in the human body and the quantification of its mechanical properties has challenged scientists over the past decades. Associated experimental results in the literature have been contradictory as characterizing the mechanical response of brain tissue not only requires well-designed experimental setups that can record the ultrasoft response, but also appropriate approaches to analyze the corresponding data. Due to the extreme complexity of brain tissue behavior, nonlinear continuum mechanics has proven an expedient tool to analyze testing data and predict the mechanical response using a combination of hyper-, visco-, or poro-elastic models. Such models can not only allow for personalized predictions through finite element simulations, but also help to comprehensively understand the physical mechanisms underlying the tissue response. Here, we use a nonlinear poro-viscoelastic computational model to evaluate the effect of different intrinsic material properties (permeability, shear moduli, nonlinearity, viscosity) on the tissue response during different quasi-static biomechanical measurements, i.e., large-strain compression and tension as well as indentation experiments. We show that not only the permeability but also the properties of the viscoelastic solid largely control the fluid flow within and out of the sample. This reveals the close coupling between viscous and porous effects in brain tissue behavior. Strikingly, our simulations can explain why indentation experiments yield that white matter tissue in the human brain is stiffer than gray matter, while large-strain compression experiments show the opposite trend. These observations can be attributed to different experimental loading and boundary conditions as well as assumptions made during data analysis. The present study provides an important step to better understand experimental data previously published in the literature and can help to improve experimental setups and data analysis for biomechanical testing of brain tissue in the future.

Electron-impact excitation of the (4d105s)S1/22→(4d95s2)D3/22 and (4d105s)S1/22→(4d106s)S1/22 transitions in silver: Experiment and theory

We present angle-differential and angle-integrated cross sections for electron-impact excitation of the ($4{d}^{10}5s)\phantom{\rule{0.16em}{0ex}}^{2}S_{1/2}\ensuremath{\rightarrow}(4{d}^{9}5{s}^{2})\phantom{\rule{0.16em}{0ex}}^{2}D_{3/2}$ and $(4{d}^{10}5s)\phantom{\rule{0.16em}{0ex}}^{2}S_{1/2}\ensuremath{\rightarrow}(4{d}^{10}6s)\phantom{\rule{0.16em}{0ex}}^{2}S_{1/2}$ transitions in atomic silver. Experimental data for four incident electron energies between 10 and 60 eV are compared with predictions from our relativistic distorted wave (RDW) and nonrelativistic atomic optical potential models. Agreement between our measured and calculated data is only fair, although in the case of the RDW it is seen to improve with increasing incident electron energy. However, only for the $(4{d}^{10}6s)\phantom{\rule{0.16em}{0ex}}^{2}S_{1/2}$ excitation process, agreement of our measured data with earlier relativistic convergent close coupling results from McNamara et al. [J. Phys. B 51, 085203 (2018)] was, with a few exceptions, typically observed to be very good, to within the uncertainties on the data.

Bactericidal efficiency and photochemical mechanisms of micro/nano bubble–enhanced visible light photocatalytic water disinfection

Microbial contamination of water in the form of highly-resistant bacterial spores can cause a long-term risk of waterborne disease. Advanced photocatalysis has become an effective approach to inactivate bacterial spores due to its potential for efficient solar energy conversion alongside reduced formation of disinfection by-products. However, the overall efficiency of the process still requires significant improvements. Here, we proposed and evaluated a novel visible light photocatalytic water disinfection technology by its close coupling with micro/nano bubbles (MNBs). The inactivation rate constant of Bacillus subtilis spores reached 1.28 h−1, which was 5.6 times higher than that observed for treatment without MNBs. The superior performance for the progressive destruction of spores’ cells during the treatment was confirmed by transmission electron microscopy (TEM) and excitation-emission matrix (EEM) spectra determination. Experiments using scavengers of reactive oxygen species (ROSs) revealed that H2O2 and •OH were the primary active species responsible for the inactivation of spores. The effective supply of oxygen from air MNBs helped accelerate the hole oxidation of H2O2 on the photocatalyst (i.e. Ag/TiO2). In addition, the interfacial photoelectric effect from the MNBs was also confirmed to contribute to the spore inactivation. Specifically, MNBs induced strong light scattering, consequently increasing the optical path length in the photocatalysis medium by 54.8% at 700nm and enhancing light adsorption of the photocatalyst. The non-uniformities in dielectricity led to a high-degree of heterogeneity of the electric field, which triggered the formation of a region of enhanced light intensity which ultimately promoted the photocatalytic reaction. Overall, this study provided new insights on the mechanisms of photocatalysis coupled with MNB technology for advanced water treatment.

Rotational (de-)excitation of oxophosphine (HPO) by collision with helium (He)

Three Dimensional Potential Energy Surface (3D-PES) of HPO-He in Jacobi coordinates is mapped. The new 3D-PES is performed at explicitly correlated Coupled Cluster level of theory with Single, Double and perturbative Triple excitation (CCSD(T)-F12a) related to aug-cc-pVTZ basis set. The computed PES is joined into quantum dynamical calculations to treat HPO nuclear motions, where HPO is considered as a rigid rotator colliding with He atom. Cross-sections for advances among the 29 lowest rotational levels of HPO (up to JKaKc = 808) are computed using quantum mechanical Close Coupling (CC) approach for total energy up to 900 cm−1. Rate coefficients relevant to HPO-He colliding system are deduced for [5–100] K temperature range. The present determination of rate coefficients will be useful in studies of HPO in astrophysical medium.

Unprecedented pressure-driven metallization and topological charge transport in an anion radical salt

The hybrid inorganic/organic closed π-stacking and soft lattice of a copper anion radial (Copper-7,7,8,8-tetracyanoquinodimethane) renders its electrical conductivity and structural modifications, which are susceptible to temperature and pressure. The geometry of its metal-ligand construction contemplates the concept of topology with a charge-transfer instability. A pressure-induced ionic-neutral phase transition occurs and accompanies an anomalously large electrical conductivity, carries topological charges, and possesses a low energy gap smaller than the Coulomb gap. X-ray absorption spectroscopy of the metal establishes the high electrical conduction by the topological charges. X-ray diffraction and the first-principles calculations further suggest that the compression leads to an irreversible alteration in the metal coordination and rotation of the quinoid rings of the anion. The present observation demonstrates a close coupling of topological charges and lattice dynamics within a relatively low-pressure regime, which may expand a novel paradigm for the comprehensive topological charge transport phenomena including thermoelectric effects in future.

Joint inversion of Rayleigh wave ellipticity and phase velocity for crustal structure in Taiwan

The convergence between the Eurasian Plate and the Philippine Sea Plate results in rapid uplifting of the Taiwan Orogen. To study the mountain building in Taiwan, we present three transects of shear wave velocity across the Taiwan mountain belt with joint inversion of teleseismic Rayleigh wave H/V ratios and phase velocities derived from ambient noise tomography. The Particle Swarm Optimization algorithm is introduced into the joint inversion and is proved to be an efficient tool in solving the geophysical inverse problems. In determining the H/V ratios, cross-correlation techniques are used to reduce the non-great circle effects of the Rayleigh wave packets and to correct sensor misorientations. The cross-correlation techniques improve the accuracy of the H/V measurements, especially at the short periods. The observed up-to-middle crustal thickening in the central segment of the Central Range suggests lithospheric collision tectonism, whereas the lower crustal thickening in southern segment is proposed to be related to subduction of the Eurasian continental crust. In the north, however, no crust thickening is observed. The variations of the crust architecture along the axis of the Taiwan Orogen favor a close coupling relationship between mountain building and slab interactions in the mantle. Beneath the Central Range, the twist of the fate of the Eurasian continental crust from consumption in the south to collision in the central segment is proposed to be resulted from the slab breakoff beneath central Taiwan.