Condensation Scheme Research Articles

Exploring chemical reactivity through a combined conceptual DFT and ELF topology approach.

In a proof-of-concept study, we explore how a combined approach using the topology of the electron localization function (ELF) and the condensed dual descriptor (DD) function can guide the optimal orientation between reactants and mimic the potential energy surfaces of molecular systems at the beginning of the chemical pathway. The DD has been chosen for its ability to evaluate the regioselectivity of neutral and soft species and to potentially mimic the interaction energy obtained from the mutual interactions between nucleophilic and electrophilic regions of the building blocks under perturbative theory. Our method has been illustrated with examples in which the optimal orientation of several systems can be successfully identified. The limitations of the presented model in predicting chemical reactivity are outlined in particular the influence of the selected condensation scheme.

Large-ensemble simulations of the North American and Greenland ice sheets at the Last Glacial Maximum with a coupled atmospheric general circulation–ice sheet model

Abstract. The Last Glacial Maximum (LGM) was characterised by huge ice sheets covering the Northern Hemisphere, especially over North America, and by its cold climate. Previous authors have performed numerical simulations of the LGM to better understand coupled climate–ice sheet systems. However, the results of such simulations are sensitive to many model parameters. Here, we perform a 200-member ensemble of simulations of the North American and Greenland ice sheets and climate of the LGM with a coupled ice sheet–atmosphere–slab ocean model (FAMOUS-BISICLES) to explore sensitivities of the coupled climate–ice system to 16 uncertain parameters. In the ensemble of simulations, the global mean surface temperature is primarily controlled by the combination of parameters in the large-scale condensation scheme and the cumulus convection scheme. In simulations with plausible LGM global mean surface temperatures, we find that the albedo parameters have only a small impact on the Greenland ice volume due to the limited area of surface ablation associated with the cold climate. Instead, the basal sliding law controls the ice volume by affecting ice transport from the interior to the margin. On the other hand, like the Greenland ice sheet in future climate change, the LGM North American ice sheet volume is controlled by parameters in the snow and ice albedo scheme. Few of our simulations produce an extensive North American ice sheet when the global temperature is above 12 °C. Based on constraints on the LGM global mean surface temperature, the ice volume and the southern extent of the North American ice sheet, we select 16 acceptable simulations. These simulations lack the southern extent of ice compared to reconstructions, but they show reasonable performance on the ice sheet configuration and ice streams facing Baffin Bay and the Arctic Ocean. The strong sensitivities of the North American ice sheet to albedo at the LGM may imply a potential constraint on the future Greenland ice sheet by constraining the albedo schemes.

Emulation of Cloud Microphysics in a Climate Model

AbstractWe present a machine learning based emulator of a microphysics scheme for condensation and precipitation processes (Zhao‐Carr) used operationally in a global atmospheric forecast model (FV3GFS). Our tailored emulator architecture achieves high skill (≥94%) in predicting condensate and precipitation amounts and maintains low global‐average bias (≤4%) for 1 year of continuous simulation when replacing the Fortran scheme. The stability and success of this emulator stems from key design decisions. By separating the emulation of condensation and precipitation processes, we can better enforce physical priors such as mass conservation and locality of condensation, and the vertical dependence of precipitation falling downward, using specific network architectures. An activity classifier for condensation imitates the discrete‐continuous nature of the Fortran microphysics outputs (i.e., tendencies are identically zero where the scheme is inactive, and condensate is zero where clouds are fully evaporated). A temperature‐scaled conditional loss function ensures accurate condensate adjustments for a high dynamic range of cloud types (e.g., cold, low‐condensate cirrus clouds or warm, condensate‐rich clouds). Despite excellent overall performance, the emulator exhibits some deficiencies in the uppermost model levels, leading to biases in the stratosphere. The emulator also has short episodic skill dropouts in isolated grid columns and is computationally slower than the original Fortran scheme. Nonetheless, our challenges and strategies should be applicable to the emulation of other microphysical schemes. More broadly, our work demonstrates that with suitable physically motivated architectural choices, ML techniques can accurately emulate complex human‐designed parameterizations of fast physical processes central to weather and climate models.

Simulation of Present Day Climate with Climate Model INMCM60

Simulation of present day climate with a new version of climate model developed in INM RAS is considered. The model differs from a previous version by the change in cloudiness and condensation scheme, that leads to higher sensitivity to CO2 increase. The changes are included also in calculation of aerosol evolution, land snow, atmospheric boundary layer parameterizations and other blocks. The model is capable to reproduce near surface air temperature, precipitation, sea level pressure, cloud radiation forcing and other parameters better than previous version. The largest improvement can be seen in simulation of temperature in tropical troposphere, polar tropopause, and surface temperature in the Southern ocean. Simulation of climate changes in 1850–2021 by two model versions is considered.

Evaluation of a modernization project of the main condensate scheme at CHP-10 power unit No. 5 using its customized simulation model

We investigate the effect of modernizing the main condensate scheme applied at the power unit No.5, CHP-10 of Baikal Energy Company LLC, on its energy and economic efficiency using a customized simulation model. Simulation modelling was carried out in the Machine Program Building System software environment. The constructed model was verified using the results of measuring control parameters in several operating modes according to a three-stage procedure of verifying the mathematical models of complex thermal power units. We propose an original approach to modernizing the main condensate thermal scheme at the power unit under study in order to reduce the specific fuel consumption for balance-of-plant needs. The idea was to expand the main condensate scheme by including an additional sealing pump to the feedwater electric pumps of the 1Кs-20-110 unit in order to avoid the incorrect selection of condensate pumps. The study showed that the redistribution of the main condensate flow between the existing condensate pumps and the proposed 1Ks-20-110 sealing pump leads to a reduction in the specific fuel consumption for the electric energy generation to 0.32 g of fuel per kWh across the range of electrical loads from 137 to 150 mW. As a result, the net efficiency of the power unit can be raised by 0.03%. It should be noted that the proposed modernization project may reduce the consumption of electricity for balance-of-plant needs when the feedwater electric pump is switched to the standby mode during an emergency shutdown of the power unit. Based on the performed energy and economic calculations, energy savings for the period of 2019 comprise 82,653 kWh, while the total annual savings are estimated at 78,030 rubles. Thus, the conducted research demonstrates the high efficiency of applying simulation modelling in the study and optimization of existing thermal power plants.

Newly Developed Multiparameter Bulk Cloud Schemes. Part I: A New Triple-Moment Condensation Scheme and Tests

Abstract Double-moment schemes cannot accurately describe the evolution of the cloud droplet spectrum during condensation. Hence, a new triple-moment condensation scheme is developed to describe the evolution of cloud droplet spectra. In this scheme, a three-parameter gamma distribution function of the cloud droplet mass is adopted, and the prognostic equations of the spectral shape parameter and slope parameter are derived by means of the number concentration, cloud water content, and reflectivity factor of cloud droplets. The new parameterization scheme is compared with high-resolution Lagrangian and Eulerian bin schemes, double-moment schemes, and existing triple-moment schemes by performing simulations under different supersaturation values. The new scheme can reduce the cloud spectral error in the cloud water content and reflectivity factor caused by the fixed shape parameter in some bulk schemes. The spectra simulated with the new scheme match the Lagrangian analytical solutions well, with errors within approximately 1% in the cloud water content and reflectivity factor. The effects of curvature and solution on condensation growth are also tested using the new scheme, and a method of using multiple gamma distribution functions to characterize the multimodal spectrum of cloud droplets is proposed in the new condensation scheme. Ultimately, the formation of rain embryos from giant aerosols can be simulated via the new scheme.

Stable Numerical Implementation of a Turbulence Scheme with Two Prognostic Turbulence Energies

Abstract In this paper, we present a new and more stable numerical implementation of the two-energy configuration of the Third Order Moments Unified Condensation and N-dependent Solver (TOUCANS) turbulence scheme. The original time-stepping scheme in TOUCANS tends to suffer from spurious oscillations in stably stratified turbulent flows. Because of their high frequency, the oscillations resemble the so-called fibrillations that are caused by the coupling between turbulent exchange coefficients and the stability parameter. However, our analysis and simulations show that the oscillations in the two-energy scheme are caused by the usage of a specific implicit–explicit temporal discretization for the relaxation terms. In TOUCANS, the relaxation technique is used on source and dissipation terms in prognostic turbulence energy equations to ensure numerical stability for relatively long time steps. We present both a detailed linear stability analysis and a bifurcation analysis, which indicate that the temporal discretization is oscillatory for time steps exceeding a critical time-step length. Based on these findings, we propose a new affordable time discretization of the involved terms that makes the scheme more implicit. This ensures stable solutions with enough accuracy for a wider range of time-step lengths. We confirm the analytical outcomes in both idealized 1D and full 3D model experiments. Significance Statement The vertical turbulent transport of momentum, heat, and moisture has to be parameterized in numerical weather prediction models. The parameterization typically employs nonlinear damping equations, whose numerical integration can lead to unphysical, time-oscillating solutions. In general, a presence of such numerical noise negatively affects the model performance. In our work, we address numerical issues of the recently developed scheme with two prognostic turbulence energies that have more realism and physical complexity. Specifically, we detect, explain, and design a numerical treatment for a new type of spurious oscillations that is connected to the temporal discretization. The treatment suppresses the oscillations and allows us to increase the model time step more than 4 times while keeping an essentially non-oscillatory solution.

Reconciling the contour-improved and fixed-order approaches for τ hadronic spectral moments. Part I. Renormalon-free gluon condensate scheme

We propose a simple and easy-to-implement scheme for a renormalon-free gluon condensate (GC) matrix element, which is analogous to implementations of short-distance heavy-quark mass renormalization schemes existing in the literature already for a long time. Because the scheme is based on a perturbative subtraction at the level of the matrix element, with a freely adaptable infrared factorization scale, it can be implemented with little effort for any observable where the GC is relevant. The scheme depends on the renormalon norm of the GC which has to be supplemented independently. We apply the scheme to the fixed-order (FOPT) and contour-improved (CIPT) perturbative expansions of τ hadronic spectral function moments. These expansions exhibit a long-standing discrepancy for moments used in high-precision determinations of the strong coupling in the commonly used GC scheme that is not renormalon-free. We show that the scheme is capable of resolving the FOPT-CIPT discrepancy problem. At the same time, the perturbative behaviour of the moments that previously showed bad convergence properties and for which the non-perturbative corrections from the GC are sizeable, is substantially improved. The new GC scheme may provide a powerful theoretical tool for future phenomenological applications.

The FastEddy® Resident‐GPU Accelerated Large‐Eddy Simulation Framework: Moist Dynamics Extension, Validation and Sensitivities of Modeling Non‐Precipitating Shallow Cumulus Clouds

AbstractHerein we describe the moist dynamics formulation implemented within the graphics processing unit‐resident large‐eddy simulation FastEddy® model, which includes a simple saturation adjustment scheme for condensation and evaporation processes. Two LES model intercomparison exercises for non‐precipitating shallow cumulus clouds are simulated in order to validate this model extension, including a static forcing and a time‐dependent forcing case. Overall, we find our dynamical, thermodynamical and microphysical quantities, along with turbulence variability and fluxes, to be commensurate with the corresponding model intercomparison results. In addition, sensitivities to specific model settings are investigated. Among these settings, it is shown that boundary layer and cloud layer structure and characteristics are sensitive to use of higher‐order advection schemes impacting the vertical distribution of cloud content and associated turbulence statistics. Increasing the timescale of the saturation scheme leads to enhanced liquid water presence and decreases vertical velocity variance within the cloud deck. In some cases, these sensitivities agree with the model‐to‐model variability reported in the intercomparison exercises, highlighting the important role of specific model implementation choices in the context of shallow cumulus convection simulations. These analyses and findings also provide the basis for future extensions and applications of FastEddy® for modeling moist convection and precipitation scenarios.

Reconciling the FOPT and CIPT Predictions for τ Hadronic Spectral Function Moments

Recently it has been clarified by Hoang and Regner that the longstanding discrepancy between the CIPT and FOPT expansion approaches in αs determinations from the τ hadronic spectral function moments has been caused by an inconsistency of CIPT with the standard OPE approach. This inconsistency arises in the presence of IR renormalons in the underlying Adler function and is numerically dominated by the dimension-4 gluon condensate renormalon. In this talk we report on an approach to reconcile the CIPT based on a perturbative definition of a renormalon-free and scale-invariant gluon condensate scheme, called RF GC scheme. The scheme implies perturbative subtractions which eliminate the CIPT inconsistency for all practical applications of the τ hadronic spectral function moments. The scheme depends on the gluon condensate renormalon norm Ng as an independent input and on an IR subtraction scale R. We discuss three different approaches to determine Ng which yield consistent results and we apply the RF GC scheme in two full-fledged phenomenological αs determinations based on the truncated OPE and the duality violation model approach. In the RF GC scheme the long-standing CIPT-FOPT discrepancy problem is gone and the CIPT and FOPT αs determinations can be consistently combined.

A Comparative Study of Atmospheric Chemistry with VULCAN

Abstract We present an update of the open-source photochemical kinetics code VULCAN to include C–H–N–O–S networks and photochemistry. The additional new features are advection transport, condensation, various boundary conditions, and temperature-dependent UV cross sections. First, we validate our photochemical model for hot Jupiter atmospheres by performing an intercomparison of HD 189733b models between Moses et al., Venot et al., and VULCAN, to diagnose possible sources of discrepancy. Second, we set up a model of Jupiter extending from the deep troposphere to upper stratosphere to verify the kinetics for low temperature. Our model reproduces hydrocarbons consistent with observations, and the condensation scheme successfully predicts the locations of water and ammonia ice clouds. We show that vertical advection can regulate the local ammonia distribution in the deep atmosphere. Third, we validate the model for oxidizing atmospheres by simulating Earth and find agreement with observations. Last, VULCAN is applied to four representative cases of extrasolar giant planets: WASP-33b, HD 189733b, GJ 436b, and 51 Eridani b. We look into the effects of the C/O ratio and chemistry of titanium/vanadium species for WASP-33b, we revisit HD 189733b for the effects of sulfur and carbon condensation, the effects of internal heating and vertical mixing (K zz) are explored for GJ 436b, and we test updated planetary properties for 51 Eridani b with S8 condensates. We find that sulfur can couple to carbon or nitrogen and impact other species, such as hydrogen, methane, and ammonia. The observable features of the synthetic spectra and trends in the photochemical haze precursors are discussed for each case.

An innovative virtual trial misalignment approach for identification of unbalance, sensor and active magnetic bearing misalignment along with its stiffness parameters in a magnetically levitated flexible rotor system

A model-based identification algorithm derived from an innovative virtual trial misalignment (VTM) strategy is developed to identify the rotor unbalance, active magnetic bearings (AMBs) residual misalignment and their displacement and current stiffness parameters. The VTM approach is aligned with the similar concept of trial unbalance utilized in balancing of the rotor. This virtual method for providing the trial misalignment to the rotor is more reliable and effective than the physical trial misalignment, as the method does not need test runs and a precise model of the rotor-sensor-bearing system. The mathematical modelling for the non-contact displacement sensors offset from the rotor center has also been presented and even the offset amounts are identified using this novel approach. To illustrate the proposed methodology, an unbalanced and misaligned flexible rotor system mounted on multiple AMBs has been considered. Non-collinearity between the rotor operating axis and the axis of supported AMBs is the prime cause of misalignment (combination of parallel and angular) fault. A finite element method with a gyroscopic dynamic condensation scheme is employed for acquiring the reduced form of system equations. The numerically generated frequency domain responses are further employed in the identification algorithm for estimating the rotor-AMB system and faults parameters. Besides this, the different levels of the random noise signal as well as rotor modelling errors are added in the developed VTM based methodology to check its efficacy and sensitiveness in a practical rotor model.

Integrated cloud macro- and micro-physics schemes with kinetic treatment of condensation processes for global models

A new parameterization scheme was developed to remove the saturation adjustment assumption and resolve the condensation process in the grid-scale cloud macrophysics scheme to build an integrated cloud microphysics scheme for global climate models. By applying a saturation prediction equation with calculations based on cloud hydrometeor properties, supersaturation or subsaturation can be determined within the macrophysics scheme. This treatment provides the basis for condensation calculation and allows the Wegener–Bergeron–Findeisen process to be resolved explicitly to render a realistic liquid–ice partition in mixed-phase clouds. The cloud fraction scheme was modified based on physics principles to complement the condensation scheme. The new scheme's performance was examined by incorporating it into the Community Atmosphere Model version 5 (CAM5) single-column model to simulate a Tropical Warm Pool–International Cloud Experiment (TWP–ICE) case. The results revealed that grid-scale cloud properties are sensitive to the condensation process's treatment, and the new scheme can produce a more reasonable cloud fraction and liquid–ice partition than the original CAM5. The theory-based scheme developed in this study may provide insight for addressing consistency between the macrophysical and microphysical schemes in global climate models.

Advanced extreme learning machine‐based ensemble classification scheme with enhanced data perturbation for human DNA sequences

AbstractThe dramatic growth in machine learning has brought in significant features and quantified non‐linear associations in the data derived from sensitive medical datasets. The data should be preserved without influencing the associated classifications by applying a robust, effective and reliable data perturbation technique before enforcing ensemble classification. In this paper, an Integrated Condensation Scheme imposed Privacy Preserving Rotation‐based Data Perturbation and Ensemble Classification (ICS‐PPR‐DPEC) is proposed for ensuring privacy of such sensitive data. Condensation Algorithm‐based Data Perturbation is used for constructing homogenous groups determined from the distance between tuples. It also generates a rotation matrix for conducting perturbation that ensures higher data sensitivity protection before it is sent for classification. Advanced Extreme Learning Machine‐based Ensemble Classification Scheme includes kernel, norm‐optimized and regularized Extreme Learning Machine (ELM)‐based classifiers for attaining predominant classification accuracy in identifying human DNA sequences. This approach facilitates classification by constructing ensembles which are trained through randomly resampled ELM classifiers. It includes an objective function that systematically improves the accuracy and diversity among resulting ensembles. The experimental results of the proposed ICS‐PPR‐DPEC are found to be excellent in terms of classification Accuracy, Precision, Recall, and Kappa statistic when compared to the benchmarked techniques.

Numerical simulations of arbitrary evolving cracks in geotechnical structures using the nonlinear augmented finite element method (N-AFEM)

This paper presents an integrated numerical algorithm based on the nonlinear augmented finite element method (N-AFEM) to accurately simulate the arbitrary evolving strong discontinuities (cracks/slip lines) and failure behaviors in geotechnical structures. A novel nonlinear elemental augmentation and condensation scheme was first proposed within the N-AFEM framework, which allows the consideration of nonlinear coupled intra-element cracks without the need of additional nodes or nodal DoFs. Then a modified exponential cohesive zone model (CZM) that considers the coupling effects between tension/compression and shear at the fracture surface was proposed to describe the fracture process of geomaterials. Besides, a nonlinear yielding function based on the Mohr-Coulomb strength theory was introduced into the framework and serves as the fracture initiation criteria for geomaterials. Finally, several benchmark examples were simulated and the predicted results were compared with existing numerical or experimental data to demonstrate the validity of the proposed method.

Adaptation of the Predicted Particles Properties (P3) Microphysics Scheme for Large-Scale Numerical Weather Prediction

AbstractA parameterization for the subgrid-scale cloud and precipitation fractions has been incorporated into the Predicted Particle Properties (P3) microphysics scheme for use in atmospheric models with relatively coarse horizontal resolution. The modified scheme was tested in a simple 1D kinematic model and in the Canadian Global Environmental Multiscale (GEM) model using an operational global NWP configuration with a 25-km grid spacing. A series of 5-day forecast simulations was run using P3 and the much simpler operational Sundqvist condensation scheme as a benchmark for comparison. The effects of using P3 in a global GEM configuration, with and without the modifications, were explored through statistical metrics of common forecast fields against upper-air and surface observations. Diagnostics of state variable tendencies from various physics parameterizations were examined to identify possible sources of errors resulting from the use of the modified scheme. Sensitivity tests were performed on the coupling between the deep convection parameterization scheme and the microphysics, specifically regarding assumptions in the physical properties of detrained ice. It was found that even without recalibration of the suite of moist physical parameterizations, substituting the Sundqvist condensation scheme with the modified P3 microphysics resulted in some significant improvements to the temperature and geopotential height bias throughout the troposphere and out to day 5, but with degradation to error standard deviation toward the end of the integrations, as well as an increase in the positive bias of precipitation quantities. The modified P3 scheme was thus shown to hold promise for potential use in coarse-resolution NWP systems.

Synthesis of coumarin derivatives in a microfluidic flow system employing the Pechmann condensation: A case study

AbstractFor the synthesis of coumarin derivatives using the Pechmann condensation scheme, an acidic ionic liquid catalyst, abbreviated as [EBsImH][HSO4], was prepared from the ring opening of 1,4‐butanesultone by 1‐ethylimidazole, followed by the addition of 1 equiv. H2SO4(c). The [EBsImH][HSO4]‐catalyzed Pechmann condensation reactions proceeded smoothly in a batch setup, with recyclable [EBsImH][HSO4] showing great catalytic activity. The acidic ionic liquid catalyst [EBsImH][HSO4] was recovered from EtOAc/H2O extraction of the product mixture, where the H2O layer was worked up and dried for reuse in consecutive runs of the Pechmann condensation reactions, maintaining >85% conversion for four times. The catalytic reactions were also carried out in a microfluidic flow setup. The flow parameters, the reactant molar amounts, and the additional H2SO4 as a modifying acid catalyst were optimized in the current case study. A minimum conversion rate of 2.8 g/hr of coumarin derivatives was demonstrated.

Synthesis, Characterization and Antimicrobial Activity of A Chalcone Derivative

An area of great interest in recent years has been chalcones. Chalcones are the important component of many natural sources and have variety of biological activities. Chalcones which are also known as α,βunsaturated ketones is an significant class of organic compounds and reported to possess a wide spectrum of biological activities such as antibacterial, antifungal, anticancer, anti-inflammatory etc. Abundant research papers have been published and chalcones continue to show promise for new drug investigations. The derivative of chalcones were prepared using Claisen–Schmidt condensation scheme. The structure of the synthesized was confirmed by UV and IR. The compound was also tested for their antimicrobial activity

Dynamic behaviour analysis of coupled rotor active magnetic bearing system in the supercritical frequency range

In this article, an attempt has been made to model and estimate speed-dependent characteristic parameters of coupling misalignment and AMB, in an AMB integrated coupled flexible rotor system running in the supercritical frequency range. For estimation algorithm, desired current and displacement responses in time series are acquired from Simulink. The practical limitation of FEM modelling is the number of sensors and availability of measurement locations that have been overcome by applying a novel gyroscopic high-frequency condensation (GHFC) scheme. The transformation matrix obtained from standard high-frequency condensation (SHFC) is modified by adding a gyroscopic effect into the transformation matrix to achieve the novel GHFC. The numerical analysis has been performed on a coupled rotor train system along with AMB. The estimations are presented and compared for SHFC and GHFC. The GHFC is found effective over SHFC techniques. The effect of noisy response and modelling error on the estimation algorithm is analysed and found competent. The experimental responses obtained for a different level of misalignment conditions have been compared with the numerically simulated response and found that the application of AMB suppresses the excessive vibration.

Thermal Properties of Ultra- and Nanodispersed Core–Shell Structures of Ti(Mo)C and Ti(Mo)C-Co Obtained During Plasma-Chemical Synthesis by Plasma Recondensation Scheme

In this work, the thermal studies of ultrafine and nanocrystalline core–shell structures of Ti(Mo)C and Ti(Mo)C-Co formed in the process of plasma chemical synthesis according to the plasma condensation scheme in a low-temperature nitrogen plasma were performed. The oxidation processes of all phase components in the core–shell structures, determined during the high-resolution transmission electron microscopy studies, are presented as experimental results. The composition of nanocompositions before and after oxidation was recorded by X-ray methods. This allowed us to determine the sequence of interaction of the phase components of the core–shell structures with oxygen present in cylinders with argon, including carbon oxidation. In addition to the high-resolution transmission electron microscopy methods, the presence of carbon on the surface of particles was also confirmed by Raman spectroscopy. The use of these analysis techniques in combination with the results of derivatography and thermogravimetry made it possible to formulate the oxidation mechanisms of the core–shell structures of Ti(Mo)C and Ti(Mo)C-Co.