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At least 631 records · Page 35

Optimization of Desalination Systems with Detailed Water Chemistry through Integration of Reaktoro in WaterTAP

Chemistry predictions are critical for an accurate estimation of performance and costs in desalination process models, which allows for the estimation of the value of new technologies and the viability of treating new water sources. Herein, we present how an implicit function formulation can be used to integrate the chemical modeling package, Reaktoro, into the techno-economic assessment and modeling platform, WaterTAP. This approach resolves the critical issues of integrating large-scale thermodynamic models and databases into equation-oriented process models while allowing more flexibility relative to previously presented surrogate-based methods. We describe how this integration into Pyomo and WaterTAP models is implemented and used through the open-source package Reaktoro-PSE . We first validate this integration approach by performing optimization on a previously presented desalination treatment train with softening and acid addition as the pretreatment steps. Then, to demonstrate the value of this approach, we extend the cost-optimization problem to include the simultaneous addition of lime and soda ash for softening, and HCl and H 2 SO 4 in the acidification steps. Finally, we were able to confirm the previously established results that were obtained by using surrogate models and demonstrate that the implicit function approach enables exploration of different feedwater compositions and a larger number of chemicals and their combinations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Resolution of a Challenge for Solvation Modeling: Calculation of Dicarboxylic Acid Dissociation Constants Using Mixed Discrete-Continuum Solvation Models

First and second dissociation constants (pK a values) of oxalic acid, malonic acid, and adipic acid were computed by using a number of theoretical protocols based on density functional theory and using both continuum solvation models and mixed discrete-continuum solvation models. We show that fully implicit solvation models (in which the entire solvent is represented by a dielectric continuum) fail badly for dicarboxylic acids with mean unsigned errors averaged over six pK a values) of 2.4-9.0 log units, depending on the particular implicit model used. The use of water-solute clusters and accounting for multiple conformations in solution significantly improve the performance of both generalized Born solvation models and models that solve the nonhomogeneous dielectric Poisson equation for bulk electrostatics. The four most successful models have mean unsigned errors of only 0.6-0.8 log units.

Environmental Molecular Sciences Laboratory↗

An Energy Consistent Discretization of the Nonhydrostatic Equations in Primitive Variables

We derive a formulation of the nonhydrostatic equations in spherical geometry with a Lorenz staggered vertical discretization. The combination conserves a discrete energy in exact time integration when coupled with a mimetic horizontal discretization. The formulation is a version of Dubos and Tort (2014, https://doi.org/10.1175/MWR-D-14-00069.1) rewritten in terms of primitive variables. It is valid for terrain following mass or height coordinates and for both Eulerian or vertically Lagrangian discretizations. The discretization relies on an extension to Simmons and Burridge (1981, https://doi.org/10.1175/1520-0493(1981)109<0758:AEAAMC>2.0.CO;2) vertical differencing, which we show obeys a discrete derivative product rule. This product rule allows us to simplify the treatment of the vertical transport terms. Energy conservation is obtained via a term-by-term balance in the kinetic, internal, and potential energy budgets, ensuring an energy-consistent discretization up to time truncation error with no spurious sources of energy. We demonstrate convergence with respect to time truncation error in a spectral element code with a horizontal explicit vertically implicit implicit-explicit time stepping algorithm.

97 MATHEMATICS AND COMPUTING↗

Seismic Diffusivity and the Influence of Heterogeneity on Injection‐Induced Seismicity

Abstract The spatiotemporal patterns of injection‐induced seismicity (IIS) are commonly interpreted with the concept of a triggering front, which propagates in a diffusion‐like manner with an associated diffusivity parameter. Here, we refer to this diffusivity as the “seismic diffusivity.” Several previous studies implicitly assume that seismic diffusivity is equivalent to the effective hydraulic diffusivity of the subsurface, which describes the behavior of the mean pressure field in heterogeneous porous media. Seismicity‐based approaches for hydraulic characterization or simulations of IIS using domains of homogeneous equivalent porous media are implicitly based on this assumed equivalence. However, seismicity is expected to propagate with the threshold triggering pressure, and thus not be controlled by the evolution of the mean pressure field. We present numerical simulations of fluid injection to compare the seismic and effective hydraulic diffusivities in heterogeneous formations (including fractured rock). The numerical model combines uncoupled, linear pressure diffusion with the Mohr‐Coulomb failure criterion to simulate IIS. We demonstrate that connected pathways of relatively high hydraulic diffusivity in heterogeneous media (particularly in fractured rock domains) allow the threshold triggering pressure to propagate more rapidly than predicted by the effective hydraulic diffusivity. As a result, the seismic diffusivity is greater than the effective hydraulic diffusivity in heterogeneous porous media, possibly by an order of magnitude or more. Additionally, we present a case study of IIS near Soultz‐sous‐Forêts where seismic diffusivity is found to be at least one order of magnitude larger than the effective hydraulic diffusivity.

Haagenson, Ryan↗

Generative adversarial networks (GAN) based efficient sampling of chemical composition space for inverse design of inorganic materials

A major challenge in materials design is how to efficiently search the vast chemical design space to find the materials with desired properties. One effective strategy is to develop sampling algorithms that can exploit both explicit chemical knowledge and implicit composition rules embodied in the large materials database. Here, we propose a generative machine learning model (MatGAN) based on a generative adversarial network (GAN) for efficient generation of new hypothetical inorganic materials. Trained with materials from the ICSD database, our GAN model can generate hypothetical materials not existing in the training dataset, reaching a novelty of 92.53% when generating 2 million samples. The percentage of chemically valid (charge-neutral and electronegativity-balanced) samples out of all generated ones reaches 84.5% when generated by our GAN trained with such samples screened from ICSD, even though no such chemical rules are explicitly enforced in our GAN model, indicating its capability to learn implicit chemical composition rules to form compounds. Our algorithm is expected to be used to greatly expand the range of the design space for inverse design and large-scale computational screening of inorganic materials.

36 MATERIALS SCIENCE↗

Bayesian calibration of thermodynamic models for the uptake of CO{sub 2} in supported amine sorbents using ab initio priors

A statistical methodology was applied to the simultaneous calibration and validation of thermodynamic models for the uptake of CO{sub 2} in mesoporous silica-supported amines. The methodology is Bayesian, and follows the procedure introduced by Kennedy and O'Hagan. One key aspect of the application presented is the use of quantum chemical calculations to define prior probability distributions for physical model parameters. Inclusion of this prior information proved to be crucial to the identifiability of model parameters against experimental thermogravimetric data. Through the statistical analysis, a quantitative assessment of the accuracy of various quantum chemical methods is produced. Another important aspect of the current approach is the conditioning of the model form discrepancy – a critical component of the Kennedy and O'Hagan methodology – to the experimental data in such a manner that it becomes an implicit function of the model parameters and thereby connected with the posterior distribution. It is shown that the inclusion of prior information in the analysis leads to a shifting of uncertainty from the posterior distribution for model parameters to this conditioned model form discrepancy. Prospects for more accurate model predictions and propagation of uncertainty in upscaling and extrapolation through a “model-plus-discrepancy” approach are discussed. The synthesis methods and thermogravimetric characterization of hybrid grafted/impregnated mesoporous silica-supported amine sorbents are presented, along with the details of the quantum chemical study, which shows that a carbamic acid–base acceptor complex is the most stable form of adsorbed CO{sub 2} in both alkanol- and ethyleneamines.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Analytical nuclear gradients for the range-separated many-body dispersion model of noncovalent interactions

An accurate treatment of the long-range electron correlation energy, including van der Waals (vdW) or dispersion interactions, is essential for describing the structure, dynamics, and function of a wide variety of systems. Among the most accurate models for including dispersion into density functional theory (DFT) is the range-separated many-body dispersion (MBD) method [A. Ambrosetti et al., J. Chem. Phys., 2014, 140, 18A508], in which the correlation energy is modeled at short-range by a semi-local density functional and at long-range by a model system of coupled quantum harmonic oscillators. In this work, we develop analytical gradients of the MBD energy with respect to nuclear coordinates, including all implicit coordinate dependencies arising from the partitioning of the charge density into Hirshfeld effective volumes. To demonstrate the efficiency and accuracy of these MBD gradients for geometry optimizations of systems with intermolecular and intramolecular interactions, we optimized conformers of the benzene dimer and isolated small peptides with aromatic side-chains. We find excellent agreement with the wavefunction theory reference geometries of these systems (at a fraction of the computational cost) and find that MBD consistently outperforms the popular TS and D3(BJ) dispersion corrections. To demonstrate the performance of the MBD model on a larger system with supramolecular interactions, we optimized the C 60 @C 60 H 28 buckyball catcher host–guest complex. In our analysis, we also find that neglecting the implicit nuclear coordinate dependence arising from the charge density partitioning, as has been done in prior numerical treatments, leads to an unacceptable error in the MBD forces, with relative errors of ~20% (on average) that can extend well beyond 100%.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Coarse-grained molecular dynamics simulation of the interface behaviour and self-assembly of CTAB cationic surfactants

Here, we study the behaviour at interfaces and the micelle self-assembly of a cationic surfactant (CTAB) by Molecular Dynamics (MD) simulations of coarse-grained models. We consider both the standard (with explicit water) Martini force field and the implicit solvent version of the Martini force field (Dry Martini). First, we study the behaviour of CTAB at a water/vacuum interface, at a water/organic solvent interface and in a pre-assembled CTAB micelle using both standard and Dry Martini and all-atomic simulations. Our results indicate that there are significant quantitative differences between the predictions of the two models. Interestingly, implicit solvent simulations with Dry Martini show good quantitative agreement with all-atomic MD simulations, better than explicit solvent Martini MD simulations. The computational efficiency of the Martini and Dry Martini models allowed us to study the self-assembly of CTAB in a large system with many micelles. We observe the self-assembly of CTAB into micelles and also the exchange of CTAB molecules between micelles by events such as micelle fusion and fission which are difficult to observe in all-atomic MD simulations due to the time and length scales involved. Under the studied conditions, both Martini models predict a rather different self-assembly behaviour. The standard Martini model predicts a final equilibrium state with spherical micelles with an average size of ≈70 CTAB molecules. In contrast, the Dry Martini model predicts the formation of large tubular micelles with ≈330 CTAB molecules. Compared with experiments, standard Martini and Dry Martini underestimate and overestimate, respectively, the micelle size.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Aqueous-phase effects on ethanol decomposition over Ru-based catalysts

The effects of an aqueous phase on ethanol decomposition for hydrogen production over a Ru(0001) catalyst surface model have been investigated from first principles. Solvent effects on the reaction mechanism and kinetic parameters have been quantified with the help of a microkinetic reactor model, density functional theory, and an implicit solvation scheme (iSMS). Our calculations indicate that in both vapor- and aqueous-phase reaction environments, the ethanol decomposition starts with acetaldehyde formation on the surface, some of which further dehydrogenates to ketenyl species (CHCO), where the C–C bond cleaves to form methylidyne (CH) and CO. In the vapor phase, adsorbed CH gets hydrogenated to methane, and CO desorbs or undergoes methanation reducing the amount of hydrogen produced. In contrast, under aqueous phase reaction conditions, the methanation is inhibited, and the water–gas shift (WGS) reaction is accelerated, leading to complete conversion of CO to CO 2 and H 2 . Furthermore, calculations indicate that the observed reaction behavior under aqueous phase reforming conditions originates primarily from the higher water chemical potential, and implicit solvent models predict only a small solvation effect.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A Parallelised ROOT for Future HEP Data Processing

In the coming years, HEP data processing will need to exploit parallelism on present and future hardware resources to sustain the bandwidth requirements. As one of the cornerstones of the HEP software ecosystem, ROOT embraced an ambitious parallelisation plan which delivered compelling results. In this contribution the strategy is characterised as well as its evolution in the medium term. The units of the ROOT framework are discussed where task and data parallelism have been introduced, with runtime and scaling measurements. We will give an overview of concurrent operations in ROOT, for instance in the areas of I/O (reading and writing of data), fitting / minimization, and data analysis. This paper introduces the programming model and use cases for explicit and implicit parallelism, where the former is explicit in user code and the latter is implicitly managed by ROOT internally.

97 MATHEMATICS AND COMPUTING↗

Nonlinear three-dimensional verification of the $\small \mathrm{SPECYL}$ and $\small \mathrm{PIXIE3D}$ magnetohydrodynamics codes for fusion plasmas

With the increasing impact of scientific discovery via advanced computation, there is presently a strong emphasis on ensuring the mathematical correctness of computational simulation tools. Such endeavor, termed verification, is now at the center of most serious code development efforts. In this study, we address a cross-benchmark nonlinear verification study between two three-dimensional magnetohydrodynamics (3D MHD) codes for fluid modeling of fusion plasmas, SPECYL [S. Cappello and D. Biskamp, Nucl. Fusion 36, 571 (1996)] and PIXIE3D [L. Chacón, Phys. Plasmas 15, 056103 (2008)], in their common limit of application: the simple viscoresistive cylindrical approximation. SPECYL is a serial code in cylindrical geometry that features a spectral formulation in space and a semi-implicit temporal advance, and has been used extensively to date for reversed-field pinch studies. PIXIE3D is a massively parallel code in arbitrary curvilinear geometry that features a conservative, solenoidal finite-volume discretization in space, and a fully implicit temporal advance. The present study is, in our view, a first mandatory step in assessing the potential of any numerical 3D MHD code for fluid modeling of fusion plasmas. Finally, excellent agreement is demonstrated over a wide range of parameters for several fusion-relevant cases in both two- and three-dimensional geometries.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Numerical Methods for the Wave Equation

We examine a variety of numerical methods, both explicit and implicit, for the wave equation. Numerical dispersion relations are used to determine stability and to analyse the linear group velocity. We find that although implicit methods can allow for large time step, the group velocity becomes increasingly inaccurate with increasing step-size.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Fast Transient And Spatially Non-Homogenous Accident Analysis Of Two-Dimensional Cylindrical Nuclear Reactor

The research about fast transient and spatially non-homogenous nuclear reactor accident analysis of two-dimensional nuclear reactor has been done. This research is about prediction of reactor behavior is during accident. In the present study, space-time diffusion equation is solved by using direct methods which consider spatial factor in detail during nuclear reactor accident simulation. Set of equations that obtained from full implicit finite-difference discretization method is solved by using iterative methods ADI (Alternating Direct Implicit). The indication of accident is decreasing macroscopic absorption cross-section that results large external reactivity. The power reactor has a peak value before reactor has new balance condition. Changing of temperature reactor produce a negative Doppler feedback reactivity. The reactivity will reduce excess positive reactivity. Temperature reactor during accident is still in below fuel melting point which is in secure condition.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Treecode-based generalized Born method

We have developed a treecode-based O(N log N) algorithm for the generalized Born (GB) implicit solvation model. Our treecode-based GB (tGB) is based on the GBr6 [J. Phys. Chem. B 111, 3055 (2007)], an analytical GB method with a pairwise descreening approximation for the R6 volume integral expression. The algorithm is composed of a cutoff scheme for the effective Born radii calculation, and a treecode implementation of the GB charge–charge pair interactions. Test results demonstrate that the tGB algorithm can reproduce the vdW surface based Poisson solvation energy with an average relative error less than 0.6% while providing an almost linear-scaling calculation for a representative set of 25 proteins with different sizes (from 2815 atoms to 65456 atoms). For a typical system of 10k atoms, the tGB calculation is three times faster than the direct summation as implemented in the original GBr6 model. Thus, our tGB method provides an efficient way for performing implicit solvent GB simulations of larger biomolecular systems at longer time scales.

59 BASIC BIOLOGICAL SCIENCES↗

Asymptotic equilibrium between Langmuir turbulence and suprathermal electrons in three dimensions

The suprathermal electron distributions with non-Maxwellian tail are commonly detected in space environment as well as in the laboratory. In a previous article [P. H. Yoon, Phys. Plasmas 18, 122303 (2011)], a self-consistent theory of asymptotically steady-state electron distribution function and Langmuir turbulence intensity was formulated in which the steady-state electron distribution is obtained by balancing the spontaneous (or collisional) drag term and velocity space diffusion term, while the steady-state turbulence intensity was obtained by balancing spontaneous and induced processes. The resulting electron distribution function was a type of kappa distribution that features a non-Maxwellian energetic tail component. However, such a discussion was based upon the assumption that both electrons and Langmuir waves are confined to one-dimensional space along the direction of the implicit ambient magnetic field. However, such an assumption may be invalidated when the implicit ambient magnetic field is sufficiently weak or absent. Consequently, in this paper the assumption of one-dimensionality is relaxed to three-dimensional situation.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Modeling time-coincident ultrafast electron transfer and solvation processes at molecule-semiconductor interfaces

Kinetic models based on Fermi's Golden Rule are commonly employed to understand photoinduced electron transfer dynamics at molecule-semiconductor interfaces. Implicit in such second-order perturbative descriptions is the assumption that nuclear relaxation of the photoexcited electron donor is fast compared to electron injection into the semiconductor. This approximation breaks down in systems where electron transfer transitions occur on 100-fs time scale. Here, we present a fourth-order perturbative model that captures the interplay between time-coincident electron transfer and nuclear relaxation processes initiated by light absorption. The model consists of a fairly small number of parameters, which can be derived from standard spectroscopic measurements (e.g., linear absorbance, fluorescence) and/or first-principles electronic structure calculations. Insights provided by the model are illustrated for a two-level donor molecule coupled to both (i) a single acceptor level and (ii) a density of states (DOS) calculated for TiO{sub 2} using a first-principles electronic structure theory. These numerical calculations show that second-order kinetic theories fail to capture basic physical effects when the DOS exhibits narrow maxima near the energy of the molecular excited state. Overall, we conclude that the present fourth-order rate formula constitutes a rigorous and intuitive framework for understanding photoinduced electron transfer dynamics that occur on the 100-fs time scale.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Issues in measure-preserving three dimensional flow integrators: Self-adjointness, reversibility, and non-uniform time stepping

Properties of integration schemes for solenoidal fields in three dimensions are studied, with a focus on integrating magnetic field lines in a plasma using adaptive time stepping. It is shown that implicit midpoint (IM) and a scheme we call three-dimensional leapfrog (LF) can do a good job (in the sense of preserving KAM tori) of integrating fields that are reversible, or (for LF) have a “special divergence-free” (SDF) property. We review the notion of a self-adjoint scheme, showing that such schemes are at least second order accurate and can always be formed by composing an arbitrary scheme with its adjoint. We also review the concept of reversibility, showing that a reversible but not exactly volume-preserving scheme can lead to a fractal invariant measure in a chaotic region, although this property may not often be observable. We also show numerical results indicating that the IM and LF schemes can fail to preserve KAM tori when the reversibility property (and the SDF property for LF) of the field is broken. We discuss extensions to measure preserving flows, the integration of magnetic field lines in a plasma and the integration of rays for several plasma waves. The main new result of this paper relates to non-uniform time stepping for volume-preserving flows. We investigate two potential schemes, both based on the general method of Feng and Shang [Numer. Math. 71, 451 (1995)], in which the flow is integrated in split time steps, each Hamiltonian in two dimensions. The first scheme is an extension of the method of extended phase space, a well-proven method of symplectic integration with non-uniform time steps. This method is found not to work, and an explanation is given. The second method investigated is a method based on transformation to canonical variables for the two split-step Hamiltonian systems. This method, which is related to the method of non-canonical generating functions of Richardson and Finn [Plasma Phys. Controlled Fusion 54, 014004 (2012)], appears to work very well.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗