Verification of a Specialized Hydrodynamic Simulation Code for Modeling Deflagration and Detonation of High Explosives

A specialized hydrodynamic simulation code has been developed to simulate one-dimensional unsteady problems involving the detonation and deflagration of high explosives. To model all the relevant physical processes in these problems, a code is required to simulate compressible hydrodynamics, unsteady thermal conduction and chemical reactions with complex rate laws. Several verification exercises are presented which test the implementation of these capabilities. The code also requires models for physics processes such as equations of state and conductivity for pure materials and mixtures as well as rate laws for chemical reactions. Additional verification tests are required to ensure these models are implemented correctly. Though this code is limited in the types of problems it can simulate, its computationally efficient formulation allow it to be used in calibration studies for reactive burn models for high explosives.

Geochemical and Biogeochemical Reaction Modeling

An indispensable primer and reference textbook, the third edition of Geochemical and Biogeochemical Reaction Modeling carries the reader from the field's origins and theoretical underpinnings through to a collection of fully worked examples. A clear exposition of the underlying equations and calculation techniques is balanced by real-world example calculations. The book depicts geochemical reaction modeling as a vibrant field of study applicable to a wide spectrum of issues of scientific, practical, and societal concern. The new edition offers a thorough description of surface complexation modeling, including two- and three-layer methods; broader treatment of kinetic rate laws; the effect of stagnant zones on transport; and techniques for determining gas partial pressures. This handbook demystifies and makes broadly accessible an elegant technique for portraying chemical processes in the geosphere. It will again prove to be invaluable for geochemists, environmental scientists and engineers, aqueous and surface chemists, microbiologists, university teachers, and government regulators.

Au(I) Catalyzed HF Transfer: Tandem Alkyne Hydrofluorination and Perfluoroarene Functionalisation

HF transfer reactions between organic substrates are an incredibly rare class of transformation. Such reactions require the development of new catalytic systems that can promote both defluorination and fluorination steps in a single reaction sequence. Herein, we report a novel catalytic protocol in which an equivalent of HF is generated from a perfluoroarene | nucleophile pair and transferred directly to an alkyne. The reaction is catalysed by [Au(IPr)NiPr2] (IPr = N,N’-1,3-Bis(2,6-diisopropylphenyl)imidazol-2-ylidene) and is 100 % atom efficient. HF transfer generates two useful products in the form of functionalised fluoroarenes and fluoroalkenes. Mechanistic studies (rate laws, KIEs, DFT calculations, competition experiments) are consistent with the Au(I) catalyst facilitating a catalytic network involving both concerted SNAr and hydrofluorination steps. The nature of the nucleophile impacts the turnover-limiting step. The cSNAr step is turnover-limiting for phenol-based nucleophiles while proteodeauration likely becomes turnover-limiting for aniline-based nucleophiles. The new approach removes the need for direct handling of HF reagents in hydrofluorination and offers new possibilities to manipulate the fluorine content of organic molecules through catalysis.

Chemical Kinetics

Chemical Kinetics discusses the rate at which chemical reactions occur and how these rates can be expressed mathematically, with a review of the factors which affect reaction rates. Topics presented with a numerical focus include reaction rate measurements, rate laws and their components including rate constants, determination of reaction orders from integrated rate laws, and effects of temperature on rates. Reaction half life and its determination are discussed. Collision theory, which forms the basis of the rate law, is presented with emphasis on the effect of temperature on the rate constant and the rate. The Arrhenius equation and the concept of activation energy are discussed with illustrative calculations for determining the energy of activation.

Polychromatic-Light Irradiation Kinetics of Dacarbazine and Nifedipine. Application as New Reliable UVA-drug-actinometers.

The photokinetic behaviour of materials driven by polychromatic light is an area that has not received a lot of attention in the literature. Most often, such photokinetic data is treated by thermal kinetic models (i.e., the classical 0th -, 1st - or 2nd -order equations). Such models were not analytically derived from the rate-laws of the photodegradation reactions. Polychromatic light kinetic modelling is hence of importance, as a means to providing adequate toolkits and metrics. This paper aims at proposing two reliable drug-actinometers useful for polychromatic UVA range. The general actinometric methodology offered here is also useful for any drugs/materials obeying a primary photoprocess where both reactant and photoproduct absorb the incident light, of the \(AB{\left(1{\Phi }\right)}_{{\epsilon }_{B}\ne 0}\) type. The present method has been consolidated by the η-order kinetics, a mathematical model analytically derived from the photosystem’s rate-law. This represents the first ever equation in the literature, to model polychromatic light of this reactive system. This framework further demonstrated the lamp-specificity of actinometers. Overall, Dacarbazine and Nifedipine photodegradations obeyed η-order kinetics, and stand as effective actinometers that can be recommended for the ICH Q1b photostability testing.

Numerical modelling of steady detonations with a variational streamline approach

Previous studies (Watt et al. in J Eng Math 75(1):1, 2012; Cartwright and Falle in J Eng Math 115(1):157, 2019) have shown that a streamline based approach to modelling of steady state detonations can produce good results for rate laws which have maximal reaction at the shock. In this paper we consider a Variational Streamline Approximation (VSA) which introduces streamline curvature. Comparing results with Direct Numerical Simulations (DNS) and the existing Straight Streamline Approximation (SSA) model, we find that the VSA improves the predictive accurary of streamlines modelling compared to DNS calculations, capturing the shock front and sonic surfaces with greater accuracy than SSA.

Constructing and analysing dynamic models with modelbase v1.2.3: a software update

Background Computational mathematical models of biological and biomedical systems have been successfully applied to advance our understanding of various regulatory processes, metabolic fluxes, effects of drug therapies, and disease evolution and transmission. Unfortunately, despite community efforts leading to the development of SBML and the BioModels database, many published models have not been fully exploited, largely due to a lack of proper documentation or the dependence on proprietary software. To facilitate the reuse and further development of systems biology and systems medicine models, an open-source toolbox that makes the overall process of model construction more consistent, understandable, transparent, and reproducible is desired. Results and discussion We provide an update on the development of , a free, expandable Python package for constructing and analysing ordinary differential equation-based mathematical models of dynamic systems. It provides intuitive and unified methods to construct and solve these systems. Significantly expanded visualisation methods allow for convenient analysis of the structural and dynamic properties of models. After specifying reaction stoichiometries and rate equations modelbase can automatically assemble the associated system of differential equations. A newly provided library of common kinetic rate laws reduces the repetitiveness of the computer programming code. is also fully compatible with SBML. Previous versions provided functions for the automatic construction of networks for isotope labelling studies. Now, using user-provided label maps, v1.2.3 streamlines the expansion of classic models to their isotope-specific versions. Finally, the library of previously published models implemented in is growing continuously. Ranging from photosynthesis to tumour cell growth to viral infection evolution, all these models are now available in a transparent, reusable and unified format through . Conclusion With this new Python software package, which is written in currently one of the most popular programming languages, the user can develop new models and actively profit from the work of others. enables reproducing and replicating models in a consistent, tractable and expandable manner. Moreover, the expansion of models to their isotopic label-specific versions enables simulating label propagation, thus providing quantitative information regarding network topology and metabolic fluxes.

Impact of Surface Reactivity on the Simulation of Mineral Dissolution Rates

<p>The kinetics of mineral dissolution plays a key role in many environmental and technical fields, e.g., weathering, building materials, as well as host rock characterization for potential nuclear waste repositories. Mineral dissolution rates are controlled by two parameters: (1) transport of dissolved species over and from the interface determined by advective fluid flow and diffusion (transport control) and (2) availability and distribution of reactive sites on the crystal surface (surface reactivity control). Reactive transport models (RTM) simulating species transport commonly calculate mineral dissolution by using rate laws [1]. However, the applied rate laws solely depend on species concentration in the fluid. While the effect of transport-controlled processes is addressed in current RTM approaches, the intrinsic variability of surface reactivity is neglected. Experimental studies under surface-controlled dissolution conditions have shown that surface reactivity is heterogeneously distributed over the surface [e.g., 2]. This heterogeneity in reactivity is largely caused by nanotopographical structures on the crystal surface, such as steps and etch pits. These structures are generated through defects in the crystal lattice. At these structures, the high density of reactive kink sites is leading to a local increase in surface reactivity observable through high dissolution rates.</p><p>In this study, we test whether the current rate calculation approach applied in RTMs is sufficient to reproduce experimentally observed rate heterogeneities. We apply a standard RTM approach combined with the measured surface topography of a calcite single crystal [2]. Calcite is an important mineral component in the sandy facies of the Opalinus clay formation, that is under investigation for nuclear waste storage. The modeled surface dissolution rate maps are compared to experimentally derived rate maps. Results show that the current RTM is not able to reproduce the measured rate heterogeneities on the calcite surface. To improve the predictive capabilities of RTMs over the large time scales required for the safety assessment of nuclear waste repositories, the surface reactivity that is intrinsic to the mineral needs to be implemented into future rate calculations. Investigating calcite surface reactivity in the context of dissolution can also yield information about other kinetic surface processes such as the adsorption of radionuclides during transport. We show the integration of surface reactivity into rate calculation by using a proxy parameter. The slope of the crystal surface at the nm scale is applied. We show that by adding a factor based on the slope to the rate law the RTM is able to approximate experimental rate maps. Other proxy parameters such as surface roughness could yield similar results as well. The implementation of surface reactivity proxy parameters will allow for a more precise prediction of host rock-fluid interaction over large time scales in RTMs, relevant for safety assessment of nuclear waste repositories.</p><p>[1] Agrawal, P., Raoof, A., Iliev, O. and Wolthers, M. (2020), Advances in Water Resources, 136, 103480. [2] Bibi, I., Arvidson, R.S., Fischer, C. and Lüttge, A. (2018), Minerals, 8, 256.</p>