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Single-point measurements from towers in cities cannot properly quantify the impact of all terms in the turbulent kinetic energy (TKE) budget and are often not representative of horizontally-averaged quantities over the entire urban domain. A series of large-eddy simulations (LES) is here performed to quantify the relevance of non-measurable terms, and to explore the spatial variability of the flow field over and within an urban geometry in the city of Basel, Switzerland. The domain has been chosen to be centered around a tower where single-point turbulence measurements at six heights are available. Buildings are represented through a discrete-forcing immersed boundary method and are based on detailed real geometries from a surveying dataset. The local model results at the tower location compare well against measurements under near-neutral stability conditions and for the two prevailing wind directions chosen for the analysis. This confirms that LES in conjunction with the immersed boundary condition is a valuable model to study turbulence and dispersion within a real urban roughness sublayer (RSL). The simulations confirm that mean velocity profiles in the RSL are characterized by an inflection point z γ located above the average building height z h . TKE in the RSL is primarily produced above z γ , and turbulence is transported down into the urban canopy layer. Pressure transport is found to be significant in the very-near-wall regions. Further, spatial variations of time-averaged variables and non-measurable dispersive terms are important in the RSL above a real urban surface and should therefore be considered in future urban canopy parametrization developments.

We carry out efforts to reproduce computational results for seven published articles and identify barriers to computational reproducibility. We then derive three principles to guide the practice and dissemination of reproducible computational research: (i) Provide transparency regarding how computational results are produced; (ii) When writing and releasing research software, aim for ease of (re-)executability; (iii) Make any code upon which the results rely as deterministic as possible. We then exemplify these three principles with 12 specific guidelines for their implementation in practice. We illustrate the three principles of reproducible research with a series of vignettes from our experimental reproducibility work. We define a novel Reproduction Package, a formalism that specifies a structured way to share computational research artifacts that implements the guidelines generated from our reproduction efforts to allow others to build, reproduce and extend computational science. We make our reproduction efforts in this paper publicly available as exemplar Reproduction Packages. This article is part of the theme issue ‘Reliability and reproducibility in computational science: implementing verification, validation and uncertainty quantification in silico’.

Evaporation is an important process in many natural and technical systems, such as the unsaturated zone of the subsurface or microchannel evaporators. For the understanding and prediction of the involved processes, numerical simulations of multiphase flow and transport processes are an important tool. In order to achieve an accurate, physically based description of kinetic interphase mass and heat transfer occurring during evaporation, the numerical model has to account for the interfacial areas between phases. A recently developed model for two‐phase flow in porous media is able to account for the involved processes by using interfacial areas explicitly as parameters in the model. The crucial issue, however, is the determination of the relationships between specific interfacial areas, capillary pressure, and saturation in this paper, we present a multiphase lattice Boltzmann model, which allows us to determine these relationships. On the basis of the scanned geometry of a natural porous medium, the relationships between specific interfacial areas, capillary pressure, and saturation are determined. To the best of our knowledge, this is the first time that fluid‐solid specific interfacial area relationships have been obtained from pore‐scale data. Using these functions, we present the results of macroscale simulations of an evaporator device and of drying in a porous medium. Key Points Obtaining constitutive relationships from micro scale LB simulations Thermodynamically consistent method including interfacial areas Modeling mass and heat tranfer kinetics across interfaces

The inherent complexity of biomedical systems is well recognized; they are multiscale, multiscience systems, bridging a wide range of temporal and spatial scales. While the importance of multiscale modelling in this context is increasingly recognized, there is little underpinning literature on the methodology and generic description of the process. The COAST (complex autonoma simulation technique) project aims to address this by developing a multiscale, multiscience framework, coined complex autonoma (CxA), based on a hierarchical aggregation of coupled cellular automata (CA) and agent-based models (ABMs). The key tenet of COAST is that a multiscale system can be decomposed into N single-scale CA or ABMs that mutually interact across the scales. Decomposition is facilitated by building a scale separation map on which each single-scale system is represented according to its spatial and temporal characteristics. Processes having well-separated scales are thus easily identified as the components of the multiscale model. This paper focuses on methodology, introduces the concept of the CxA and demonstrates its use in the generation of a multiscale model of the physical and biological processes implicated in a challenging and clinically relevant problem, namely coronary artery in-stent restenosis.

This article provides a concise exposition of the multiple-relaxation-time lattice Boltzmann equation, with examples of 15-velocity and 19-velocity models in three dimensions. Simulation of a diagonally lid-driven cavity flow in three dimensions at Re = 500 and 2000 is performed. The results clearly demonstrate the superior numerical stability of the multiple-relaxation-time lattice Boltzmann equation over the popular lattice Bhatnagar-Gross-Krook equation.

This paper introduces a nonlinear multigrid solution approach for the discrete Boltzmann equation discretized by an implicit second-order Finite Difference scheme. For simplicity we restrict the discussion to the stationary case. A numerical example shows the drastically improved efficiency in comparison to the widely used Lattice–Bathnagar–Gross–Krook (LBGK) approach.

Exercise-induced bronchoconstriction describes the narrowing of the airway that occurs with exercise. More than 10 percent of the general population and up to 90 percent of persons previously diagnosed with asthma have exercise-induced bronchoconstriction. Common symptoms include coughing, wheezing, and chest tightness with exercise; however, many athletes will present with nonspecific symptoms, such as fatigue and impaired performance. Spirometry should be performed initially to evaluate for underlying chronic asthma, although results are often normal. An empiric trial of short-acting beta 2 agonists or additional bronchial provocation testing may be necessary to confirm the diagnosis. Nonpharmacologic treatment options include avoiding known triggers, choosing sports with low minute ventilation, warming up before exercising, and wearing a heat exchange mask in cold weather. Short-acting beta 2 agonists are recommended first-line agents for pharmacologic treatment, although leukotriene receptor antagonists or inhaled corticosteroids with or without long-acting beta 2 agonists may be needed in refractory cases. If symptoms persist despite treatment, alternative diagnoses such as cardiac or other pulmonary etiologies, vocal cord dysfunction, or anxiety should be considered.

The discovery rate of optical transients will explode to 10 million public alerts per night once the Vera C. Rubin Observatory's Legacy Survey of Space and Time comes online, overwhelming the traditional physics-based inference pipelines. A continuous-time forecasting AI model is of interest because it can deliver millisecond-scale inference for thousands of objects per day, whereas legacy MCMC codes need hours per object. In this paper, we propose SELDON, a new continuous-time variational autoencoder for panels of sparse and irregularly time-sampled (gappy) astrophysical light curves that are nonstationary, heteroscedastic, and inherently dependent. SELDON combines a masked GRU-ODE encoder with a latent neural ODE propagator and an interpretable Gaussian-basis decoder. The encoder learns to summarize panels of imbalanced and correlated data even when only a handful of points are observed. The neural ODE then integrates this hidden state forward in continuous time, extrapolating to future unseen epochs. This extrapolated time series is further encoded by deep sets to a latent distribution that is decoded to a weighted sum of Gaussian basis functions, the parameters of which are physically meaningful. Such parameters (e.g., rise time, decay rate, peak flux) directly drive downstream prioritization of spectroscopic follow-up for astrophysical surveys. Beyond astronomy, the architecture of SELDON offers a generic recipe for interpretable and continuous-time sequence modeling in any time domain where data are multivariate, sparse, heteroscedastic, and irregularly spaced.