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AbstractThe English language has adopted the word Tardis for something that looks simple from the outside but is much more complicated when inspected from the inside. The word comes from a BBC science fiction series, in which the Tardis is a machine for traveling in time and space, that looks like a phone booth from the outside. This paper claims that simulation models are a Tardis in a way that calls into question their transferability. The argument is developed taking Molecular Modeling and Simulation as an example. There, simulation models are force fields that describe the molecular interactions and that look like simple and highly modular mathematical expressions. To make them work, they contain parameters that are adjusted to match certain data. The role of these parameters and the way they are obtained is seriously under-appreciated. It is constitutive for the model and central for its applicability and performance. Hence, the model is more than it seems so that working with adjustable parameters deeply affects the ontology of simulation models. This is particularly crucial for the transferability of the models: the information on how a model was trained is like luggage the model must carry on its voyage.

A coordinate system parameterizing the interior of organs is/na powerful tool for a systematic localization of injured tissue. If the same/ncoordinate values are assigned to speci c anatomical sites, parameterizations/nensure integration of data across di erent medical image modalities./nHarmonic mappings have been used to produce parametric meshes over/nthe surface of anatomical shapes, given their /nexibility to set values at/nspeci c locations through boundary conditions. However, most of the existing/nimplementations in medical imaging restrict to either anatomical/nsurfaces, or the depth coordinate with boundary conditions is given at/nsites of limited geometric diversity. In this paper we present a method for/nanatomical volumetric parameterization that extends current harmonic/nparameterizations to the interior anatomy using information provided by/nthe volume medial surface. We have applied the methodology to de ne/na common reference system for the liver shape and functional anatomy./nThis reference system sets a solid base for creating anatomical models of/nthe patient's liver, and allows comparing livers from several patients in/na common framework of reference. ; This research has been funded by the Catalan project 2009-TEM-00007, Spanish/nprojects TIN2009-13618, TIN2012-3311, and the European Union FP7 grant agreement/nno. HEAR-EU 304857

Unmanned aerial vehicles (UAVs) represent an increasingly important and prolific technology in today's world,finding use in myriad applications across multiple domains, including civil, commercial, military, and researchenvironments. Control of these aircraft requires fundamental information on the vehicle's position and orientation inspace. Attitude determination algorithms calculate this spatial orientation by propagating the attitude kinematicequations that estimate the current attitude based on previous estimates along with information about the vehicle's angularvelocities. Within the domain of low-cost UAVs, numerous options exist for the choice of 1) propagation algorithms, 2) attitude representation, and 3) the assumptions about the behavior of the angular velocity vector between samples withinthe discrete-time hardware of the embedded system typically running the estimation algorithms. This thesis examines theimpact of these three variables upon propagatedattitude estimates with respect to accuracy, computational efficiency, and noise response. Noise response is evaluated interms of the algorithm's ability to track an underlying clean signal in spite of inputs corrupted by additive Gaussiannoise. Various propagation methods are evaluated across four attitude representations: the direction cosine matrix, Eulerangles, quaternions, and the angle-axis or eigen-axis parameterization. Lastly, the nature of angular velocity (constant,linear, and quadratic) is evaluated in terms of accuracy, computational efficiency, and noise resilience.The algorithms were tested using simulated angular velocity inputs from analytic functions as well as flight test data fromlow-cost, fixed wing UAVs. Implementation was done in Matlab as well as Simulink-based test modules to evaluate algorithmperformance.The quaternion parameterization proved most beneficial across all three test metrics, though theDCM representation was only slightly deficient in terms of computational load. Matrix exponential propagation methodsoffered higher accuracy and better noise response than direct integration using the first-orderEuler method, though the latter offered better computational efficiency. For low-cost UAV applications, where MEMS-basedsensors have large noise on the gyros, a DCM parameterizationusing the matrix exponential with linear fit to the data gives the best results for reasonable computation. This isespecially true when using either magnetometer or accelerometer feedback into the attitude filter for biaselimination.

AbstractLeast squares estimators of the parameters of the generalized Eyring Model are obtained by using data from censored life tests conducted at several accelerated environments. These estimators are obtained after establishing that the Gauss‐Markov conditions for least squares estimation are satisfied. Confidence intervals for the hazard rate at use conditions are obtained after empirically showing that the logarithm of the estimate of the hazard rate at use conditions is approximately normally distributed. The coverage probabilities of the confidence intervals are also verified by a Monte Carlo experiment. The techniques are illustrated by an application to some real data.

The Weather Research and Forecasting model (WRF), like other numerical models, can make use of several parameterization schemes. The purpose of this study is to determine how available cumulus parameterization (CP) and microphysics (MP) schemes in the WRF model simulate extreme precipitation events in the Basque Country. Possible combinations among two CP schemes (Kain–Fritsch and Betts–Miller–Janjic) and five MP (WSM3, Lin, WSM6, new Thompson and WDM6) schemes were tested. A set of simulations, corresponding to 21st century extreme precipitation events that have caused significant flood episodes have been compared with point observational data coming from the Basque Country Automatic Weather Station Mesonetwork. Configurations with Kain–Fritsch CP scheme produce better quantity of precipitation forecast (QPF) than BMJ scheme configurations. Depending on the severity level and the river basin analysed different MP schemes show the best behaviours, demonstrating that there is not a unique configuration that solve exactly all the studied events. ; The authors would like to thank the 100–120 50 Emergencies and Meteorology Directorate – Security Department – Basque Government for public provision of data and operational service financial support.

A seismic traveltime inversion method is proposed for building smooth velocity models using traveltime observed on irregular surface. Model parameterization in this study is described by a piecewise constant velocity field on a rectangular grid parameterized by sigmodal functions, which is beneficial for the description of irregular surface with high degree of approximation. The velocity field is defined in the rectangular grid which is used for the description of velocity distribution everywhere in the model sigmoidal interpolation. In addition, we use the simple Genetic Algorithm for the inversion procedure. Through this global scope inversion method, we provide high-resolution estimates of the model parameter and ensure that the results obtained are in accordance with the actual data. Our method is validated with synthetic examples of heterogeneous isotropic media and compared to Simulating Annealing. The inverted velocity models and approximate ray paths obtained coincide well with the trajectories simulated using the seismic ray tracing in synthetic heterogeneous isotropic media.

Quantifying groundwater recharge in crystalline rocks presents great difficulties due to the high heterogeneity of the underground medium (mainly, due to heterogeneity in fracture network, which determines hydraulic parameters of the bedrock like hydraulic conductivity or effective porosity). Traditionally these rocks have been considered to have very low permeability, and their groundwater resources have usually been neglected; however, they can be of local importance when the bedrock presents a net of well-developed fractures. The current European Water Framework Directive requires an efficient management of all groundwater resources; this begins with a proper knowledge of the aquifer and accurate recharge estimation. In this study, an assessment of groundwater resources in the Spanish hydrologic district of Galicia-Costa, dominated by granitic and metasedimentary rocks, was carried out. A water-balance modeling approach was used for estimating recharge rates in nine pilot catchments representatives of both geologic materials. These results were cross-validated with an independent technique, i.e. the chloride mass balance (CMB). A relation among groundwater recharge and annual precipitation according to two different logistic curves was found for both granites and metasedimentary rocks, thus allowing the parameterization of recharge by means of only a few hydrogeological parameters. Total groundwater resources in Galicia-Costa were estimated to be 4427 hm3 yr−1. An analysis of spatial and temporal variability of recharge was also carried out. ; This work has been co-funded by Augas de Galicia and the Galician government Xunta de Galicia, within the framework of research project INCITE09 203 072 PR and by the European Regional Development Fund (ERDF). The first author has been granted a F.P.U. fellowship by the Spanish Ministry of Education ; SI

We complement the NEMO stochastic modules to calculate explicitly variable 2D spatial scales. The FORTRAN subroutine integrated within the "stopar.F90" module is compatible with the NEMO MPI environment. Acknowledgments. This work was carried out as part of the Copernicus Marine Environment Monitoring Service (CMEMS) "Stochastic Coastal/Regional Uncertainty Modelling" - SCRUM and SCRUM2 projects. CMEMS is implemented by Mercator Ocean International in the framework of a delegation agreement with the European Union. Part of this research was also made possible through the IKY Scholarships Programme and co-financed by the European Union (European Social Fund-ESF) and Greek national funds through the action entitled "Reinforcement of Postdoctoral Researchers", in the framework of the Operational Programme "Human Resources Development Programme, Education and Lifelong Learning" of the National Strategic Reference Framework (NSRF) 2014-2020. We acknowledge the use of ECMWF's computing and archive facilities in this research. This work was also supported by computational time granted from the Greek Research & Technology Network (GRNET) in the National HPC facility – ARIS – under project ID PA002007. cite: Vervatis, V.D., De Mey-Frémaux, P., Ayoub, N., Karagiorgos, J., Ghantous, M., Kailas, M., Testut, C.-E., and Sofianos, S., 2021. Assessment of a regional physical-biogeochemical stochastic ocean model. Part 1: ensemble generation, Ocean Modell., 160, 101781, https://doi.org/10.1016/j.ocemod.2021.101781 Vervatis, V.D., De Mey-Frémaux, P., Ayoub, N., Karagiorgos, J., Ciavatta, S., Brewin, R., and Sofianos, S., 2021. Assessment of a regional physical-biogeochemical stochastic ocean model. Part 2: empirical consistency. Ocean Modell., 160, 101770, https://doi.org/10.1016/j.ocemod.2021.101770

In the Arctic, air temperatures are warming and sea ice is declining, resulting in larger waves and a longer open water season, all of which intensify the thaw and erosion of ice-rich coasts. This change in climate has been shown to increase the rate of Arctic coastal erosion, causing problems for industrial, military, and civil infrastructure as well as changes in nearshore biogeochemistry. Numerical models that reproduce historical and project future Arctic erosion rates are necessary to understand how further climate change will affect these problems, and no such model yet exists to simulate the physics of erosion on a pan-Arctic scale. We have coupled a bathystrophic storm surge model to a simplified physical erosion model of a partially frozen cliff and beach. This Arctic erosion model, called ArcticBeach v1.0, is a first step toward a parameterization of Arctic shoreline erosion for larger-scale models, which are not able to resolve the fine spatial scale (up to about 40 m) needed to capture shoreline erosion rates from years to decades. It is forced by wind speeds and directions, wave period and height, sea surface temperature, all of which are masked during times of sea ice cover near the coastline. Model tuning requires observed historical retreat rates (at least one value), as well as rough nearshore bathymetry. These parameters are already available on a pan-Arctic scale. The model is validated at two study sites at Drew Point (DP), Alaska, and Mamontovy Khayata (MK), Siberia, which are respectively located in the Beaufort and Laptev Seas, on different sides of the Arctic Ocean. Simulated cumulative retreat rates for DP and MK respectively (169 and 170 m) over the time periods studied at each site (2007–2016, and 1995–2018) are found to be within the same order of magnitude as observed cumulative retreat rates (172 and 120 m). Given the large differences in geomorphology and weather systems between the two study sites, this study provides a proof-of-concept that ArcticBeach v1.0 can be applied on very different partially frozen coastlines. ArcticBeach v1.0 provides a promising starting point to project the retreat of Arctic shorelines, or to evaluate historical retreat in places that have had few observations. Further, this model can provide estimates of the flux of sediment from land to sea for Arctic nearshore biogeochemical studies, while leaving an opportunity for further development of modelling the physics of a partially frozen shoreline.