Integration of CFD Methods into Concurrent Design of Internal Combustion Engine

This paper describes patterns of algorithms for different innovative levels of design at parametric, configuration and conceptual levels. They can be applied to Computer-aided Engine Design (CED). Data structures, process simulation hierarchy, engine simulation modules and the requirements for further development are described. An example of advanced thermodynamics modeling of combustion engines is included

Complicated variations of early optical afterglow of GRB 090726

We report on a detection of an early rising phase of optical afterglow (OA) of a long GRB 090726. We resolve a complicated profile of the optical light curve. We also investigate the relation of the optical and X-ray emission of this event. We make use of the optical photometry of this OA obtained by the 0.5 m telescope of AI AS CR, supplemented by the data obtained by other observers, and the X-ray Swift/XRT data. The optical emission peaked at ~ 17.5 mag (R) at t-T0 ~ 500 s. We find a complex profile of the light curve during the early phase of this OA: an approximately power-law rise, a rapid transition to a plateau, a weak flare superimposed on the center of this plateau, and a slowly steepening early decline followed by a power-law decay. We discuss several possibilities to explain the short flare on the flat top of the optical light curve at t-T0 ~ 500 s; activity of the central engine is favored although reverse shock cannot be ruled out. We show that power-law outflow with Theta_obs/Theta_c > 2.5 is the best case for OA of GRB 090726. The initial Lorentz factor is Gamma_0 ~ 230-530 in case of propagation of the blast wave in a homogeneous medium, while propagation of this wave in a wind environment gives Gamma_0 ~ 80-300. The value of Gamma_0 in GRB 090726 thus falls into the lower half of the range observed in GRBs and it may even lie on the lower end. We also show that both the optical and X-ray emission decayed simultaneously and that the spectral profile from X-ray to the optical band did not vary. This OA belongs to the least luminous ones in the phase of its power-law decay corresponding to that observed for the ensemble of OAs of long GRBs.Comment: 5 pages, 5 figures, accepted to A&

Europe-wide spatial trends in copper and imidacloprid sensitivity of macroinvertebrate assemblages

Exposure to synthetic chemicals, such as pesticides and pharmaceuticals, affects freshwater communities at broad spatial scales. This risk is commonly managed in a prospective environmental risk assessment (ERA). Relying on generic methods, a few standard test organisms, and safety factors to account for uncertainty, ERA determines concentrations that are assumed to pose low risks to ecosystems. Currently, this procedure neglects potential variation in assemblage sensitivity among ecosystem types and recommends a single low-risk concentration for each compound. Whether systematic differences in assemblage sensitivity among ecosystem types exist or their size, are currently unknown. Elucidating spatial patterns in sensitivity to chemicals could therefore enhance ERA precision and narrow a fundamental knowledge gap in ecology, the Hutchinsonian shortfall. We analyzed whether taxonomic turnover between field-sampled macroinvertebrate assemblages of different broad river types across Europe results in systematic differences in assemblage sensitivity to copper and imidacloprid. We used an extensive database of macroinvertebrate assemblage compositions throughout Europe and employed a hierarchical species sensitivity distribution model to predict the concentration that would be harmful to 5% of taxa (HC5) in each assemblage. Predicted $$H{C}_{5}$$ H C 5 values varied over several orders of magnitude. However, variation within the 95% highest density intervals remained within one order of magnitude. Differences between the river types were minor for imidacloprid and only slightly higher for copper. The largest difference between river-type-specific median $$H{C}_{5}$$ H C 5 values was a factor of 3.1. This level of variation is below the assessment factors recommended by the European Food Safety Authority and therefore would be captured in the current ERA for plant protection products. We conclude that the differences in taxonomic composition between broad river types translate into relatively small differences in macroinvertebrate assemblage sensitivity toward the evaluated chemicals at the European scale. However, systematic differences in bioavailability and multi-stressor context were not evaluated and might exacerbate the differences in the ecological effects of chemicals among broad river types in real-world ecosystems

Multi-decadal improvements in the ecological quality of European rivers are not consistently reflected in biodiversity metrics

Humans impact terrestrial, marine and freshwater ecosystems, yet many broad-scale studies have found no systematic, negative biodiversity changes (for example, decreasing abundance or taxon richness). Here we show that mixed biodiversity responses may arise because community metrics show variable responses to anthropogenic impacts across broad spatial scales. We first quantified temporal trends in anthropogenic impacts for 1,365 riverine invertebrate communities from 23 European countries, based on similarity to least-impacted reference communities. Reference comparisons provide necessary, but often missing, baselines for evaluating whether communities are negatively impacted or have improved (less or more similar, respectively). We then determined whether changing impacts were consistently reflected in metrics of community abundance, taxon richness, evenness and composition. Invertebrate communities improved, that is, became more similar to reference conditions, from 1992 until the 2010s, after which improvements plateaued. Improvements were generally reflected by higher taxon richness, providing evidence that certain community metrics can broadly indicate anthropogenic impacts. However, richness responses were highly variable among sites, and we found no consistent responses in community abundance, evenness or composition. These findings suggest that, without sufficient data and careful metric selection, many common community metrics cannot reliably reflect anthropogenic impacts, helping explain the prevalence of mixed biodiversity trends.We thank J. England for assistance with calculating ecological quality and the biomonitoring indices in the UK. Funding for authors, data collection and processing was provided by the European Union Horizon 2020 project eLTER PLUS (grant number 871128). F.A. was supported by the Swiss National Science Foundation (grant numbers 310030_197410 and 31003A_173074) and the University of Zurich Research Priority Program Global Change and Biodiversity. J.B. and M.A.-C. were funded by the European Commission, under the L‘Instrument Financier pour l’Environnement (LIFE) Nature and Biodiversity program, as part of the project LIFE-DIVAQUA (LIFE18 NAT/ES/000121) and also by the project ‘WATERLANDS’ (PID2019-107085RB-I00) funded by the Ministerio de Ciencia, Innovación y Universidades (MCIN) and Agencia Estatal de Investigación (AEI; MCIN/AEI/10.13039/501100011033/ and by the European Regional Development Fund (ERDF) ‘A way of making Europe’. N.J.B. and V.P. were supported by the Lithuanian Environmental Protection Agency (https://aaa.lrv.lt/) who collected the data and were funded by the Lithuanian Research Council (project number S-PD-22-72). J.H. was supported by the Academy of Finland (grant number 331957). S.C.J. acknowledges funding by the Leibniz Competition project Freshwater Megafauna Futures and the German Federal Ministry of Education and Research (Bundesministerium für Bildung und Forschung or BMBF; 033W034A). A.L. acknowledges funding by the Spanish Ministry of Science and Innovation (PID2020-115830GB-100). P.P., M.P. and M.S. were supported by the Czech Science Foundation (GA23-05268S and P505-20-17305S) and thank the Czech Hydrometeorological Institute and the state enterprises Povodí for the data used to calculate ecological quality metrics from the Czech surface water monitoring program. H.T. was supported by the Estonian Research Council (number PRG1266) and by the Estonian national program ‘Humanitarian and natural science collections’. M.J.F. acknowledges the support of Fundação para a Ciência e Tecnologia, Portugal, through the projects UIDB/04292/2020 and UIDP/04292/2020 granted to the Marine and Environmental Sciences Centre, LA/P/0069/2020 granted to the Associate Laboratory Aquatic Research Network (ARNET), and a Call Estímulo ao Emprego Científico (CEEC) contract.Peer reviewe