Ballistic performance of nanocrystalline and nanotwinned ultrafine crystal steel

Because of their remarkable mechanical properties, nanocrystalline metals have been the focus of much research in recent years. Refining their grain size to the nanometer range (<100 nm) effectively reduces their dislocation mobility, thus achieving very high yield strength and surface hardness—as predicted by the Hall–Petch relation—as well as higher strain-rate sensitivity. Recent works have additionally suggested that nanocrystalline metals exhibit an even higher compressive strength under shock loading. However, the increase in strength of these materials is generally accompanied by an important reduction in ductility. As an alternative, efforts have been focused on ultrafine crystals, i.e. polycrystals with a grain size in the range of 500 nm to 1 μm, in which “growth twins” (twins introduced inside the grain before deformation) act as barriers against dislocation movement, thus increasing the strength in a similar way as nanocrystals but without significant loss of ductility. Due to their outstanding mechanical properties, both nanocrystalline and nanotwinned ultrafine crystalline steels appear to be relevant candidates for ballistic protection. The aim of the present work is to compare their ballistic performance against coarse-grained steel, as well as to identify the effect of the hybridization with a carbon fiber–epoxy composite layer. Hybridization is proposed as a way to improve the nanocrystalline brittle properties in a similar way as is done with ceramics in other protection systems. The experimental campaign is finally complemented by numerical simulations to help identify some of the intrinsic deformation mechanisms not observable experimentally. As a conclusion, nanocrystalline and nanotwinned ultrafine crystals show a lower energy absorption than coarse-grained steel under ballistic loading, but under equal impact conditions with no penetration, deformation in the impact direction is smaller by nearly 40%. This a priori surprising difference in the energy absorption is rationalized by the more important local contribution of the deviatoric stress vs. volumetric stress under impact than under uniaxial deformation. Ultimately, the deformation advantage could be exploited in the future for personal protection systems where a small deformation under impact is of key importance

Multi-scale Inference of Interaction Rules in Animal Groups Using Bayesian Model Selection

Inference of interaction rules of animals moving in groups usually relies on an analysis of large scale system behaviour. Models are tuned through repeated simulation until they match the observed behaviour. More recent work has used the fine scale motions of animals to validate and fit the rules of interaction of animals in groups. Here, we use a Bayesian methodology to compare a variety of models to the collective motion of glass prawns (Paratya australiensis). We show that these exhibit a stereotypical ‘phase transition’, whereby an increase in density leads to the onset of collective motion in one direction. We fit models to this data, which range from: a mean-field model where all prawns interact globally; to a spatial Markovian model where prawns are self-propelled particles influenced only by the current positions and directions of their neighbours; up to non-Markovian models where prawns have ‘memory’ of previous interactions, integrating their experiences over time when deciding to change behaviour. We show that the mean-field model fits the large scale behaviour of the system, but does not capture fine scale rules of interaction, which are primarily mediated by physical contact. Conversely, the Markovian self-propelled particle model captures the fine scale rules of interaction but fails to reproduce global dynamics. The most sophisticated model, the non-Markovian model, provides a good match to the data at both the fine scale and in terms of reproducing global dynamics. We conclude that prawns' movements are influenced by not just the current direction of nearby conspecifics, but also those encountered in the recent past. Given the simplicity of prawns as a study system our research suggests that self-propelled particle models of collective motion should, if they are to be realistic at multiple biological scales, include memory of previous interactions and other non-Markovian effects

Multi-objective optimization for optimum tolerance synthesis with process and machine selection using a genetic algorithm

This paper presents a new approach to the tolerance synthesis of the component parts of assemblies by simultaneously optimizing three manufacturing parameters: manufacturing cost, including tolerance cost and quality loss cost; machining time; and machine overhead/idle time cost. A methodology has been developed using the Genetic Algorithm (GA) technique to solve this multi-objective optimization problem. The effectiveness of the proposed methodology has been demonstrated by solving a wheel mounting assembly problem consisting of five components, two subassemblies, two critical dimensions, two functional tolerances, and eight operations. Significant cost saving can be achieved by employing this methodology

Study of e+e−→ppˉe^+e^- \rightarrow p\bar{p} in the vicinity of ψ(3770)\psi(3770)

Using 2917 $\rm{pb}^{-1}$ of data accumulated at 3.773~$\rm{GeV}$, 44.5~$\rm{pb}^{-1}$ of data accumulated at 3.65~$\rm{GeV}$ and data accumulated during a $\psi(3770)$ line-shape scan with the BESIII detector, the reaction $e^+e^-\rightarrow p\bar{p}$ is studied considering a possible interference between resonant and continuum amplitudes. The cross section of $e^+e^-\rightarrow\psi(3770)\rightarrow p\bar{p}$, $\sigma(e^+e^-\rightarrow\psi(3770)\rightarrow p\bar{p})$, is found to have two solutions, determined to be ($0.059\pm0.032\pm0.012$) pb with the phase angle $\phi = (255.8\pm37.9\pm4.8)^\circ$ ($<$0.11 pb at the 90% confidence level), or $\sigma(e^+e^-\rightarrow\psi(3770)\rightarrow p\bar{p}) = (2.57\pm0.12\pm0.12$) pb with $\phi = (266.9\pm6.1\pm0.9)^\circ$ both of which agree with a destructive interference. Using the obtained cross section of $\psi(3770)\rightarrow p\bar{p}$, the cross section of $p\bar{p}\rightarrow \psi(3770)$, which is useful information for the future PANDA experiment, is estimated to be either ($9.8\pm5.7$) nb ($<17.2$ nb at 90% C.L.) or $(425.6\pm42.9)$ nb

Temperature increase reduces global yields of major crops in four independent estimates

Imbalance-P paper contact with: josep peñuelas: [email protected], rice, maize, and soybean provide two-thirds of human caloric intake. Assessing the impact of global temperature increase on production of these crops is therefore critical to maintaining global food supply, but different studies have yielded different results. Here, we investigated the impacts of temperature on yields of the four crops by compiling extensive published results from four analytical methods: global grid-based and local point-based models, statistical regressions, and field-warming experiments. Results from the different methods consistently showed negative temperature impacts on crop yield at the global scale, generally underpinned by similar impacts at country and site scales. Without CO2 fertilization, effective adaptation, and genetic improvement, each degree-Celsius increase in global mean temperature would, on average, reduce global yields of wheat by 6.0%, rice by 3.2%, maize by 7.4%, and soybean by 3.1%. Results are highly heterogeneous across crops and geographical areas, with some positive impact estimates. Multimethod analyses improved the confidence in assessments of future climate impacts on global major crops and suggest crop- and region-specific adaptation strategies to ensure food security for an increasing world population