Detecting Delamination via Nonlinear Wave Scattering in a Bonded Elastic Bar

In this paper we examine the effect of delamination on wave scattering, with the aim of creating a control measure for layered waveguides of various bonding types. Previous works have considered specific widths of solitary waves for the simulations, without analysing the effect of changing the soliton parameters. We consider two multi-layered structures: one containing delamination "sandwiched" by perfect bonding and one containing delamination but "sandwiched" by soft bonding. These structures are modelled by coupled Boussinesq-type equations. Matched asymptotic multiple-scale expansions lead to coupled Ostrovsky equations in soft bonded regions and Korteweg-De Vries equations in the perfectly bonded and delaminated region. We use the Inverse Scattering Transform to predict the behaviour in the delaminated regions. In both cases, numerical analysis shows that we can predict the delamination length by changes in the wave structure, and that these changes depend upon the Full Width at Half Magnitude (FWHM) of the incident soliton. In the case of perfect bonding, we derive a theoretical prediction for the change and confirm this numerically. For the soft bonding case, we numerically identify a similar relationship using the change in amplitude. Therefore we only need to compute one curve to determine the behaviour for any incident solitary wave, creating a framework for designing measurement campaigns for rigorously testing the integrity of layered structures.Comment: 12 pages, 7 figure

Atmospheric Density Uncertainty Quantification for Satellite Conjunction Assessment

Conjunction assessment requires knowledge of the uncertainty in the predicted orbit. Errors in the atmospheric density are a major source of error in the prediction of low Earth orbits. Therefore, accurate estimation of the density and quantification of the uncertainty in the density is required. Most atmospheric density models, however, do not provide an estimate of the uncertainty in the density. In this work, we present a new approach to quantify uncertainties in the density and to include these for calculating the probability of collision Pc. For this, we employ a recently developed dynamic reduced-order density model that enables efficient prediction of the thermospheric density. First, the model is used to obtain accurate estimates of the density and of the uncertainty in the estimates. Second, the density uncertainties are propagated forward simultaneously with orbit propagation to include the density uncertainties for Pc calculation. For this, we account for the effect of cross-correlation in position uncertainties due to density errors on the Pc. Finally, the effect of density uncertainties and cross-correlation on the Pc is assessed. The presented approach provides the distinctive capability to quantify the uncertainty in atmospheric density and to include this uncertainty for conjunction assessment while taking into account the dependence of the density errors on location and time. In addition, the results show that it is important to consider the effect of cross-correlation on the Pc, because ignoring this effect can result in severe underestimation of the collision probability.Comment: 15 pages, 6 figures, 5 table

How Many Species Are There on Earth and in the Ocean?

The diversity of life is one of the most striking aspects of our planet; hence knowing how many species inhabit Earth is among the most fundamental questions in science. Yet the answer to this question remains enigmatic, as efforts to sample the world's biodiversity to date have been limited and thus have precluded direct quantification of global species richness, and because indirect estimates rely on assumptions that have proven highly controversial. Here we show that the higher taxonomic classification of species (i.e., the assignment of species to phylum, class, order, family, and genus) follows a consistent and predictable pattern from which the total number of species in a taxonomic group can be estimated. This approach was validated against well-known taxa, and when applied to all domains of life, it predicts ∼8.7 million (±1.3 million SE) eukaryotic species globally, of which ∼2.2 million (±0.18 million SE) are marine. In spite of 250 years of taxonomic classification and over 1.2 million species already catalogued in a central database, our results suggest that some 86% of existing species on Earth and 91% of species in the ocean still await description. Renewed interest in further exploration and taxonomy is required if this significant gap in our knowledge of life on Earth is to be closed

Designing eco-evolutionary experiments for restoration projects: Opportunities and constraints revealed during stickleback introductions.

Eco-evolutionary experiments are typically conducted in semi-unnatural controlled settings, such as mesocosms; yet inferences about how evolution and ecology interact in the real world would surely benefit from experiments in natural uncontrolled settings. Opportunities for such experiments are rare but do arise in the context of restoration ecology-where different "types" of a given species can be introduced into different "replicate" locations. Designing such experiments requires wrestling with consequential questions. (Q1) Which specific "types" of a focal species should be introduced to the restoration location? (Q2) How many sources of each type should be used-and should they be mixed together? (Q3) Which specific source populations should be used? (Q4) Which type(s) or population(s) should be introduced into which restoration sites? We recently grappled with these questions when designing an eco-evolutionary experiment with threespine stickleback (Gasterosteus aculeatus) introduced into nine small lakes and ponds on the Kenai Peninsula in Alaska that required restoration. After considering the options at length, we decided to use benthic versus limnetic ecotypes (Q1) to create a mixed group of colonists from four source populations of each ecotype (Q2), where ecotypes were identified based on trophic morphology (Q3), and were then introduced into nine restoration lakes scaled by lake size (Q4). We hope that outlining the alternatives and resulting choices will make the rationales clear for future studies leveraging our experiment, while also proving useful for investigators considering similar experiments in the future

Marine Biodiversity in the Australian Region

The entire Australian marine jurisdictional area, including offshore and sub-Antarctic islands, is considered in this paper. Most records, however, come from the Exclusive Economic Zone (EEZ) around the continent of Australia itself. The counts of species have been obtained from four primary databases (the Australian Faunal Directory, Codes for Australian Aquatic Biota, Online Zoological Collections of Australian Museums, and the Australian node of the Ocean Biogeographic Information System), but even these are an underestimate of described species. In addition, some partially completed databases for particular taxonomic groups, and specialized databases (for introduced and threatened species) have been used. Experts also provided estimates of the number of known species not yet in the major databases. For only some groups could we obtain an (expert opinion) estimate of undiscovered species. The databases provide patchy information about endemism, levels of threat, and introductions. We conclude that there are about 33,000 marine species (mainly animals) in the major databases, of which 130 are introduced, 58 listed as threatened and an unknown percentage endemic. An estimated 17,000 more named species are either known from the Australian EEZ but not in the present databases, or potentially occur there. It is crudely estimated that there may be as many as 250,000 species (known and yet to be discovered) in the Australian EEZ. For 17 higher taxa, there is sufficient detail for subdivision by Large Marine Domains, for comparison with other National and Regional Implementation Committees of the Census of Marine Life. Taxonomic expertise in Australia is unevenly distributed across taxa, and declining. Comments are given briefly on biodiversity management measures in Australia, including but not limited to marine protected areas

Building Partnerships to Address Social and Technological Challenges to Enhance Farm Profitability and Improve Water Quality Through Better Grassland Management

With 2.1 million acres of pastureland and 1.25 million acres of hay land in Virginia, the rural Virginia landscape is predominately grassland. These lands form the base of the $3.96 billion-dollar livestock and dairy industry in Virginia. Managing these livestock in a profitable manner for farmers and beneficial to the environment is important. A cultural tradition with roots in colonial times has been to run animals in large fields year-round throughout Virginia. Livestock often graze from spring until fall (about 220 days), and farmers feed hay the remainder of the year. Spikes in the cost of fuel, fertilizer, and equipment are making traditional grazing/haying systems less profitable. The Virginia Cooperative Extension Farm Enterprise budgets show that that the cost of hay accounts for over 50$75 per cow by extending their grazing season. The same phenomenon applies to other types of grazing livestock. If ten percent of the livestock producers in the state adopted better grazing management to extend their grazing season by 60 days, profitability is expected for Virginia grazing livestock producers by over $5 million per year. Practices such as rotational grazing and stream exclusion are directly tied to National and State goals to improve water quality in the Chesapeake Bay. Virginia’s Phase III WIP (Chesapeake Bay Watershed Improvement Plan) seeks the exclusion of livestock from all perennial streams and achieving good rotational grazing practices on 347,000 acres of pasture. A number of agencies and private sector groups have been providing cost share and technical guidance to incentivize livestock stream exclusion and the installation of pasture management infrastructure. Installation is only part of the challenge. Farmers also need to be taught how to how to manage the system in a profitable manner and have been slow to adopt good pasture management practices. Preliminary data show that 87% of Virginia’s cow-calf producers manage their grasslands using traditional methods. Only six percent have extended their grazing season beyond 265 days