富锂巨星的观测研究

锂在温度达到T＞2.5×106 K时即参与7Li(p,α)4He反应燃烧,经典恒星理论推测,当恒星演化到红巨星阶段时,由于向内非常延伸的对流包层的存在,锂的丰度A(Li)=12+ lg[n(Li)/n(H)]应为A(Li)＜0.5.但是,陆续有处于不同光谱型、不同演化阶段的富锂巨星被发现,其中一些巨星的锂丰度甚至远超出宇宙大爆炸的原初锂丰度,给经典恒星演化模型带来了难题.回顾了从恒星主序到巨星支的锂丰度观测研究历史,并详细介绍了我们对银河系矮星系中富锂巨星的最新发现,总结了所有富锂巨星的观测证据,以及为解决此难题所提出的理论解释.     

Power spectrum for the small-scale Universe

The first objects to arise in a cold dark matter (CDM) universe present a daunting challenge for models of structure formation. In the ultra small-scale limit, CDM structures form nearly simultaneously across a wide range of scales. Hierarchical clustering no longer provides a guiding principle for theoretical analyses and the computation time required to carry out credible simulations becomes prohibitively high. To gain insight into this problem, we perform high-resolution  ( N = 720³–1584³)  simulations of an Einstein–de Sitter cosmology where the initial power spectrum is   P ( k ) ∝ k ⁿ ,  with  −2.5 ≤ n ≤− 1  . Self-similar scaling is established for   n =−1  and −2 more convincingly than in previous, lower resolution simulations and for the first time, self-similar scaling is established for an   n =−2.25  simulation. However, finite box-size effects induce departures from self-similar scaling in our   n =−2.5  simulation. We compare our results with the predictions for the power spectrum from (one-loop) perturbation theory and demonstrate that the renormalization group approach suggested by McDonald improves perturbation theory's ability to predict the power spectrum in the quasi-linear regime. In the non-linear regime, our power spectra differ significantly from the widely used fitting formulae of Peacock & Dodds and Smith et al. and a new fitting formula is presented. Implications of our results for the stable clustering hypothesis versus halo model debate are discussed. Our power spectra are inconsistent with predictions of the stable clustering hypothesis in the high- k limit and lend credence to the halo model. Nevertheless, the fitting formula advocated in this paper is purely empirical and not derived from a specific formulation of the halo model.     

The relative role of constructive and destructive processes in dune evolution on Cape Lookout National Seashore,North Carolina,USA

Coastal dunes are dynamic features that are continuously evolving due to constructive (e.g., wind- and wave-driven sediment transport) and destructive (e.g., elevated total water levels during storm events) processes. However, the relative importance of these processes in determining dune evolution is often poorly understood. In this study, ten lidar datasets from 1997 to 2016 are used to determine the relative role of erosion and accretion processes driving foredune change on the coast of Cape Lookout National Seashore, North Carolina, USA. Beach and dune morphometrics reveal that dune toe locations have generally retreated since 1997, while dune crest heights accreted by 0.01–0.02 m/year. We develop three univariate metrics that represent (1) the potential for erosion, i.e., total water level impact hours per year, (2) accretion, i.e., dune building hours per year, and (3) the relative net effect of foredune accretion and erosion processes, i.e., constructive–destructive dune forcing (CDDF) ratio, and test the correlative power of these metrics in explaining changes in foredune morphology. The total water level impact hours per year metric explained as much as 66% and 67% of the variance in dune crest and toe elevations, respectively, across the nearly two decades of dune evolution. The greatest number of dune building hours per year and largest dunes within the study site co-occurred at locations exposed to the dominant cross-shore wind direction as a result of varying shoreline orientation. The CDDF ratio was positively correlated to changes in the dune toe elevation in approximately 70% of dunes within the study site, outperforming the impact and dune building hours per year metrics. Our results show that these three metrics can provide first-order estimates of dune morphometric change across multiple spatial and temporal scales, which may be particularly useful at sites where lidar acquisition is intermittent.     

Climate-induced primary productivity change and fishing impacts on the Central North Pacific ecosystem and Hawaii-based pelagic longline fishery

An existing Ecopath with Ecosim (EwE) model for the Central North Pacific was updated and modified to focus on the area used by the Hawaii-based pelagic longline fishery. The EwE model was combined with output from a coupled NOAA Geophysical Fluid Dynamics Laboratory climate and biogeochemical model to investigate the likely ecosystem impacts of fishing and climate-induced primary productivity changes. Four simulations were conducted based on 2 fishing effort and climate scenarios from 2010 to 2100. Modeled small and large phytoplankton biomass decreased by 10 % and 20 % respectively, resulting in a 10 % decline in the total biomass of all higher trophic level groups combined. Climate impacts also affected the Hawaii longline fishery, with a 25–29 % reduction in modeled target species yield. Climate impacts on the ecosystem and the fishery were partially mitigated by a drop in fishing effort. Scenarios with a 50 % reduction in fishing effort partially restored longline target species yield to current levels, and decreased longline non-target species yield. These model results suggest that a further reduction in fishery landings mortality over time than the 2010 level may be necessary to mitigate climate impacts and help sustain yields of commercially preferred fish species targeted by the Hawaii longline fishery through the 21st century.     

A Practical Approach to Shallow Petroleum Hydrocarbon Recovery

A practical pumping system for the recovery of free petroleum hydrocarbon product from shallow aquifers has been developed. The system is patterned after suction-lift well point dewatering systems used in the construction industry. Pumping equipment consists of double-diaphragm suction-lift pumps manifolded to up to four recovery wells. Recovery wells are constructed with screens below the water table and sealed wellheads to enable vacuum-assisted flow of fluids to the wells. Pumps utilized are pneumatically driven, can be pumped dry without damage, induce a vacuum on the wells when pumping dry, and provide delivery of pumped fluids to fluid separation and storage facilities. The system is effective in both low- and high-permeability formations due to the wide range in available pumping rates afforded by the pumps.     

Identifying Synergy Between Remedial Strategies and Land Reuse

"Today the environmental professional teams with the developer to use remedial technologies and approaches that complement planned land use and, conversely, use land in a fashion that accommodates environmental site conditions."     

The influence of thermal and cyclic stressing on the strength of rocks from Mount St. Helens, Washington

Stratovolcanoes and lava domes are particularly susceptible to sector collapse resulting from wholesale rock failure as a consequence of decreasing rock strength. Here, we provide insights into the influence of thermal and cyclic stressing on the strength and mechanical properties of volcanic rocks. Specifically, this laboratory study examines the properties of samples from Mount St. Helens; chosen because its strength and stability have played a key role in its history, influencing the character of the infamous 1980 eruption. We find that thermal stressing exerts different effects on the strengths of different volcanic units; increasing the heterogeneity of rocks in situ. Increasing the uniaxial compressive stress generates cracking, the timing and magnitude of which was monitored via acoustic emission (AE) output during our experiments. AEs accelerated in the approach to failure, sometimes following the pattern predicted by the failure forecast method (Kilburn 2003). Crack damage during the experiments was tracked using the evolving static Young’s modulus and Poisson’s ratio, which represent the quasi-static deformation in volcanic edifices more accurately than dynamic elastic moduli which are usually implemented in volcanic models. Cyclic loading of these rocks resulted in a lower failure strength, confirming that volcanic rocks may be weakened by repeated inflation and deflation of the volcanic edifice. Additionally, volcanic rocks in this study undergo significant elastic hysteresis; in some instances, a material may fail at a stress lower than the peak stress which has previously been endured. Thus, a volcanic dome repeatedly inflated and deflated may progressively weaken, possibly inducing failure without necessarily exceeding earlier conditions.     

Neural network simulation of spring flow in karst environments

Daily discharges of two springs lying in a karstic environment were simulated for a period of 2.5 years with the use of a multi-layer perceptron back-propagation neural network. Two models were developed for the springs, one relying on the original data and another where the missing discharge values were supplemented by assuming linear relationships during base flow conditions. For both springs the mean square error of the two models did not differ significantly, with an improvement exhibited at the extremes, during the network’s training phase, by the model that utilized the extended data set, the results of which are reported here. The time lag between precipitation and spring discharge differed significantly for the two springs indicating that in karstic environments hydraulic behavior is dominated, even within a few hundred meters, by local conditions. Optimum training results were attained with a Levenberg–Marquardt algorithm resulting in a network architecture consisting of two input layer neurons, four hidden layer neurons, and one output layer neuron, the spring’s discharge. The neural network’s predictions captured the behavior for both springs and followed very closely the discontinuities in the discharge time series. Under-/over-estimation of observed discharges for the two springs remained below 3 %, with the exception of a few local maxima where the predicted discharges diverged more strongly from observed values. Inclusion of temperature data did not add to the improvement of predictions. Finally, optimum predictions were attained when past discharge data were added to the input record and discharge differentials rather than direct discharges were calculated resulting in elimination of any local maximum discrepancy between observed and predicted discharge values.