Feedstock powder processing research needs for additive manufacturing development

Additive manufacturing (AM) promises to redesign traditional manufacturing by enabling the ultimate in agility for rapid component design changes in commercial products and for fabricating complex integrated parts. By significantly increasing quality and yield of metallic alloy powders, the pace for design, development, and deployment of the most promising AM approaches can be greatly accelerated, resulting in rapid commercialization of these advanced manufacturing methods. By successful completion of a critical suite of processing research tasks that are intended to greatly enhance gas atomized powder quality and the precision and efficiency of powder production, researchers can help promote continued rapid growth of AM. Other powder-based or spray-based advanced manufacturing methods could also benefit from these research outcomes, promoting the next wave of sustainable manufacturing technologies for conventional and advanced materials.     

Duration of treatment with progesterone and regression of persistent ovarian follicles in cattle

The objective of the present study was to determine the duration of elevated concentrations of progesterone necessary to induce atresia of persistent ovarian follicles. Heifers were administered 25 mg of PGF2alpha on d 6 and 7 (d 0 = d of synchronized estrus) and a norgestomet implant from d 6 to 14. Ovaries were monitored by ultrasonography, and blood samples were collected on d 3, 5, 7, 9, 11, and 12 and daily from d 14 until ovulation. On d 12, heifers received either two progesterone-releasing intravaginal devices (PRID) for 6 h (6-h; n = 5), two PRID for 24 h (24-h; n = 5), or no treatment (CON; n = 5). Blood samples were collected at 15-min intervals from h -6 to 30 (PRID insertion = h 0) and analyzed for concentrations of LH. Characteristics of LH secretion were determined for consecutive 6-h periods (Period 0 to 5). Hourly blood samples, collected from h 0 to 29, were analyzed for concentrations of 17beta-estradiol (estradiol) and progesterone. The dominant ovarian follicles present on d 7 increased in size to 15.4+/-.3 mm on d 12 ("persistent follicle"). Following removal of the PRID and norgestomet implants, atresia of persistent follicles and ovulation of new follicles were induced in one of five and in four of five heifers in the 6-h and 24-h treatments, respectively. Persistent follicles ovulated after withdrawal of norgestomet in all other heifers. Concentrations of progesterone were increased from h 1 to 7 in the 6-h and h 1 to 26 in the 24-h treatment. Frequency of LH pulses was reduced (P < .05) during Periods 1 to 2 in the 6-h and Periods 1 to 5 in the 24-h treatment relative to the CON treatment. By h 10, concentrations of estradiol in the 6-h and 24-h treatments were lower (P < . 05) than in the CON treatment. This suppression continued through h 29 in the 24-h treatment (P < .05), whereas concentrations in the 6-h treatment were intermediate to those of the CON and 24-h treatments after h 14. Suppression of pulsatile LH release and estradiol secretion was evident with 6 and 24 h of treatment with progesterone, but only the 24-h treatment induced atresia of persistent follicles in a majority of the heifers.     

Genetic effects of 1,3-butadiene and associated risk for heritable damage

A summary of the results of the studies conducted in the EU Project "Multi-endpoint analysis of genetic damage induced by 1,3-butadiene and its major metabolites in somatic and germ cells of mice, rats and man" is presented. Results of the project are summarized on the detection of DNA and hemoglobin adducts, on the cytotoxic and clastogenic effects in somatic and germinal cells of mice and rats, on the induction of somatic mutations at the hprt locus of experimental rodents and occupationally exposed workers, on the induction of dominant lethal mutations in mice and rats, and on heritable translocations induced in mice, after exposure to butadiene (BD) or its major metabolites, butadiene monoepoxide (BMO), diepoxybutane (DEB) and butadiene diolepoxide (BDE). The primary goal of this project was to collect experimental data on the genetic effects of BD in order to estimate the germ cell genetic risk to humans of exposure to BD. To achieve this, the butadiene exposure are based on data for heritable translocations and bone marrow micronuclei induced in mice and chromosome aberrations observed in lymphocytes of exposed workers. A doubling dose for heritable translocations in human germ cells of 4900 ppm/h is estimated, which, assuming cumulative BD exposure over the sensitive period of spermatogenesis, corresponds to 5-6 weeks of continuous exposure at the workplace to 20-25 ppm. Alternatively, the rate of heritable translocation induction per ppm/h of BD exposure is estimated to be approximately 0.8 per million live born, compared to a spontaneous incidence of balanced translocations in humans of approximately 800 per million live born. These estimates have large confidence intervals and are only intended to indicate orders of magnitude of human genetic risk. These risk estimates are based on data from germ cells of BD-exposed male mice. The demonstration that clastogenic damage was induced by DEB in preovulatory oocytes at doses which were not ovotoxic implies that additional studies on the response of mammalian female germ cells to BD and its metabolites are needed. The basic assumption of the above genetic risk estimates is that experimental mouse data obtained after BD exposure can be extrapolated to humans. Several points exist in the present report and in the literature which contradict this assumption: (1) the level of BMO-hemoglobin adducts was significantly elevated in BD-exposed workers; however, it was considerably lower than would have been predicted from comparable rat and mouse exposures; (2) the concentrations of the metabolites DEB and BMO were significantly higher in mouse than in rat blood after BD exposure. Thus, while metabolism of BD is qualitatively similar in the two species, it is quantitatively different; (3) no increase of HPRT mutations was shown in 19 workers exposed on average to 1.8 ppm of BD, while in a different population of workers from a US plant exposed on average to 3.5 ppm of BD, a significant increase of HPRT variants was detected; and (4) data from cancer bioassays and cancer epidemiology suggest that rat is a more appropriate model than mouse for human cancer risk from BD exposure. However, the dominant lethal study in rats gave a negative result. At present, we do not know which BD metabolite(s) may be responsible for the genetic effects even though the bifunctional alkylating agent DEB is the most likely candidate for the induction of clastogenic events. Unfortunately, methods to measure DEB adducts in hemoglobin or DNA are only presently being developed. Despite these several uncertainties the use of the mouse genetic data is regarded as a justifiable and conservative approach to human genetic risk estimation given the considerable heterogeneity observed in the biotransformation of BD in humans.     

Using LiDAR and quickbird data to model plant production and quantify uncertainties associated with wetland detection and land cover generalizations

Spatiotemporal data from satellite remote sensing and surface meteorology networks have made it possible to continuously monitor global plant production, and to identify global trends associated with land cover/use and climate change. Gross primary production (GPP) and net primary production (NPP) are routinely derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard satellites Terra and Aqua, and estimates generally agree with independent measurements at validation sites across the globe. However, the accuracy of GPP and NPP estimates in some regions may be limited by the quality of model input variables and heterogeneity at fine spatial scales. We developed new methods for deriving model inputs (i.e., land cover, leaf area, and photosynthetically active radiation absorbed by plant canopies) from airborne laser altimetry (LiDAR) and Quickbird multispectral data at resolutions ranging from about 30 m to 1 km. In addition, LiDAR-derived biomass was used as a means for computing carbon-use efficiency. Spatial variables were used with temporal data from ground-based monitoring stations to compute a six-year GPP and NPP time series for a 3600 ha study site in the Great Lakes region of North America. Model results compared favorably with independent observations from a 400 m flux tower and a process-based ecosystem model (BIOME-BGC), but only after removing vapor pressure deficit as a constraint on photosynthesis from the MODIS global algorithm. Fine-resolution inputs captured more of the spatial variability, but estimates were similar to coarse-resolution data when integrated across the entire landscape. Failure to account for wetlands had little impact on landscape-scale estimates, because vegetation structure, composition, and conversion efficiencies were similar to upland plant communities. Plant productivity estimates were noticeably improved using LiDAR-derived variables, while uncertainties associated with land cover generalizations and wetlands in this largely forested landscape were considered less important.     

Detecting palindromes,patterns and borders in regular languages

Given a language L and a non-deterministic finite automaton M, we consider whether we can determine efficiently (in the size of M) if M accepts at least one word in L, or infinitely many words. Given that M accepts at least one word in L, we consider how long a shortest word can be. The languages L that we examine include the palindromes, the non-palindromes, the k-powers, the non-k-powers, the powers, the non-powers (also called primitive words), the words matching a general pattern, the bordered words, and the unbordered words.     

Parallel Implementation of a Low Order Algorithm for Dynamics of Multibody Systems on a Distributed Memory Computing System

In this paper, a new hybrid parallelisable low order algorithm, developed by the authors for multibody dynamics analysis, is implemented numerically on a distributed memory parallel computing system. The presented implementation can currently accommodate the general spatial motion of chain systems, but key issues for its extension to general tree and closed loop systems are discussed. Explicit algebraic constraints are used to increase coarse grain parallelism, and to study the influence of the dimension of system constraint load equations on the computational efficiency of the algorithm for real parallel implementation using the Message Passing Interface (MPI). The equation formulation parallelism and linear system solution strategies which are used to reduce communication overhead are addressed. Numerical results indicate that the algorithm is scalable, that significant speed-up can be obtained, and that a quasi-logarithmic relation exists between time needed for a function call and numbers of processors used. This result agrees well with theoretical performance predictions. Numerical comparisons with results obtained from independently developed analysis codes have validated the correctness of the new hybrid parallelisable low order algorithm, and demonstrated certain computational advantages.     

Query-driven visualization of time-varying adaptive mesh refinement data

The visualization and analysis of AMR-based simulations is integral to the process of obtaining new insight in scientific research. We present a new method for performing query-driven visualization and analysis on AMR data, with specific emphasis on time-varying AMR data. Our work introduces a new method that directly addresses the dynamic spatial and temporal properties of AMR grids that challenge many existing visualization techniques. Further, we present the first implementation of query-driven visualization on the GPU that uses a GPU-based indexing structure to both answer queries and efficiently utilize GPU memory. We apply our method to two different science domains to demonstrate its broad applicability.