32,442 research outputs found
Test results and facility description for a 40-kilowatt stirling engine
A 40 kilowatt Stirling engine, its test support facilities, and the experimental procedures used for these tests are described. Operating experience with the engine is discussed, and some initial test results are presente
Sets of Priors Reflecting Prior-Data Conflict and Agreement
In Bayesian statistics, the choice of prior distribution is often debatable,
especially if prior knowledge is limited or data are scarce. In imprecise
probability, sets of priors are used to accurately model and reflect prior
knowledge. This has the advantage that prior-data conflict sensitivity can be
modelled: Ranges of posterior inferences should be larger when prior and data
are in conflict. We propose a new method for generating prior sets which, in
addition to prior-data conflict sensitivity, allows to reflect strong
prior-data agreement by decreased posterior imprecision.Comment: 12 pages, 6 figures, In: Paulo Joao Carvalho et al. (eds.), IPMU
2016: Proceedings of the 16th International Conference on Information
Processing and Management of Uncertainty in Knowledge-Based Systems,
Eindhoven, The Netherland
Initial test results with a single-cylinder rhombic-drive Stirling engine
A 6 kW (8 hp), single-cylinder, rhombic-drive Stirling engine was restored to operating condition, and preliminary characterization tests run with hydrogen and helium as the working gases. Initial tests show the engine brake specific fuel consumption (BSFC) with hydrogen working gas to be within the range of BSFC observed by the Army at Fort Belvoir, Virginia, in 1966. The minimum system specific fuel consumption (SFC) observed during the initial tests with hydrogen was 669 g/kW hr (1.1 lb/hpx hr), compared with 620 g/kWx hr (1.02 lb/hpx hr) for the Army tests. However, the engine output power for a given mean compression-space pressure was lower than for the Army tests. The observed output power at a working-space pressure of 5 MPa (725 psig) was 3.27 kW (4.39 hp) for the initial tests and 3.80 kW (5.09 hp) for the Army tests. As expected, the engine power with helium was substantially lower than with hydrogen
Electrical resistivity near Pomeranchuk instability in two dimensions
We analyze the DC charge transport in the quantum critical regime near a
d-wave Pomeranchuk instability in two dimensions. The transport decay rate is
linear in temperature everywhere on the Fermi surface except at cold spots on
the Brillouin zone diagonal. For pure systems, this leads to a DC resistivity
proportional to T^{3/2} in the low-temperature limit. In the presence of
impurities the residual impurity resistance at T=0 is approached linearly at
low temperatures.Comment: 9 pages, no figure
Influence of gaseous hydrogen on metals Interim report
Gaseous hydrogen embrittlement in Inconel 718, Inconel 625, AISI 321 stainless steel, Ti-5Al-25Sn ELI, and OFHC coppe
A High-Resolution Rotation Curve of NGC 6822: A Test-case for Cold Dark Matter
We present high resolution rotation curves of the local group dwarf irregular
galaxy NGC 6822 obtained with the Australia Telescope Compact Array. Our best
curves have an angular resolution of 8'' or 20 pc and contain some 250
independent points. The stellar and gas components of NGC 6822 cannot explain
the shape of the curve, except for the very inner regions, and NGC 6822 is
consequently very dark matter dominated. There is no evidence for the presence
of a steep density cusp down to scales of ~20 pc, contrary to the predictions
of Cold Dark Matter.Comment: Accepted for publication in MNRA
UG^2: a Video Benchmark for Assessing the Impact of Image Restoration and Enhancement on Automatic Visual Recognition
Advances in image restoration and enhancement techniques have led to
discussion about how such algorithmscan be applied as a pre-processing step to
improve automatic visual recognition. In principle, techniques like deblurring
and super-resolution should yield improvements by de-emphasizing noise and
increasing signal in an input image. But the historically divergent goals of
the computational photography and visual recognition communities have created a
significant need for more work in this direction. To facilitate new research,
we introduce a new benchmark dataset called UG^2, which contains three
difficult real-world scenarios: uncontrolled videos taken by UAVs and manned
gliders, as well as controlled videos taken on the ground. Over 160,000
annotated frames forhundreds of ImageNet classes are available, which are used
for baseline experiments that assess the impact of known and unknown image
artifacts and other conditions on common deep learning-based object
classification approaches. Further, current image restoration and enhancement
techniques are evaluated by determining whether or not theyimprove baseline
classification performance. Results showthat there is plenty of room for
algorithmic innovation, making this dataset a useful tool going forward.Comment: Supplemental material: https://goo.gl/vVM1xe, Dataset:
https://goo.gl/AjA6En, CVPR 2018 Prize Challenge: ug2challenge.or
- …