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