Cavitation damage in liquid metals /potassium studies/ Technical progress report, 1 Aug. - 31 Oct. 1966

Cavitation damage resistance of refractory alloys in high temperature liquid potassiu

Mean flow field and surface heating produced by unequal shock interactions at hypersonic speeds

Mean velocity profiles were measured in a free shear layer produced by the interaction of two unequal strength shock waves at hypersonic free-stream Mach numbers. Measurements were made over a unit Reynolds number range of 3,770,000 per meter to 17,400,000 per meter based on the flow on the high velocity side of the shear layer. The variation in measured spreading parameters with Mach number for the fully developed flows is consistent with the trend of the available zero velocity ratio data when the Mach numbers for the data given in this study are taken to be characteristic Mach numbers based on the velocity difference across the mixing layer. Surface measurements in the shear-layer attachment region of the blunt-body model indicate peak local heating and static pressure consistent with other published data. Transition Reynolds numbers were found to be significantly lower than those found in previous data

Comments on the role of diagonal dominance in implicit difference methods

Numerical tests were made for a model of the Navier-Stokes equations using a second-order accurate implicit scheme which guarantees diagonal dominance. The results suggest that the failure of implicit methods using large marching steps may not always be attributed to the lack of diagonal dominance in the coefficient matrix. In some cases the failure may be caused by a nonlinear instability associated with the solution method

Cavitation damage in liquid metals technical progress report no. 467-3, 1 apr. - 31 may 1965

Cavitation damage resistance of refractory alloys in high temperature liquid sodiu

Cavitation damage in liquid metals technical progress report, 1 jan. - 31 mar. 1965

Temperature effect on rate of cavitation damage of 316 stainless steel in pure liquid sodium at temperatures up to 1500 deg

Adaptive Neural Compilation

This paper proposes an adaptive neural-compilation framework to address the problem of efficient program learning. Traditional code optimisation strategies used in compilers are based on applying pre-specified set of transformations that make the code faster to execute without changing its semantics. In contrast, our work involves adapting programs to make them more efficient while considering correctness only on a target input distribution. Our approach is inspired by the recent works on differentiable representations of programs. We show that it is possible to compile programs written in a low-level language to a differentiable representation. We also show how programs in this representation can be optimised to make them efficient on a target distribution of inputs. Experimental results demonstrate that our approach enables learning specifically-tuned algorithms for given data distributions with a high success rate.Comment: Submitted to NIPS 2016, code and supplementary materials will be available on author's pag

A Unified View of Piecewise Linear Neural Network Verification

The success of Deep Learning and its potential use in many safety-critical applications has motivated research on formal verification of Neural Network (NN) models. Despite the reputation of learned NN models to behave as black boxes and the theoretical hardness of proving their properties, researchers have been successful in verifying some classes of models by exploiting their piecewise linear structure and taking insights from formal methods such as Satisifiability Modulo Theory. These methods are however still far from scaling to realistic neural networks. To facilitate progress on this crucial area, we make two key contributions. First, we present a unified framework that encompasses previous methods. This analysis results in the identification of new methods that combine the strengths of multiple existing approaches, accomplishing a speedup of two orders of magnitude compared to the previous state of the art. Second, we propose a new data set of benchmarks which includes a collection of previously released testcases. We use the benchmark to provide the first experimental comparison of existing algorithms and identify the factors impacting the hardness of verification problems.Comment: Updated version of "Piecewise Linear Neural Network verification: A comparative study

Cavitation damage in liquid metals /potassium studies/ Technical progress report, 10 Jan. - 31 Jul. 1966

High-temperature liquid potassium cavitation damage test

Data-driven PDE discovery with evolutionary approach

The data-driven models allow one to define the model structure in cases when a priori information is not sufficient to build other types of models. The possible way to obtain physical interpretation is the data-driven differential equation discovery techniques. The existing methods of PDE (partial derivative equations) discovery are bound with the sparse regression. However, sparse regression is restricting the resulting model form, since the terms for PDE are defined before regression. The evolutionary approach described in the article has a symbolic regression as the background instead and thus has fewer restrictions on the PDE form. The evolutionary method of PDE discovery (EPDE) is described and tested on several canonical PDEs. The question of robustness is examined on a noised data example

Physiological Response of Reared Bali Cattle Based on Different Peat Land Characteristics

This study aimed to investigate the effect of microclimate conditions within cattle houses at wet peatlands and dry peatlands on Bali cow's physiological responses.  The study was carried out from November 2017 to February 2018 in Pulang Pisau Regency, Central Kalimantan Province. There were 58 heads of Bali cows used in this study, comprising 38 cattle at wet peatland in Jabiren Raya sub-district and 20 animals at a dry bog in Maliku sub-district. The observed parameters included microclimate conditions. It was air temperature, humidity, and temperature-humidity index, THI and wind speed, physiological responses (respiratory rate, pulse, and rectal temperature) and leucocyte (neutrophils, lymphocytes, and neutrophils/lymphocytes ratio). The results indicated that the morning microclimate at wet peatland showed significantly (p0.05) lower humidity, higher THI, and wind speed than that at dry land. The marked difference of microclimate between the two locations in the afternoon occurred only on wind speed.  There were differences between dry and wet peatlands in Bali cow's physiological responses, including respiration rate in the morning, the pulse at noon, rectal temperature in the afternoon, and leucocyte.  However, the local cattle' physiological responses kept in wet and dry peatland were still under normal conditions