Contact Pressure Measurement System in Cross Wedge Rolling

In the cross wedge rolling process (CWR), plastic deformation is geared by a driving torque transmitted by friction on die surface. Friction plays a role which has to be further identified in this metal forming process. The local contact pressure between a cylindrical billet and flat dies seems to be a relevant parameter to characterize the severe contact conditions during the rolling. This paper deals with an experimental measurement technology, which has been designed and implemented on a semi-industrial CWR test bench with plate configuration. This measurement system using pin and piezoelectric sensor is presented, with an analysis of the system operation and design detail. Characterization of systematic error and calibration tests are then explained. Additional tests performed on hot steel preforms allow to check the ability of the contact pressure measurement system to resist under severe operating conditions. Realistic results for varying temperatures are then discussed

Multi-bot Easy Control Hierarchy

The goal of our project is to create a software architecture that makes it possible to easily control a multi-robot system, as well as seamlessly change control modes during operation. The different control schemes first include the ability to implement on-board and off-board controllers. Second, the commands can specify either actuator level, vehicle level, or fleet level behavior. Finally, motion can be specified by giving a waypoint and time constraint, a velocity and heading, or a throttle and angle. Our code is abstracted so that any type of robot - ranging from ones that use a differential drive set up, to three-wheeled holonomic platforms, to quadcopters - can be added to the system by simply writing drivers that interface with the hardware used and by implementing math packages that do the required calculations. Our team has successfully demonstrated piloting a single robots while switching between waypoint navigation and a joystick controller. In addition, we have demonstrated the synchronized control of two robots using joystick control. Future work includes implementing a more robust cluster control, including off-board functionality, and incorporating our architecture into different types of robots

Determination of pyrotechnic functional margin

Following the failure of a previously qualified pyrotechnically actuated pin puller design, an investigation led to a redesign and requalification. The emphasis of the second qualification was placed on determining the functional margin of the pin puller by comparing the energy deliverable by the pyrotechnic cartridge to the energy required to accomplish the function. Also determined were the effects of functional variables. This paper describes the failure investigation, the test methods employed and the results of the evaluation, and provides a recommended approach to assure the successful functioning of pyrotechnic devices

Organic dairy cows: milk yield and lactation characteristics in thirteen established herds and development of a herd simulation model for organic milk production

As a consequence of organic standards and principles, organic dairy producers are frequently faced with a different set of management considerations than those found in conventional dairy systems. The broad objective of this study was to examine in detail the production characteristics of 13 well-established organic dairy herds, and to relate these to the specific conditions that exist within organic dairy farming. Monthly milk records for 13 organic herds for three years were collected and converted into a Microsoft Access database, using InterHerd™ (Agrisoft Plc., UK) herd management software. The data were sorted and analysed using the InterHerd-herd management, Excel for Windows™ and Statistix for Windows software programmes. Estimated parameters were used to examine the importance of two important indicators: lifetime yield/lactation length and economic efficiency. To assess the first, a spreadsheet model based on the Wood's lactation curve was developed. With regard to the latter, a model calculator was used. Five herds were chosen for case studies, that examined the farm performance by using InterHerd™-generated data and by interviewing the producer retrospectively and asking him to comment on the data. Results Milk yield and lactation characteristics The 13 established, organic herds were characterised with relatively low yields, but herd variation was great: from a total lactation yield of 5,100 kg to 7,000 kg. Milk fat and protein content, lactation length and individual cow SCC means were similar to those reported in conventional, milk recorded herds. Lactation yields increased up to the third lactation, whereas persistency of lactations decreased up to the third lactation. This pattern followed similar patterns reported in conventionally managed herds. Similarly, somatic cell counts increased with parity, mimicking similar phenomenon reported in conventionally managed dairy cows. Length of lactation and lactation persistency were associated with month of calving, with autumn calving cows tending to have shorter lactations with better persistency. This phenomenon was, however, confounded with parity. Fertility It is concluded that fertility performance in terms of culling for fertility and mean calving intervals were better in the organic survey herds when compared with existing data from conventionally managed UK dairy herds. Good fertility performance even in the highest yielding organically managed cows suggests that early lactation energy deficit may not be a major problem in these herds. It is also suggested that financial impact of high number of services per conception, as observed in majority of the survey herds, may be insignificant as the main losses caused by poor fertility are attributable to culling and prolonged calving intervals. Herd models Herd productivity indices were generated, using an existing model based on a measure of feed conversion efficiency at the herd level. The advantage of using this approach in the estimation of productivity is that it takes full account of the entire feed input to the system, including forage. The production index was closely and independently associated with yield and calving rate. Culling was not independently associated with the production index but once calving rate and lactation yield are taken into account, culling rate also becomes a significant factor. Case studies Case studies demonstrated the usefulness of recorded data analysis, using herd management software and observation of seasonally adjusted lactation curves to examine feeding management. In all five herds, apparent and reoccurring seasonal feeding and grazing management shortcomings were detected. Recommendations Further research would need to be carried out to establish financial consequences of poor fertility in organic systems with different milk pricing and cow values. Similarly, further research is needed to establish causes for high numbers of services per conception in these herds and to establish whether this phenomenon exists in other organically managed herds. The herd productivity calculator model (LPEC) showed to be a good and robust measure of productivity. Next logical step in this analysis would be to gain data on purchased feeds, so that the productivity index can be expressed in terms of a gross margin per unit of forage input. This would allow the full importance of forage to organic dairy systems to be expressed, and would also allow productivity to be evaluated in terms economic margin per unit of input produced on-farm. The LPEC generated indices could also be utilised to examine the potential impact of changes to systems before an intervention is implemented, by including costs of intervention and assumed values of production post-intervention. Sensitivity analyses may be conducted to identify the relative importance of individual production parameters to overall herd productivity. Careful assessment of lactation characteristics in a herd is needed to predict the overall impact of extended calving intervals. It is likely that in most organic herds feeding management would need to be adjusted in order to produce lactations with low late lactation decline to avoid financial losses caused by longer calving intervals. Analysis of seasonally adjusted lactation curves as a monitoring and decision support system for feeding management is likely to be a useful for organic herds, particularly during conversion period when new feeding systems need to be introduced in a herd

Neutronic design for a lithium-cooled reactor for space applications

Neutronic design calculations for lithium 7 cooled nuclear reactor for space application

Debris control design achievements of the booster separation motors

The stringent debris control requirements imposed on the design of the Space Shuttle booster separation motor are described along with the verification program implemented to ensure compliance with debris control objectives. The principal areas emphasized in the design and development of the Booster Separation Motor (BSM) relative to debris control were the propellant formulation and nozzle closures which protect the motors from aerodynamic heating and moisture. A description of the motor design requirements, the propellant formulation and verification program, and the nozzle closures design and verification are presented

Graph Convolutional Neural Networks for Web-Scale Recommender Systems

Recent advancements in deep neural networks for graph-structured data have led to state-of-the-art performance on recommender system benchmarks. However, making these methods practical and scalable to web-scale recommendation tasks with billions of items and hundreds of millions of users remains a challenge. Here we describe a large-scale deep recommendation engine that we developed and deployed at Pinterest. We develop a data-efficient Graph Convolutional Network (GCN) algorithm PinSage, which combines efficient random walks and graph convolutions to generate embeddings of nodes (i.e., items) that incorporate both graph structure as well as node feature information. Compared to prior GCN approaches, we develop a novel method based on highly efficient random walks to structure the convolutions and design a novel training strategy that relies on harder-and-harder training examples to improve robustness and convergence of the model. We also develop an efficient MapReduce model inference algorithm to generate embeddings using a trained model. We deploy PinSage at Pinterest and train it on 7.5 billion examples on a graph with 3 billion nodes representing pins and boards, and 18 billion edges. According to offline metrics, user studies and A/B tests, PinSage generates higher-quality recommendations than comparable deep learning and graph-based alternatives. To our knowledge, this is the largest application of deep graph embeddings to date and paves the way for a new generation of web-scale recommender systems based on graph convolutional architectures.Comment: KDD 201