Mechanical and fracture behavior of powder metalurgy processed Ti3Al-based alloys

This work considers structural and compression mechanical properties of three Ti₃Al-based alloys processed by powder metallurgy. Mechanically alloyed powders were compacted by hot-pressing to non-porous homogenous compacts. Prior to compression tests, all compacts were homogenized by a solution treatment at 1050°C (α + β region) for 1h, followed by water quenching. The compression tests were performed from room temperature to 500°C in vacuum at a strain rate of 2.4 × 10⁻³ s⁻¹. Detailed microstructural characterization has been evaluated by scanning electron microscopy (SEM), followed by electron dispersive spectroscopy (EDS) and X-ray diffraction analysis. Fracture topography was examined by SEM. The Ti₃Al-Nb alloy exhibits the highest ductility in the whole temperature range, whereas addition of Mo to Ti₃Al-Nb alloy yields the highest ultimate compression strength. A correlation between ductility and the fracture mode exists for all materials.     

Maximizing Reward in a Non-Stationary Mobile Robot Environment

The ability of a robot to improve its performance on a task can be critical, especially in poorly known and non-stationary environments where the best action or strategy is dependent upon the current state of the environment. In such systems, a good estimate of the current state of the environment is key to establishing high performance, however quantified. In this paper, we present an approach to state estimation in poorly known and non-stationary mobile robot environments, focusing on its application to a mine collection scenario, where performance is quantified using reward maximization. The approach is based on the use of augmented Markov models (AMMs), a sub-class of semi-Markov processes. We have developed an algorithm for incrementally constructing arbitrary-order AMMs on-line. It is used to capture the interaction dynamics between a robot and its environment in terms of behavior sequences executed during the performance of a task. For the purposes of reward maximization in a non-stationary environment, multiple AMMs monitor events at different timescales and provide statistics used to select the AMM likely to have a good estimate of the environmental state. AMMs with redundant or outdated information are discarded, while attempting to maintain sufficient data to reduce conformation to noise. This approach has been successfully implemented on a mobile robot performing a mine collection task. In the context of this task, we first present experimental results validating our reward maximization performance criterion. We then incorporate our algorithm for state estimation using multiple AMMs, allowing the robot to select appropriate actions based on the estimated state of the environment. The approach is tested first with a physical robot, in a non-stationary environment with an abrupt change, then with a simulation, in a gradually shifting environment.     

Decentralized overlapping control of a formation of unmanned aerial vehicles

Decentralized overlapping feedback laws are designed for a formation of unmanned aerial vehicles. The dynamic model of the formation with an information structure constraint in which each vehicle, except the leader, only detects the vehicle directly in front of it, is treated as an interconnected system with overlapping subsystems. Using the mathematical framework of the inclusion principle, the interconnected system is expanded into a higher dimensional space in which the subsystems appear to be disjoint. Then, at each subsystem, a static state feedback controller is designed to robustly stabilize the perturbed nominal dynamics of the subsystem. The design procedure is based on the application of convex optimization tools involving linear matrix inequalities. As a final step, the decentralized controllers are contracted back to the original interconnected system for implementation.     

Nelson Goodman’s Arguments Against Perspective: A Geometrical Analysis

Nelson Goodman’s highly influential book Languages of Art argued that that all visual experience is merely a cultural construct. In presenting his thesis Goodman relied on a series of geometrical arguments intended to show that the geometrical construction of perspective does not rely on the geometry of light rays. In this article I analyze the geometrical validity of Goodman’s arguments.     

Metals in organic and conventional wheat flours determined by an optimised and validated ICP‐MS method

This study was undertaken (i) to optimise and validate a suitable method for multi‐element determination in cereal products and (ii) to evaluate multi‐element content differences in commercially available conventional vs. organic wheat flours. Presented ICP‐MS method is simple and accurate for the determination of eighteen elements in cereal food. Obtained results show differences in metal content between conventional and organic wheat flours and confirm that both types of production are well within the toxicological safety limits regarding the metal contents. The significant differences among conventional vs. organic wheat flours were obtained for As, Cd, Cr, Fe, Mg, Mo, Ni and V. Toxic metals (Al, As, Cd and Pb) input was higher in conventional compared with organic wheat flours. However, further and long‐term research is needed to clearly underline the effects of organic agricultural practice on the quality of food products.     

Optimal attacks on qubit-based Quantum Key Recycling

Quantum Key Recycling (QKR) is a quantum cryptographic primitive that allows one to reuse keys in an unconditionally secure way. By removing the need to repeatedly generate new keys, it improves communication efficiency. ?kori? and de Vries recently proposed a QKR scheme based on 8-state encoding (four bases). It does not require quantum computers for encryption/decryption but only single-qubit operations. We provide a missing ingredient in the security analysis of this scheme in the case of noisy channels: accurate upper bounds on the required amount of privacy amplification. We determine optimal attacks against the message and against the key, for 8-state encoding as well as 4-state and 6-state conjugate coding. We provide results in terms of min-entropy loss as well as accessible (Shannon) information. We show that the Shannon entropy analysis for 8-state encoding reduces to the analysis of quantum key distribution, whereas 4-state and 6-state suffer from additional leaks that make them less effective. From the optimal attacks we compute the required amount of privacy amplification and hence the achievable communication rate (useful information per qubit) of qubit-based QKR. Overall, 8-state encoding yields the highest communication rates.     

Particle Swarm Optimization and Pure Adaptive Search in Finish Goods’ Inventory Management

Abstract

Inventory management deals with a tradeoff between the benefits of keeping stocks of goods that allows fulfillment of the customer’s demand, and the cost of carrying inventory. Inventory control techniques are very important components and the most organizations can substantially reduce their costs associated with the flow of materials. This paper presents new inventory management model based on particle swarm optimization and pure adaptive search global optimization algorithm in production-inventory system. The proposed model is focusing on planned level of demand for finished goods, production and raw materials cost, production capacity as the norm, change of the production cost and inventory capital cost, all of which are typical factors in automobile manufacture industry. The model determines different factors such as the minimizing inventory quantity, minimizing inventory value, and minimizing production cost based on demand for production items. The model is tested with original real-world dataset obtained from the automotive company Lear from US and its factory in Novi Sad, Serbia.     

Fuzzy gain-scheduling control of a gas-liquid separation plant implemented on a PLC

In the paper an approach to the non-linear control of a gas-liquid separation plant is presented. To solve the problem the fuzzy gain-scheduling method was used and implemented on a programmable logic controller (PLC). Velocity-based linearization approach was used for control system design and implementation for the first time in process control application. Emphasis was placed on the appropriate adaptation of the method and some important implementation issues. The algorithm was carefully designed and tested by using ordinary simulation, hardware-in-the-loop simulation, and experiments on the real plant. The results show that the proposed approach substantially improves the closed-loop performance of the plant.