An epitrochoidal pocket—A new canned cycle for CNC milling machines

A machining strategy for milling a particular set of pockets with epitrochoidal boundary is proposed. The method is suitable to be integrated into the controller of a CNC milling machine and is particularly useful for machining chambers of rotary internal combustion engines (Wankel), rotary piston pumps and generally epitrochoidal-shaped housings. Motion generation is achieved by an algorithm which utilizes real-time CNC interpolation providing the highest possible accuracy, of which the milling machine is capable. The surface quality is controlled by applying roughing and finishing passes. The whole machining task can be programmed in a single block of the part program. Finally, the effectiveness of the proposed method is verified by simulation tests of the generated tool path.     

Gesture recognition and sensorimotor learning‐by‐doing of motor skills in manual professions: A case study in the wheel‐throwing art of pottery

This paper presents a methodological framework for the use of gesture recognition technologies in the learning/mastery of the gestural skills required in wheel‐throwing pottery. In the case of self‐instruction or training, learners face difficulties due to the absence of the teacher/expert and the consequent lack of guidance. Motion capture technologies, machine learning, and gesture recognition may provide a way of overcoming such issues. The proposed methodology is used to record and model expert gestures and then to compare this model in real time with the gestures performed by the learner. Differences in kinematic aspects such as hand distances are detected, and optical/sonic sensorimotor feedback is provided to the learner by the system, alerting him/her when errors occur and guiding him/her to achieve better results. In the case described here, the system was evaluated with 11 learners. With the use of our system, the gestural performance of learners during self‐training has been improved in comparison to cases of self‐training without computer assistance.     

Assembly Line Balancing Using Differential Evolution Models

There is a growing research interest on the application of evolutionary computation-based techniques in manufacturing optimization due to the fact that this field is associated with a plethora of complex combinatorial optimization problems. Differential evolution (DE), one of the latest developed evolutionary algorithms, has rarely been applied on manufacturing optimization problems (MOPs). A possible reason for the absence of DE from this research field is that DE was introduced as global optimizer over continuous spaces, while most of MOPs are of combinatorial nature with discrete decision variables. DE maintains and evolves floating-point vectors and therefore its application to MOPs that have solutions represented by permutations is not straightforward. This paper investigates the use of DE for the solution of the simple assembly line balancing problem (SALBP), a well-known NP-hard MOP. Two basic formulation types for SALBP are examined, namely type-1 and type-2: the former attempts to minimize the number of workstations required to manufacture a product in an assembly line for a given fixed cycle time; while the latter attempts to minimize the cycle time of the line for a given number of stations. Extensive experiments carried out over public benchmarks test instances estimate the performance of DE approach.     

Exploring cache performance in multithreaded processors

Multithreading is a well known technique to hide latency in a non-blocking cache architecture. By switching execution from one thread to another, the CPU can perform useful work, while waiting for pending requests to be processed by the main memory. In this paper we examine the effects of varying the associativity and block size on cache performance in a reduced locality of reference environment, due to multithreading. We find that for associativity equal to the number of threads, the cache produces very low miss rate even for small sizes. Also by taking into account the increase in cycle time due to larger cache size or associativity we find that the optimum cache configuration for best processor performance is 16Kbytes direct mapped. Finally, with a constant main memory bandwidth, increasing the block size to more than 32 bytes, reduces the miss rate, but degrades processor performance.     

Kinetics of Titanium(IV) Chloride Oxidation

The oxidation rate of TiCl₄ vapor was measured by FTIR spectroscopy between 700° and 1000°C in a furnace aerosol reactor. The reaction rate was found to be first order with respect to TiCl₄ and to follow the Arrhenius form. The apparent activation energy for the reaction was 88.8 ± 3.2 kJ/mol and the preexponential factor 8.26 × 10⁴ s⁻¹. A kinetic mechanism for the oxidation of TiCl₄ was proposed that was consistent with the observed dependence of oxygen concentration on the apparent rate constant.     

Dynamics and dispersion modelling of nanoparticles from road traffic in the urban atmospheric environment—A review

Reducing exposure to atmospheric nanoparticles in urban areas is important for protecting public health. Developing new or improving the capabilities of existing dispersion models will help to design effective mitigation strategies for nanoparticle rich environments. The aims of this review are to summarise current practices of nanoparticle dispersion modelling at five local scales (i.e. vehicle wake, street canyons, neighbourhood, city and road tunnels), together with highlighting associated challenges, research gaps and priorities. The review begins with a synthesis of available information about the flow and mixing characteristics in urban environments which is followed by a brief discussion on dispersion modelling of nanoparticles. Further sections cover the effects of transformation processes in dispersion modelling of nanoparticles, and a critical discussion on associated structural and parametric uncertainties in modelling. The article concludes with a comprehensive summary of current knowledge and future research required on the topic areas covered.Appropriate treatment of transformation processes (i.e. nucleation, coagulation, deposition and condensation) in existing dispersion models is essential for extending the applicability of gaseous dispersion models to nanoparticles. Some modelling studies that consider the particles down to 1 nm size indicate importance of coagulation and condensation processes on street-scale modelling whereas others neglecting either sub-10 nm particles or Van der Waals forces along with fractal geometry suggest to discard these processes due to negligible effects on particle number and size distributions. Further, it is important to consider those transformation processes e.g. at city scale or in road tunnels because of the much longer residence time or much higher concentration levels compared to the street scale processes. Structural and parametric uncertainties affect the modelled results considerably. In particular, parametric uncertainty in the form of particle number emission factors appears to be the most significant due to considerably large variations in their estimates. A consistent approach to the use of emission factors, appropriate treatment of transformation processes in particle dispersion models and the evaluation of model performance against measured data are essential for producing reliable modelled results.     

Spatial patterns,controlling factors,and characteristics of landslides triggered by strike-slip faulting earthquakes: case study of Lefkada island,Greece

Bulletin of Engineering Geology and the Environment - The correlation of coseismic landslides with the seismic and morphological parameters has been investigated in detail by many researchers,...     

Impact and uncertainty of a traffic management intervention: population exposure to polycyclic aromatic hydrocarbons

In urban areas, road traffic is a major source of carcinogenic polycyclic aromatic hydrocarbons (PAH), thus any changes in traffic patterns are expected to affect PAH concentrations in ambient air. Exposure to PAH and other traffic-related air pollutants has often been quantified in a deterministic manner that disregards the various sources of uncertainty in the modelling systems used. In this study, we developed a generic method for handling uncertainty in population exposure models. The method was applied to quantify the uncertainty in population exposure to benzo[a]pyrene (BaP) before and after the implementation of a traffic management intervention. This intervention would affect the movement of vehicles in the studied area and consequently alter traffic emissions, pollutant concentrations and population exposure. Several models, including an emission calculator, a dispersion model and a Geographic Information System were used to quantify the impact of the traffic management intervention. We established four exposure zones defined by distance of residence postcode centroids from major road or intersection. A stochastic method was used to quantify the uncertainty in the population exposure model. The method characterises uncertainty using probability measures and propagates it applying Monte Carlo analysis. The overall model predicted that the traffic management scheme would lead to a minor reduction in mean population exposure to BaP in the studied area. However, the uncertainty associated with the exposure estimates was much larger than this reduction. The proposed method is generic and provides realistic estimates of population exposure to traffic-related pollutants, as well as characterises the uncertainty in these estimates. This method can be used within a decision support tool to evaluate the impact of alternative traffic management policies.     

Semi-tensor product-based algebra-logic mixed representation and fault diagnosis for a class of gate networks

This article studies an algebra-logic mixed representation of gate networks and its application to stuck-at fault diagnosis. First, the gate network is characterized through a logic expression of disjoint sum-of-products, and the system structure of the gate network is described based on 2-to-1 multiplexers. Then, by resorting to the semi-tensor product of matrices, a novel algebra-logic mixed representation is proposed for the gate network through its logic expression and system structure. Furthermore, a novel stuck-at fault diagnosis algorithm for the gate network is presented, where the stuck-at fault testability of the gate network is equivalent to the solution existence of the system of linear equations. Finally, the fault diagnosis of the 4-bit carry look-ahead adder is carried out to demonstrate the effectiveness and feasibility of the proposed theoretical approach and algorithms.