Abrasive waterjet micro-machining of channels in metals: Comparison between machining in air and submerged in water

Abrasive water jet technology can be used for micro-milling using recently developed miniaturized nozzles. Abrasive water jet (AWJ) machining is often used with both the nozzle tip and workpiece submerged in water to reduce noise and contain debris. This paper compares the performance of submerged and unsubmerged abrasive water jet micro-milling of channels in 316L stainless steel and 6061-T6 aluminum at various nozzle angles and standoff distances. The effect of submergence on the diameter and effective footprint of AWJ erosion footprints was measured and compared. It was found that the centerline erosion rate decreased with channel depth due to the spreading of the jet as the effective standoff distance increased, and because of the growing effect of stagnation as the channel became deeper. The erosive jet spread over a larger effective footprint in air than in water, since particles on the jet periphery were slowed much more quickly in water due to increased drag. As a result, the width of a channel machined in air was wider than that in water. Moreover, it was observed that the instantaneous erosion rate decreased with channel depth, and that this decrease was a function only of the channel cross-sectional geometry, being independent of the type of metal, the jet angle, the standoff distance, and regardless of whether the jet was submerged or in air, in either the forward or backward directions. It is shown that submerged AWJM results in narrower features than those produced while machining in air, without a decrease in centerline etch rate.     

The effects of blast lag in abrasive jet machined micro-channel intersections

Abrasive jet micro-machining (AJM) uses compressed air carrying abrasive solid particles to micro-machine a variety of features into surfaces. If the feature sizes are less than the size of the abrasive jet footprint, then a patterned erosion-resistant mask is used to protect the substrate material, leaving exposed areas to define the features. Previous investigations have revealed a ‘blast lag’ phenomenon in which, for the same dose of abrasive particles, narrower mask openings lead to channels that are shallower than wider ones. Blast lag occurs when using AJM on brittle substrates because of the natural tendency to rapidly form a V-shaped cross-sectional profile which inhibits abrasive particle strikes on the narrow vertex at the feature centerline. In this paper, the blast lag phenomenon is studied when using AJM to machine a network of microfluidic channels. It is found that, in some cases, differences in blast lag occurring at channel intersections and within the channels themselves, can lead to channel networks of nonuniform depth. A previously developed surface evolution model is adapted to allow prediction of the onset of blast lag in the channels and intersections and thus explain these differences. Finally, methods to eliminate the differences are discussed.     

Effect of boron on the low-cycle fatigue behavior and deformation structure of INCONEL 718 at 650 °C

Symmetrical push-pull low-cycle fatigue (LCF) tests were performed on INCONEL 718 (IN718) containing 12, 29, 60, and 100 ppm B at 650 °C. The results showed that all the alloys experienced a relatively short period of initial cyclic hardening at low strain amplitudes, followed by a regime of saturation or slightly continuous cyclic softening. The initial cyclic hardening phase decreased with increasing strain amplitudes, and disappeared at the high strain amplitudes. A serrated flow was observed in the plastic regions of cyclic stress-strain hysteresis loops. The saturated cyclic stress amplitude at a given strain amplitude was highest for the alloy with 60 ppm B, and lowest for the alloy with 12 ppm B. The LCF lifetime increased with increasing B concentration up to 60 ppm, and then decreased as the B content increased from 60 to 100 ppm. Fractographic analysis suggested that the fracture mode changed from intergranular to transgranular cracking as the B concentration increased. The characteristic deformation microstructures produced by LCF tests at 650 °C, examined via transmission electron microscopy, were regularly spaced arrays of planar deformation bands on {111} slip planes in all four alloys. A ladderlike structure was observed in some local regions in the alloy with 12 ppm B. Heavily deformed planar deformation bands were observed in the fatigued specimens with 100 ppm B. The mechanism of improvement in the LCF life of IN718 due to B addition is discussed.     

Statistical analysis of uniform-sampling phase-locked loops based on Volterra functional expansions

With the use of Volterra functional expansions in the domain of the multidimensional z transform, discrete uniform-sampling analogues of digital phase-locked loops of the first, second, and (N + 2)th orders with a delay of N sampling periods are analyzed.     

Measuring the likelihood of VR visual fatigue through ocular biomechanics

Immersion in virtual reality is still linked to symptoms of visual fatigue such as eye strain, dizziness, and overall discomfort. Studies have investigated visual fatigue through pre- and post-immersion tests of the visual function. In this work, we extend on our previous study and derive a visual fatigue likelihood metric using biomechanical analysis. Previously, we have investigated the effect of VR on the vergence system during immersion. The proposed visual fatigue metric exhibited a significant correlation to vergence angle variability which was previously linked to vergence accommodation conflict in VR. We also discuss subjective feedback and its relationship with the proposed visual fatigue metric.     

Secure authentication scheme for passive C1G2 RFID tags

Privacy and security concerns inhibit the fast adaption of RFID technology for many applications. A number of authentication protocols that address these concerns have been proposed but real-world solutions that are secure, maintain low communication cost and can be integrated into the ubiquitous EPCglobal Class 1 Generation 2 tag protocol (C1G2) are still needed and being investigated. We present a novel authentication protocol, which offers a high level of security through the combination of a random key scheme with a strong cryptography. The protocol is applicable to resource, power and computationally constraint platforms such as RFID tags. Our investigation shows that it can provide mutual authentication, untraceability, forward and backward security as well as resistance to replay, denial-ofth-service and man-in-the-middle attacks, while retaining a competitive communication cost. The protocol has been integrated into the EPCglobal C1G2 tag protocol, which assures low implementation cost. We also present a successful implementation of our protocol on real-world components such as the INTEL WISP UHF RFID tag and a C1G2 compliant reader.     

Continuous-time norm-constrained Kalman filtering

This paper considers continuous-time state estimation when part of the state estimate or the entire state estimate is norm-constrained. In the former case continuous-time state estimation is considered by posing a constrained optimization problem. The optimization problem can be broken up into two separate optimization problems, one which solves for the optimal observer gain associated with the unconstrained state estimates, while the other solves for the optimal observer gain associated with the constrained state estimates. The optimal constrained state estimate is found by projecting the time derivative of an unconstrained estimate onto the tangent space associated with the norm constraint. The special case where the entire state estimate is norm-constrained is briefly discussed. The utility of the filtering results developed are highlighted through a spacecraft attitude estimation example. Numerical simulation results are included.     

Strength, durability and micro-structural aspects of high performance volcanic ash concrete

This paper presents the results of investigations to assess the suitability of using volcanic ash (VA) as a cement replacement material to produce high performance concrete. Tests were conducted on concrete mixtures replacing 0 to 20% by mass of ordinary Portland cement (OPC) by VA. The performance of high performance volcanic ash concrete (HPVAC) mixtures was evaluated by conducting comprehensive series of tests on fresh and hardened properties as well as durability. The mechanical properties were assessed by compressive strength, while durability characteristics were investigated by rapid chloride permeability (RCP), drying shrinkage (DS), mercury intrusion porosimetry (MIP), differential scanning calorimetry (DSC) and microhardness tests. HPVACs showed better durability properties compared to control concrete with 0% VA. The improved performance of HPVACs was attributed to the refinement of pore structure, and pozzolanic action of VA. HPVAC having a minimum 28-day compressive strength of 60 MPa can be obtained by replacing up to 20% (by mass) of cement by VA. Development of non-expensive and environmentally friendly HPVAC with acceptable strength and durability characteristics (as illustrated in this study) is extremely helpful for the sustainable development and rehabilitation of volcanic disaster areas around the world.     

AR-based deep learning for real-time inspection of cable brackets in aircraft

In the process of aircraft assembly, there exist numerous and ubiquitous cable brackets that shall be installed on frames and subsequently need to be manually verified with CAD models. Such a task is usually performed by special operators, hence is time-consuming, labor-intensive, and error-prone. In order to save the inspection time and increase the reliability of results, many researchers attempt to develop intelligent inspection systems using robotic, AR, or AI technologies. However, there is no comprehensive method to achieve enough portability, intelligence, efficiency, and accuracy while providing intuitive task assistance for inspectors in real time. In this paper, a combined AR+AI system is introduced to assist brackets inspection in a more intelligent yet efficient manner. Especially, AR-based Mask R-CNN is proposed by skillfully integrating markerless AR into deep learning-based instance segmentation to generate more accurate and fewer region proposals, and thus alleviates the computation load of the deep learning program. Based on this, brackets segmentation can be performed robustly and efficiently on mobile devices such as smartphones or tablets. By using the proposed system, CAD model checking can be automatically performed between the segmented physical brackets and the corresponding virtual brackets rendered by AR in real time. Furthermore, the inspection results can be directly projected on the corresponding physical brackets for the convenience of maintenance. To verify the feasibility of the proposed method, experiments are carried out on a full-scale mock-up of C919 aircraft main landing gear cabin. The experimental results indicate that the inspection accuracy is up to 97.1%. Finally, the system has been deployed in the real C919 aircraft final-assembly workshop. The preliminary evaluation reveals that the proposed real-time AR-assisted intelligent inspection approach is effective and promising for large-scale industrial applications.     

Improved genetic algorithm based on multi-layer encoding approach for integrated process planning and scheduling problem

Integrated process planning and scheduling (IPPS) is of great significance for modern manufacturing enterprises to achieve high efficiency in manufacturing and maximize resource utilization. In this paper, the integration strategy and solution method of IPPS problem are deeply studied, and an improved genetic algorithm based on multi-layer encoding (IGA-ML) is proposed to solve the IPPS problem. Firstly, considering the interaction ability between the two subsystems and the multi-flexibility characteristics of the IPPS problem, a new multi-layer integrated encoding method is designed. The encoding method includes feature layer, operation layer, machine layer and scheduling layer, which respectively correspond to the four sub-problems of IPPS problem, which provides a premise for a more flexible and deeper exploration in the solution space. Then, based on the coupling characteristics of process planning and shop scheduling, six evolutionary operators are designed to change the four-layer coding interdependently and independently. Two crossover operators change the population coding in the unit of jobs, and search the solution space globally. The four mutation operators change the population coding in the unit of gene and search the solution space locally. The six operators are used in series and iteratively optimized to ensure a fine balance between the global exploration ability and the local exploitation ability of the algorithm. Finally, performance of IGA-ML is verified by testing on 44 examples of 14 benchmarks. The experimental results show that the proposed algorithm can find better solutions (better than the optimal solutions found so far) on some problems, and it is an effective method to solve the IPPS problem with the maximum completion time as the optimization goal.