Development of a virtual reality laboratory stressor

Virtual Reality - This research report describes the development of a virtual reality (VR) laboratory stressor to study the effects of exposure to stressful events. The aim of the research was to...     

Polyester functionalization for mycobacterial capture

Tuberculosis (TB) is one of the deadliest diseases known to man and ranks among the top ten global causes of fatalities. Children often develop a paucibacillary form of this disease which makes diagnosis arduous even with the aid of sophisticated techniques. In these cases, the concentration of bacteria in their sputum falls below the lowest limit of detection for sputum smear microscopy, the technique predominantly used in developing countries. In this study we aim to test the hypothesis that modifying a polymer, often used in buccal swabs, could assist in creating a capturing and concentrating oral swab for Mycobacterium tuberculosis (Mtb), the pathogenic bacterial species responsible for TB. Such a device will assist in meeting the detection limit and allow for rapid detection of the disease. The polymer used was a micro fibrous form of poly(ethylene terephthalate) (PET) which was surface functionalized with Concanavalin A (Con A), a lectin based adhesin with an affinity for the mannose groups on the Mtb cell wall. The functionalization was mediated with glutaraldehyde as bioconjugate molecule and found to produce a surface uniformly covered with Con A. Affinity studies between the modified fibers and the Mycobacterium bovis bacillus Calmette-Guérin (BCG), as Mtb mimic, were conducted to evaluate the capturing abilities of the substrate. The results indicate that the fibers avidly captured BCG and that the fibrous matrix aided in its function. Dilution studies showed successful capturing of the bacterial species at concentrations characteristic of paucibacillary cases. In this study a commercial polymeric material was successfully surface modified with a biological entity to create a substrate to which Mtb could adhere and accordingly be captured.     

High-throughput drilling of titanium alloys

Experiments of high-throughput drilling of Ti–6Al–4V at 183 m/min cutting speed and 156 mm³/s material removal rate (MRR) using a 4 mm diameter WC–Co spiral point drill were conducted. The tool material and geometry and drilling process parameters, including cutting speed, feed, and fluid supply, were studied to evaluate the effect on drill life, thrust force, torque, energy, and burr formation. The tool wear mechanism, hole surface roughness, and chip light emission and morphology for high-throughput drilling were investigated. Supplying the cutting fluid via through-the-drill holes has proven to be a critical factor for drill life, which can be increased by 10 times compared to that of dry drilling at 183 m/min cutting speed and 0.051 mm/rev feed. Under the same MRR of 156 mm³/s with a doubled feed of 0.102 mm/rev (91 m/min cutting speed), over 200 holes can be drilled. The balance of cutting speed and feed is essential to achieve long drill life and good hole surface roughness. This study demonstrates that, using proper drilling process parameters, spiral point drill geometry, and fine-grained WC–Co tool material, the high-throughput drilling of Ti alloy is technically feasible.     

In situ repair welding of steam turbine shroud for replacing a cracked blade

A root-cracked blade in a high-pressure steam turbine of a nuclear power plant had to be replaced with a new blade by cutting the shroud to remove the cracked blade. This necessitated in situ welding of a new shroud piece with the existing shroud after the blade replacement. The in situ welding of the shroud, a 12% Cr martensitic stainless steel with tempered martensite microstructure, was carried out using gastungsten arc welding and 316L austenitic stainless steel filler metal followed by localized postweld heat treatment at 873 K for 1 h using a specially designed electrical resistance-heating furnace. Mock-up trials were carried out to ensure that sound welds could be made under the constraints present during the in situ repair welding operation. In situ metallography of the repair weld after postweld heat treatment confirmed the adequate tempering of the martensitic structure in the heat-affected zone. Metallurgical investigations carried out in the laboratory on a shroud test-piece that had been welded using the same procedure as employed in the field confirmed the success of the in situ repair operation. The alternate option available was replacing the cracked blade and the shroud piece to which it is riveted with a new one, reducing the height of all the blades attached to the shroud by machining, riveting the blades with reduced height to the new shroud, and, finally, dynamic balancing of the entire turbine after completion of the repair. This option is both time-consuming and expensive. Hence, the successful completion of this repair welding resulted in enormous savings both in terms of reducing the downtime of the plant and the cost of the repair. The turbine has been put back into service and has been operating satisfactorily since December 2000.     

A fuzzy expert system for the design of machining operations

In this paper, a fuzzy expert system called Smart Assistant to Machinist, or SAM, is introduced. The system consists of four modules: a database, a cutter selection module, a cutting condition design module and a learning module. The database consists of four data files: work material data file, machine tool data file, machining plan data file (which defines desirable material removal rate, surface finish, cutting speed, feed, depth of cut, etc.) and cutter data file. The cutter selection module is developed based on fuzzy logic, in which the cutter selection is conducted in three steps. First, the input information is “fuzzyized” Next, using the fuzzy correlation functions, cutter grades and cutters are selected. Then, the selected grades and cutters are searched against the cutter data file to check the availability. The cutting condition design module is developed based on fuzzy non-linear programming and user interactive graphics. The learning module is developed so that users can fine-tune the fuzzy functions to further improve the performance of the system. The system has two distinct features: (1) it can select cutters and design cutting conditions based on partial and imprecise information, and (2) it selects commercial cutter products used on shop floors. The use of the system is demonstrated using two examples.     

Speeding up the spatial adiabatic passage of matter waves in optical microtraps by optimal control

We numerically investigate the performance of atomic transport in optical microtraps via the so called spatial adiabatic passage technique. Our analysis is carried out by means of optimal control methods, which enable us to determine suitable transport control pulses. We investigate the ultimate limits of the optimal control in speeding up the transport process in a triple well configuration for both a single atomic wave packet and a Bose-Einstein condensate within a regime of experimental parameters achievable with current optical technology.     

Inferring (Biological) Signal Transduction Networks via Transitive Reductions of Directed Graphs

In this paper we consider the p-ary transitive reduction (TR _p ) problem where p>0 is an integer; for p=2 this problem arises in inferring a sparsest possible (biological) signal transduction network consistent with a set of experimental observations with a goal to minimize false positive inferences even if risking false negatives. Special cases of TR _p have been investigated before in different contexts; the best previous results are as follows:

Dynamic Verification of Memory Consistency in Cache-Coherent Multithreaded Computer Architectures

Multithreaded servers with cache-coherent shared memory are the dominant type of machines used to run critical network services and database management systems. To achieve the high availability required for these tasks, it is necessary to incorporate mechanisms for error detection and recovery. Correct operation of the memory system is defined by the memory consistency model. Errors can therefore be detected by checking if the observed memory system behavior deviates from the specified consistency model. Based on recent work, we design a framework for dynamic verification of memory consistency (DVMC). The framework consists of mechanisms to verify three invariants that are proven to guarantee that a specified memory consistency model is obeyed. We describe an implementation of the framework for the SPARCv9 architecture, and we experimentally evaluate its performance using full-system simulation of commercial workloads.     

An augmented Lagrangian approach to non-convex SAO using diagonal quadratic approximations

Successful gradient-based sequential approximate optimization (SAO) algorithms in simulation-based optimization typically use convex separable approximations. Convex approximations may however not be very efficient if the true objective function and/or the constraints are concave. Using diagonal quadratic approximations, we show that non-convex approximations may indeed require significantly fewer iterations than their convex counterparts. The nonconvex subproblems are solved using an augmented Lagrangian (AL) strategy, rather than the Falk-dual, which is the norm in SAO based on convex subproblems. The results suggest that transformation of large-scale optimization problems with only a few constraints to a dual form via convexification need sometimes not be required, since this may equally well be done using an AL formulation.