Numerical and Experimental Investigation of Aircraft Panel Deformations During Riveting Process

In collaboration with Airbus-UK, the dimensional growth of aircraft panels while being riveted with stiffeners is investigated. Small panels are used in this investigation. The stiffeners have been fastened to the panels with rivets and it has been observed that during this operation the panels expand in the longitudinal and transverse directions. It has been observed that the growth is variable and the challenge is to control the riveting process to minimize this variability. In this investigation, the assembly of the small panels and longitudinal stiffeners has been simulated using static stress and nonlinear explicit finite element models. The models have been validated against a limited set of experimental measurements; it was found that more accurate predictions of the riveting process are achieved using explicit finite element models. Yet, the static stress finite element model is more time efficient, and more practical to simulate hundreds of rivets and the stochastic nature of the process. Furthermore, through a series of numerical simulations and probabilistic analyses, the manufacturing process control parameters that influence panel growth have been identified. Alternative fastening approaches were examined and it was found that dimensional growth can be controlled by changing the design of the dies used for forming the rivets.

Investigation of Aircraft Panel Deformations during Riveting Process

In collaboration with Airbus-UK, the dimensional growth of small panels while being riveted with stiffeners is investigated. The stiffeners have been fastened to the panels with rivets and it has been observed that during this operation the panels expand in the longitudinal and transverse directions. It has been observed that the growth is variable and the challenge is to control the riveting process to minimize this variability. In this investigation, the assembly of the small panels and longitudinal stiffeners has been simulated using low and high fidelity nonlinear finite element models. The models have been validated against a limited set of experimental measurements; it was found that more accurate predictions of the riveting process are achieved using high fidelity explicit finite element models. Furthermore, through a series of numerical simulations and probabilistic analyses, the manufacturing process control parameters that influence panel growth have been identified. Alternative fastening approaches were examined and it was found that dimensional growth can be controlled by changing the design of the dies used for forming the rivets.

A simple inhibition coefficient for quantifying potency of biocontrol agents against plant-pathogenic fungi

Microbial interactions depend on a range of biotic and environmental variables, and are both dynamic and unpredictable. For some purposes, and under defined conditions, it is nevertheless imperative to evaluate the inhibitory efficacy of microbes, such as those with potential as biocontrol agents. We selected six, phylogenetically diverse microbes to determine their ability to inhibit the ascomycete Fusarium
coeruleum, a soil-dwelling pathogen of potato tubers that causes the storage disease dry rot. Interaction assays, where colony development was quantified (for both fungal pathogen and potential control agents), were therefore carried out on solid media. The key parameters that contributed to, and were indicative of, inhibitory efficacy were identified as: fungal growth-rates (i) prior to contact with the biocontrol
agent and (ii) if/once contact with the biocontrol agent was established (i.e. in the zone of mixed
culture), and (iii) the ultimate distance traveled by the fungal mycelium. It was clear that there was no correlation between zones of fungal inhibition and the overall reduction in the extent of fungal colony development. An inhibition coefficient was devised which incorporated the potential contributions of distal inhibition of fungal growth-rate; prevention of mycelium development in the vicinity of the biocontrol
agent; and ability to inhibit plant-pathogen growth-rate in the zone of mixed culture (in a ratio of 2:2:1). The values derived were 84.2 for Bacillus subtilis (QST 713), 74.0 for Bacillus sp. (JC12GB42), 30.7 for Pichia anomala (J121), 19.3 for Pantoea agglomerans (JC12GB34), 13.9 for Pantoea sp. (S09:T:12), and
21.9 (indicating a promotion of fungal growth) for bacterial strain (JC12GB54). This inhibition coefficient, with a theoretical maximum of 100, was consistent with the extent of F. coeruleum-colony development (i.e. area, in cm2) and assays of these biocontrol agents carried out previously against Fusarium
spp., and other fungi. These findings are discussed in relation to the dynamics and inherent complexity of natural ecosystems, and the need to adapt models for use under specific sets of conditions.

Improved Principal Component Monitoring of Large-Scale Processes

This is the first paper that shows and theoretically analyses that the presence of auto-correlation can produce considerable alterations in the Type I and Type II errors in univariate and multivariate statistical control charts. To remove this undesired effect, linear inverse ARMA filter are employed and the application studies in this paper show that false alarms (increased Type I errors) and an insensitive monitoring statistics (increased Type II errors) were eliminated.

Nonlinear PCA with Local Approach for Diesel Engine Fault Detection and Diagnosis

This brief examines the application of nonlinear statistical process control to the detection and diagnosis of faults in automotive engines. In this statistical framework, the computed score variables may have a complicated nonparametric distri- bution function, which hampers statistical inference, notably for fault detection and diagnosis. This brief shows that introducing the statistical local approach into nonlinear statistical process control produces statistics that follow a normal distribution, thereby enabling a simple statistical inference for fault detection. Further, for fault diagnosis, this brief introduces a compensation scheme that approximates the fault condition signature. Experimental results from a Volkswagen 1.9-L turbo-charged diesel engine are included.

Fault reconstruction in linear dynamic systems using multivariate statistics

Treasure et al. (2004) recently proposed a new sub space-monitoring technique, based on the N4SID algorithm, within the multivariate statistical process control framework. This dynamic-monitoring method requires considerably fewer variables to be analysed when compared with dynamic principal component analysis (PCA). The contribution charts and variable reconstruction, traditionally employed for static PCA, are analysed in a dynamic context. The contribution charts and variable reconstruction may be affected by the ratio of the number of retained components to the total number of analysed variables. Particular problems arise if this ratio is large and a new reconstruction chart is introduced to overcome these. The utility of such a dynamic contribution chart and variable reconstruction is shown in a simulation and by application to industrial data from a distillation unit.

High tolerance to gate misalignment in low voltage gate-underlap double gate MOSFETs

.In this letter, we demonstrate for the first time that gate misalignment is not a critical limiting factor for low voltage operation in gate-underlap double gate (DG) devices. Our results show that underlap architecture significantly extends the tolerable limit of gate misalignment in 25 nm devices. DG MOSFETs with high degree of gate misalignment and optimal gate-underlap design can perform comparably or even better than self-aligned nonunderlap devices. Results show that spacer-to-straggle (s/sigma) ratio, a key design parameter for underlap devices, should be within the range of 2.3-3.0 to accommodate back gate misalignment. These results are very significant as the stringent process control requirements for achieving self-alignment in nanoscale planar DG MOSFETs are considerably relaxed

Vasoactivity of AG014699, a clinically active small molecule inhibitor of poly(ADP-ribose) polymerase: a contributory factor to chemopotentiation in vivo?

Purpose: Poly(ADP-ribose) polymerase (PARP) plays an important role in DNA repair, and PARP inhibitors can enhance the activity of DNA-damaging agents in vitro and in vivo. AG014699 is a potent PARP inhibitor in phase II clinical development. However, the range of therapeutics with which AG014699 could interact via a DNA-repair based mechanism is limited. We aimed to investigate a novel, vascular-based activity of AG014699, underlying in vivo chemosensitization, which could widen its clinical application.

Experimental Design: Temozolomide response was analyzed in vitro and in vivo. Vessel dynamics were monitored using “mismatch” following the administration of perfusion markers and real-time analysis of fluorescently labeled albumin uptake in to tumors established in dorsal window chambers. Further mechanistic investigations used ex vivo assays of vascular smooth muscle relaxation, gut motility, and myosin light chain kinase (MLCK) inhibition.

Results: AG014699 failed to sensitize SW620 cells to temozolomide in vitro but induced pronounced enhancement in vivo. AG014699 (1 mg/kg) improved tumor perfusion comparably with the control agents nicotinamide (1 g/kg) and AG14361 (forerunner to AG014699; 10 mg/kg). AG014699 and AG14361 relaxed preconstricted vascular smooth muscle more potently than the standard agent, hydralazine, with no impact on gut motility. AG014699 inhibited MLCK at concentrations that relaxed isolated arteries, whereas AG14361 had no effect.

Conclusion: Increased vessel perfusion elicited by AG014699 could increase tumor drug accumulation and therapeutic response. Vasoactive concentrations of AG014699 do not cause detrimental side effects to gut motility and may increase the range of therapeutics with which AG014699 could be combined with for clinical benefit.

Variation of strand break yield for plasmid DNA irradiated with high-Z metal nanoparticles.

PURPOSE: Poly(ADP-ribose) polymerase (PARP) plays an important role in DNA repair, and PARP inhibitors can enhance the activity of DNA-damaging agents in vitro and in vivo. AG014699 is a potent PARP inhibitor in phase II clinical development. However, the range of therapeutics with which AG014699 could interact via a DNA-repair based mechanism is limited. We aimed to investigate a novel, vascular-based activity of AG014699, underlying in vivo chemosensitization, which could widen its clinical application. EXPERIMENTAL DESIGN: Temozolomide response was analyzed in vitro and in vivo. Vessel dynamics were monitored using "mismatch" following the administration of perfusion markers and real-time analysis of fluorescently labeled albumin uptake in to tumors established in dorsal window chambers. Further mechanistic investigations used ex vivo assays of vascular smooth muscle relaxation, gut motility, and myosin light chain kinase (MLCK) inhibition. RESULTS: AG014699 failed to sensitize SW620 cells to temozolomide in vitro but induced pronounced enhancement in vivo. AG014699 (1 mg/kg) improved tumor perfusion comparably with the control agents nicotinamide (1 g/kg) and AG14361 (forerunner to AG014699; 10 mg/kg). AG014699 and AG14361 relaxed preconstricted vascular smooth muscle more potently than the standard agent, hydralazine, with no impact on gut motility. AG014699 inhibited MLCK at concentrations that relaxed isolated arteries, whereas AG14361 had no effect. CONCLUSION: Increased vessel perfusion elicited by AG014699 could increase tumor drug accumulation and therapeutic response. Vasoactive concentrations of AG014699 do not cause detrimental side effects to gut motility and may increase the range of therapeutics with which AG014699 could be combined with for clinical benefi

Application of auto-associative neural networks to transient fault detection in an IC engine

The tailpipe emissions from automotive engines have been subject to steadily reducing legislative limits. This reduction has been achieved through the addition of sub-systems to the basic four-stroke engine which thereby increases its complexity. To ensure the entire system functions correctly, each system and / or sub-systems needs to be continuously monitored for the presence of any faults or malfunctions. This is a requirement detailed within the On-Board Diagnostic (OBD) legislation. To date, a physical model approach has been adopted by me automotive industry for the monitoring requirement of OBD legislation. However, this approach has restrictions from the available knowledge base and computational load required. A neural network technique incorporating Multivariant Statistical Process Control (MSPC) has been proposed as an alternative method of building interrelationships between the measured variables and monitoring the correct operation of the engine. Building upon earlier work for steady state fault detection, this paper details the use of non-linear models based on an Auto-associate Neural Network (ANN) for fault detection under transient engine operation. The theory and use of the technique is shown in this paper with the application to the detection of air leaks within the inlet manifold system of a modern gasoline engine whilst operated on a pseudo-drive cycle. Copyright © 2007 by ASME.

Lean Software Management: BBC Worldwide Case Study

This case study examines how the lean ideas behind the Toyota production system can be applied to software project management. It is a detailed investigation of the performance of a nine-person software development team employed by BBC Worldwide based in London. The data collected in 2009 involved direct observations of the development team, the kanban boards, the daily stand-up meetings, semistructured interviews with a wide variety of staff, and statistical analysis. The evidence shows that over the 12-month period, lead time to deliver software improved by 37%, consistency of delivery rose by 47%, and defects reported by customers fell 24%. The significance of this work is showing that the use of lean methods including visual management, team-based problem solving, smaller batch sizes, and statistical process control can improve software development. It also summarizes key differences between agile and lean approaches to software development. The conclusion is that the performance of the software development team was improved by adopting a lean approach. The faster delivery with a focus on creating the highest value to the customer also reduced both technical and market risks. The drawbacks are that it may not fit well with existing corporate standards.

How crucial is back gate misalignment/oversize in double gate MOSFETs for ultra-low-voltage analog/rf applications?

In the present work, by investigating the influence of source/drain (S/D) extension region engineering (also known as gate-underlap architecture) in planar Double Gate (DG) SOI MOSFETs, we offer new design insights to achieve high tolerance to gate misalignment/oversize in nanoscale devices for ultra-low-voltage (ULV) analog/rf applications. Our results show that (i) misaligned gate-underlap devices perform significantly better than DC devices with abrupt source/drain junctions with identical misalignment, (ii) misaligned gate underlap performance (with S/D optimization) exceeds perfectly aligned DG devices with abrupt S/D regions and (iii) 25% back gate misalignment can be tolerated without any significant degradation in cut-off frequency (f(T)) and intrinsic voltage gain (A(VO)). Gate-underlap DG devices designed with spacer-to-straggle ratio lying within the range 2.5 to 3.0 show best tolerance to misaligned/oversize back gate and indeed are better than self-aligned DG MOSFETs with non-underlap (abrupt) S/D regions. Impact of gate length and silicon film thickness scaling is also discussed. These results are very significant as the tolerable limit of misaligned/oversized back gate is considerably extended and the stringent process control requirements to achieve self-alignment can be relaxed for nanoscale planar ULV DG MOSFETs operating in weak-inversion region. The present work provides new opportunities for realizing future ULV analog/rf design with nanoscale gate-underlap DG MOSFETs. (C) 2008 Elsevier Ltd. All rights reserved.

Thermoforming carbon fibre-reinforced thermoplastic composites

The use of carbon fibre composites is growing in many sectors but their use remains stronger in very high value industries such as aerospace where the demands of the application more easily justify the high energy input needed and the corresponding costs incurred. This energy and cost input is returned through gains over the whole life of the product, with for example, longer maintenance intervals for an aircraft and lower fuel burn. Thermoplastic composites however have a different energy and cost profile compared to traditional thermosets with notable differences in recyclability, but this profile is not well quantified or documented. This study considers the key process control parameters and identifies an optimal window for processing, along with the effect this has on the final characteristics of the manufactured parts. Interactions between parameters and corresponding sensitivities are extracted from the results.

Max separation clustering for feature extraction from Optical Emission Spectroscopy Data

This paper proposes max separation clustering (MSC), a new non-hierarchical clustering method used for feature extraction from optical emission spectroscopy (OES) data for plasma etch process control applications. OES data is high dimensional and inherently highly redundant with the result that it is difficult if not impossible to recognize useful features and key variables by direct visualization. MSC is developed for clustering variables with distinctive patterns and providing effective pattern representation by a small number of representative variables. The relationship between signal-to-noise ratio (SNR) and clustering performance is highlighted, leading to a requirement that low SNR signals be removed before applying MSC. Experimental results on industrial OES data show that MSC with low SNR signal removal produces effective summarization of the dominant patterns in the data.