Uncertainty and Sensitivity Analysis in Aircraft Operating Costs in Structural Design Optimization

The paper focuses on the development of an aircraft design optimization methodology that models uncertainty and sensitivity analysis in the tradeoff between manufacturing cost, structural requirements, andaircraft direct operating cost.Specifically,ratherthanonlylooking atmanufacturingcost, direct operatingcost is also consideredintermsof the impact of weight on fuel burn, in addition to the acquisition cost to be borne by the operator. Ultimately, there is a tradeoff between driving design according to minimal weight and driving it according to reduced manufacturing cost. Theanalysis of cost is facilitated withagenetic-causal cost-modeling methodology,andthe structural analysis is driven by numerical expressions of appropriate failure modes that use ESDU International reference data. However, a key contribution of the paper is to investigate the modeling of uncertainty and to perform a sensitivity analysis to investigate the robustness of the optimization methodology. Stochastic distributions are used to characterize manufacturing cost distributions, andMonteCarlo analysis is performed in modeling the impact of uncertainty on the cost modeling. The results are then used in a sensitivity analysis that incorporates the optimization methodology. In addition to investigating manufacturing cost variance, the sensitivity of the optimization to fuel burn cost and structural loading are also investigated. It is found that the consideration of manufacturing cost does make an impact and results in a different optimal design configuration from that delivered by the minimal-weight method. However, it was shown that at lower applied loads there is a threshold fuel burn cost at which the optimization process needs to reduce weight, and this threshold decreases with increasing load. The new optimal solution results in lower direct operating cost with a predicted savings of 640=m2 of fuselage skin over the life, relating to a rough order-of-magnitude direct operating cost savings of $500,000 for the fuselage alone of a small regional jet. Moreover, it was found through the uncertainty analysis that the principle was not sensitive to cost variance, although the margins do change.

Multibody modelling of a TB31 and a TB32 crash test with vertical portable concrete barriers: model verification and sensitivity analysis.

In this article the multibody simulation software package MADYMO for analysing and optimizing occupant safety design was used to model crash tests for Normal Containment barriers in accordance with EN 1317. The verification process was carried out by simulating a TB31 and a TB32 crash test performed on vertical portable concrete barriers and by comparing the numerical results to those obtained experimentally. The same modelling approach was applied to both tests to evaluate the predictive capacity of the modelling at two different impact speeds. A sensitivity analysis of the vehicle stiffness was also carried out. The capacity to predict all of the principal EN1317 criteria was assessed for the first time: the acceleration severity index, the theoretical head impact velocity, the barrier working width and the vehicle exit box. Results showed a maximum error of 6% for the acceleration severity index and 21% for theoretical head impact velocity for the numerical simulation in comparison to the recorded data. The exit box position was predicted with a maximum error of 4°. For the working width, a large percentage difference was observed for test TB31 due to the small absolute value of the barrier deflection but the results were well within the limit value from the standard for both tests. The sensitivity analysis showed the robustness of the modelling with respect to contact stiffness increase of ±20% and ±40%. This is the first multibody model of portable concrete barriers that can reproduce not only the acceleration severity index but all the test criteria of EN 1317 and is therefore a valuable tool for new product development and for injury biomechanics research.

Global Sensitivity Analysis for MAP Inference in Graphical Models

We study the sensitivity of a MAP configuration of a discrete probabilistic graphical model with respect to perturbations of its parameters. These perturbations are global, in the sense that simultaneous perturbations of all the parameters (or any chosen subset of them) are allowed. Our main contribution is an exact algorithm that can check whether the MAP configuration is robust with respect to given perturbations. Its complexity is essentially the same as that of obtaining the MAP configuration itself, so it can be promptly used with minimal effort. We use our algorithm to identify the largest global perturbation that does not induce a change in the MAP configuration, and we successfully apply this robustness measure in two practical scenarios: the prediction of facial action units with posed images and the classification of multiple real public data sets. A strong correlation between the proposed robustness measure and accuracy is verified in both scenarios.

Association Analysis of Dyslipidemia-Related Genes in Diabetic Nephropathy

Type 1 diabetes (T1D) increases risk of the development of microvascular complications and cardiovascular disease (CVD). Dyslipidemia is a common risk factor in the pathogenesis of both CVD and diabetic nephropathy (DN), with CVD identified as the primary cause of death in patients with DN. In light of this commonality, we assessed single nucleotide polymorphisms (SNPs) in thirty-seven key genetic loci previously associated with dyslipidemia in a T1D cohort using a casecontrol design. SNPs (n = 53) were genotyped using Sequenom in 1467 individuals with T1D (718 cases with proteinuric nephropathy and 749 controls without nephropathy i.e. normal albumin excretion). Cases and controls were white and recruited from the UK and Ireland. Association analyses were performed using PLINK to compare allele frequencies in cases and controls. In a sensitivity analysis, samples from control individuals with reduced renal function (estimated glomerular filtration rate,60 ml/min/1.73 m2) were excluded. Correction for multiple testing was performed by permutation testing. A total of 1394 samples passed quality control filters. Following regression analysis adjusted by collection center, gender, duration of diabetes, and average HbA1c, two SNPs were significantly associated with DN. rs4420638 in the APOC1 region (odds ratio [OR] = 1.51; confidence intervals [CI]: 1.19–1.91; P = 0.001) and rs1532624 in CETP (OR = 0.82; CI: 0.69–0.99; P = 0.034); rs4420638 was also significantly associated in a sensitivity analysis (P = 0.016) together with rs7679 (P = 0.027). However, no association was significant following correction for multiple testing. Subgroup analysis of end-stage renal disease status failed to reveal any association. Our results suggest common variants associated with dyslipidemia are not strongly associated with DN in T1D among white individuals. Our findings, cannot entirely exclude these key genes which are central to the process of dyslipidemia, from involvement in DN pathogenesis as our study had limited power to detect variants of small effect size. Analysis in larger independent cohorts is required.

Analysis of IL6 Signal Transduction Model using Reduced Rank Regression

This work presents the application of reduced rank regression to the field of systems biology. A computational approach is used to investigate the mechanisms of the janus-associated kinases/signal transducers and transcription factors (JAK/STAT) and mitogen activated protein kinases (MAPK) signal transduction pathways in hepatic cells stimulated by interleukin-6. The results obtained identify the contribution of individual reactions to the dynamics of the model. These findings are compared to previously available results from sensitivity analysis of the model which focused on the parameters involved and their effect. This application of reduced rank regression allows for an understanding of the individual reaction terms involved in the modelled signal transduction pathways and has the benefit of being computationally inexpensive. The obtained results complement existing findings and also confirm the importance of several protein complexes in the MAPK pathway which hints at benefits that can be achieved by further refining the model.

Lifestyle factors and small intestine adenocarcinoma risk: a systematic review and meta-analysis.

Background: Although the incidence of small intestinal adenocarcinoma (SIA) is low, rates are increasing and little information regarding modifiable lifestyle risk factors is available.

Aim: To provide a systematic review of lifestyle factors and SIA risk.

Methods: Ovid MEDLINE, EMBASE and WEB OF SCIENCE were searched from inception to Week 1 October 2013. Nine publications that reported on SIA risk in relation to alcohol intake (n=6), tobacco smoking (n=6), diet (n=5), body mass (n=3), physical activity (n=1), hormone use (n=1) and/or socio-economic status (n=3) were retrieved. Results for alcohol, smoking and SIA risk were pooled using random-effects meta-analyses to produce relative risks (RR) and 95% confidence intervals (CI).

Results: The summary RR for individuals consuming the highest versus lowest category of alcohol intake was 1.51 (95% CI 0.83-2.75; n=5 studies) with significant increased risks emerging in sensitivity analysis with reduced heterogeneity (RR: 1.82, 95% CI: 1.05-3.15; n=4 studies). The pooled SIA RR for individuals in the highest versus lowest category of smoking was 1.24 (95% CI 0.71-2.17; n=5 studies). In relation to dietary factors, high fibre intakes and normal body weight may be protective, while high intakes of red/processed meat and sugary drinks may increase SIA risk. Evidence on socio-economic status and SIA risk was equivocal. Data on other factors were too sparse to draw any conclusions.

Conclusions: Alcohol may be associated with an increased risk of SIA. Further investigation of lifestyle factors, particularly alcohol, smoking and diet, in the aetiology of this cancer is warranted in large consortial studies.

Surrogate-based analysis and optimization for the design of heat sinks with jet impingement

Heat sinks are widely used for cooling electronic devices and systems. Their thermal performance is usually determined by the material, shape, and size of the heat sink. With the assistance of computational fluid dynamics (CFD) and surrogate-based optimization, heat sinks can be designed and optimized to achieve a high level of performance. In this paper, the design and optimization of a plate-fin-type heat sink cooled by impingement jet is presented. The flow and thermal fields are simulated using the CFD simulation; the thermal resistance of the heat sink is then estimated. A Kriging surrogate model is developed to approximate the objective function (thermal resistance) as a function of design variables. Surrogate-based optimization is implemented by adaptively adding infill points based on an integrated strategy of the minimum value, the maximum mean square error approach, and the expected improvement approaches. The results show the influence of design variables on the thermal resistance and give the optimal heat sink with lowest thermal resistance for given jet impingement conditions. 

A systematic review and meta-analysis of the survival of non-feldspathic porcelain veneers over 5 and 10 years

PURPOSE: This systematic review aimed to report and explore the survival of dental veneers constructed from non-feldspathic porcelain over 5 and 10 years.

MATERIALS AND METHODS: A total of 4,294 articles were identified through a systematic search involving all databases in the Cochrane Library, MEDLINE (OVID), EMBASE, Web of Knowledge, specific journals (hand-search), conference proceedings, clinical trials registers, and collegiate contacts. Articles, abstracts, and gray literature were sought by two independent researchers. There were no language limitations. One hundred sixteen studies were identified for full-text assessment, with 10 included in the analysis (5 qualitative, 5 quantitative). Study characteristics and survival (Kaplan-Meier estimated cumulative survival and 95% confidence interval [CI]) were extracted or recalculated. A failed veneer was one which required an intervention that disrupted the original marginal integrity, had been partially or completely lost, or had lost retention more than twice. A meta-analysis and sensitivity analysis of Empress veneers was completed, with an assessment of statistical heterogeneity and publication bias. Clinical heterogeneity was explored for results of all veneering materials from included studies.

RESULTS: Within the 10 studies, veneers were fabricated with IPS Empress, IPS Empress 2, Cerinate, and Cerec computer-aided design/computer-assisted manufacture (CAD/CAM) materials VITA Mark I, VITA Mark II, Ivoclar ProCad. The meta-analysis showed the pooled estimate for Empress veneers to be 92.4% (95% CI: 89.8% to 95.0%) for 5-year survival and 66% to 94% (95% CI: 55% to 99%) for 10 years. Data regarding other non-feldspathic porcelain materials were lacking, with only a single study each reporting outcomes for Empress 2, Cerinate, and various Cerec porcelains over 5 years. The sensitivity analysis showed data from one study had an influencing and stabilizing effect on the 5-year pooled estimate.

CONCLUSION: The long-term outcome (> 5 years) of non-feldspathic porcelain veneers is sparsely reported in the literature. This systematic review indicates that the 5-year cumulative estimated survival for etchable non-feldspathic porcelain veneers is over 90%. Outcomes may prove clinically acceptable with time, but evidence remains lacking and the use of these materials for veneers remains experimental.

Performance projections and design optimization of planar double gate SOI MOSFETs for logic technology applications

In this paper, by investigating the influence of source/drain extension region engineering (also known as gate-source/drain underlap) in nanoscale planar double gate (DG) SOI MOSFETs, we offer new insights into the design of future nanoscale gate-underlap DG devices to achieve ITRS projections for high performance (HP), low standby power (LSTP) and low operating power (LOP) logic technologies. The impact of high-kappa gate dielectric, silicon film thickness, together with parameters associated with the lateral source/drain doping profile, is investigated in detail. The results show that spacer width along with lateral straggle can not only effectively control short-channel effects, thus presenting low off-current in a gate underlap device, but can also be optimized to achieve lower intrinsic delay and higher on-off current ratio (I-on/I-off). Based on the investigation of on-current (I-on), off-current (I-off), I-on/I-off, intrinsic delay (tau), energy delay product and static power dissipation, we present design guidelines to select key device parameters to achieve ITRS projections. Using nominal gate lengths for different technologies, as recommended from ITRS specification, optimally designed gate-underlap DG MOSFETs with a spacer-to-straggle (s/sigma) ratio of 2.3 for HP/LOP and 3.2 for LSTP logic technologies will meet ITRS projection. However, a relatively narrow range of lateral straggle lying between 7 to 8 nm is recommended. A sensitivity analysis of intrinsic delay, on-current and off-current to important parameters allows a comparative analysis of the various design options and shows that gate workfunction appears to be the most crucial parameter in the design of DG devices for all three technologies. The impact of back gate misalignment on I-on, I-off and tau is also investigated for optimized underlap devices.

An Analytical Study of Surplus Value using a Value Driven Design Methodology

People are now becoming more environmentally aware and as a consequence of this, industries such as the aviation industry are striving to design more environmentally friendly products. To achieve this, the current design methodologies must be modified to ensure these issues are considered from product conception through to disposal. This paper discusses the environmental problems in relation to the aviation industry and highlights some logic for making the change from the traditional Systems Engineering approach to the recent design paradigm known as Value Driven Design. Preliminary studies have been undertaken to aid in the understanding of this methodology and the existing surplus value objective function. The main results from the work demonstrate that surplus value works well bringing disparate issues such as manufacture and green taxes together to aid decision making. Further, to date studies on surplus value have used simple sensitivity analysis, but deeper consideration shows non-linear interactions between some of the variables and further work will be needed to fully account for complex issues such as environmental impact and taxes.

Hypermobility and musculoskeletal pain in children:a systematic review

Objective: To examine the evidence of an association between hypermobility and musculoskeletal pain in children. Methods: A systematic review of the literature was performed using the databases PubMed, EMBASE, NHS Evidence, and Medline. Inclusion criteria were observational studies investigating hypermobility and musculoskeletal pain in children. Exclusion criteria were studies conducted on specialist groups (i.e. dancers) or hospital referrals. Pooled odds ratios (ORs) were calculated using random effects models and heterogeneity was tested using ?(2)-tests. Study quality was assessed using the Newcastle-Ottawa Scale for case-control studies. Results: Of the 80 studies identified, 15 met the inclusion criteria and were included in the review. Of these, 13 were included in the statistical analyses. Analysing the data showed that the heterogeneity was too high to allow for interpretation of the meta-analysis (I(2) = 72%). Heterogeneity was much lower when the studies were divided into European (I(2) = 8%) and Afro-Asian subgroups (I(2) = 65%). Sensitivity analysis based on data from studies reporting from European and Afro-Asian regions showed no association in the European studies [OR 1.00, 95% confidence interval (CI) 0.79-1.26] but a marked relationship between hypermobility and joint pain in the Afro-Asian group (OR 2.01, 95% CI 1.45-2.77). Meta-regression showed a highly significant difference between subgroups in both meta-analyses (p <0.001). Conclusion: There seems to be no association between hypermobility and joint pain in Europeans. There does seem to be an association in Afro-Asians; however, there was a high heterogeneity. It is unclear whether this is due to differences in ethnicity, nourishment, climate or study design.

Algorithms for Hidden Markov Models With Imprecisely Specified Parameters

Hidden Markov models (HMMs) are widely used models for sequential data. As with other probabilistic graphical models, they require the specification of precise probability values, which can be too restrictive for some domains, especially when data are scarce or costly to acquire. We present a generalized version of HMMs, whose quantification can be done by sets of, instead of single, probability distributions. Our models have the ability to suspend judgment when there is not enough statistical evidence, and can serve as a sensitivity analysis tool for standard non-stationary HMMs. Efficient inference algorithms are developed to address standard HMM usage such as the computation of likelihoods and most probable explanations. Experiments with real data show that the use of imprecise probabilities leads to more reliable inferences without compromising efficiency.

Modeling of titanium alloys by using artificial neural networks

Titanium alloy exhibits an excellent combination of bio-compatibility, corrosion resistance, strength and toughness. The microstructure of an alloy influences the properties. The microstructures depend mainly on alloying elements, method of production, mechanical, and thermal treatments. The relationships between these variables and final properties of the alloy are complex, non-linear in nature, which is the biggest hurdle in developing proper correlations between them by conventional methods. So, we developed artificial neural networks (ANN) models for solving these complex phenomena in titanium alloys.

In the present work, ANN models were used for the analysis and prediction of the correlation between the process parameters, the alloying elements, microstructural features, beta transus temperature and mechanical properties in titanium alloys. Sensitivity analysis of trained neural network models were studied which resulted a better understanding of relationships between inputs and outputs. The model predictions and the analysis are well in agreement with the experimental results. The simulation results show that the average output-prediction error by models are less than 5% of the prediction range in more than 95% of the cases, which is quite acceptable for all metallurgical purposes.