Aircraft Cost Modelling using the Genetic Causal Technique within a Systems Engineering Approach

The paper is primarily concerned with the modelling of aircraft manufacturing cost. The aim is to establish an integrated life cycle balanced design process through a systems engineering approach to interdisciplinary analysis and control. The cost modelling is achieved using the genetic causal approach that enforces product family categorisation and the subsequent generation of causal relationships between deterministic cost components and their design source. This utilises causal parametric cost drivers and the definition of the physical architecture from the Work Breakdown Structure (WBS) to identify product families. The paper presents applications to the overall aircraft design with a particular focus on the fuselage as a subsystem of the aircraft, including fuselage panels and localised detail, as well as engine nacelles. The higher level application to aircraft requirements and functional analysis is investigated and verified relative to life cycle design issues for the relationship between acquisition cost and Direct Operational Cost (DOC), for a range of both metal and composite subsystems. Maintenance is considered in some detail as an important contributor to DOC and life cycle cost. The lower level application to aircraft physical architecture is investigated and verified for the WBS of an engine nacelle, including a sequential build stage investigation of the materials, fabrication and assembly costs. The studies are then extended by investigating the acquisition cost of aircraft fuselages, including the recurring unit cost and the non-recurring design cost of the airframe sub-system. The systems costing methodology is facilitated by the genetic causal cost modeling technique as the latter is highly generic, interdisciplinary, flexible, multilevel and recursive in nature, and can be applied at the various analysis levels required of systems engineering. Therefore, the main contribution of paper is a methodology for applying systems engineering costing, supported by the genetic causal cost modeling approach, whether at a requirements, functional or physical level.

System oriented neural networks - Problem formulation, methodology and application

A novel methodology is proposed for the development of neural network models for complex engineering systems exhibiting nonlinearity. This method performs neural network modeling by first establishing some fundamental nonlinear functions from a priori engineering knowledge, which are then constructed and coded into appropriate chromosome representations. Given a suitable fitness function, using evolutionary approaches such as genetic algorithms, a population of chromosomes evolves for a certain number of generations to finally produce a neural network model best fitting the system data. The objective is to improve the transparency of the neural networks, i.e. to produce physically meaningful

6-T SRAM cell design with nanoscale double-gate SOI MOSFETs: impact of source/drain engineering and circuit topology

The impact of source/drain engineering on the performance of a six-transistor (6-T) static random access memory (SRAM) cell, based on 22 nm double-gate (DG) SOI MOSFETs, has been analyzed using mixed-mode simulation, for three different circuit topologies for low voltage operation. The trade-offs associated with the various conflicting requirements relating to read/write/standby operations have been evaluated comprehensively in terms of eight performance metrics, namely retention noise margin, static noise margin, static voltage/current noise margin, write-ability current, write trip voltage/current and leakage current. Optimal design parameters with gate-underlap architecture have been identified to enhance the overall SRAM performance, and the influence of parasitic source/drain resistance and supply voltage scaling has been investigated. A gate-underlap device designed with a spacer-to-straggle (s/sigma) ratio in the range 2-3 yields improved SRAM performance metrics, regardless of circuit topology. An optimal two word-line double-gate SOI 6-T SRAM cell design exhibits a high SNM similar to 162 mV, I-wr similar to 35 mu A and low I-leak similar to 70 pA at V-DD = 0.6 V, while maintaining SNM similar to 30% V-DD over the supply voltage (V-DD) range of 0.4-0.9 V.

Phenomenology and system engineering of micro- and nano-antenna FPA sensors for detection of concealed weapons and improvised explosive devices

The ability of millimetre wave and terahertz systems to penetrate clothing is well known. The fact that the transmission of clothing and the reflectivity of the body vary as a function of frequency is less so. Several instruments have now been developed to exploit this capability. The choice of operating frequency, however, has often been associated with the maturity and the cost of the enabling technology rather than a sound systems engineering approach. Top level user and systems requirements have been derived to inform the development of design concepts. Emerging micro and nano technology concepts have been reviewed and we have demonstrated how these can be evaluated against these requirements by simulation using OpenFx. Openfx is an open source suite of 3D tools for modeling, animation and visualization which has been modified for use at millimeter waves. © 2012 SPIE.

Towards optimal software engineering: learning from agile practice

In essence, optimal software engineering means creating the right product, through the right process, to the overall satisfaction of everyone involved. Adopting the agile approach to software development appears to have helped many companies make substantial progress towards that goal. The purpose of this paper is to clarify that contribution from comparative survey information gathered in 2010 and 2012. The surveys were undertaken in software development companies across Northern Ireland. The paper describes the design of the surveys and discusses optimality in relation to the results obtained. Both surveys aimed to achieve comprehensive coverage of a single region rather than rely on a voluntary sample. The main outcome from the work is a collection of insights into the nature and advantages of agile development, suggesting how further progress towards optimality might be achieved.

Engineering Innovative Products: A Practical Experience

Engineering Innovative Products: A Practical Experience is a pioneering book that will be of key use to senior undergraduate and graduate engineering students who are being encouraged to explore innovation and commercialization as part of their courses. The book will teach the essential skills of entrepreneurship and address the fundamental requirements needed to establish a successful technology company.

Histogram of oriented gradients front end processing: An FPGA based processor approach

The Field Programmable Gate Array (FPGA) implementation of the commonly used Histogram of Oriented Gradients (HOG) algorithm is explored. The HOG algorithm is employed to extract features for object detection. A key focus has been to explore the use of a new FPGA-based processor which has been targeted at image processing. The paper gives details of the mapping and scheduling factors that influence the performance and the stages that were undertaken to allow the algorithm to be deployed on FPGA hardware, whilst taking into account the specific IPPro architecture features. We show that multi-core IPPro performance can exceed that of against state-of-the-art FPGA designs by up to 3.2 times with reduced design and implementation effort and increased flexibility all on a low cost, Zynq programmable system.

Emotional insecurity in the family and community and youth delinquency in Northern Ireland: A person-oriented analysis across five-waves

Background: Over one billion children are exposed worldwide to political violence and armed conflict. Currently, conclusions about bases for adjustment problems are qualified by limited longitudinal research from a process-oriented, social-ecological perspective. In this study, we examined a theoretically-based model for the impact of multiple levels of the social ecology (family, community) on adolescent delinquency. Specifically, this study explored the impact of children’s emotional insecurity about both the family and community on youth delinquency in Northern Ireland. Methods: In the context of a five-wave longitudinal research design, participants included 999 mother-child dyads in Belfast (482 boys, 517 girls), drawn from socially-deprived, ethnically-homogenous areas that had experienced political violence. Youth ranged in age from 10 to 20 and were 12.18 (SD = 1.82) years old on average at Time 1. Findings: The longitudinal analyses were conducted in hierarchical linear modeling (HLM), allowing for the modeling of inter-individual differences in intra-individual change. Intra-individual trajectories of emotional insecurity about the family related to children’s delinquency. Greater insecurity about the community worsened the impact of family conflict on youth’s insecurity about the family, consistent with the notion that youth’s insecurity about the community sensitizes them to exposure to family conflict in the home. Conclusions: The results suggest that ameliorating children’s insecurity about family and community in contexts of political violence is an important goal toward improving adolescents’ well-being, including reduced risk for delinquency.

Exploiting Human Resource Requirements to Infer Human Movement Patterns for Use in Modelling Disease Transmission Systems: An Example from Eastern Province, Zambia

In this research, an agent-based model (ABM) was developed to generate human movement routes between homes and water resources in a rural setting, given commonly available geospatial datasets on population distribution, land cover and landscape resources. ABMs are an object-oriented computational approach to modelling a system, focusing on the interactions of autonomous agents, and aiming to assess the impact of these agents and their interactions on the system as a whole. An A* pathfinding algorithm was implemented to produce walking routes, given data on the terrain in the area. A* is an extension of Dijkstra's algorithm with an enhanced time performance through the use of heuristics. In this example, it was possible to impute daily activity movement patterns to the water resource for all villages in a 75 km long study transect across the Luangwa Valley, Zambia, and the simulated human movements were statistically similar to empirical observations on travel times to the water resource (Chi-squared, 95% confidence interval). This indicates that it is possible to produce realistic data regarding human movements without costly measurement as is commonly achieved, for example, through GPS, or retrospective or real-time diaries. The approach is transferable between different geographical locations, and the product can be useful in providing an insight into human movement patterns, and therefore has use in many human exposure-related applications, specifically epidemiological research in rural areas, where spatial heterogeneity in the disease landscape, and space-time proximity of individuals, can play a crucial role in disease spread.

Mechanical properties and cellular response of novel electrospun nanofibers for ligament tissue engineering: Effects of orientation and geometry

Electrospun nanofibers are a promising material for ligamentous tissue engineering, however weak mechanical properties of fibers to date have limited their clinical usage. The goal of this work was to modify electrospun nanofibers to create a robust structure that mimics the complex hierarchy of native tendons and ligaments. The scaffolds that were fabricated in this study consisted of either random or aligned nanofibers in flat sheets or rolled nanofiber bundles that mimic the size scale of fascicle units in primarily tensile load bearing soft musculoskeletal tissues. Altering nanofiber orientation and geometry significantly affected mechanical properties; most notably aligned nanofiber sheets had the greatest modulus; 125% higher than that of random nanofiber sheets; and 45% higher than aligned nanofiber bundles. Modifying aligned nanofiber sheets to form aligned nanofiber bundles also resulted in approximately 107% higher yield stresses and 140% higher yield strains. The mechanical properties of aligned nanofiber bundles were in the range of the mechanical properties of the native ACL: modulus=158±32MPa, yield stress=57±23MPa and yield strain=0.38±0.08. Adipose derived stem cells cultured on all surfaces remained viable and proliferated extensively over a 7 day culture period and cells elongated on nanofiber bundles. The results of the study suggest that aligned nanofiber bundles may be useful for ligament and tendon tissue engineering based on their mechanical properties and ability to support cell adhesion, proliferation, and elongation.