Development of an automated aircraft subsystem architecture generation and analysis tool

Purpose – The purpose of this paper is to present a new computational framework to address future preliminary design needs for aircraft subsystems. The ability to investigate multiple candidate technologies forming subsystem architectures is enabled with the provision of automated architecture generation, analysis and optimization. Main focus lies with a demonstration of the frameworks workings, as well as the optimizers performance with a typical form of application problem. Design/methodology/approach – The core aspects involve a functional decomposition, coupled with a synergistic mission performance analysis on the aircraft, architecture and component levels. This may be followed by a complete enumeration of architectures, combined with a user defined technology filtering and concept ranking procedure. In addition, a hybrid heuristic optimizer, based on ant systems optimization and a genetic algorithm, is employed to produce optimal architectures in both component composition and design parameters. The optimizer is tested on a generic architecture design problem combined with modified Griewank and parabolic functions for the continuous space. Findings – Insights from the generalized application problem show consistent rediscovery of the optimal architectures with the optimizer, as compared to a full problem enumeration. In addition multi-objective optimization reveals a Pareto front with differences in component composition as well as continuous parameters. Research limitations/implications – This paper demonstrates the frameworks application on a generalized test problem only. Further publication will consider real engineering design problems. Originality/value – The paper addresses the need for future conceptual design methods of complex systems to consider a mixed concept space of both discrete and continuous nature via automated methods

Hierarchical strategies for efficient fault recovery on the reconfigurable PAnDA device

A novel hierarchical fault-tolerance methodology for reconfigurable devices is presented. A bespoke multi-reconfigurable FPGA architecture, the programmable analogue and digital array (PAnDA), is introduced allowing fine-grained reconfiguration beyond any other FPGA architecture currently in existence. Fault blind circuit repair strategies, which require no specific information of the nature or location of faults, are developed, exploiting architectural features of PAnDA. Two fault recovery techniques, stochastic and deterministic strategies, are proposed and results of each, as well as a comparison of the two, are presented. Both approaches are based on creating algorithms performing fine-grained hierarchical partial reconfiguration on faulty circuits in order to repair them. While the stochastic approach provides insights into feasibility of the method, the deterministic approach aims to generate optimal repair strategies for generic faults induced into a specific circuit. It is shown that both techniques successfully repair the benchmark circuits used after random faults are induced in random circuit locations, and the deterministic strategies are shown to operate efficiently and effectively after optimisation for a specific use case. The methods are shown to be generally applicable to any circuit on PAnDA, and to be straightforwardly customisable for any FPGA fabric providing some regularity and symmetry in its structure

Application of an automated aircraft architecture generation and analysis tool to unmanned aerial vehicle subsystem design

The work presents the application of a new computational framework, addressing future preliminary design needs for aircraft subsystems. The ability to investigate multiple candidate technologies forming subsystem architectures is enabled with the provision of automated architecture generation, analysis and optimisation. The core aspects involve a functional decomposition, coupled with a synergistic mission performance analysis on the aircraft, architecture and component level. This may be followed by a complete enumeration of architectures combined with a user-defined technology filtering and concept ranking procedure. In addition, a novel hybrid heuristic optimiser, based on ant colony optimisation and a genetic algorithm, is employed to produce optimal architectures in both component composition and design parameters. The framework is applied to the design of a regenerative energy system for a long endurance high altitude unmanned aerial vehicle, considering various emerging technologies. A comparison with the traditional design processes and certification requirements is made as well as technology trends summarised and substantiated

Diagnosing faults in autonomous robot plan execution

A major requirement for an autonomous robot is the capability to diagnose faults during plan execution in an uncertain environment. Many diagnostic researches concentrate only on hardware failures within an autonomous robot. Taking a different approach, the implementation of a Telerobot Diagnostic System that addresses, in addition to the hardware failures, failures caused by unexpected event changes in the environment or failures due to plan errors, is described. One feature of the system is the utilization of task-plan knowledge and context information to deduce fault symptoms. This forward deduction provides valuable information on past activities and the current expectations of a robotic event, both of which can guide the plan-execution inference process. The inference process adopts a model-based technique to recreate the plan-execution process and to confirm fault-source hypotheses. This technique allows the system to diagnose multiple faults due to either unexpected plan failures or hardware errors. This research initiates a major effort to investigate relationships between hardware faults and plan errors, relationships which were not addressed in the past. The results of this research will provide a clear understanding of how to generate a better task planner for an autonomous robot and how to recover the robot from faults in a critical environment

Effects of more electric systems on fuel tank thermal behaviour

With the advent of more electric airframe systems and ultra-high bypass ratio turbofan engines, there is growing interest in the associated thermal implications. In this research project, an aircraft level model that is appropriate to enable investigations into novel thermal management solution on future aircraft is developed. In this paper, an investigation into the effects of more electric systems on the thermal behaviour of fuel tanks in civil transport aircraft is presented.Specifically, the influence of the heat generated by conventional and more electric systems on the fuel tank was modelled and simulated. A fuel thermal model was developed, which consists of a tank geometry representation, coupled to a module that calculates remaining mission fuel mass. The systems architectures are represented by connected thermal component models. Standard approaches were then employed to estimate convection and conduction heat transfer coefficients at the tank interfaces. The model solves 1-D transient heat equations, coupling heat transfer and material heat capacity via heat flux balances. The thermal and systems models were integrated into a baseline aircraft performance model, which was used to dynamically simulate the tank thermal behaviour during representative missions. The initial results indicate that switching to more electric environmental control and iceprotection systems likely have negligible thermal impact on the bulk fuel temperature. However, some benefits may be obtained regarding safety and certification, but this requires further study

Structure of the Mycobacterium smegmatis alpha-maltose-1-phosphate synthase GlgM

Mycobacterium tuberculosis produces glycogen (also known as alpha-glucan) to help evade human immunity. This pathogen uses the GlgE pathway to generate glycogen rather than the more well known glycogen synthase GlgA pathway, which is absent in this bacterium. Thus, the building block for this glucose polymer is alpha-maltose-1-phosphate rather than an NDP-glucose donor. One of the routes to alpha-maltose-1-phosphate is now known to involve the GlgA homologue GlgM, which uses ADP-glucose as a donor and alpha-glucose-1-phosphate as an acceptor. To help compare GlgA (a GT5 family member) with GlgM enzymes (GT4 family members), the X-ray crystal structure of GlgM from Mycobacterium smegmatis was solved to 1.9 angstrom resolution. While the enzymes shared a GT-B fold and several residues responsible for binding the donor substrate, they differed in some secondary-structural details, particularly in the N-terminal domain, which would be expected to be largely responsible for their different acceptor-substrate specificities

Nuclear-localized focal adhesion kinase regulates inflammatory VCAM-1 expression.

Vascular cell adhesion molecule-1 (VCAM-1) plays important roles in development and inflammation. Tumor necrosis factor-α (TNF-α) and focal adhesion kinase (FAK) are key regulators of inflammatory and integrin-matrix signaling, respectively. Integrin costimulatory signals modulate inflammatory gene expression, but the important control points between these pathways remain unresolved. We report that pharmacological FAK inhibition prevented TNF-α-induced VCAM-1 expression within heart vessel-associated endothelial cells in vivo, and genetic or pharmacological FAK inhibition blocked VCAM-1 expression during development. FAK signaling facilitated TNF-α-induced, mitogen-activated protein kinase activation, and, surprisingly, FAK inhibition resulted in the loss of the GATA4 transcription factor required for TNF-α-induced VCAM-1 production. FAK inhibition also triggered FAK nuclear localization. In the nucleus, the FAK-FERM (band 4.1, ezrin, radixin, moesin homology) domain bound directly to GATA4 and enhanced its CHIP (C terminus of Hsp70-interacting protein) E3 ligase-dependent polyubiquitination and degradation. These studies reveal new developmental and anti-inflammatory roles for kinase-inhibited FAK in limiting VCAM-1 production via nuclear localization and promotion of GATA4 turnover

The structure of a GH149 β‐(1 → 3) glucan phosphorylase reveals a new surface oligosaccharide binding site and additional domains that are absent in the disaccharide‐specific GH94 glucose‐β‐(1 → 3)‐glucose (laminaribiose) phosphorylase

Glycoside phosphorylases (GPs) with specificity for β-(1 → 3)-gluco-oligosaccharides are potential candidate biocatalysts for oligosaccharide synthesis. GPs with this linkage specificity are found in two families thus far—glycoside hydrolase family 94 (GH94) and the recently discovered glycoside hydrolase family 149 (GH149). Previously, we reported a crystallographic study of a GH94 laminaribiose phosphorylase with specificity for disaccharides, providing insight into the enzyme's ability to recognize its' sugar substrate/product. In contrast to GH94, characterized GH149 enzymes were shown to have more flexible chain length specificity, with preference for substrate/product with higher degree of polymerization. In order to advance understanding of the specificity of GH149 enzymes, we herein solved X-ray crystallographic structures of GH149 enzyme Pro_7066 in the absence of substrate and in complex with laminarihexaose (G6). The overall domain organization of Pro_7066 is very similar to that of GH94 family enzymes. However, two additional domains flanking its catalytic domain were found only in the GH149 enzyme. Unexpectedly, the G6 complex structure revealed an oligosaccharide surface binding site remote from the catalytic site, which, we suggest, may be associated with substrate targeting. As such, this study reports the first structure of a GH149 phosphorylase enzyme acting on β-(1 → 3)-gluco-oligosaccharides and identifies structural elements that may be involved in defining the specificity of the GH149 enzymes