Human activity-induced vibration in slender structural systems

Human activity-induced vibrations in slender structural sys tems become apparent in many different excitation modes and consequent action effects that cause discomfort to occupants, crowd panic and damage to public infrastructure. Resulting loss of public confidence in safety of structures, economic losses, cost of retrofit and repairs can be significant. Advanced computational and visualisation techniques enable engineers and architects to evolve bold and innovative structural forms, very often without precedence. New composite and hybrid materials that are making their presence in structural systems lack historical evidence of satisfactory performance over anticipated design life. These structural systems are susceptible to multi-modal and coupled excitation that are very complex and have inadequate design guidance in the present codes and good practice guides. Many incidents of amplified resonant response have been reported in buildings, footbridges, stadia a nd other crowded structures with adverse consequences. As a result, attenuation of human-induced vibration of innovative and slender structural systems very ofte n requires special studies during the design process. Dynamic activities possess variable characteristics and thereby induce complex responses in structures that are sensitive to parametric variations. Rigorous analytical techniques are available for investigation of such complex actions and responses to produce acceptable performance in structural systems. This paper presents an overview and a critique of existing code provisions for human-induced vibration followed by studies on the performance of three contrasting structural systems that exhibit complex vibration. The dynamic responses of these systems under human-induced vibrations have been carried out using experimentally validated computer simulation techniques. The outcomes of these studies will have engineering applications for safe and sustainable structures and a basis for developing design guidance.

A review of system safety failure probability objectives for Unmanned Aircraft Systems

Unmanned Aircraft Systems (UAS) are one of a number of emerging aviation sectors. Such new aviation concepts present a significant challenge to National Aviation Authorities (NAAs) charged with ensuring the safety of their operation within the existing airspace system. There is significant heritage in the existing body of aviation safety regulations for Conventionally Piloted Aircraft (CPA). It can be argued that the promulgation of these regulations has delivered a level of safety tolerable to society, thus justifying the “default position” of applying these same standards, regulations and regulatory structures to emerging aviation concepts such as UAS. An example of this is the proposed “1309” regulation for UAS, which is based on the 1309 regulation for CPA. However, the absence of a pilot on-board an unmanned aircraft creates a fundamentally different risk paradigm to that of CPA. An appreciation of these differences is essential to the justification of the “default position” and in turn, to ensure the development of effective safety standards and regulations for UAS. This paper explores the suitability of the proposed “1309” regulation for UAS. A detailed review of the proposed regulation is provided and a number of key assumptions are identified and discussed. A high-level model characterising the expected number of third party fatalities on the ground is then used to determine the impact of these assumptions. The results clearly show that the “one size fits all” approach to the definition of 1309 regulations for UAS, which mandates equipment design and installation requirements independent of where the UAS is to be operated, will not lead to an effective management of the risks.

RCA method for fault diagnosis in digital substations of power systems

The authors present a Cause-Effect fault diagnosis model, which utilises the Root Cause Analysis approach and takes into account the technical features of a digital substation. The Dempster/Shafer evidence theory is used to integrate different types of fault information in the diagnosis model so as to implement a hierarchical, systematic and comprehensive diagnosis based on the logic relationship between the parent and child nodes such as transformer/circuit-breaker/transmission-line, and between the root and child causes. A real fault scenario is investigated in the case study to demonstrate the developed approach in diagnosing malfunction of protective relays and/or circuit breakers, miss or false alarms, and other commonly encountered faults at a modern digital substation.

Investigating the potential value of individual parameters of histological grading systems in a sheep model of cartilage damage : the modified Mankin method

A total histological grade does not necessarily distinguish between different manifestations of cartilage damage or degeneration. An accurate and reliable histological assessment method is required to separate normal and pathological tissue within a joint during treatment of degenerative joint conditions and to sub-classify the latter in meaningful ways. The Modified Mankin method may be adaptable for this purpose. We investigated how much detail may be lost by assigning one composite score/grade to represent different degenerative components of the osteoarthritic condition. We used four ovine injury models (sham surgery, anterior cruciate ligament/medial collateral ligament instability, simulated anatomic anterior cruciate ligament reconstruction and meniscal removal) to induce different degrees and potentially 'types' (mechanisms) of osteoarthritis. Articular cartilage was systematically harvested, prepared for histological examination and graded in a blinded fashion using a Modified Mankin grading method. Results showed that the possible permutations of cartilage damage were significant and far more varied than the current intended use that histological grading systems allow. Of 1352 cartilage specimens graded, 234 different manifestations of potential histological damage were observed across 23 potential individual grades of the Modified Mankin grading method. The results presented here show that current composite histological grading may contain additional information that could potentially discern different stages or mechanisms of cartilage damage and degeneration in a sheep model. This approach may be applicable to other grading systems.

Soil carbon sequestration and associated economic costs for farming systems of the Indo-Gangetic Plain : a meta-analysis

Soil organic carbon sequestration rates over 20 years based on the Intergovernmental Panel for Climate Change (IPCC) methodology were combined with local economic data to determine the potential for soil C sequestration in wheat-based production systems on the Indo-Gangetic Plain (IGP). The C sequestration potential of rice–wheat systems of India on conversion to no-tillage is estimated to be 44.1 Mt C over 20 years. Implementing no-tillage practices in maize–wheat and cotton–wheat production systems would yield an additional 6.6 Mt C. This offset is equivalent to 9.6% of India's annual greenhouse gas emissions (519 Mt C) from all sectors (excluding land use change and forestry), or less than one percent per annum. The economic analysis was summarized as carbon supply curves expressing the total additional C accumulated over 20 year for a price per tonne of carbon sequestered ranging from zero to USD 200. At a carbon price of USD 25 Mg C−1, 3 Mt C (7% of the soil C sequestration potential) could be sequestered over 20 years through the implementation of no-till cropping practices in rice–wheat systems of the Indian States of the IGP, increasing to 7.3 Mt C (17% of the soil C sequestration potential) at USD 50 Mg C−1. Maximum levels of sequestration could be attained with carbon prices approaching USD 200 Mg C−1 for the States of Bihar and Punjab. At this carbon price, a total of 34.7 Mt C (79% of the estimated C sequestration potential) could be sequestered over 20 years across the rice–wheat region of India, with Uttar Pradesh contributing 13.9 Mt C.

Relative entropy rate based model selection for linear hybrid system filters of uncertain nonlinear systems

Hybrid system representations have been exploited in a number of challenging modelling situations, including situations where the original nonlinear dynamics are too complex (or too imprecisely known) to be directly filtered. Unfortunately, the question of how to best design suitable hybrid system models has not yet been fully addressed, particularly in the situations involving model uncertainty. This paper proposes a novel joint state-measurement relative entropy rate based approach for design of hybrid system filters in the presence of (parameterised) model uncertainty. We also present a design approach suitable for suboptimal hybrid system filters. The benefits of our proposed approaches are illustrated through design examples and simulation studies.

Differential effects of ERP systems on user outcomes : a longitudinal investigation

Adopting a model of job enrichment we report on a longitudinal case investigating the perceived impact of an Enterprise Resource Planning (ERP) system on user job design characteristics. Our results indicated that in the context of an ERP geared towards centralisation and standardisation the extent to which users perceived an increase or decrease in job enrichment was associated with aspects such as formal authority and the nature of their work role. Experienced operational employees proficient in the original legacy system perceived ERP system protocols to constrain their actions, limit training and increase dependence on others in the workflow. Conversely, managerial users reported a number of benefits relating to report availability, improved organisational transparency and increased overall job enrichment. These results supported our argument concerning the relationship between ERPs with a standardisation intent and positive job enrichment outcomes for managerial users and negative job-related outcomes for operational users.

A parallel cooperative co-evolutionary genetic algorithm for the composite SaaS placement problem in Cloud computing

A composite SaaS (Software as a Service) is a software that is comprised of several software components and data components. The composite SaaS placement problem is to determine where each of the components should be deployed in a cloud computing environment such that the performance of the composite SaaS is optimal. From the computational point of view, the composite SaaS placement problem is a large-scale combinatorial optimization problem. Thus, an Iterative Cooperative Co-evolutionary Genetic Algorithm (ICCGA) was proposed. The ICCGA can find reasonable quality of solutions. However, its computation time is noticeably slow. Aiming at improving the computation time, we propose an unsynchronized Parallel Cooperative Co-evolutionary Genetic Algorithm (PCCGA) in this paper. Experimental results have shown that the PCCGA not only has quicker computation time, but also generates better quality of solutions than the ICCGA.