Speaking Risk With Our Project Managers

Effective communication between the system safety engineer and the project manager (PM) is an essential characteristic of good risk management in a robust system safety program. However, these two disciplines often use similar terms with disparate meanings that can lead to sub-optimal technical or programmatic outcomes. MIL-STD-882E defines “risk” as “a combination of the severity of the mishap and the probability that the mishap will occur”. The Project Management Book of Knowledge (PMBOK) Guide, 6th Edition, defines “individual project risk” as “an uncertain event or condition that, if it occurs, has a positive or negative effect on one or more project objectives”. It is incumbent upon the system safety professional to clearly communicate safety-related issues, hazards, risks and concerns using language most likely to be understood by the PM to ensure that he or she has the requisite information to make a sound programmatic decision. This paper explores the discrepancies between project risk management and safety risk management standard processes that hinder clear communication and can drastically impact program performance. We present methods to consider that will improve understanding between the system safety professional and the PM, along with two framework approaches for integrating safety and project risks

SWAT Operations Unmanned Vehicle

During SWAT operations, it is common to have a barricaded suspect who may be armed and a serious threat to SWAT team personnel. In these cases, sending a robot into harm\u27s way to assess the situation as opposed to an operator has become the standard. The purpose of this of this research was to design and develop an unmanned system for the City of Akron\u27s SWAT Team that can be injected into these scenarios to improve outcomes and mitigate risk to SWAT operators

Determination of crack growth for 6082-T6 Aluminium subjected to periodic single and block overloads and underloads using a two dimensional finite element model

The estimation of crack growth under variable amplitude loading is complex due to interaction effects such as plasticity, crack tip blunting, residual stresses, crack tip closure and crack tip branching. Crack closure has been identified to be one of the main interaction effects. In order to study the effect of crack closure the authors have previously carried out experimental testing to obtain more accurate measurements of crack opening and closure ; . They have also developed two dimensional plane stress Finite Element models utilising high mesh density whilst maintaining the ability to measure crack growth over long crack lengths [3]. This initial work has been extended in this paper to examine the effects of single and block overloads and random spectrum loading on crack growth. The crack length distance that is affected by overloads and underloads measured experimentally and predicted numerically are shown to be very close when using cyclic hardening material properties and kinematic hardening. In addition the comparison of experimental and numerical crack growth versus crack length graphs shows good correlation of the crack growth acceleration and retardation after the applied overload which has not been seen previously. These comparisons seem to be a very useful tool to validate numerical models

Experimental validation of an ANN model for random loading fatigue analysis

The use of artificial intelligence especially based on artificial neural networks (ANN) is now prevalent in many fields of data analysis and interpretation. There have been a number of papers published in the literature on the use of ANN for fatigue characterisation. Most of these have however been developed for rather focussed application with limited capability for fatigue life prediction for a broad scope of material and loading conditions. The authors recently presented a uniquely generalised ANN model that is capable of making fatigue life prediction for a broad range of material fatigue properties and loading spectral forms. The model was developed using simulated data albeit subject to conceivable constraints between possible materials properties and load forms. This paper presents a validation of the ANN model using a Society of Automotive Engineers (SAE) random fatigue loading experimental test data. The capabilities and potentials of the model are demonstrated by comparison with the SAE random load fatigue test results and with results obtained from other predictive methods. The performance of the ANN is highly encouraging as a general tool for random loading fatigue analysis

The obstructions for toroidal graphs with no K3,3K_{3,3}'s

Forbidden minors and subdivisions for toroidal graphs are numerous. We consider the toroidal graphs with no $K_{3,3}$-subdivisions that coincide with the toroidal graphs with no $K_{3,3}$-minors. These graphs admit a unique decomposition into planar components and have short lists of obstructions. We provide the complete lists of four forbidden minors and eleven forbidden subdivisions for the toroidal graphs with no $K_{3,3}$'s and prove that the lists are sufficient.Comment: 10 pages, 7 figures, revised version with additional detail

Are spherulitic lacustrine carbonates an expression of large-scale mineral carbonation? : A case study from the East Kirkton Limestone, Scotland

BP Exploration Co. is thanked for funding, and particularly the Carbonate Team for supporting this research and for fruitful discussions. West Lothian Council and Scottish Natural Heritage are thanked for allowing access and permission for sampling the site. The Core Store Team at BGS Keyworth is particularly acknowledged for their assistance. Mark Anderson, Tony Sinclair (University of Hull), and Bouk Lacet (VU University Amsterdam) are thanked for technical support. Anne Kelly (SUERC) for carrying out the Strontium Isotope analyses. Mark Tyrer is thanked for his advice on PHREEQC modelling.Peer reviewedPostprin

Community acquired Panton-Valentine Leukocidin (PVL) positive Methicilin Resistant Staphylococcal aureus cerebral abscess in an 11-month old boy: a case study.

BACKGROUND: Brain abscess are uncommon childhood infection. Brain abscess caused by Panton-Valentine Leukocidin positive Community acquired Methicillin Resistant Staphylococcal aureus have never been reported in the United Kingdom. CASE PRESENTATION: We report a case of a previously well 11-month old boy of Indian origin who developed a parietal lobe abscess from PVL positive CA-MRSA. CONCLUSION: This case is one of the few described cases of brain abscess caused by PVL CA-MRSA in children. The unusual (insidious) presentation, the absence of a clear staphylococcal focus and the unexpected finding of a CA-MRSA in this patient highlight the challenges of managing such cases in clinical settings and the potential future risk to public health

Ex-vivo HRMAS of adult brain tumours: metabolite quantification and assignment of tumour biomarkers

Background: High-resolution magic angle spinning (HRMAS) NMR spectroscopy allows detailed metabolic analysis of whole biopsy samples for investigating tumour biology and tumour classification. Accurate biochemical assignment of small molecule metabolites that are “NMR visible” will improve our interpretation of HRMAS data and the translation of NMR tumour biomarkers to in-vivo studies. Results: 1D and 2D 1H HRMAS NMR was used to determine that 29 small molecule metabolites, along with 8 macromolecule signals, account for the majority of the HRMAS spectrum of the main types of brain tumour(astrocytoma grade II, grade III gliomas, glioblastomas, metastases, meningiomas and also lymphomas). Differences in concentration of 20 of these metabolites were statistically significant between these brain tumour types. During the course of an extended 2D data acquisition the HRMAS technique itself affects sample analysis: glycine, glutathione and glycerophosphocholine all showed small concentration changes; analysis of the sample after HRMAS indicated structural damage that may affect subsequent histopathological analysis. Conclusions: A number of small molecule metabolites have been identified as potential biomarkers of tumour type that may enable development of more selective in-vivo 1H NMR acquisition methods for diagnosis and prognosis of brain tumours