The characteristics of railway service disruption: implications for disruption management

Rail disruption management is central to operational continuity and customer satisfaction. Disruption is not a unitary phenomenon - it varies by time, cause, location and complexity of coordination. Effective, user-centred technology for rail disruption must reflect this variety. A repertory grid study was conducted to elicit disruption characteristics. Construct elicitation with a group of experts (n=7) captured 26 characteristics relevant to rail disruption. A larger group of operational staff (n=28) rated 10 types of rail incident against the 26 characteristics. The results revealed distinctions such as business impact and public perception, and the importance of management of the disruption over initial detection. There were clear differences between those events that stop the traffic, as opposed to those that only slow the traffic. The results also demonstrate the utility of repertory grid for capturing the characteristics of complex work domains

New measurements of total ionizing dose in the lunar environment

[1] We report new measurements of solar minimum ionizing radiation dose at the Moon onboard the Lunar Reconnaissance Orbiter (LRO) from June 2009 through May 2010. The Cosmic Ray Telescope for the Effects of Radiation (CRaTER) instrument on LRO houses a compact and highly precise microdosimeter whose design allows measurements of dose rates below 1 micro-Rad per second in silicon achieved with minimal resources (20 g, ∼250 milliwatts, and ∼3 bits/second). We envision the use of such a small yet accurate dosimeter in many future spaceflight applications where volume, mass, and power are highly constrained. As this was the first operation of the microdosimeter in a space environment, the goal of this study is to verify its response by using simultaneous measurements of the galactic cosmic ray ionizing environment at LRO, at L1, and with other concurrent dosimeter measurements and model predictions. The microdosimeter measured the same short timescale modulations in the galactic cosmic rays as the other independent measurements, thus verifying its response to a known source of minimum-ionizing particles. The total dose for the LRO mission over the first 333 days was only 12.2 Rads behind ∼130 mils of aluminum because of the delayed rise of solar activity in solar cycle 24 and the corresponding lack of intense solar energetic particle events. The dose rate in a 50 km lunar orbit was about 30 percent lower than the interplanetary rate, as one would expect from lunar obstruction of the visible sky

Measurements of galactic cosmic ray shielding with the CRaTER instrument

[1] The Cosmic Ray Telescope for the Effects of Radiation (CRaTER) instrument aboard the Lunar Reconnaissance Orbiter has been measuring energetic charged particles from the galactic cosmic rays (GCRs) and solar particle events in lunar orbit since 2009. CRaTER includes three pairs of silicon detectors, separated by pieces of tissue-equivalent plastic that shield two of the three pairs from particles incident at the zenith-facing end of the telescope. Heavy-ion beams studied in previous ground-based work have been shown to be reasonable proxies for the GCRs when their energies are sufficiently high. That work, which included GCR simulations, led to predictions for the amount of dose reduction that would be observed by CRaTER. Those predictions are compared to flight data obtained by CRaTER in 2010–2011

The radiation environment near the lunar surface: CRaTER observations and Geant4 simulations

[1] At the start of the Lunar Reconnaissance Orbiter mission in 2009, its Cosmic Ray Telescope for the Effects of Radiation instrument measured the radiation environment near the Moon during the recent deep solar minimum, when galactic cosmic rays (GCRs) were at the highest level observed during the space age. We present observations that show the combined effects of GCR primaries, secondary particles (“albedo”) created by the interaction of GCRs with the lunar surface, and the interactions of these particles in the shielding material overlying the silicon solid-state detectors of the Cosmic Ray Telescope for the Effects of Radiation. We use Geant4 to model the energy and angular distribution of the albedo particles, and to model the response of the sensor to the various particle species reaching the 50 kilometer altitude of the Lunar Reconnaissance Orbiter. Using simulations to gain insight into the observations, we are able to present preliminary energy-deposit spectra for evaluation of the radiation environment\u27s effects on other sensitive materials, whether biological or electronic, that would be exposed to a similar near-lunar environment

The first cosmic ray albedo proton map of the Moon

[1] Neutrons emitted from the Moon are produced by the impact of galactic cosmic rays (GCRs) within the regolith. GCRs are high-energy particles capable of smashing atomic nuclei in the lunar regolith and producing a shower of energetic protons, neutrons and other subatomic particles. Secondary particles that are ejected out of the regolith become “albedo” particles. The neutron albedo has been used to study the hydrogen content of the lunar regolith, which motivates our study of albedo protons. In principle, the albedo protons should vary as a function of the input GCR source and possibly as a result of surface composition and properties. During the LRO mission, the total detection rate of albedo protons between 60 MeV and 150 MeV has been declining since 2009 in parallel with the decline in the galactic cosmic ray flux, which validates the concept of an albedo proton source. On the other hand, the average yield of albedo protons has been increasing as the galactic cosmic ray spectrum has been hardening, consistent with a disproportionately stronger modulation of lower energy GCRs as solar activity increases. We construct the first map of the normalized albedo proton emission rate from the lunar surface to look for any albedo variation that correlates with surface features. The map is consistent with a spatially uniform albedo proton yield to within statistical uncertainties

Limonite – a weathered residual soil heterogeneous at all scales

Limonite is a residual soil produced by the decomposition of magnesium silicate (olivine) rocks in tropical environments. During weathering most of the original rock is leached away leaving only its iron content, which is precipitated out in the form of iron sesqui-oxides to create a soft and highly porous soil. The predominant mineral present in limonite is goethite, which forms acicular nanoparticles that agglomerate to produce a silty sand with porous particles. The void ratio varies from 2 to 6, with higher values being a consequence of structure-supported voids. An extensive set of laboratory tests have been performed on a limonite soil profile which extends 50 m to rock. These data show that there is no pattern to shear strength with depth, with the shear strength equally likely to be 50 or 200 kPa through much of the profile. It is argued that the shear strength parameters for failure mechanisms, having any significant length, should be based on average values. The letter presents scanning electron microscopy photographs showing the fundamental particles, the results of triaxial tests comparing natural and reconstituted behaviour which show the effects of microstructure on the meso-scale response, and field data to show site variability

Substrate Effect on the High Temperature Oxidation Behavior of a Pt-modified Aluminide Coating. Part II: Long-term Cyclic-oxidation Tests at 1,050 C

This second part of a two-part study is devoted to the effect of the substrate on the long-term, cyclic-oxidation behavior at 1,050 C of RT22 industrial coating deposited on three Ni-base superalloys (CMSX-4, SCB, and IN792). Cyclicoxidation tests at 1,050 C were performed for up to 58 cycles of 300 h (i.e., 17,400 h of heating at 1,050 C). For such test conditions, interdiffusion between the coating and its substrate plays a larger role in the damage process of the system than during isothermal tests at 900, 1,050, and 1,150 C for 100 h and cyclicoxidation tests at 900 C which were reported in part I [N. Vialas and D. Monceau, Oxidation of Metals 66, 155 (2006)]. The results reported in the present paper show that interdiffusion has an important effect on long-term, cyclic-oxidation resistance, so that clear differences can be observed between different superalloys protected with the same aluminide coating. Net-mass-change (NMC) curves show the better cyclic-oxidation behavior of the RT22/IN792 system whereas uncoated CMSX-4 has the best cyclic-oxidation resistance among the three superalloys studied. The importance of the interactions between the superalloy substrate and its coating is then demonstrated. The effect of the substrate on cyclic-oxidation behavior is related to the extent of oxide scale spalling and to the evolution of microstructural features of the coatings tested. SEM examinations of coating surfaces and cross sections show that spalling on RT22/CMSX-4 and RT22/SCB was favored by the presence of deep voids localized at the coating/oxide interface. Some of these voids can act as nucleation sites for scale spallation. The formation of such interfacial voids was always observed when the b to c0 transformation leads to the formation of a two-phase b/c0 layer in contact with the alumina scale. On the contrary, no voids were observed in RT22/IN792, since this b to c0 transformation occurs gradually by an inward transformation of b leading to the formation of a continuous layer of c0 phase, parallel to the metal/scale interface

Earth‐Moon‐Mars Radiation Environment Module framework

[1] We are preparing to return humans to the Moon and setting the stage for exploration to Mars and beyond. However, it is unclear if long missions outside of low-Earth orbit can be accomplished with acceptable risk. The central objective of a new modeling project, the Earth-Moon-Mars Radiation Exposure Module (EMMREM), is to develop and validate a numerical module for characterizing time-dependent radiation exposure in the Earth-Moon-Mars and interplanetary space environments. EMMREM is being designed for broad use by researchers to predict radiation exposure by integrating over almost any incident particle distribution from interplanetary space. We detail here the overall structure of the EMMREM module and study the dose histories of the 2003 Halloween storm event and a June 2004 event. We show both the event histories measured at 1 AU and the evolution of these events at observer locations beyond 1 AU. The results are compared to observations at Ulysses. The model allows us to predict how the radiation environment evolves with radial distance from the Sun. The model comparison also suggests areas in which our understanding of the physics of particle propagation and energization needs to be improved to better forecast the radiation environment. Thus, we introduce the suite of EMMREM tools, which will be used to improve risk assessment models so that future human exploration missions can be adequately planned for

A cross-sector analysis of human and organisational factors in the deployment of data-driven predictive maintenance

Domains such as utilities, power generation, manufacturing and transport are increasingly turning to data-driven tools for management and maintenance of key assets. Whole ecosystems of sensors and analytical tools can provide complex, predictive views of network asset performance. Much research in this area has looked at the technology to provide both sensing and analysis tools. The reality in the field, however, is that the deployment of these technologies can be problematic due to user issues, such as interpretation of data or embedding within processes, and organisational issues, such as business change to gain value from asset analysis. 13 experts from the field of remote condition monitoring, asset management and predictive analytics across multiple sectors were interviewed to ascertain their experience of supplying data-driven applications. The results of these interviews are summarised as a framework based on a predictive maintenance project lifecycle covering project motivations and conception, design and development, and operation. These results identified critical themes for success around having a target or decision-led, rather than data-led, approach to design; long-term resourcing of the deployment; the complexity of supply chains to provide data-driven solutions and the need to maintain knowledge across the supply chain; the importance of fostering technical competency in end-user organisations; and the importance of a maintenance-driven strategy in the deployment of data-driven asset management. Emerging from these themes are recommendations related to culture, delivery process, resourcing, supply chain collaboration and industry-wide cooperation

A population Monte Carlo scheme with transformed weights and its application to stochastic kinetic models

This paper addresses the problem of Monte Carlo approximation of posterior probability distributions. In particular, we have considered a recently proposed technique known as population Monte Carlo (PMC), which is based on an iterative importance sampling approach. An important drawback of this methodology is the degeneracy of the importance weights when the dimension of either the observations or the variables of interest is high. To alleviate this difficulty, we propose a novel method that performs a nonlinear transformation on the importance weights. This operation reduces the weight variation, hence it avoids their degeneracy and increases the efficiency of the importance sampling scheme, specially when drawing from a proposal functions which are poorly adapted to the true posterior. For the sake of illustration, we have applied the proposed algorithm to the estimation of the parameters of a Gaussian mixture model. This is a very simple problem that enables us to clearly show and discuss the main features of the proposed technique. As a practical application, we have also considered the popular (and challenging) problem of estimating the rate parameters of stochastic kinetic models (SKM). SKMs are highly multivariate systems that model molecular interactions in biological and chemical problems. We introduce a particularization of the proposed algorithm to SKMs and present numerical results.Comment: 35 pages, 8 figure