Theoretical and experimental studies of the bell-jar-top inductively coupled plasma

The present paper describes a systematic study of argon plasmas in a bell-jar inductively coupled plasma (ICP) source over the range of pressure 5-20 mtorr and power input 0.2-0.5 kW, Experimental measurements as well as results of numerical simulations are presented. The models used in the study include the well-known global balance model (or the global model) as well as a detailed two-dimensional (2-D) fluid model of the system, The global model is able to provide reasonably accurate values for the global electron temperature and plasma density, The 2-D model provides spatial distributions of various plasma parameters that make it possible to compare with data measured in the experiments, The experimental measurements were obtained using a tuned Langmuir double-probe technique to reduce the RF interference and obtain the light versus current (I-V) characteristics of the probe. Time-averaged electron temperature and plasma density were measured for various combinations of pressure and applied RF power, The predictions of the 2-D model were found to be in good qualitative agreement with measured data, It was found that the electron temperature distribution T-e was more or less uniform in the chamber, It was also seen that the electron temperature depends primarily on pressure, but is almost independent of the power input, except in the very low-pressure regime. The plasma density goes up almost linearly with the power input

New progress in LURR-integrating with the dimensional method

The evolution laws of LURR (Loading-Unloading Response Ratio) before strong earthquakes, especially the peak point of LURR, are described in this paper. The results of four methods (experimental, numerical simulation, seismic data analysis and with damage mechanics analysis) lead to a consistent conclusion-the evolution laws of LURR before strong earthquakes are that, at the early stage of the seismic cycle, LURR will fluctuate around 1 and in the late stage, it rises swiftly and to its peak point. At some time after this peak point, a catastrophic event or events occur. These do not occur at the peak point, but lag behind. The lag time which is denoted by T (2) depends on the magnitude M of the upcoming earthquake among other factors. In order to consider the influence of geophysical parameters in a specific region such as E (a) and J ((t)), where is the shear strain rate of tectonic loading in situ, E (a) is the sum of radiated energy of all earthquake occurring in a specific region measured during a long time duration (110 years in this paper) divided by the area of the region and the time duration, and J ((t)) is a parameter denoting the LURR anomaly area weighted with Y (the value of LURR) and represents the expanse and degree of the seismogenic zone. The dimensional analysis method has been used to reveal the relation between M, T (2) and other parameters in situ for more reliable earthquake prediction

Back stress strengthening and strain hardening in gradient structure

We report significant back stress strengthening and strain hardening in gradient structured (GS) interstitial-free (IF) steel. Back stress is long-range stress caused by the pileup of geometrically necessary dislocations (GNDs). A simple equation and a procedure are developed to calculate back stress basing on its formation physics from the tensile unloading-reloading hysteresis loop. The gradient structure has mechanical incompatibility due to its grain size gradient. This induces strain gradient, which needs to be accommodated by GNDs. Back stress not only raises the yield strength but also significantly enhances strain hardening to increase the ductility. [GRAPHICS]

Pan-cancer analysis of whole genomes

Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale(1-3). Here we report the integrative analysis of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). We describe the generation of the PCAWG resource, facilitated by international data sharing using compute clouds. On average, cancer genomes contained 4-5 driver mutations when combining coding and non-coding genomic elements; however, in around 5% of cases no drivers were identified, suggesting that cancer driver discovery is not yet complete. Chromothripsis, in which many clustered structural variants arise in a single catastrophic event, is frequently an early event in tumour evolution; in acral melanoma, for example, these events precede most somatic point mutations and affect several cancer-associated genes simultaneously. Cancers with abnormal telomere maintenance often originate from tissues with low replicative activity and show several mechanisms of preventing telomere attrition to critical levels. Common and rare germline variants affect patterns of somatic mutation, including point mutations, structural variants and somatic retrotransposition. A collection of papers from the PCAWG Consortium describes non-coding mutations that drive cancer beyond those in the TERT promoter(4); identifies new signatures of mutational processes that cause base substitutions, small insertions and deletions and structural variation(5,6); analyses timings and patterns of tumour evolution(7); describes the diverse transcriptional consequences of somatic mutation on splicing, expression levels, fusion genes and promoter activity(8,9); and evaluates a range of more-specialized features of cancer genomes(8,10-18).Peer reviewe

Measuring Surface Deformation Caused by Permafrost Thawing Using Radar Interferometry, Case Study: Zackenberg, NE Greenland

Permafrost in high-arctic regions has been very much influenced by global warming. Many thousands of square kilometers of permafrost are under certain degree of thawing. Site measurements have provided useful data for researchers. However, these ground-based measurements are usually site-specific with poor spatial coverage. Here we apply Multi-Temporal Interferometric Synthetic Aperture Radar (MT-InSAR) to measure the surface deformation over permafrost north-east Greenland during the past two periods 1995--1999 and 2006--2009 to infer permafrost behaviors. We have found a considerable rate of surface subsidence occurring with respect to a relatively stable area. Over the whole study area, during 1995--1999, we find a surface subsidence rate of 0.3--2.4 mm/yr and a seasonally varying displacement of 0.4--6.1 mm with subsidence occurring during the thawing season of each year. While in period of 2006--2009, we find the overall surface subsidence rate goes up to 0.8--2.7 mm/yr and the seasonally varying displacements increased to 2.3--7.4 mm within the thawing season. Comparing with the two periods, we find a general accelerating trend in subsidence rate of 4.5 x 102 mm/yr2, which indicates a acceleration in permafrost thawing rate. We also find a general increment in surface seasonal varying displacements of 1.9 mm, which indicates a thickening trend in the active layer. In total, by applying MT-InSAR technique over the 5000 km2 study area, we have found a permafrost area 506.1 km2 of that is under thawing and the general magnitude of permafrost thawing rate is 17.0±8.4 cm/yr during 1995--1999. During 2006--2009, we have found 633.9 km2 of permafrost area is thawing with a magnitude of thawing rate about 24.0±12.0cm/yr. We have also estimated the total volume loss of permafrost as (2.1±1.1) x 108 m2 and (3.0±1.5) x 108 m3 in each corresponding period. Further, assuming the linear relationship between the thawed permafrost and the released methane fluxes observed during 19-Jun-1997 to 18-Aug-1997 at Zackenberg valley, we apply this relationship to the whole subsidence area. We estimate the total magnitude of methane fluxes released from the study area within this period, which is about 1081.7±398.5 T.GeomaticsMathematical Geodesy and PositioningAerospace Engineerin

Lagrangian Multi-Class Traffic State Estimation

Road traffic is important to everybody in the world. People travel and commute everyday. For those who travel by cars (or other types of road vehicles), traffic congestion is a daily experience. One essential goal of traffic researchers is to reduce traffic congestion and to improve the whole traffic system operation and the environment. To achieve this goal, we have to first understand prevailing traffic situations, then perform pro-active traffic control and management. The estimation of traffic states in the past, in the present and in the future plays an important role in traffic management and control systems. This thesis focuses on the development of traffic state estimation approaches, which provide such traffic state information. In road networks, traffic states refer to typical quantities, such as travel times, traffic speeds, traffic flow and density. These quantities reflect the traffic conditions. Based on these data, we are able to find out when a traffic jam starts, or where a traffic accident occurs. However, it is not feasible to get the full picture of traffic states from the current monitoring systems. Due to cost and technical constraints, we can only obtain spatially and temporally discretised traffic data. These traffic data are collected mainly from point-based sensors, such as inductive loops, radars, and cameras. Alternatively, traffic information might be observed by probe vehicles with a selected penetration rate. In all cases, the detected data usually contain errors and noise, which might hinder further analyses. Based on these constraints, this thesis aims to develop a traffic state estimation procedure to solve the foregoing problems and to provide accurate and complete traffic state information. In this procedure, both traffic flow models and the available observation data are used to estimate the most probable traffic states within a data-assimilation framework. Our approach is formulated using a moving observer perspective, resulting in a Lagrangian formulation of traffic state estimation. In the Lagrangian coordinate system, coordinates move with the vehicles. The Lagrangian formulated first-order traffic flow model is applied to describe the evolution of traffic state variables. The proposed Lagrangian formulation of traffic state estimation offers both theoretical and computational advantages over the conventional Eulerian formation. Moreover, this approach can capture the dynamics of multiple vehicle classes by implementing a multi-class traffic flow model. In this thesis, data pre-processing methods are also developed to improve the quality of the observation inputs. Both Eulerian and Lagrangian sensing data are incorporated into the state estimation. The online technique, known as the Extended Kalman Filter (EKF), is applied for data assimilation: this combines traffic model prediction with observation input correction. Importantly, the Lagrangian concept is not restricted to the EKF method with the first-order traffic flow model, but can also be applied to other data-assimilation techniques in combination with more involved macroscopic traffic flow models. A series of experimental studies based on both synthetic and real-world data have been performed to test the proposed methodology. These studies have validated both the mixed-class and the multi-class traffic state estimation methods. The results have demonstrated that the Lagrangian traffic state estimation outperforms the Eulerian approaches in the EKF-based framework, and the multi-class approach further improves the performance of state estimation compared with the mixed-class case. In summary, Lagrangian multi-class state estimation can provide accurate class-specific traffic information for class-specific control applications and traffic management.Transport & PlanningCivil Engineering and Geoscience

Traffic state estimation based on Eulerian and Lagrangian observations in a mesoscopic modeling framework

The paper proposes a model-based framework for estimating traffic states from Eulerian (loop) and/or Lagrangian (probe) data. Lagrangian-Space formulation of the LWR model adopted as the underlying traffic model provides suitable properties for receiving both Eulerian and Lagrangian external information. Three independent methods are proposed to address Eulerian data, Lagrangian data and the combination of both, respectively. These methods are defined in a consistent framework so as to be implemented simultaneously. The proposed framework has been verified on the synthetic data derived from the same underlying traffic flow model. Strength and weakness of both data sources are discussed. Next, the proposed framework has been applied to a freeway corridor. The validity has been tested using the data from a microscopic simulator, and the performance is satisfactory even for low rate of probe vehicles around 5%.Transport and Plannin

Generalized Adaptive Smoothing Method for State Estimation of Generic Two-Dimensional Flows

In big cities, the proportion of slow-mode (such as pedestrian) flows in total trip demand is steadily growing every year. Along with this trend, many concerns arise about accessibility and safety. The monitoring and the management of pedestrians serve as a potential solution to maintain the resilience of the transport network. Monitoring and state estimation of pedestrian flows are crucial as a foundation for a successful crowd management support system. This paper focuses on the development of pedestrian state estimation. A two-dimensional (2-D) generalized adaptive smoothing method (2D-GASM) is presented to estimate the full state of an area on the basis of an increasing amount of available pedestrian observations in practice. The 2D-GASM method was developed on the basis of similar concepts in the adaptive smoothing method for motorway traffic, which was based on the characteristic that traffic travels forward in free flow and backward in congestion. The same mechanism is assumed for pedestrian flows. This extension accommodates the 2-D nature of the pedestrian flow and allows for the fusion and filtering of multisource data (e.g., data from counting cameras, data from wireless fidelity sensors, and GPS samples). Although focused on pedestrian flow, the approach is applicable to any generic 2-D flows, including bicyclist or mixed flows. This newly developed method is validated on the basis of trajectory data from a walking experiment at a narrow bottleneck. The test results present promising estimation performance, and possible extensions for future applications are suggested.Transport and Plannin

New Extended Discrete First-Order Model to Reproduce Propagation of Jam Waves

This paper proposes an extension of the discrete Lighthill–Whitham–Richards model of the cell transmission model type to reproduce capacity drop and the propagation of jam waves. Recent studies have tried to incorporate the capacity drop into discrete first-order traffic flow models for traffic optimization purposes. It was found that the inflow to a discharging cell predicted by these models might have been overestimated, and this overestimation influenced the propagation of a jam wave. An empirical analysis was carried out to confirm this assumption. It was found that the extent of the flow reduction depended on the state difference between the targeting cell and its upstream cell. On the basis of these findings, a new mathematical model formulation is given. Simulations with both a hypothetical freeway stretch and a real-life freeway stretch are performed to test the behavior of the proposed model. The previously mentioned models are also simulated for comparison. The simulation results indicate that the proposed model is better able to reproduce jam waves. In addition, the proposed model can be used in a linear model predictive control framework and formulated as a linear optimization problem, which may be beneficial for a real-life, real-time application.Transport and Plannin

An operational simulation framework for modelling the multi-interaction of two-wheelers on mixed-traffic road segments

In recent years, the interest in riding in cities using the two-wheeler (e.g., bicycles, electric bicycles, electric mopeds, etc.) increases. Mixed-traffic road segments are one of the most common traffic scenes where the mixed two-wheeler flows exist. Because the movements are often not restricted by lanes, the two-wheeler uses lateral road space more freely and shows obvious multilateral interactions (i.e. multi-interaction) with others, bringing issues that endanger traffic safety. A precise estimation of its impacts on traffic operation and safety is necessary, while the microscopic simulation model can satisfy the need as a helpful tool. However, most existing simulation models of these three types of two-wheelers are essentially focusing on handling the one-on-one interaction. The capability to deal with the two-wheeler multi-interaction in mixed traffic is still rare, and the description of what endogenous tasks are contained by the multi-interaction has also not given by literature. To this end, this paper first defines what the multi-interaction entails on the operational behaviour level, claiming that it contains three intertwined processes, namely a (mental) perception, a (mental) decision, and a physical process. The (mental) perception and decision processes represent the recognition of interactions and the response to traffic conditions, while the physical process refers to the execution of these mental activities. A three-layer simulation framework has then been developed, where each layer sequentially corresponds to one of the operational behaviour tasks. Integrated component models are also proposed in each layer to cover these operational tasks. A Comfort Zone model is hence put forward to dynamically perceive the multiple interactive road users, while a Bayesian network model is developed to deal with the decision-making process under multi-interaction situations. Meanwhile, a behaviour force model is also proposed to capture the non-lane based movements following the selected behaviour and current interaction states. Finally, we face validate the proposed models by the comparison between simulation results and observations obtained from trajectory dataset. Results indicate the model performance matches the observed interaction and motion well.Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Transport and Plannin