Nonlinear spectral-like schemes for hybrid schemes

In spectral-like resolution-WENO hybrid schemes, if the switch function takes more grid points as discontinuity points, the WENO scheme is often turned on, and the numerical solutions may be too dissipative. Conversely, if the switch function takes less grid points as discontinuity points, the hybrid schemes usually are found to produce oscillatory solutions or just to be unstable. Even if the switch function takes less grid points as discontinuity points, the final hybrid scheme is inclined to be more stable, provided the spectral-like resolution scheme in the hybrid scheme has moderate shock-capturing capability. Following this idea, we propose nonlinear spectral-like schemes named weighted group velocity control (WGVC) schemes. These schemes show not only high-resolution for short waves but also moderate shock capturing capability. Then a new class of hybrid schemes is designed in which the WGVC scheme is used in smooth regions and the WENO scheme is used to capture discontinuities. These hybrid schemes show good resolution for small-scales structures and fine shock-capturing capabilities while the switch function takes less grid points as discontinuity points. The seven-order WGVC-WENO scheme has also been applied successfully to the direct numerical simulation of oblique shock wave-turbulent boundary layer interaction

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

Planning and Operation of Automated Taxi Systems

In recent years, technology development has accelerated the future roll-out of vehicle automation. An automated vehicle (AV), also known as a driverless car and a self-driving car is an advanced type of vehicle that can drive itself on existing roads. A possible area of application for AVs is public transport. The concept of automated taxis (ATs) is supposed to offer a seamless door-to-door service within a city area for all passengers. With automation technology maturing, we may be able to see the situation in which hundreds or even thousands of ATs will be on the road replacing private vehicles accounting for the majority of people’s daily trips. However, little attention has been devoted to the usage of a fleet of ATs and their effect on a real-scale road network. In this thesis, we explore how automated driving can serve mobility and what is the best way to introduce this technology as part of the existing transport networks. This is also the research gap this thesis is going to fill. The objective of this thesis is to contribute to the planning and operational strategies that these AT systems should follow in order to satisfy mobility demand. This thesis uses mathematical optimization to address the above research problems. A mathematical optimization problem consists of maximizing or minimizing a function by systematically selecting some input values within a defined domain. It aims to find the best available values of the objective function and the corresponding values of the problem input. The purpose of this thesis is to provide a tool to support the decision-making processes both for long-term planning strategies and short-term tactical operations when ATs are going to be applied in the urban transport system.TRAIL Thesis Series no. T2019/13Transport and Plannin

Re-public City: A strategic planning of public space for local people in the context of globalization in Shanghai Lujiazui Finance & Trade Zone

complex cityUrbanismArchitectur

Numerical Study of Flow around Bypass Pigs

In the oil and gas industry, pipeline networks are used to transport the production fluids from wells to production plants. During normal operation, the pipelines need regular cleaning and inspection. Typically, the pipeline maintenance is performed by pigging, which refers to using devices known as “pigs ”(Pipeline Inspection Gauges) to perform various maintenance operations of the pipeline. In order to describe the motion of the pig in the pipeline, detailed understanding of the flow around the pig is required. In this research, a CFD (computational fluid dynamics) approach was applied to model fully turbulent flow (Re ¼ 107) around various types of bypass pigs. We especially focused on the relation between the overall pressure drop, which was represented by a dimensionless pressure loss coefficient, and various dimensionless parameters describing the flow and the configuration. The pressure loss coefficient is caused by the fluid that passes through the bypass area. If the pressure loss coefficient is known, together with the friction between the moving pig and the pipe wall, the motion of the pig can be described. Moreover, often the flow in the pipeline is in multiphase (stratified flow) condition. Therefore, in this research the effect of multiphase flow around a bypass pig was also investigated. For the single phase study, two types of bypass pigs were investigated: the disk pig and the complex bypass pig. The disk pig has a fixed and relatively simple geometry, and it is based on the conventional bypass pig, with a deflector plate in front of the pig body. The complex bypass pig geometry is based on the disk pig, though now the bypass area is created by holes which can be adjusted. In reality, for these complex bypass pigs, the bypass pig velocity is controlled by adjusting the bypass area. For the conventional bypass pig, previous studies have shown that the Idelchik’s correlation for thick orifices can predict the pressure loss coefficient accurately. Thus a similar approach was applied in the disk pig study in order to obtain a theoretical correlation to predict the pressure loss coefficient for the disk pig. Indeed such a correlation was found which gives an accurate prediction for a certain parameter regime. In the complex bypass pig study, we mainly focused on the influence of the bypass area fraction on the pressure loss coefficient. Two correlations based on two approaches were suggested. It was found that these correlations can predict the overall pressure drop across the complex bypass pig accurately, especially when the opening fraction of the bypass adjusting holes was relatively large. Furthermore, for the multiphase study, the simpler pig models were investigated. First of all, the flow in front of a pig without bypass region was investigated. One of the practical purposes of this study is that we want to investigate under which condition the full pipeline perimeter gets wetted with liquid. This is important for the distribution of corrosion inhibitors. Moreover, the multiphase flow around a (conventional) bypass pig was investigated, to obtain a better understanding of the multiphase flow behaviour for bypass pigs.Energy TechnologySustainable Process and Energy TechnologyMechanical, Maritime and Materials Engineerin

An optimal charging location model of an automated electric taxi system considering two types of charging

In this paper, we propose an optimization model to select the charging locations of an automated electric taxi (AET) system. The service provided by this AET system is a seamless door-to-door service connected to the train station, which helps improve the last mile transport. We individualize the vehicles instead of treating them as a flow to track the remaining battery level of each AET. Two types of charging are considered containing depot charging with lower charging speed and opportunity charging with higher charging speed. We formulate a mixed-integer programming model with linear constraints to optimize the locations of depot charging and opportunity charging according to the objective function of maximizing the number ofsatisfied requests. The proposed model is applied to the case study city of Delft, the Netherlands with the travel demand generated by the Delft Zuid train station. Results show that the charging scheme with two types of charging can provide sufficient electrical energy for shared use AETs to serve passengers’ last mile travel demand.Accepted Author ManuscriptTransport and Plannin

Deep residual learning for acoustic emission source localization in A steel-concrete composite slab

Large errors can be introduced in traditional acoustic emission (AE) source localization methods using extracted signal features such as arrival time difference. This issue is obvious in the case of irregular structural geometries, complex composite structure types or presence of cracks in wave travel paths. In this study, based on a novel deep learning algorithm called deep residual network (DRN), a structural health monitoring (SHM) strategy is proposed for AE source localization through classifying and recognizing the AE signals generated in different sub-regions of critical areas in structures. Hammer hits and pencil-leak break (PLB) tests were carried out on a steel-concrete composite slab specimen to register time-domain AE signals under multiple structural damage conditions. The obtained time-domain AE signals were then converted into time-frequency images as inputs for the proposed DRN architecture using the continuous wavelet transform (CWT). The DRNs were trained, validated and tested by AE signals generated from different source types at various damage states of the slab specimen. The proposed DRN architecture shows an effective potential for AE source localization. The results show that the DRN models pre-trained by the AE signals obtained in the undamaged specimen are able to accurately classify and identify the locations of different types of AE sources with 3–4.5 cm intervals even when multiple cracks with widths up to 4–6 mm are present in the wave travel paths. Moreover, the influence factors on the model performance are investigated, including structural damage conditions, sensor-to-source distances and AE sensor mounting positions; in accordance with the parametric analyses, recommendations are proposed for the engineering application of the proposed SHM strategy.Concrete StructuresMaterials and EnvironmentElectronic Instrumentatio

Effects of temperature on autogenous deformation and early-age stress evolution in cement pastes with low water to cement ratio

This paper investigates the influence of temperature on autogenous deformation and early-age stress (EAS) evolution in ordinary Portland cement paste using a recently developed Mini Temperature Stress Testing Machine (Mini-TSTM) and Mini Autogenous Deformation Testing Machine (Mini-ADTM). In the Mini-TSTM/ ADTM, CEM I 42.5 N paste with a water-cement ratio of 0.30 was tested under a curing temperature of 10, 15, 20, 25, 30, and 40 °C. X-Ray diffraction (XRD) tests were conducted to measure the amount of ettringite and calcium hydroxide, which reveals the micro-scale mechanisms of autogenous expansion. The applicability of the Maturity Concept (MC) for the prediction of autogenous deformation and relaxation modulus under different temperatures was also examined by the experimental data and the viscoelastic model. This paper leads to the following findings: 1) The autogenous deformation of ordinary Portland cement paste is a four-stage process comprising the initial shrinkage, autogenous expansion, plateau, and autogenous shrinkage; 2) Higher temperature leads to higher early-age cracking (EAC) risk because it accelerates the transitions through the first three stages and causes the autogenous shrinkage stage to start earlier. Moreover, higher temperatures also result in increased rates of autogenous shrinkage and EAS in the autogenous shrinkage stage; 3) Autogenous expansion and plateau are attributed to the crystallization pressure induced by CH. Temperature-dependent CH formation rates determine the duration of the plateau stage; 4) Low-temperature curing can delay but not completely prevent the EAC induced by autogenous deformation; 5) The MC cannot predict the autogenous deformation at different temperatures but can be used to calculate the relaxation modulus, which in turn aids in EAS prediction based on autogenous deformation data.Materials and Environmen

An optimization model for vehicle routing of automated taxi trips with dynamic travel times

In this paper, we propose a method of automated vehicle operation in taxi systems that addresses the problem of associating trips to automated taxis (ATs) and assigning those vehicles to paths on an urban road network. This system is envisioned to provide a transport service within a city area with a seamless door-to-door connection for all passengers' origins and destinations. ATs can drive themselves on the roads with reduced direct human input, which allow taxis to satisfy the next trip or park themselves while waiting for a request if needed. We propose an integer programming model to define the routing of the vehicles according to a profit maximization function while depending on dynamic travel times which vary with the flow of the ATs. This will be especially important when the number of automated vehicles circulating on the roads is so high that will cause traffic congestion. The total profit involves the system revenue, vehicle fuel costs, vehicle depreciation costs, parking costs, penalties for unsatisfied trips and passengers' congestion delay. The model is applied to a small case study and the results allow assessing the impact of the ATs movements on traffic congestion and the profitability of the system. Even with a small case study, it is possible to conclude that having in consideration the effect of the vehicle flows on travel time leads to different results in terms of the system profit, the parking cost and the driving distance which points out the importance of this type of models.Transport and Plannin

Effect of CaO content in raw material on the mineral composition of ferric-rich sulfoaluminate clinker

Ferric-rich calcium sulfoaluminate (FR-CSA) cement is an eco-friendly cement. Fe2O3 exists in different minerals of FR-CSA clinker, e.g., Ca4Al2Fe2O10 (C4AF), Ca2Fe2O5 (C2F), and Ca4Al6-2xFe2xSO16 (C4A3-xFxS-). The mineral composition depends on the chemical composition of the raw materials and significantly determines the reactivity of FR-CSA cement. To optimize the phase composition of the FR-CSA clinker, chemical reagent raw mixtures with different amounts of CaO were used to prepare the FR-CSA clinker. X-ray diffraction (XRD) analysis, Rietveld quantitative phase analysis (RQPA), Fourier Transform Infrared spectroscopy (FT-IR), and scanning electron microscopy/energy-dispersive spectroscopy (SEM/EDS) were used to identify the mineralogical conditions of the FR-CSA clinker. The results indicated that the amounts of CaO in raw materials greatly affected the iron-bearing phase formation in the FR-CSA clinker. With decreasing CaO content involved in calcination reaction, the amounts of Fe2O3 incorporated in C4A3-xFxS- increased up to 17.72 wt% (where x = 0.36). The findings make it possible to optimize the mineral composition of the FR-CSA clinker by changing the CaO content in raw materials. Furthermore, low CaO content in the raw material is beneficial to the formation of C4A3-xFxS-, which enables the use of solid wastes containing low calcium for producing FR-CSA cement.Accepted author manuscriptMaterials and Environmen