Feasibility study on lengthening the high-voltage cable section and reducing the number of cable joints via alternative bonding methods

The mesosphere is perhaps the least explored region in the atmosphere with very few methods of observing. This thesis will primarily be exploring a new technique for measuring the distribution of kinetic energy in the mesosphere across a wide range of spatial and temporal scales. The method being used relies on correlation functions between pairs of meteor measurements. These measurements are made using a network of specular meteor radars located in Northern Norway. This network produced 32 million meteor measurements over a 2 year period. The correlation function estimation method has been previously used on a smaller data set, but has so far not been used for a longer data set and at high latitudes. The main advantage of the new technique is that by studying the second order statistics of the wind field, we can obtain significantly better temporal and spatial resolution than before. Such a large data set allows for great resolution for both spatial and temporal correlation functions. By using temporal correlation functions and the kinetic energy spectrum, different atmospheric wave phenomena can be studied. These include diurnal and semi diurnal tides. The horizontal and vertical correlation functions will be used to verify that the kinetic energy follows a power law, as theoretically expected by the Kolmogorov theory for turbulence. This was done by using a second order structure function applied to correlation functions. The temporal and horizontal correlation functions were used to study the summer-winter variation in kinetic energy, some variation in the temporal domain is the impact from large scale waves as well as in the power spectra were there is a steeper power law slope during the winter. As for the horizontal domain there are differences in kinetic energy in the zonal and meridional direction for both large and small scale waves. The dataset in this thesis a lot more can be found out about the mesosphere, in this thesis only a few of the possibilities are explored. The results are in agreement with earlier work, confirming the results obtained by the earlier study

The evolution of cooperation in the public goods game on the scale-free community networks under multiple strategy updating rules

Social networks have a scale-free property and community structure, and many problems in life have the characteristic of public goods, such as resource shortage. Due to different preferences of individuals, there exist individuals who adopt heterogeneous strategies updating rules in the network. We investigate the evolution of cooperation in the scale-free community network with public goods games and the influence of multiple strategy updating rules. Here, two types of strategy updating rules are considered which are pairwise comparison rules and aspiration-driven rules. Numerical simulations are conducted and presented corresponding results. We find that community structure promotes the emergence of cooperation in public goods games. In the meantime, there is a "U" shape relationship between the frequency of cooperators and the proportion of the two strategy updating rules. With the variance in the proportion of the two strategy updating rules, pairwise comparison rules seem to be more sensitive. Compared with aspiration-driven rules, pairwise comparison rules play a more important role in promoting cooperation. Our work may be helpful to understand the evolution of cooperation in social networks.Comment: 6 figures, 11 page

Development of a Waste-to-Energy Decision Support System (WTEDSS)

International audienceRapid increase in urban population has created the need for the development of efficient Decision Support Systems (DSS) guiding municipal planners to mitigate urban sprawl, pollution and waste generation, unsustainable production and consumption patterns. To ensure sustainable urban planning, a DSS must provide not only an optimal planning solution based on input assumptions, but must also help to identify concrete city challenges, determine available resources (e.g., land and energy sources) and highlight any implementation constraints. It must support the creation of flexible interactive scenarios for urban development and their realistic representation in an urban context. This paper presents a Waste-to-Energy Decision Support System (WTEDSS) that identifies the optimal long-term deployment strategy for waste-to-energy infrastructures under future uncertain operational conditions and then directly assesses its feasibility and integration into an urban environment using 3D visualization. The WTEDSS is designed as an interactive and analytical waste management planning tool integrating four modules: data analytics, optimization, simulation and a user-friendly graphical interface. Emphasis is placed on the development and integration of the optimization module and 3D urban simulation, which provides users with decision support based on 3D visualized optimum facilities deployment plans. The optimization module receives calibrated data and solves a model based on inputs obtained from the user interface. The simulation platform developed in Unity 3D provides a friendly real-world environment for studying and understanding the facility deployment process over time and space, while also considering uncertainty

Fabrications and Applications of Micro/nanofluidics in Oil and Gas Recovery: A Comprehensive Review

Understanding fluid flow characteristics in porous medium, which determines the development of oil and gas oilfields, has been a significant research subject for decades. Although using core samples is still essential, micro/nanofluidics have been attracting increasing attention in oil recovery fields since it offers direct visualization and quantification of fluid flow at the pore level. This work provides the latest techniques and development history of micro/nanofluidics in oil and gas recovery by summarizing and discussing the fabrication methods, materials and corresponding applications. Compared with other reviews of micro/nanofluidics, this comprehensive review is in the perspective of solving specific issues in oil and gas industry, including fluid characterization, multiphase fluid flow, enhanced oil recovery mechanisms, and fluid flow in nano-scale porous media of unconventional reservoirs, by covering most of the representative visible studies using micro/nanomodels. Finally, we present the challenges of applying micro/nanomodels and future research directions based on the work

Pattern Recognition for Steam Flooding Field Applications based on Hierarchical Clustering and Principal Component Analysis

Steam flooding is a complex process that has been considered as an effective enhanced oil recovery technique in both heavy oil and light oil reservoirs. Many studies have been conducted on different sets of steam flooding projects using the conventional data analysis methods, while the implementation of machine learning algorithms to find the hidden patterns is rarely found. In this study, a hierarchical clustering algorithm (HCA) coupled with principal component analysis is used to analyze the steam flooding projects worldwide. The goal of this research is to group similar steam flooding projects into the same cluster so that valuable operational design experiences and production performance from the analogue cases can be referenced for decision-making. Besides, hidden patterns embedded in steam flooding applications can be revealed based on data characteristics of each cluster for different reservoir/fluid conditions. In this research, principal component analysis is applied to project original data to a new feature space, which finds two principal components to represent the eight reservoir/fluid parameters (8D) but still retain about 90% of the variance. HCA is implemented with the optimized design of five clusters, Euclidean distance, and Ward\u27s linkage method. The results of the hierarchical clustering depict that each cluster detects a unique range of each property, and the analogue cases present that fields under similar reservoir/fluid conditions could share similar operational design and production performance

Mechanism of activation and the rewired network: New drug design concepts

Precision oncology benefits from effective early phase drug discovery decisions. Recently, drugging inactive protein conformations has shown impressive successes, raising the cardinal questions of which targets can profit and what are the principles of the active/inactive protein pharmacology. Cancer driver mutations have been established to mimic the protein activation mechanism. We suggest that the decision whether to target an inactive (or active) conformation should largely rest on the protein mechanism of activation. We next discuss the recent identification of double (multiple) same-allele driver mutations and their impact on cell proliferation and suggest that like single driver mutations, double drivers also mimic the mechanism of activation. We further suggest that the structural perturbations of double (multiple) in cis mutations may reveal new surfaces/pockets for drug design. Finally, we underscore the preeminent role of the cellular network which is deregulated in cancer. Our structure-based review and outlook updates the traditional Mechanism of Action, informs decisions, and calls attention to the intrinsic activation mechanism of the target protein and the rewired tumor-specific network, ushering innovative considerations in precision medicine