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We apply keyquery-based taxonomy composition to compute a classification system for the CORE dataset, a shared crawl of about 850,000 scientific papers. Keyquery-based taxonomy composition can be understood as a two-phase hierarchical document clustering technique that utilizes search queries as cluster labels: In a first phase, the document collection is indexed by a reference search engine, and the documents are tagged with the search queries they are relevant—for their so-called keyqueries. In a second phase, a hierarchical clustering is formed from the keyqueries within an iterative process. We use the explicit topic model ESA as document retrieval model in order to index the CORE dataset in the reference search engine. Under the ESA retrieval model, documents are represented as vectors of similarities to Wikipedia articles; a methodology proven to be advantageous for text categorization tasks. Our paper presents the generated taxonomy and reports on quantitative properties such as document coverage and processing requirements.
A Hybrid Clustering and Classification Technique for Forecasting Short-Term Energy Consumption
(2018)
Electrical energy distributor companies in Iran have to announce their energy demand at least three 3-day ahead of the market opening. Therefore, an accurate load estimation is highly crucial. This research invoked methodology based on CRISP data mining and used SVM, ANN, and CBA-ANN-SVM (a novel hybrid model of clustering with both widely used ANN and SVM) to predict short-term electrical energy demand of Bandarabbas. In previous studies, researchers introduced few effective parameters with no reasonable error about Bandarabbas power consumption. In this research we tried to recognize all efficient parameters and with the use of CBA-ANN-SVM model, the rate of error has been minimized. After consulting with experts in the field of power consumption and plotting daily power consumption for each week, this research showed that official holidays and weekends have impact on the power consumption. When the weather gets warmer, the consumption of electrical energy increases due to turning on electrical air conditioner. Also, con-sumption patterns in warm and cold months are different. Analyzing power consumption of the same month for different years had shown high similarity in power consumption patterns. Factors with high impact on power consumption were identified and statistical methods were utilized to prove their impacts. Using SVM, ANN and CBA-ANN-SVM, the model was built. Sine the proposed method (CBA-ANN-SVM) has low MAPE 5 1.474 (4 clusters) and MAPE 5 1.297 (3 clusters) in comparison with SVM (MAPE 5 2.015) and ANN (MAPE 5 1.790), this model was selected as the final model. The final model has the benefits from both models and the benefits of clustering. Clustering algorithm with discovering data structure, divides data into several clusters based on similarities and differences between them. Because data inside each cluster are more similar than entire data, modeling in each cluster will present better results. For future research, we suggest using fuzzy methods and genetic algorithm or a hybrid of both to forecast each cluster. It is also possible to use fuzzy methods or genetic algorithms or a hybrid of both without using clustering. It is issued that such models will produce better and more accurate results.
This paper presents a hybrid approach to predict the electric energy usage of weather-sensitive loads. The presented methodutilizes the clustering paradigm along with ANN and SVMapproaches for accurate short-term prediction of electric energyusage, using weather data. Since the methodology beinginvoked in this research is based on CRISP data mining, datapreparation has received a gr eat deal of attention in thisresear ch. Once data pre-processing was done, the underlyingpattern of electric energy consumption was extracted by themeans of machine learning methods to precisely forecast short-term energy consumption. The proposed approach (CBA-ANN-SVM) was applied to real load data and resulting higher accu-racy comparing to the existing models.
2018 American Institute of Chemical Engineers Environ Prog, 2018
https://doi.org/10.1002/ep.12934
A geometrical inclusion-matrix model for the finite element analysis of concrete at multiple scales
(2003)
This paper introduces a method to generate adequate inclusion-matrix geometries of concrete in two and three dimensions, which are independent of any specific numerical discretization. The article starts with an analysis on shapes of natural aggregates and discusses corresponding mathematical realizations. As a first prototype a two-dimensional generation of a mesoscale model is introduced. Particle size distribution functions are analysed and prepared for simulating an adequate three-dimensional representation of the aggregates within a concrete structure. A sample geometry of a three-dimensional test cube is generated and the finite element analysis of its heterogeneous geometry by a uniform mesh is presented. Concluding, aspects of a multiscale analysis are discussed and possible enhancements are proposed.
Modern distributed engineering applications are based on complex systems consisting of various subsystems that are connected through the Internet. Communication and collaboration within an entire system requires reliable and efficient data exchange between the subsystems. Middleware developed within the web evolution during the past years provides reliable and efficient data exchange for web applications, which can be adopted for solving the data exchange problems in distributed engineering applications. This paper presents a generic approach for reliable and efficient data exchange between engineering devices using existing middleware known from web applications. Different existing middleware is examined with respect to the suitability in engineering applications. In this paper, a suitable middleware is shown and a prototype implementation simulating distributed wind farm control is presented and validated using several performance measurements.
We propose a novel method that applies the light transport matrix for performing an image-based radiometric compensation which accounts for all possible types of light modulation. For practical application the matrix is decomposed into clusters of mutually influencing projector and camera pixels. The compensation is modeled as a linear system that can be solved with respect to the projector patterns. Precomputing the inverse light transport in combination with an efficient implementation on the GPU makes interactive compensation rates possible. Our generalized method unifies existing approaches that address individual problems. Based on examples, we show that it is possible to project corrected images onto complex surfaces such as an inter-reflecting statuette, glossy wallpaper, or through highly-refractive glass. Furthermore, we illustrate that a side-effect of our approach is an increase in the overall sharpness of defocused projections.
A comprehensive framework of information management system for construction projects in China has been established through extensive literature survey and field investigation. It utilizes the potential information technologies and covers the practical management patterns as well as the major aspects of construction project management. It can be used to guide and evaluate the design of the information management systems for construction projects in order to make the system to be applicable to a wide variety of construction projects and survive the changes in project management.
Interactive visualization based on 3D computer graphics nowadays is an indispensable part of any simulation software used in engineering. Nevertheless, the implementation of such visualization software components is often avoided in research projects because it is a challenging and potentially time consuming task. In this contribution, a novel Java framework for the interactive visualization of engineering models is introduced. It supports the task of implementing engineering visualization software by providing adequate program logic as well as high level classes for the visual representation of entities typical for engineering models. The presented framework is built on top of the open source visualization toolkit VTK. In VTK, a visualization model is established by connecting several filter objects in a so called visualization pipeline. Although designing and implementing a good pipeline layout is demanding, VTK does not support the reuse of pipeline layouts directly. Our framework tailors VTK to engineering applications on two levels. On the first level it adds new – engineering model specific – filter classes to VTK. On the second level, ready made pipeline layouts for certain aspects of engineering models are provided. For instance there is a pipeline class for one-dimensional elements like trusses and beams that is capable of showing the elements along with deformations and member forces. In order to facilitate the implementation of a graphical user interface (GUI) for each pipeline class, there exists a reusable Java Swing GUI component that allows the user to configure the appearance of the visualization model. Because of the flexible structure, the framework can be easily adapted and extended to new problem domains. Currently it is used in (i) an object-oriented p-version finite element code for design optimization, (ii) an agent based monitoring system for dam structures and (iii) the simulation of destruction processes by controlled explosives based on multibody dynamics. Application examples from all three domains illustrates that the approach presented is powerful as well as versatile.
This paper describes a framework for computer-aided conceptual design of building structures that results from building architectural considerations. The central task that is carried out during conceptual design is the synthesis of the structural system. This paper proposes a methodology for the synthesis of structural solutions. Given the nature of architectural constraints, user-model interactivity is devised as the most suitable computer methodology for driving the structural synthesis process. Taking advantage of the hierarchical organization of the structural system, this research proposes a top-down approach for structural synthesis. Through hierarchical refinement, the approach lends itself to the synthesis of global and local structural solutions. The components required for implementing the proposed methodology are briefly described. The main components have been incorporated in a proof-of-concept prototype that is being tested and validated with actual buildings.
Tropical coral reefs, one of the world’s oldest ecosystems which support some of the highest levels of biodiversity on the planet, are currently facing an unprecedented ecological crisis during this massive human-activity-induced period of extinction. Hence, tropical reefs symbolically stand for the destructive effects of human activities on nature [4], [5]. Artificial reefs are excellent examples of how architectural design can be combined with ecosystem regeneration [6], [7], [8]. However, to work at the interface between the artificial and the complex and temporal nature of natural systems presents a challenge, i.a. in respect to the B-rep modelling legacy of computational modelling.
The presented doctorate investigates strategies on how to apply digital practice to realise what is an essential bulwark to retain reefs in impossibly challenging times. Beyond the main question of integrating computational modelling and high precision monitoring strategies in artificial coral reef design, this doctorate explores techniques, methods, and linking frameworks to support future research and practice in ecology led design contexts.
Considering the many existing approaches for artificial coral reefs design, one finds they often fall short in precisely understanding the relationships between architectural and ecological aspects (e.g. how a surface design and material composition can foster coral larvae settlement, or structural three-dimensionality enhance biodiversity) and lack an integrated underwater (UW) monitoring process. Such a process is necessary in order to gather knowledge about the ecosystem and make it available for design, and to learn whether artificial structures contribute to reef regeneration or rather harm the coral reef ecosystem.
For the research, empirical experimental methods were applied: Algorithmic coral reef design, high precision UW monitoring, computational modelling and simulation, and validated through parallel real-world physical experimentation – two Artificial Reef Prototypes (ARPs) in Gili Trawangan, Indonesia (2012–today). Multiple discrete methods and sub techniques were developed in seventeen computational experiments and applied in a way in which many are cross valid and integrated in an overall framework that is offered as a significant contribution to the field. Other main contributions include the Ecosystem-aware design approach, Key Performance Indicators (KPIs) for coral reef design, algorithmic design and fabrication of Biorock cathodes, new high precision UW monitoring strategies, long-term real-world constructed experiments, new digital analysis methods and two new front-end web-based tools for reef design and monitoring reefs. The methodological framework is a finding of the research that has many technical components that were tested and combined in this way for the very first time.
In summary, the thesis responds to the urgency and relevance in preserving marine species in tropical reefs during this massive extinction period by offering a differentiated approach towards artificial coral reefs – demonstrating the feasibility of digitally designing such ‘living architecture’ according to multiple context and performance parameters. It also provides an in-depth critical discussion of computational design and architecture in the context of ecosystem regeneration and Planetary Thinking. In that respect, the thesis functions as both theoretical and practical background for computational design, ecology and marine conservation – not only to foster the design of artificial coral reefs technically but also to provide essential criteria and techniques for conceiving them.
Keywords: Artificial coral reefs, computational modelling, high precision underwater monitoring, ecology in design.
Iso-parametric finite elements with linear shape functions show in general a too stiff element behavior, called locking. By the investigation of structural parts under bending loading the so-called shear locking appears, because these elements can not reproduce pure bending modes. Many studies dealt with the locking problem and a number of methods to avoid the undesirable effects have been developed. Two well known methods are the >Assumed Natural Strain< (ANS) method and the >Enhanced Assumed Strain< (EAS) method. In this study the EAS method is applied to a four-node plane element with four EAS-parameters. The paper will describe the well-known linear formulation, its extension to nonlinear materials and the modeling of material uncertainties with random fields. For nonlinear material behavior the EAS parameters can not be determined directly. Here the problem is solved by using an internal iteration at the element level, which is much more efficient and stable than the determination via a global iteration. To verify the deterministic element behavior the results of common test examples are presented for linear and nonlinear materials. The modeling of material uncertainties is done by point-discretized random fields. To show the applicability of the element for stochastic finite element calculations Latin Hypercube Sampling was applied to investigate the stochastic hardening behavior of a cantilever beam with nonlinear material. The enhanced linear element can be applied as an alternative to higher-order finite elements where more nodes are necessary. The presented element formulation can be used in a similar manner to improve stochastic linear solid elements.
Business and engineering knowledge in AEC/FM is captured mainly implicitly in project and corporate document repositories. Even with the increasing integration of model-based systems with project information spaces, a large percentage of the information exchange will further on rely on isolated and rather poorly structured text documents. In this paper we propose an approach enabling the use of product model data as a primary source of engineering knowledge to support information externalisation from relevant construction documents, to provide for domain-specific information retrieval, and to help in re-organising and re-contextualising documents in accordance to the user’s discipline-specific tasks and information needs. Suggested is a retrieval and mining framework combining methods for analysing text documents, filtering product models and reasoning on Bayesian networks to explicitly represent the content of text repositories in personalisable semantic content networks. We describe the proposed basic network that can be realised on short-term using minimal product model information as well as various extensions towards a full-fledged added value integration of document-based and model-based information.
The methods currently used for scheduling building processes have some major advantages as well as disadvantages. The main advantages are the arrangement of the tasks of a project in a clear, easily readable form and the calculation of valuable information like critical paths. The main disadvantage on the other hand is the inflexibility of the model caused by the modeling paradigms. Small changes of the modeled information strongly influence the whole model and lead to the need to change many more details in the plan. In this article an approach is introduced allowing the creation of more flexible schedules. It aims towards a more robust model that lowers the need to change more than a few information while being able to calculate the important propositions of the known models and leading to further valuable conclusions.
A Flexible Model for Incorporating Construction Product Data into Building Information Models
(2006)
When considering the integration and interoperability between AEC-FM software applications and construction products' data, it is essential to investigate the state-of-the-art and conduct an extensive review in the literature of both Building Information Models and electronic product catalogues. It was found that there are many reasons and key-barriers that hinder the developed solutions from being implemented. Among the reasons that are attributed to the failure of many previous research projects to achieve this integration aim are the proprietary developments of CAD vendors, the fragmented nature of construction product data i.e. commercial and technical data, the prefabrication versus on-site production, marketing strategies and brand-naming, the referencing of a product to the data of its constituents, availability of life-cycle data in a single point in time where it is needed all over the whole life-cycle of the product itself, taxonomy problems, the inability to extract search parameters from the building information model to participate in the conduction of parametric searches. Finally and most important is keeping the product data in the building information model consistent and up-to-date. Hence, it was found that there is a great potential for construction product data to be integrated to building information models by electronic means in a dynamic and extensible manner that prevents the model from getting obsolete. The study has managed to establish a solution concept that links continually updated and extensible life-cycle product data to a software independent building information model (IFC) all over the life span of the product itself. As a result, the solution concept has managed to reach a reliable building information model that is capable of overcoming the majority of the above mentioned barriers. In the meantime, the solution is capable of referencing, retrieving, updating, and merging product data at any point in time. A distributed network application that represents all the involved parties in the construction product value chain is simulated by real software tools to demonstrate the proof of concept of this research work.
The purpose of this research is to develop the method to retrieve a building name from the impression of the building. First, the images of the building are registered as database by the questionnaire. Next, the images of the objective building are compared with the degree of matching in image databases, and the building with high synthetic matching degree is retrieved. This system could get a good retrieval result. Moreover, image processing was done, and image databases are trained by neural network from the amount of characteristics of the image, and the retrieval system by image processing was examined.
Abstract Developing and emerging tropical Asian countries have encountered fast urban development due to the migration of farmers seeking a better life in the city. This resulted in a lack of appro-priate infrastructure and inappropriate social services in many cities. Municipal solid waste management is no exception and is in fact often placed at the bottom of the list of priorities for the cities’ appropriate urban management plans since laws and regulations must first be for-mulated and implemented. The problem of unmanaged municipal solid waste certainly leads to air pollution, disease, and to soil and water contamination. These problems in tropical climates are compounded with high temperature, high-level humidity, heavy rainfall and frequent flooding. Stagnant water and leachate from waste quickly become the breeding grounds of in-sects, rodents and bacteria, thus creating a health hazard for workers and local populations. Moreover, water and groundwater contamination may lead to serious environmental degrada-tion with direct impacts on water supplies, and in the fast degradation of agricultural products, the backbone of most tropical Asian countries. Many cities still allow or tolerate dumping of waste in uncontrolled sites, and open burning that disperses particulates that most likely contain dioxins and furans. Even with increasingly scarce land availability within or in proximity of the cities, sanitary landfill is still the most often cho-sen disposal method around Asia because of its lower cost when compared to modern treatment systems. Yet, most of these landfill sites do not have proper lining, daily covering, methane recovery devices, leachate control systems, nor do they have long-term closure and monitoring plans, which implies short and long-term hazards. Some municipalities opted for incineration, which usually entails high operation and maintenance costs because of the need for supple-mental fuel and often-inappropriate running conditions. Although tropical conditions appear to favor certain disposal systems such as composting, appropriate technology needs to be identi-fied in order to reduce operation and maintenance costs while ensuring good quality outputs; compost plants have often been closed because of poor quality products due to the high content of plastic and glass particulates in the finished product. Tropical Asian cities are now required to identify affordable and sustainable solutions for the management of their increasing amount of waste generated daily, while ensuring minimal environmental impact, social acceptance and minimal land use. The purpose of this dissertation was to develop a user-friendly decision-making tool for public administrators and government officials in tropical Asian developing and emerging cities. This tool was developed based on a list of selected decision-making issues necessary in making an informed decision. The decision-making tool is to be used by decision-makers in making a pre-liminary assessment of a most appropriate waste management and treatment system for their municipality. Tropical Asian cities must consider a number of issues when deciding on their waste management plan such as the continuously changing quantum and composition of waste associated with the increasing population and income per capita, the high humidity levels, and the often-limited financial resources. Other determinant factors include legal, political, institu-tional, social and technical issues. Furthermore, administrators must realize the importance of each stage involved in waste management, which includes waste generation, collection, trans-port, waste characteristics, disposal and treatment. To better understand the complexity of the issues involved in tropical Asian municipalities, the city of Bangkok, Thailand’s largest city and capital, was selected as a case study for the management of its 9,000 tonnes of waste gen-erated daily. Numerous interviews, meetings along with the review of documents, reports and site visits offered an inside view of the tropical city’s various decision-making issues towards its waste management plan, and examine specific problems encountered by the city’s decision-makers. The review and analysis of the decision-making issues involved in Bangkok’s waste management plan showed how the decision-making tool can be used in various Asian tropical cities. In conclusion, waste management in an emerging tropical country involves specific challenges that need to be addressed. Economical, technical and social criteria need to be fully understood as to capacitate government officials in the selection of the most appropriate urban waste man-agement system. Limited budgets, lack of public awareness and poor systems’ management often cloud decision-makers in choosing what appears to be the best solution in the short term, but more costly over the years. Weather conditions and scarcity of land in proximity of the city make waste management especially challenging. The decision-making framework offers a tool to decision-makers, as to facilitate the understanding and identification of key issues necessary in the formulation of a sustainable urban waste management plan and in the selection of a tech-nically, economically and socially acceptable integrated MSW management system. A detailed feasibility study and master plan will follow the preliminary study as to define the plant´s specifications, its location and its financing.
Interactive scientific visualizations are widely used for the visual exploration and examination of physical data resulting from measurements or simulations. Driven by technical advancements of data acquisition and simulation technologies, especially in the geo-scientific domain, large amounts of highly detailed subsurface data are generated. The oil and gas industry is particularly pushing such developments as hydrocarbon reservoirs are increasingly difficult to discover and exploit. Suitable visualization techniques are vital for the discovery of the reservoirs as well as their development and production. However, the ever-growing scale and complexity of geo-scientific data sets result in an expanding disparity between the size of the data and the capabilities of current computer systems with regard to limited memory and computing resources.
In this thesis we present a unified out-of-core data-virtualization system supporting geo-scientific data sets consisting of multiple large seismic volumes and height-field surfaces, wherein each data set may exceed the size of the graphics memory or possibly even the main memory. Current data sets fall within the range of hundreds of gigabytes up to terabytes in size. Through the mutual utilization of memory and bandwidth resources by multiple data sets, our data-management system is able to share and balance limited system resources among different data sets. We employ multi-resolution methods based on hierarchical octree and quadtree data structures to generate level-of-detail working sets of the data stored in main memory and graphics memory for rendering. The working set generation in our system is based on a common feedback mechanism with inherent support for translucent geometric and volumetric data sets. This feedback mechanism collects information about required levels of detail during the rendering process and is capable of directly resolving data visibility without the application of any costly occlusion culling approaches. A central goal of the proposed out-of-core data management system is an effective virtualization of large data sets. Through an abstraction of the level-of-detail working sets, our system allows developers to work with extremely large data sets independent of their complex internal data representations and physical memory layouts.
Based on this out-of-core data virtualization infrastructure, we present distinct rendering approaches for specific visualization problems of large geo-scientific data sets. We demonstrate the application of our data virtualization system and show how multi-resolution data can be treated exactly the same way as regular data sets during the rendering process. An efficient volume ray casting system is presented for the rendering of multiple arbitrarily overlapping multi-resolution volume data sets. Binary space-partitioning volume decomposition of the bounding boxes of the cube-shaped volumes is used to identify the overlapping and non-overlapping volume regions in order to optimize the rendering process. We further propose a ray casting-based rendering system for the visualization of geological subsurface models consisting of multiple very detailed height fields. The rendering of an entire stack of height-field surfaces is accomplished in a single rendering pass using a two-level acceleration structure, which combines a minimum-maximum quadtree for empty-space skipping and sorted lists of depth intervals to restrict ray intersection searches to relevant height fields and depth ranges. Ultimately, we present a unified rendering system for the visualization of entire geological models consisting of highly detailed stacked horizon surfaces and massive volume data. We demonstrate a single-pass ray casting approach facilitating correct visual interaction between distinct translucent model components, while increasing the rendering efficiency by reducing processing overhead of potentially invisible parts of the model. The combination of image-order rendering approaches and the level-of-detail feedback mechanism used by our out-of-core data-management system inherently accounts for occlusions of different data types without the application of costly culling techniques.
The unified out-of-core data-management and virtualization infrastructure considerably facilitates the implementation of complex visualization systems. We demonstrate its applicability for the visualization of large geo-scientific data sets using output-sensitive rendering techniques. As a result, the magnitude and multitude of data sets that can be interactively visualized is significantly increased compared to existing approaches.
For the safe and efficient operation of dams, frequent monitoring and maintenance are required. These are usually expensive, time consuming, and cumbersome. To alleviate these issues, we propose applying a wave-based scheme for the location and quantification of damages in dams.
To obtain high-resolution “interpretable” images of the damaged regions, we drew inspiration from non-linear full-multigrid methods for inverse problems and applied a new cyclic multi-stage full-waveform inversion (FWI) scheme. Our approach is less susceptible to the stability issues faced by the standard FWI scheme when dealing with ill-posed problems. In this paper, we first selected an optimal acquisition setup and then applied synthetic data to demonstrate the capability of our approach in identifying a series of anomalies in dams by a mixture of reflection and transmission tomography. The results had sufficient robustness, showing the prospects of application in the field of non-destructive testing of dams.
A coupled thermo-hydro-mechanical model of jointed hard rock for compressed air energy storage
(2014)
Renewable energy resources such as wind and solar are intermittent, which causes instability when being connected to utility grid of electricity. Compressed air energy storage (CAES) provides an economic and technical viable solution to this problem by utilizing subsurface rock cavern to store the electricity generated by renewable energy in the form of compressed air. Though CAES has been used for over three decades, it is only restricted to salt rock or aquifers for air tightness reason. In this paper, the technical feasibility of utilizing hard rock for CAES is investigated by using a coupled thermo-hydro-mechanical (THM) modelling of nonisothermal gas flow. Governing equations are derived from the rules of energy balance, mass balance, and static equilibrium. Cyclic volumetric mass source and heat source models are applied to simulate the gas injection and production. Evaluation is carried out for intact rock and rock with discrete crack, respectively. In both cases, the heat and pressure losses using air mass control and supplementary air injection are compared.
The contribution focuses on the development of a basic computational scheme that provides a suitable calculation environment for the coupling of analytical near-field solutions with numerical standard procedures in the far-field of the singularity. The proposed calculation scheme uses classical methods of complex function theory, which can be generalized to 3-dimensional problems by using the framework of hypercomplex analysis. The adapted approach is mainly based on the factorization of the Laplace operator EMBED Equation.3 by the Cauchy-Riemann operator EMBED Equation.3 , where exact solutions of the respective differential equation are constructed by using an orthonormal basis of holomorphic and anti-holomorphic functions.
The research of the best building design requires a concerted design approach of both structure and foundation. Our work is an application of this approach. Our objective is also to create an interactive tool, which will be able to define, at the early design stages, the orientations of structure and foundation systems that satisfy as well as possible the client and the architect. If the concerns of these two actors are primarily technical and economical, they also wish to apprehend the environmental and social dimensions of their projects. Thus, this approach bases on alternative studies and on a multi-criterion analysis. In this paper, we present the context of our work, the problem formulation, which allows a concerted design of Structure and Foundation systems and the feasible solutions identifying process.