Classification of Knowledge for Generating Engineering Models

Process modelling is the foundation of developing process controllers for monitoring and improving process/system health. Modelling process behaviours using a pure empirical approach might not be feasible due to limitation in collecting large amount of data. Engineering models provide valuable information about processes’ general behaviours but they might not capture distinct characteristics in the particular process studied. Many recent publications presented various ideas of using limited experimental data to adjust engineering models for making them suitable for certain applications. However, the focuses there are global adjustments, where modification of engineering models impacts the entire model-application region. In practice, some engineering models are only valid in a part of experimental data domain. Moreover, many discrepancies between engineering models and experimental data are in local regions. For example, in a chemical vapour deposition process, at high temperatures a process may be described by a diffusion limited model, while at low temperatures the process may be described by a reaction limited model. To address these problems, this article proposes two approaches for integrating engineering and data models: local model calibration and local model averaging. Through the local model calibration, the discrepancies between engineering’s first-principle models and experimental data are resolved locally based on experts’ feedbacks. To combine models adjusted locally in some regions and also models required little adjustments in other regions, a model averaging procedure based on local kernel weights is proposed. The effectiveness of the proposed method is demonstrated on simulated examples, and compared against a well-known existing global-adjustment method.

This paper presents design, modeling, and analysis of satellite model used for remote sensing. A detailed study is carried out for the design and modeling of the satellite structure focusing on the factors such as the selection of material, optimization of shape and geometry, and accommodation of different subsystems and payload. The center of mass is required to be kept within the range of (1-2) cm from its geometric center. Once the model is finalized it is required to be analyzed by the use ofAnsys, a tool for finite element analysis (FEA) under given loading and boundary conditions. Static, modal, and harmonic analyses inAnsysare performed at the time of ground testing and launching phase. The finite element analysis results are also validated and compared with the theoretical predictions. These analyses are quite helpful and suggest that the satellite structure does not fail and retains its structural integrity during launch environment.

Docking allows to predict ligand binding to proteins, since the 3D-structure for the target is available. Several docking studies have been carried out to identify potential ligands for drug targets. Many of these studies resulted in the leads that were later developed as drugs. Our goal here is to describe the development of an integrated computational tool to assess docking accuracy and build new scoring functions to predict ligandbinding affinity. We carried out docking simulations using MVD program for a data set available on CSAR 2014 database (coagulation factor Xa) for which ligand-binding information and structures are available. These docking results were analyzed using SAnDReS available at www.sandres.net. Machine learning methods were applied to build new scoring functions and our results were compared with previously published benchmarks. Our integrated docking strategy generated poses with docking accuracy higher than previously published benchmarks. In addition, the new scoring function developed using SAnDReS shows better performance than well-established scoring functions such the ones available in Autodock, Autodock- Vina, Gold, Glide, and MVD. The big data generated during docking lacked an integrated computational tool for statistical analysis of the influence of structural parameters on docking and scoring function performance. Here we describe methods to evaluate docking results using SAnDReS, a computational environment for statistical analysis of docking results and development of scoring functions. We believe that SAnDReS is a computational tool with potential to improve accuracy in docking projects.

The investigation and implementation of product modeling methods are two of the most important research objectives in the field of computer-aided engineering design. Commercial product modeling systems go beyond geometric modeling systems in that they are adapted to user requirements through the addition of systems that aid in the generation of engineering models and methods. The embodiment design of a mechanical energy storage system serves as an example of future continuous and flexible computer-aided design (CAD). This example is implemented with GEKO, a user system for the layout of design elements. GEKO is coupled with a commercial geometric modeler (CATIA) and uses several programming interfaces.

Chapter 1 - Genome to phenome: bioinformatics of crop plants

With the development of Building Information Modeling (BIM) technology, there has been an increased application of BIM-based modeling and energy analysis tools in building design. Although there are several popular energy analysis tools available, there is currently no effective way for users to verify the accuracy and reliability of their results and to compare the differences between different analysis tools. Therefore, the Computer-Aided Engineering Group at Department of Civil Engineering, National Taiwan University is developing a test bed for researchers and practitioners to share verification data, with both the BIM model of a test-case building and the actual measurement data of the energy performance of the building, which can be used for verification and comparison of various building energy analysis tools. This paper discusses the design and implementation of the test bed. The test bed consists of three major parts: (1) the repository of the BIM model of the test-case building with measured energy data; (2) user interfaces for users to upload and retrieve test-case information and model data in an organized and convenient way; and (3) utilities for users to convert data between different formats used by different energy analysis tools and to evaluate the energy analysis tools based on comparisons of analysis results with actual measurement data.

An integrated energy system (IES) is responsible for aggregating various energy carriers, such as electricity, gas, heating, and cooling, with a focus on integrating these components to provide an efficient, low-carbon, and reliable energy supply. This paper aims to review the modeling methods, tools, and service modes of IES in China to evaluate opportunities for improving current practices. The models reviewed in this paper are classified as demand forecasting or energy system optimization models based on their modeling progress. Additionally, the main components involved in the IES modeling process are presented, and typical domestic tools utilized in the modeling processes are discussed. Finally, based on a review of several demonstration projects of IES, future development directions of IES are summarized as the integration of data-driven and engineering models, improvements in policies and mechanisms, the establishment of regional energy management centers, and the promotion of new energy equipment.

Before a new structure can be built, it must be designed. This design phase is a very important step in the building process. The total cost of the structure and its structural performance are largely dependent on the structural design process. The impact of decisions on the design process is initially high and declines as the design matures. However, few computational tools are available for the conceptual design phase; thus, an opportunity exists to create such tools. In the conventional workflow, the architect uses geometric modeling tools and the engineer uses structural analysis tools in sequential steps. Parametric modeling tools represent an improvement to this workflow, as structural analysis plug-ins are available. This allows the architect or engineer to receive structural feedback at an earlier stage, but still as a sequential step to the geometric modeling. The present work aims to improve this workflow by integrating structural feedback with geometric modeling.The user interfaces of conceptual design tools should be interactive and agile enough to follow the designer’s iterative workflow. Direct manipulation involves human-computer interaction, which enables an interactive user interface. In this user interface style, users can directly manipulate on-screen objects using real-world metaphors, which engages the users with their task and encourages further explorations. This is achieved by reducing the perceptual and cognitive resources required to understand and use the interface. New technologies have opened up the possibility of creating new design tools that make use of very direct manipulation. This possibility is further explored in this thesis through the development of two such applications. The first application makes use of multi-touch tablets. The multi-touch interface has literally closed the gap between humans and computers, enabling very direct manipulation interactions with two-dimensional user interfaces. The developed application is an interactive conceptual design tool with real-time structural feedback that allows the user to quickly input and modify structural models through the use of gestures. The second application extends these concepts and ideas into a three-dimensional user interface using an input device named the Leap Motion Controller.

Use of CAPE-OPEN standards in the interoperability between modelling tools (MoT) and process simulators (Simulis ® Thermodynamics and ProSimPlus)

Bioinformatics workflows frequently access various distributed biological data sources and computational analysis tools for data analysis and knowledge discovery. They move large volumes of data from biological data sources to computational analysis tools and follow the traditional data migration approach for workflow execution. However, in the advent of big-data in bioinformatics, moving large volumes of data to computation during workflow execution is no longer feasible. Considering the fact that the size of biological data is continuously growing and is much larger than the computational analysis tool size, moving computation to data in a workflow is a better solution to handle the growing data. In this paper, we therefore propose a computation migration approach to execute bioinformatics workflows. We move computational analysis tools to data sources during workflow execution and demonstrate with workflow patterns that moving computation instead of data yields high performance gains in terms of data-flow and execution time.

BackgroundGene transcription in eukaryotic cells is collectively controlled by a large panel of chromatin associated proteins and ChIP‐seq is now widely used to locate their binding sites along the whole genome. Inferring the differential binding sites of these proteins between biological conditions by comparing the corresponding ChIP‐seq samples is of general interest, yet it is still a computationally challenging task.ResultsHere, we briefly review the computational tools developed in recent years for differential binding analysis with ChIP‐seq data. The methods are extensively classified by their strategy of statistical modeling and scope of application. Finally, a decision tree is presented for choosing proper tools based on the specific dataset.ConclusionsComputational tools for differential binding analysis with ChIP‐seq data vary significantly with respect to their applicability and performance. This review can serve as a practical guide for readers to select appropriate tools for their own datasets.

Elementary Flight Dynamics with an Introduction to Bifurcation and Continuation Methods, Second Edition is aimed at senior undergraduate and graduate students of aerospace and mechanical engineering. The book uses an optimal mix of physical insight and mathematical presentation to illustrate the core concepts of professional aircraft flight dynamics. An updated version of the aerodynamic model is presented with the corrected definition of rate (dynamic) derivatives, supported with examples of real-life airplanes and related data and by open-source computational tools. It introduces bifurcation and continuation methods as a tool for flight dynamic analysis. FEATURES Covers an up-to-date, corrected, ‘clean’ presentation of the elements of flight dynamics Presents a blend of theory, practice and application with real-life practical examples Provides a unique viewpoint of applied aerodynamicists and aircraft designers Introduces bifurcation and continuation methods as a tool for flight dynamics analysis Includes a computational tool with real-life examples carried throughout the chapters The book is enriched with case studies of flight dynamics of a bird’s flight, of a six-seater rigid-wing airplane from a design perspective, and airship dynamics to highlight the modal behaviour of similar-looking vehicles that are distinct from each other. Excerpts from reviews of the first edition: "Flight dynamics is a topic that can cause difficulties to aerospace engineering students. This text leads the reader gently through the material with plenty of practical examples and student exercises. As such, it is easy to follow the material and to gradually develop a deep understanding of a demanding topic. The book is ideal for undergraduate students and is a good text for graduate students."––James F. Whidborne, Cranfield University, United Kingdom "The book covers all the aspects of flight dynamics traditionally found in such texts interspersed with examples of the treatment of features of current air vehicles....In my opinion, this book covers the subject comprehensively and is a desirable reference source for undergraduates and graduates alike."––R.J. Poole, MRAeS, The Aeronautical Journal, June 2014 "The book design and the methodology of interpretation are directed to a wide range of target audience/population interested in studying the dynamics of flight. Given the scale and organization of information, the book will also be a useful tool in the analysis of flight dynamics for professionals in this field. The book is sure to appeal to anyone interested in the dynamics of flight."––Jaroslav Salga, Advances in Military Technology, June 2014

An interactive digital hydro-climatologic atlas of Colombia, HidroSIG, has been developed with distributed maps and time series of monthly and long-term average hydro-climatological variables, as part of a more comprehensive geographical information system (GIS) and database. Maps were developed so as to capture the spatial variability of the diverse geophysical fields resulting from major geographic, topographic and climatic controls. HidroSIG contains modules that perform diverse hydrological and geomorphological estimations including: (i) extraction of geomorphological parameters of drainage channel networks and river basins from Digital Elevation Maps (DEM), (ii) estimation of long-term and monthly water balances and other hydro-climatic variables in river basins, (iii) estimation of extreme flows (floods and low flows) of different return periods along the river network of Colombia by combining long-term water balance with scaling methods, (iv) interpolation of geophysical fields, (v) temporal analysis of hydrological time series including standardization, autocorrelation function, Fourier spectrum and cross-correlations analysis with macro-climatic indices, and (vi) simulation of rainfall–runoff processes using a hydrologic distributed model. The most relevant features of HidroSIG are described in terms of the methods used for hydrologic estimations, visualization capabilities, tools for analysis and interpolation of hydro-climatic variables in space and time, geomorphologic analysis and estimation from DEMs, and other features. Water resources planning and management and diverse socio-economic sectors benefit from this freely available database and computational tool.

The future of the developed, developing and emerging countries in a global world strongly depends on the availability and transport of energy. It is believed that the near future the consumption of energy will continuously grow. Security and sustainability have become major priorities to both customers and electric companies. Deployment of sustainable / renewable energy sources is crucial to a healthy relationship of society and the environment. The electric power grid is a crucial part of society infrastructure and needs constant attention for maintaining its performance and reliability. Sometimes called the largest machine man has ever made, the grid is a widespread, interconnected system that is as strong as its weakest link. The electrification of our society has empowered countless advances in other fields such that the US National Academy of Engineering ranked it as the greatest engineering achievement of the last century [2]. Successful smart grid deployment requires a systemic perspective, as most of the smart grid benefits are systemic in nature. System integration and full engagement of customer are crucial elements of this development [3]. Project investments in Europe currently amount to over 5 billion euros and estimated 56 billion by 2020 [4]. The electrical infrastructure of the future will be much more complex than the current one. It will have to integrate traditional and sustainable energy sources, present and new distribution systems, customers with quite different consumption patterns, and smart control systems. However, at this moment there are no comprehensively enough engineering models and tools that can cope with the higher level of complexity of future electric grids. Consequently, engineers use traditional models to design the next generation of electrical infrastructure with the result that important interactions between technical systems will be overlooked; non-technical dimensions like social behavior of customers or moral dimensions of smart control systems will be ignored; and the justified interests of economically weak stakeholders will be neglected. It is of utmost importance that engineering models and tools will be developed that do justice to the complexity of electrical grids, the complexity of our technological society, and the complex relation between man, technology and nature. Fundamentally, philosophy as a discipline would be most well-equipped to give insight in the vast complexity that electrical engineers have to deal with. However, a philosophical approach cannot be taken for granted. Most people believe that philosophy is at best an interesting game of reason but not a discipline that can solve any problem. Tom Morris cites in his book Philosophy for Dummies (1999) in a humorous way, a statement from Voltaire, who in self-mockery says on the alleged `not so practical' inset of philosophers as such: `if he who hears does not understand what he who speaks means, and if he who speaks himself does not understand what he means, that is philosophy' (Morris, 1999, p.14). It was, of course, meant as a joke; however for many this will be recognizable towards their own prejudices about philosophers. The authors of this paper believe that a philosophical approach may be extremely useful if: (1) It gives tools and concepts to criticize present approaches in engineering, economics and politics; (2) It gives more insight in the complexity of future micro, super and smart grids; (3) It shows a direction how to develop more efficient, human-oriented, environmental friendly, and sustainable electrical systems. Among the lessons learned from several smart grid European projects and reported on [3] were: the difficulties encountered during the data collection process; the lack of quantitative data to perform analysis; the recognition of the higher complexity of the system and the lack of proper integration; the difficulties with the setting of business models; the lack of consumer involvement; the need for proper ICT infrastructure; the need of better data protection and security; and the need for legislative framework to ensure proper division of responsibilities. The report highlights that “a scan of the collected projects seems to suggest a lack of specific attention t the social implications of Smart Grids.” This paper has the following set-up: first, a description of smart grids characteristics is presented (section 2). Then the societal implications are discussed (section 3), followed by the need of philosophy to deal of the complexity of the smart grid system (section 4). Some analysis considerations and tools are the introduced followed by case studies and applications (section 5). Finally some recommendations for the development of an overall framework is presented (section 6).

This article presents a method of analyzing mixed logic/dynamic systems. The article describes the development of a computational tool for the analysis of piecewise linear (PL) dynamical systems. Unfortunately, many PL controllers are developed from ad hoc "intelligent systems" ideas which do not aim or allow the associated dynamic behavior to be predicted. An example of such a system is the anti-skid braking system in a car, where the controller is rule-based and designed using the engineer's knowledge of the system. The only current viable approach to testing such a system is by using extensive simulation and prototype testing, which must be repeated for each of the different car models on which it is installed. Anything that provides insight into the logic and dynamic interaction of such a system would be useful: hence the development of the work in this article. Similarly, systems with programmable logic controllers and gain schedulers also fall into the class of piecewise linear systems. The authors take ideas and known results from linear systems, convex set theory, and computational geometry and synthesize them to create an analysis tool for studying a class of systems that mix logic and dynamics. We choose to develop a computational analysis tool primarily because the traditional theoretical analysis of piecewise linear processes is intractable, except, that is, for certain local dynamic behavior.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>