This paper proposes an efficient, adaptive importance sampling (AIS) method that can be used to compute component and system reliability and reliability sensitivities. The AIS approach uses a sampling density that is ...
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This paper proposes an efficient, adaptive importance sampling (AIS) method that can be used to compute component and system reliability and reliability sensitivities. The AIS approach uses a sampling density that is proportional to the joint probability density function of the random variables. Starting from an initial approximate failure domain, sampling proceeds adaptively and incrementally to reach a sampling domain that is slightly greater than the failure domain to minimize oversampling in the safe region. Several reliability sensitivity coefficients are proposed that can be computed directly and easily from the previous AIS-based failure points. These sensitivities can be used to identify key random variables and to adjust a design to achieve reliability-based objectives. The proposed methodology is demonstrated using a turbine blade reliability analysis problem.
Electron tomography (ET) has emerged as a powerful technique to address fundamental questions in molecular and cellular biology. It makes possible visualization of the molecular architecture of complex viruses, organe...
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Electron tomography (ET) has emerged as a powerful technique to address fundamental questions in molecular and cellular biology. It makes possible visualization of the molecular architecture of complex viruses, organelles and cells at a resolution of a few nanometres. In the last decade ET has allowed major breakthroughs that have provided exciting insights into a wide range of biological processes. In ET the biological sample is imaged with an electron microscope, and a series of images is taken from the sample at different views. Prior to imaging, the sample has to be specially prepared to withstand the conditions within the microscope. Subsequently, those images are processed and combined to yield the three-dimensional reconstruction or tomogram. Afterwards, a number of computational steps are necessary to facilitate the interpretation of the tomogram, such as noise reduction, segmentation and analysis of subvolumes. As the computational demands are huge in some of the stages, high performance computing (HPC) techniques are used to make the problem affordable in reasonable time. This article intends to comprehensively review the methods, technologies and tools involved in the different computational stages behind structural studies by Er, from image acquisition to interpretation of tomograms. The HPC techniques usually employed to cope with the computational demands are also briefly described. (C) 2012 Elsevier Ltd. All rights reserved.
Electron tomography (ET) is a powerful imaging technique that enables thorough three-dimensional (3D) analysis of materials at the nanometre and even atomic level. The recent technical advances have established ET as ...
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Electron tomography (ET) is a powerful imaging technique that enables thorough three-dimensional (3D) analysis of materials at the nanometre and even atomic level. The recent technical advances have established ET as an invaluable tool to carry out detailed 3D morphological studies and derive quantitative structural information. Originally from life sciences, ET was rapidly adapted to this field and has already provided new and unique insights into a variety of materials. The principles of ET are based on the acquisition of a series of images from the sample at different views, which are subsequently processed and combined to yield the 3D volume or tomogram. Thereafter, the tomogram is subjected to 3D visualization and post-processing for proper interpretation. Computation is of utmost importance throughout the process and the development of advanced specific methods is proving to be essential to fully take advantage of ET in materials science. This article aims to comprehensively review the computational methods involved in these ET studies, from image acquisition to tomogram interpretation, with special focus on the emerging methods. (C) 2013 Elsevier Ltd. All rights reserved.
The cellular automaton model of computation has drawn the interest of researchers from different disciplines including computer science, biology, mathematics, economy, biochemistry and philosophy. Although a cellular ...
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The cellular automaton model of computation has drawn the interest of researchers from different disciplines including computer science, biology, mathematics, economy, biochemistry and philosophy. Although a cellular automaton is based on a set of simple rules, over time complex patterns may evolve. We present computational methods for implementing and optimizing a well known two-state cellular automaton, Conway's Game of Life, on a 16-core Intel Xeon. The evaluation is based on three multicore algorithms. The first algorithm is coherent and utilizes shared memory and barrier synchronization. The remaining two algorithms are distributed and utilize private memories and explicit core-to-core message passing. We provide a link to our open source simulation software. (C) 2013 Elsevier B.V. All rights reserved.
The mathematical modeling of real welding technologies based on a physicochemical analysis of the interaction between the phases (metal, slag, and gas) is employed in the present work. The model is based on the fundam...
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The mathematical modeling of real welding technologies based on a physicochemical analysis of the interaction between the phases (metal, slag, and gas) is employed in the present work. The model is based on the fundamental equations of thermodynamics and kinetics of high-temperature metallurgical reactions and factors which take into account the thermal and hydrodynamics conditions of the real process. Such an approach permits optimization of the composition of the materials and the technology of the process already in the planning stage with minimal expenditures of time and materials. The model is used to develop fundamentally new compositions for electrode coatings and flux-cored electrodes (including those based on the use of industrial waste products and recycled materials). The performance and adequacy of the model was tested using special technological experiments and as the research goes on the software is modified. The data base of the model includes the relevant experimental and theoretical data concerning the complex interaction of various alloying components. (c) 2006 Elsevier B.V. All rights reserved.
Using the finite volume method, the Navier-Stokes equations are solved on a body-fitted structured grid. The low speed and hovering flight of MI-171V5 helicopter are numerically simulated, and the flowfield characteri...
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Using the finite volume method, the Navier-Stokes equations are solved on a body-fitted structured grid. The low speed and hovering flight of MI-171V5 helicopter are numerically simulated, and the flowfield characteristics around its engine inlet are calculated. Following this, beginning with a prescribed wake model, a semi-empirical correction for the vortex core effect on rotor wake is made, and a free-wake calculation is carried out. The calculated results show that both computational-fluid-dynamics method and free-wake analytical technique can predict the vortex wake flowfield distributions.
作者：
Haider, ShozebUCL
UCL Sch Pharm 29-39 Brunswick Sq London WC1N 1AX England
Quadruplexes are four-stranded DNA or RNA structures formed from tandem repeats of guanine-rich sequences. They are present throughout the genome, namely at telomeres, in promoter and untranslated regions of important...
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Quadruplexes are four-stranded DNA or RNA structures formed from tandem repeats of guanine-rich sequences. They are present throughout the genome, namely at telomeres, in promoter and untranslated regions of important genes. Quadruplexes are thermodynamically stable structures and once formed can be a hindrance to cellular processes like transcription, translation, replication among others. Based on these findings, it has been proposed that small molecules can be used to selectively bind and stabilise quadruplexes. In this review, we explore computational methods that can be used to study quadruplex-ligand interactions. These methods not only provide interpretation of experimental data but also generate information that cannot be accessed by experimental methods.
The use of computational methods in carbene chemistry has a long-standing tradition. Indeed, the field has come a long way since the first ab initio calculations on methylene. Computations now routinely accompany most...
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The use of computational methods in carbene chemistry has a long-standing tradition. Indeed, the field has come a long way since the first ab initio calculations on methylene. Computations now routinely accompany most experimental studies, either to validate the obtained results or to help design appropriate experiments. Advances in computational carbene chemistry within the last decade are covered in this text, encompassing a plethora of studies on alkyl-, aryl-, halo-, and heterocarbenes (N, P, O, S) as well as on persistent triplet carbenes. Moreover, the conceptual advancements in the fields of theoretical chemistry and computing technology have enabled researchers to conduct intricate ab initio studies. The application of leading-edge theory to multireference problems, high-accuracy thermochemical evaluations, atom tunneling, and the description of bonding is thoroughly reviewed. In addition, general recommendations for the choice of an appropriate method for a specific computational problem are given. Practitioners of the art are likely to discover new computational approaches in carbene chemistry applied to various examples from the current literature. (c) 2012 John Wiley & Sons, Ltd.
Since ground-coupled heat pump system (GCHPs) has been more and more widely applied, it is vital to build an accurate method for sizing borehole heat exchangers (BHEs), and the methods for determining the heat transfe...
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Since ground-coupled heat pump system (GCHPs) has been more and more widely applied, it is vital to build an accurate method for sizing borehole heat exchangers (BHEs), and the methods for determining the heat transfer between the boreholes and surrounding ground under time-varying loads in different time scales are the kernel of optimizing design of BHEs, which is helpful to obtain accurate results and significantly decrease computation time consuming. This paper summarizes computational methods for the ground thermal response of BHE under time-varying loads and thermal interaction of multiple BHEs, compares the representative design tools in terms of their performance characteristics, and analyzes the direct applications of computational methods in thermal response test (TRT) and operating performance simulation of GCHPs. Finally, some recommendations for future development of computational methods are proposed. (C) 2018 Elsevier Ltd. All rights reserved.
The accurate annotation of protein localization is crucial in understanding protein function in tandem with a broad range of applications such as pathological analysis and drug design. Since most proteins do not have ...
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The accurate annotation of protein localization is crucial in understanding protein function in tandem with a broad range of applications such as pathological analysis and drug design. Since most proteins do not have experimentally-determined localization information, the computational prediction of protein localization has been an active research area for more than two decades. In particular, recent machinelearning advancements have fueled the development of new methods in protein localization prediction. In this review paper, we first categorize the main features and algorithms used for protein localization prediction. Then, we summarize a list of protein localization prediction tools in terms of their coverage, characteristics, and accessibility to help users find suitable tools based on their needs. Next, we evaluate some of these tools on a benchmark dataset. Finally, we provide an outlook on the future exploration of protein localization methods. (C) 2021 The Authors. Published by Elsevier B.V. on behalf of Research Network of computational and Structural Biotechnology.
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