Repetitive Calculations Research Articles

Accelerating gradient-based topology optimization design with dual-model artificial neural networks

Topology optimization (TO) is a common technique used in free-form designs. However, conventional TO-based design approaches suffer from high computational cost due to the need for repetitive forward calculations and/or sensitivity analysis, which are typically done using high-dimensional simulations such as finite element analysis (FEA). In this work, artificial neural networks are used as efficient surrogate models for forward and sensitivity calculations in order to greatly accelerate the design process of topology optimization. To improve the accuracy of sensitivity analyses, dual-model artificial neural networks that are trained with both forward and sensitivity data are constructed and are integrated into the Solid Isotropic Material with Penalization (SIMP) method to replace the FEA. The performance of the accelerated SIMP method is demonstrated on two benchmark design problems namely minimum compliance design and metamaterial design. The efficiency gained in the problem with size of 64 × 64 is 137 times in forward calculation and 74 times in sensitivity analysis. In addition, effective data generation methods suitable for TO designs are investigated and developed, which lead to a great saving in training time. In both benchmark design problems, a design accuracy of 95% can be achieved with only around 2000 training data.

Electrochemical noise analysis to obtain the Rsn value via FFT using Excel

Electrochemical noise (EN) measurements are based on the fluctuations of the electrochemical potential and the current that occur during, for example, a corrosion process without an external signal perturbation. EN analysis (ENA) allows assessment of the type of corrosion and rapid determination of the corrosion rate. Microsoft Excel®, an inexpensive and readily available software package, is an excellent tool for performing repetitive calculations, with automation that saves time for the users. It is a useful tool for the analysis of EN data using fast Fourier transform (FFT), a process that is often made repeatedly and, if not automated, is quite laborious. This work presents a step-by-step procedure using Excel to perform these calculations, automating the process of obtaining the spectral electrochemical noise resistance, . This routine was used to analyze experimental potential and current noise data recorded for chalcopyrite. The results were comparable to those obtained for the same set of experimental data using Origin® software.

A Gaussian-process-based framework for high-dimensional uncertainty quantification analysis in thermoacoustic instability predictions

When combining a flame model with acoustic tools to predict thermoacoustic instability, uncertainties embedded in the flame model and acoustic system parameters propagate through the thermoacoustic model, inducing variations in calculation results. Therefore, uncertainty quantification (UQ) analysis is essential for delivering a reliable prediction of thermoacoustic instability. The present paper proposes a general, surrogate-based framework to efficiently perform UQ analysis in thermoacoustic instability predictions that (1) can handle large variational ranges and flexible statistical descriptions of the uncertain parameters, (2) takes into account uncertainties from both acoustic system parameters and high-dimensional flame response models (e.g. the finite impulse response model (FIR), the flame describing function (FDF), etc.), (3) quantifies uncertainties in modal frequency and linear growth rate for linear thermoacoustic analysis, or (4) quantifies uncertainties in limit cycle frequency and amplitude for nonlinear thermoacoustic analysis. The framework is built upon Gaussian process (GP) surrogate models. An active learning strategy from the machine learning community has been adopted to significantly enhance the efficiency of GP model training, thus achieving a significant reduction in computational cost. The effectiveness of the proposed UQ framework is demonstrated by two case studies: one linear case with an uncertain FIR model and acoustic system parameters, and one nonlinear case with an uncertain FDF dataset and acoustic system parameters. Compared with reference Monte Carlo simulations, the case studies reveal UQ analyses that are, respectively, 20 and 15 times faster, but nevertheless highly accurate. The proposed GP-based framework also forms an efficient foundation on which to address other types of studies, in which repetitive thermoacoustic calculations are required, such as parametric investigations, sensitivity analyses, nonlinear bifurcation studies and robust design.

A Simple Time-Varying Sensitivity Analysis (TVSA) for Assessment of Temporal Variability of Hydrological Processes

Time-varying sensitivity analysis (TVSA) allows sensitivity in a moving window to be estimated and the time periods in which the specific components of a model can affect its performance to be identified. However, one of the disadvantages of TVSA is its high computational cost, as it estimates sensitivity in a moving window within an analyzed series, performing a series of repetitive calculations. In this article a function to implement a simple TVSA with a low computational cost using regional sensitivity analysis is presented. As an example of its application, an analysis of hydrological model results in daily, monthly, and annual time windows is carried out. The results show that the model allows the time sensitivity of a model with respect to its parameters to be detected, making it a suitable tool for the assessment of temporal variability of processes in models that include time series analysis. In addition, it is observed that the size of the moving window can influence the estimated sensitivity; therefore, analysis of different time windows is recommended.

MinReduct: A new algorithm for computing the shortest reducts

Abstract This paper deals with the problem of computing the shortest reducts of a decision system. The shortest reducts are useful for attribute reduction in classification problems and data size reduction. Unfortunately, finding all the shortest reducts is an NP-hard problem. There are some algorithms reported in the literature to overcome the complexity of computing the shortest reducts. However, most of these algorithms relay on costly operations for candidate evaluation. In this paper, we propose a new algorithm for computing all the shortest reducts; based on binary cumulative operations over a pair-wise comparison matrix, and a fast candidate evaluation process. Binary cumulative operations save computation time by avoiding repetitive calculations. Furthermore, unlike other algorithms reported in the literature, our candidate evaluation process relays on low-cost operations which reduce the runtime in most cases. Our experiments over synthetic and real-world decision systems show that our proposal is faster than state of the art algorithms in most decision systems.

Meet fractal curves with 1C:MathKit

The article presents a methodological approach to studying iterative processes in the school course of geometry, by the example of constructing a Koch snowflake fractal curve and calculating a few characteristics of it. The interactive creative environment 1C:MathKit is chosen to visualize the method discussed. By performing repetitive constructions and algebraic calculations using ICT tools, students acquire a steady skill of work with geometric objects of various levels of complexity, comprehend the possibilities of mathematical interpretation of iterative processes in practice, and learn how to understand the dialectical unity between finite and infinite parameters of flat geometric figures. When students are getting familiar with such contradictory concepts and categories, that replenishes their experience of worldview comprehension of the subject areas they study through the concept of “big ideas”. The latter allows them to take a fresh look at the processes in the world around. The article is a matter of interest to schoolteachers of computer science and mathematics, as well as university scholars who teach the course “Concepts of modern natural sciences”.

Field Programmable Gate Arrays for Enhancing the Speed and Energy Efficiency of Quantum Dynamics Simulations.

We present the first application of field programmable gate arrays (FPGAs) as new, customizable hardware architectures for carrying out fast and energy-efficient quantum dynamics simulations of large chemical/material systems. Instead of tailoring the software to fixed hardware, which is the typical case for writing quantum chemistry code for central processing units (CPUs) and graphics processing units (GPUs), FPGAs allow us to directly customize the underlying hardware (even at the level of specific electrical signals in the circuit) to give a truly optimized computational performance for quantum dynamics calculations. By offloading the most intensive and repetitive calculations onto an FPGA, we show that the computational performance of our real-time electron dynamics calculations can even exceed that of optimized commercial mathematical libraries running on high-performance GPUs. In addition to this impressive computational speedup, we show that FPGAs are immensely energy-efficient and consume 4 times less energy than modern GPU or CPU architectures. These energy savings are a practical and important metric for supercomputing centers (many of which exceed over $1 million in power costs alone), as exascale computing capabilities become more widespread and commonplace. Taken together, the implementation techniques and performance metrics of our study demonstrate that FPGAs could play a promising role in upcoming quantum chemistry and materials science applications, particularly for the acceleration and energy-efficient execution of quantum dynamics calculations.

Parametric Study of Crack Width in Reinforced Concrete Circular Water Tank under Direct Tension as per IS 3370-2009

The design of the Reinforced Concrete (RC) water tank was carried out using the working stress method as per IS 3370 (Part-II):1965 in earlier time, which led to heavily reinforced and thicker concrete sections. IS 3370 (Part II) was revised in 2009, in line of Euro codes. As per revised IS 3370 (Part II) limit state method can also be adopted for the design of RC water retaining structures. While following limit state method for design of RC liquid retaining structures, crack width needs to be less than 0.2 mm. Through control of cracking leakage of water and other durability problems can be avoided. For effective design procedure, the parameters affecting the crack width in RC water tank need to be understood. Pure tension cracks are more harmful to the serviceability of the structures that must be treated carefully. The present study aims to understand various parameters affecting crack width calculations for design of RC circular water tanks. By considering water tanks of different capacities with different aspect ratios, relationship is established to select the appropriate geometrical dimensions of the circular water tank as per the provision of IS 3370 – 2009. Such relationships will be very useful to structural engineers for selecting the appropriate geometry and reinforcement details for the RC circular water tank that would ultimately help to keep the crack width under permissible limit. To carry out parametric study a computer program is developed for limit state design of RC circular water tank to speed up the repetitive calculations and to generate database.

Leafkin—An R package for automated kinematic data analysis of monocot leaves

Growth is one of the most studied plant responses. At the cellular level, plant growth is driven by cell division and cell expansion. A means to quantify these two cellular processes is through kinematic analysis, a methodology that has been developed and perfected over the past decades, with in-depth descriptions of the methodology available. Unfortunately, after performing the lab work, researchers are required to perform time-consuming, repetitive and error-prone calculations. To lower the barrier towards this final step in the analysis and to aid researchers currently applying this technique, we have created leafkin, an R-package to perform all the calculations involved in the kinematic analysis of monocot leaves using only four functions. These functions support leaf elongation rate calculations, fitting of cell length profiles, extraction of fitted cell lengths and execution of kinematic equations. With the leafkin package, kinematic analysis of monocot leaves becomes more accessible than before.

R3MR: Region Growing Based 3D Mesh Reconstruction for Big Data Platform

Visualization is one of the most intuitive and perceptible ways for information representation in the big data era. As an essential part of the visualization, 3D mesh reconstruction is facing great challenges due to its characteristics of quantity, non-structure, and low-accuracy. The traditional 3D mesh reconstruction method has strict theoretical proof and can be used to reconstruct the surface of the complex topological structure for computer rendering and display. However, it is not suitable to handle a large number of point cloud and noise point cloud in a big data platform because the process is inefficient, low-automation and requires massive calculations. To address this issue, we propose a region growing based 3D mesh reconstruction (R3MR) in the big data platform. Firstly, we divide the large data points into three categories: flat point set, high curvature point set, and boundary point set. The errors of topological structure for 3D meshes usually occur in the place with large curvatures and noise points, so the division of high curvature point set is beneficial to solve the low-accuracy problem in 3D mesh reconstruction. Moreover, the flat points can be treated as one kind of point to avoid repetitive calculations because their features are basically the same. Hence, the division of the flat point set is beneficial to solve the problem of quantity and massive calculations. Secondly, our proposal is to start the mesh reconstruction from the flat point set progressively, because it can obtain the outline of the 3D model. In many scenarios, such as autonomous driving, only the overall outline of the model is required. Finally, during the 3D mesh reconstruction, the inner edge adjacency list and optimal selection principle are set to improve the robustness of the whole system. Simulation experiments show that the proposed 3D mesh reconstruction can naturally reflect the detailed features of objects in the big data platform, especially effective for the scattered point cloud.

An Improvement to Exact Reanalysis Algorithm for Local Non-topological Structural Modifications

A new direct reanalysis algorithm for local high-rank structural modifications, based on triangular factorization, has recently been developed. In this work, an improvement is proposed for further reduction of the workload so that the algorithm becomes more efficient and also suitable for low-rank modifications. Compared to the original algorithm, firstly, an alternative formula for updating the triangular factors is derived to avoid repetitive calculations for certain low-rank cases. Secondly, to maximize the efficiency, a combined algorithm is proposed that estimates the workloads of the original and alternative algorithms for each row individually before numerical calculations and selects the one with smaller workload. Numerical experiments show that compared with full factorization, the combined algorithm is significantly more efficient and expected to save up to 75% of execution time in our numerical examples. The new method can be easily implemented and applied to engineering problems, especially to local and step-by-step modification of structures.

Application of Mechanistic Modeling for Gas Lift Optimization: A General Scaling Curve for Variations of Tubing Size to Optimum Gas Injection

Gas Lift is currently held as one of the most prominent method in artificial lift, proudly operated flawlessly in hundreds of oil wells in Indonesia. However, gas lift optimization is still governed by the exhaustive Gas Lift Performance Curves (GLPC). This practice, albeit as established as it should be, does require repetitive calculations to be able to perform in life of well operations. Therefore, a new approach is introduced based on the mechanistic modeling. This research highlights the application of fundamental mechanistic modeling and its derivative, the Flow Pattern Map (FPM) for quick estimation of optimum injection gas rate, accompanied by a novel correction factor to account changing tubing sizes. It is hoped that this approach can be beneficial in developing a multitude of gas lift wells with changing tubing sizes.

A Highly Flexible Architecture for Morphological Gradient Processing Implemented on FPGA

Nowadays, image processing algorithms present essential components of advanced systems in industrial, robotic and medical applications. In most cases, there are high requirements for reduced delays and optimal processing performances. Mathematical morphological operations are one of the most popular and powerful tools used in image processing offering high-level performance operations at low design complexity. However, mathematical morphology is based on repetitive calculations for a wide range of data, resulting in high execution time and memory requirement. Hence, hardware acceleration presents one of the most appropriate solutions to overcome this limitation. In this paper, we propose an efficient hardware architecture aiming to increase performances of morphological gradient computation for grayscale images. The architecture exploits both intra-level and inter-level parallelisms to speed up calculations. In addition, it processes data on stream which decreases memory utilization. The architecture allows extracting the standard edge gradient as well as the external and internal edge gradients at the desired magnitude and thickness level. Unlike most of existing works, the proposed architecture supports reconfigurable shapes and sizes of structuring elements. It is successfully implemented on FPGA. The proposed architecture can process data at a throughput of 356 Mpx/s. Accordingly, a high frame rate for moderate size of structuring elements and high image resolution is achieved.

Dynamic Sensitivity Analysis Based on Sherman–Morrison–Woodbury Formula

The sensitivity analysis plays a significant role in structural optimization, and repetitive calculations are necessary for the analysis procedure. A reanalysis approach of frequency response functions (FRFs) is proposed based on the Sherman–Morrison–Woodbury (SMW) formula. Multiple perturbations are considered as the change of elements in the dynamic stiffness matrix, and the SMW formula is used as an efficient mathematical tool for solving the problem of repetitive calculations. The perturbed FRFs are directly calculated by the SWM formula, and then the sensitivity of the FRFs is obtained by using the finite difference procedure. The basic theory of the proposed method is illustrated by adopting a mass–spring system, which is extended to truss structures. A five-bay truss and a cantilever plate are adopted to verify the method. The lumped mass, the damping, and the cross-sectional area can be regarded as design variables. Results show that the FRF sensitivity is obtained efficiently by using the initial FRFs and parameter perturbations to avoid repeated finite element analyses, and the FRF sensitivity of simultaneously perturbed multiparameters can be determined by using the proposed method.

A simplified skyline-based method for estimating the annual solar energy potential in urban environments

Architects, engineers and urban planners have today at their disposal several tools for simulating the energy yield of photovoltaic systems. These tools are based on mathematical models that perform repetitive calculations to determine the annual irradiation received by solar panels; hence when photovoltaic systems are installed in complex urban environments, the simulations become highly computationally demanding. Here we present a simplified and yet accurate model for the direct calculation of the annual irradiation and energy yield of photovoltaic systems in urban environments. Our model is based on the correlation between the solar radiation components and the shape of the skyline profile. We show how calculations can be simplified by quantifying the skyline using two indicators: the sky view factor and the sun coverage factor. Model performance is evaluated in different climates using measured data from different photovoltaic systems. Results indicate that the proposed model significantly reduces the required computation time while preserving a high estimation accuracy.

Outsourced dynamic provable data possession with batch update for secure cloud storage

With the advent of data outsourcing, how to efficiently verify the integrity of data stored at an untrusted cloud service provider (CSP) has become a significant problem in cloud storage. Provable data possession (PDP) is a model that allows clients or a trusted auditor to verify whether CSP possesses the outsourced data without downloading it. However, this model requires clients to tolerate non-negligible computation burden incurred by frequent verifications in private schemes, and does not provide any security assurances when client or/and auditor are dishonest. Therefore, it cannot be directly transformed into a secure outsourced auditing scheme, where any one of three participants (i.e., CSP, client and auditor) may be dishonest and any two participants may be colluded with each other. In this paper, we propose an outsourced dynamic provable data possession (ODPDP) scheme, which migrates frequent auditing task to an external auditor to reduce clients’ verification overhead, and simultaneously provides log audit mechanism with lower computation burden for clients to prevent from dishonest auditor. In addition, we propose a batch update algorithm that can perform and verify multiple update operations at once, avoiding repetitive calculations and transmissions. Security analysis proves that our scheme is secure in the enhanced threat model, and experimental results show that our scheme achieves high efficiency in terms of computation time and communication cost compared with existing outsourced auditing schemes.

基于能值的陆域受威胁和濒危物种价值估算——以福建省厦门市为例

PDF HTML阅读 XML下载 导出引用 引用提醒 基于能值的陆域受威胁和濒危物种价值估算——以福建省厦门市为例 DOI: 10.5846/stxb201803080461 作者: 作者单位: 中国环境科学研究院,中国环境科学研究院,福建省环境科学研究院,中国环境科学研究院,中国环境科学研究院,生态环境部信息中心,中国环境科学研究院 作者简介: 通讯作者: 中图分类号: 基金项目: 国家重点研发计划项目（2016YFC0500205）；国家自然科学基金青年科学基金项目（41501381）；中国工程院重点咨询项目（2017-ZD-09-01） Emergy-based assessment of threatened and endangered terrestrial species: A case study from Xiamen City, Fujian Province Author: Affiliation: Chinese Research Academy of Environmental Sciences,Chinese Research Academy of Environmental Sciences,Fujian Research Academy of Environmental Sciences,Chinese Research Academy of Environmental Sciences,,, Fund Project: National Key Research and Development Plan 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:开展受威胁和濒危物种价值评估是生物多样性研究的关键问题之一。当前受威胁和濒危物种研究正处于濒危等级界定和保护优先性确定阶段，存在不同保护等级交叉管理、价值评估方法欠缺及重复性计算等多方面问题。利用IUCN濒危等级和中国特有种等级名录确定厦门市不同濒危等级物种数，在此基础上利用能值转换率和修正的中国能值/货币比率对厦门市陆域受威胁和濒危物种价值进行估算。结果显示，通过多途径整理纳入估算的厦门市陆域野生动植物物种数为1444种，其中受威胁和濒危物种数为318种；2015年厦门市物种能值价值约为3.53×1011元，2010年约为3.08×1011元，其中两期受威胁和濒危物种能值价值均占物种总价值的88.31%；中国特有种等级对价值贡献最大达73.25%，其次是IUCN濒危等级达23.24%。研究表明，能值评估法能够客观凸显受威胁和濒危物种价值，研究结果可为生物多样性及物种保育的管理决策提供技术支撑。 Abstract:The implementation of value assessments and analysis of the effectiveness of protection of different types of threatened and endangered species has become a key issue in biodiversity research. Current research into threatened and endangered species focuses on defining the level of endangerment and determining the priority of protection, and it is subject to problems, such as cross-management of different protection levels, lack of value assessment methods, and repetitive calculations. In this study, the number of different endangered species in Xiamen was determined using the IUCN endangered grade and the list of endemic species in China. Based on this, the emergy/GDP ratio was used to estimate the number of threatened and endangered species in Xiamen City. According to the collected, summarized, and analyzed results, there are 1444 terrestrial wildlife species in Xiamen, of which 318 are threatened or endangered. The estimated emergy value of those species was found to be approximately 3.53×1011 yuan in 2015 and about 3.08×1011 yuan in 2010. The emergy value of threatened and endangered species in the two periods accounted for 88.31% of the total value of the species. The endemic species hierarchy in China contributed 73.25% of the emergy value, but the contribution rate of the IUCN endangerment classification was 23.24%. Research indicates that the emergy assessment method can highlight the value of threatened and endangered species in an objective manner. These results can provide technical support for decision-making in biodiversity and species conservation management. 参考文献 相似文献 引证文献

Solving Initial-Value Problem of the First-Order Differential Equation by Euler’s Method using Casio fx 570EX Classwiz Scientific Calculator

Solving numerical methods manually without using a scientific calculator or using scientific calculator traditionally without input the iterative formula into the calculator can be quite tedious and boring due to its repetitive calculations. There is a series of studies discussing the implementation of numerical methods using Excel spread sheet as well as Casio scientific calculators, such as Casio fx-570 MS scientific calculator, Casio fx-570 ES scientific calculator and Casio fx-570 ES plus scientific calculator. Even though Excel spreadsheet made the implementation of numerical methods easier to be understood by the learner of numerical methods, but it is not port classrooms (teaching and learning purposes) and examination hall (evaluation purpose). All the three mentioned models of scientific calculators allow the input of iterative formula but users still need to rein put the new inputs then press CALC bu iterative solutions. The new model of Casio fx FX classwiz scientific calculator offers a spreadsheet ability of 45 rows and 5 columns which made the implementation of the numerical methods much easier if compared to previous models. Hence, in this paper, we solved the initial-value problem (IVP) of the first order ordinary differential equations by the Euler’s method using Casio fx-570 FX class calculator for the classroom and examination purposes.

Analytical representation of nonlinear Froude-Krylov forces for 3-DoF point absorbing wave energy devices

Accurate and computationally efficient mathematical models are fundamental for designing, optimizing, and controlling wave energy converters. Many wave energy devices exhibit significant nonlinear behaviour over their full operational envelope, so nonlinear models may become indispensable.Froude-Krylov nonlinearities are of great importance in point absorbers but, in general, their calculation requires an often unacceptable increase in model complexity/computational time. However, for axisymmetric bodies, it is possible to describe the whole geometry analytically, thereby allowing faster calculation of nonlinear Froude-Krylov forces.In this paper, a convenient parametrization of axisymmetric body geometries is proposed, applicable to devices moving in surge, heave, and pitch. While, in general, Froude-Krylov integrals must be solved numerically, by assuming small pitch angles, it is possible to simplify the problem, and achieve a considerably faster algebraic solution. However, both nonlinear models compute in real-time.The framework presented in the paper offers flexibility in terms of computational and fidelity levels, while still representing important nonlinear phenomena such as parametric pitch instability. Models with lower computational requirements may be more suitable for repetitive calculations, such as real-time control, or long-term power production assessment, while higher fidelity models may be more appropriate for maximum load estimation, or short-term power production capability assessment.

Investigation on the uncertain factors of the elastic–plastic contact characteristics of the planetary roller screw mechanism

The scatter of uncertain factors of the planetary roller screw mechanism, which originated from the manufacturing process, has a significant influence on its serving performance. However, this influence remains insufficiently studied. Further, the elastic–plastic contact analysis of the planetary roller screw mechanism with considering the uncertainties needs large numbers of repetitive calculations by traditional finite element method, which is labor intensive and often impractical. In this paper, an uncertain model of the planetary roller screw mechanism, including parameterization and finite element calculation, is established to conduct the elastic–plastic contact analysis automatically. Besides, the finite element method results can be also obtained automatically with the self-compiled flow program and the secondary development platform using the design of experiment method. Then, a mathematic model is applied to value the influence of the uncertain factors on the contact characteristics. The Pareto graphs are plotted to clearly show this sequence of the percent effects of all the uncertain factors. The present work, for the first time, developed an automatic modeling method for analyzing efficiently the uncertain factors of planetary roller screw mechanism, which is worthy in industrial application.