Calculation Time Research Articles

Reduction of computational time for structural optimisation and application to optimisation of structures

ABSTRACT Structural optimization method takes more computational time because it performs iterative calculation to obtain the optimal value. In particular, the larger the number of elements, the higher the accuracy of the solution, which takes more time. In this study, the superelement method and the static condensation method were used to solve this computational time problem. However, since the general static condensation method generates many equations during the condensation process, the computational time was shortened by developing a multi-step static condensation method that makes the superelement the minimum amount of calculation. In addition, in the optimization process, the calculated stiffness matrix of superelements was reused to shorten the iterative calculation time. In this research model, through the developed method, the computational time was reduced to 39% in the first calculation process and to 60% in the second calculation process to convergence. Therefore, we propose this method as a new optimization process.

New Approach: Tabular Fuzzy Arithmetic of the LR Type by Jomatopfe

This paper presents a fuzzy approach of LR types, also called LR-type tabular fuzzy arithmetic capable of handling or computing simultaneously the kernels and supports of trapezoidal fuzzy numbers, instead of doing it separately (Advantage of this approach) in order to minimize the tedious steps of alpha-cut based approaches. On the theoretical level, the aim of this article is to explain in a concise and clear manner some basic concepts of fuzzy logic that seem to continue to complicate authors and readers (researchers) in this field, given the important place of this theory in Artificial Intelligence today. Some user interfaces have been created in this article, with the python language, in order to automatically calculate certain results; and especially to minimize the calculation time, in particular of membership degrees, kernels and supports. Trapezoidal fuzzy numbers are transformed into LR form in order to allow a comparative study between the alpha-cut approach with the Jomatopfe LR-type tabular fuzzy arithmetic presented in this paper. We successfully demonstrated the transition from the trapezoidal fuzzy form to the LR type form and vice versa. After a comparative study between the alpha-cut approach and the tabular fuzzy arithmetic of the LR type, Jomatopfe's LR type arithmetic significantly reduced the complexity of the calculation processes compared to classical methods, which require distinct steps for each element. This fuzzy tabular altimetry is not to be confused with other fuzzy tables operations on membership degrees.

Developing surrogate models for the early-stage design of residential blocks using graph neural networks

Abstract Building simulation based on physical modeling is commonly adopted for performance prediction, but the high time costs hinder its application in the early design stage of buildings. Data-driven surrogate models have been proposed as a means to replicate computationally expensive simulation models. However, existing surrogate models for sustainable residential block design are limited in scope, focusing either on individual buildings or on specific cases within multi-block projects. This study leverages graph neural networks to develop optimal surrogate models incorporating inter-building effects to predict multiple indicators of sustainable performance for residential blocks at a region level. A graph schema is proposed to represent the general geometric features and relations among buildings in residential block design. A regional dataset is generated for model training and testing, using real residential zones in Hong Kong. The surrogate models are developed and evaluated, using two kinds of architectures (individual architectures for specific indicators and an integrative architecture) and three different neural networks (graph attention network (GAT), graph convolutional network, and artificial neural network). The results showed that the surrogate models using the individual architectures and GAT outperform the models using other architectures and neural networks. These surrogate models achieve a high prediction accuracy with CV(RMSE)s of 11.79%, 7.63%, and 8.00% in terms of energy consumption, indoor thermal comfort, and daylighting, respectively, on the regional test set. Moreover, they enable a significant acceleration of the performance evaluation, reducing the calculation time from 6.346 min to 1.565 ms (243,297 times) per case compared to physics-based simulations.

Numerical testing method and mechanical property evaluation of large particle size asphalt mixture.

The large particle size asphalt mixture with nominal maximum aggregate size 53 mm(LSAM-50) has good technical and economic performance and will become an effective technical way to build a full-thick long-life asphalt pavement with Chinese characteristics. In order to reveal the mechanical properties and influencing factors of LSAM-50 in depth, a numerical test method for the mechanical properties of the large particle size LSAM-50 asphalt mixture was developed, and a reasonable specimen size for LSAM-50 performance test was proposed by combining the numerical test and the indoor test. The results show that: LSAM-50 numerical test conditions are the calculation time step 10-3 s/step, the loading rate is 2 mm/min (uniaxial compression numerical test) and 50 mm/min (splitting numerical test) when LSAM-50 numerical experiment calculation rate and numerical experiment accuracy are better; after the size of the specimen reaches 200×160mm, the influence of the size effect is eliminated. The reasonable specimen size of LSAM-50 is Φ200mm×h160mm; the LSAM-50 numerical test method and the indoor test have low error Less than 10%.

Acceleration of Large‐Scale Power System Analysis Including Phase‐Domain Rotating Machine Models Using Partial Refactorization in Electromagnetic Transient Analysis

ABSTRACTOne of the models for rotating machines, such as synchronous machines and induction machines, is the phase‐domain model, which is characterized by formulating the circuit equations of the rotating machine in the phase domain and solving them simultaneously with the external system to which the rotating machine is connected. Although this model has excellent numerical stability and calculation accuracy, it requires refactorization of the subcircuit that includes the rotating machine at each calculation time step, which degrades the calculation speed. This paper describes the results of an attempt to improve the calculation speed when using the phase‐domain model by using partial refactorization, which makes the refactorization process more efficient.

Development of an algorithm for automated calculation of the technical condition index of 110 kV gas-insulated circuit breakers

RELEVANCE of the study is to develop an algorithm for automated calculation of the technical condition index (TCI) for 110 kV gas-insulated circuit breakers according to the TCI calculation method developed by the Ministry of Energy of Russia. THE PURPOSE. To analyze the errors arising at calculation of TCI. To consider the problems arising at calculation of TCI and to offer ways of the decision of the given problem. To perform manual calculation of the technical condition index of the VEB-110 gas-insulated circuit breaker according to the approved methodology. Develop a working version of the algorithm for automated calculation of the technical condition index (TCI) for 110 kV gas-insulated circuit breakers according to the TCI calculation methodology developed by the Ministry of Energy of Russia. To carry out TCI calculation of VEB-110 circuit breaker with the help of the created algorithm. METHODS. The method of modeling of the TCI calculation method implemented in the Delphi7 programming environment was used to solve the task. RESULTS. The article describes the relevance of the topic, considers the peculiarities of TCI calculation for different types of circuit breakers. Manual TCI calculation and TCI calculation with the help of the developed algorithm for VEB-110 gas-insulated circuit breaker are made, the comparative analysis of the calculation results is carried out. In this paper the working algorithm of automated calculation of ITS for gas-insulated circuit breakers of VEB-110 type is modeled. CONCLUSION. The use of the algorithm of the automated calculation of TCI gives an opportunity to reduce (practically to exclude) the errors arising at manual calculation. Also the calculation time is greatly reduced and there is a possibility of more operative obtaining of data on the state of circuit breakers. The developed algorithm recommends the control action on the equipment based on its condition, thus facilitating the planning of repairs, maintenance of equipment. Based on the calculated TCI value, the circuit breakers are ranked according to the priority of inclusion in the maintenance plan.

Novelty in Modifing the Weibull Distribution by Using Fast Fourier Transformation for Wind Energy Assessment

Wind energy considered to be the most recent source of power that inexpensive, non-depleting, also simple for a variety of users to capture and employ. The location of Ali El Gharbi is one of the preferable sites for clean energy production in Iraq, however as there is a lack of information about the power exploration potentials at this place, more related researches and studies for wind power wind are fundamental. An accurate comprehension for the behaviour of the wind is required for the preparation and operation of every wind conversions to energy project. The study is aimed at investigating the novelty in modifying the Weibull distribution by means of the Fast Fourier Transform with the purpose of estimate the possibility of wind energy harvesting in Ali El-Gharbi area of Ammarah, Iraq. The results from the modification of the Weibull distribution was a reduction in the value of the shape parameter for the new Weibull distribution which will lead to a smoother curve, the reduction of the shape parameter from about 5 to 1 implies a shift from the scenario where failures occur randomly and independently of the parameter. A second benefit of the modification was a reduction the time for calculation the Weibull parameters and PDF’s with increasing the accuracy. As an outcome of the wind speed data values were recorded at a 10-minutes interval for a year starting from December 2014 till December 2015 at heights of 10, 30, and 50 meters. Subsequently, the datasets were examined by means of the Weibull probability distribution function (WPD) to assess wind energy production, and for the spectral part of the analysis was conducted by employing the Fast-Fourier-Transform. According to the spectral analysis for the data, the average yearly wind speed at 50 m was 6.134 m/sec, whereas highest wind speed recorded there during the day were about 17.011 , and the peak wind speed was 226236.282 m/sec/12hour at a frequency(2 Hz) at that height of 50 m all through night hours. And for lowest values of wind speed was about 115863.7 m/sec/12hour for the (2 Hz) frequency at that height throughout night hours. The blowing of wind was more rapidly in the morning than it was at night periods. While the main wind directions in the region were from the north-northwest and west-northwest.

Evaluation of dose calculation method with a combination of Monte Carlo method and removal-diffusion equation in heterogeneous geometry for boron neutron capture therapy.

Clinical research in boron neutron capture therapy (BNCT) has been conducted worldwide. Currently, the Monte Carlo (MC) method is the only dose calculation algorithm implemented in the treatment planning system for the clinical treatment of BNCT. We previously developed the MC-RD calculation method, which combines the MC method and the removal-diffusion (RD) equation, for fast dose calculation in BNCT. This study aimed to verify the partial-MC-RD calculation method, which utilizes the MC-RD calculation method for a portion of the entire neutron energy range, in terms of calculation accuracy and time as the dose calculation method. We applied the partial-MC-RD calculation method to calculate the total dose for head phantom, comprising soft tissue, brain tissue, and bone. The calculation time and accuracy were evaluated based on the full-MC method. Our accuracy verifications indicated that the partial-MC-RD calculation was mostly comparable with full-MC calculation in the accuracy. However, the assumptions and approximation used in the RD calculation mainly occurred the discrepancy from the full-MC calculation result. Additionally, the partial-MC-RD calculation reduced the time required to approximately 45% for the irradiation to the top and cheek region of head phantom, compared to the full-MC calculation. In conclusion, the MC-RD calculation method can be the basis of a fast dose calculation method in BNCT.

Cholesterol-ester prevents lipoprotein core from solidifying: Molecular dynamics simulation.

As an important part of lipid metabolism the liver produces large particles called very low density lipoproteins, filled mostly with triglyceride and cholesterol esters mixture. A large percentage of the mixture composition components has a melting point above physiological temperature. Thus solid cluster formation or phase transition could be expected. Though various single-component triglyceride systems are well researched both experimentally and by various simulation techniques, to our best knowledge, tripalmitin/cholesteryl-palmitate binary mixture was not yet studied. We study tripalmitin single component system, as well as 20%-80% and 50%-50% binary mixtures of cholesteryl-palmitate and tripalmitin using molecular dynamics approach. All systems are studied at the pressure of 1 atm and the physiological temperature of 310 K, which is below the melting points of both tripalmitin and cholesteryl-palmitate. Our results show that at the time of 1000 ns, there is still no phase transition, but there is a noticeable tendency to intermolecular organizing and early signs of clustering. We check fatty acid arrangements of tripalmitin molecules in both single component system and binary mixtures with two different percentages of cholesteryl-palmitate mixed in. Our results show that the more cholesteryl-palmitate molecules are in the mixture the smaller number of tripalmitin molecules transitions to 'a fork/chair' configuration during the same calculation time. Calculated angle distributions between fatty acid chains of tripalmitin molecules confirm that. Thus, our simulation results suggest slowing down or interfering effect of cholesteryl-palmitate on the crystallizing process of the binary mixture.

Evaluating and extending speedup techniques for optimal crossing minimization in layered graph drawings.

A layered graph is an important category of graph in which every node is assigned to a layer, and layers are drawn as parallel or radial lines. They are commonly used to display temporal data or hierarchical graphs. Previous research has demonstrated that minimizing edge crossings is the most important criterion to consider when looking to improve the readability of such graphs. While heuristic approaches exist for crossing minimization, we are interested in optimal approaches to the problem that prioritize human readability over computational scalability. We aim to improve the usefulness and applicability of such optimal methods by understanding and improving their scalability to larger graphs. This paper categorizes and evaluates the state-of-the-art linear programming formulations for exact crossing minimization and describes nine new and existing techniques that could plausibly accelerate the optimization algorithm. Through a computational evaluation, we explore each technique's effect on calculation time and how the techniques assist or inhibit one another, allowing researchers and practitioners to adapt them to the characteristics of their graphs. Our best-performing techniques yielded a median improvement of 2.5-17× depending on the solver used, giving us the capability to create optimal layouts faster and for larger graphs. We provide an open-source implementation of our methodology in Python, where users can pick which combination of techniques to enable according to their use case. A free copy of this paper and all supplemental materials, datasets used, and source code are available at https://osf.io/5vq79.

A Novel Map Matching Method Based on Improved Hidden Markov and Conditional Random Fields Model

ABSTRACT Aiming at the inherent “labeling bias” problem of Hidden Markov Models (HMMs) in the process of low-frequency sampling rate GPS trajectory map matching, this paper proposes a map matching method that combines HMMs and Conditional Random Field Models (CRFs). Various features including vehicle driving direction, direction change between candidate roads, shortest path, and spatial localization accuracy of trajectory points are integrated to optimize the state transfer process in the HMM model. The Viterbi algorithm was then employed to calculate the joint probability values of all candidate paths and the path with maximum probability value was selected as the matching path. The proposed map matching method was validated using publicly available Global Positioning System (GPS) vehicle trajectories from Guangzhou, Dongguan, and field-collected vehicle trajectory data from Ganzhou, China. The results demonstrated that the proposed method achieves high matching accuracy while maintaining efficient matching efficiency. The percentage of correct matching of GPS sampling points remains above 95%, and the average calculation time for each candidate road segment is kept within 50 ms. These advancements can greatly benefit location-based services that rely on map matching technology.

Investigation on the reliability calculation method of gravity dam based on CNN-LSTM and Monte Carlo method

ABSTRACT To improve the calculation accuracy of the Monte Carlo (MC) method and reduce the calculation time. Firstly, CNN and LSTM deep learning networks are introduced for designing nonlinear dynamic systems simulating dam stress. Then, spatial feature mining and sequence information extraction of nonlinear data of dam stress are carried out respectively, and a combined prediction model of dam stress depth (DS-FEM-CNN-LSTM) is proposed. Secondly, to solve the problem of a long time and heavy workload for the MC method to calculate a single sample point, the DOE test method is used to design the sample points. The weight factor and the distance to the failure surface are used as screening criteria. The reliability calculation method of the gravity dam (DS-FEM-CNN-LSTM-MC) is established. Finally, numerical results show that the proposed DS-FEM-CNN-LSTM-MC method performs better than the existing methods in terms of computational time consumption and accuracy.

Numerical simulation for low permeability reservoirs based on POD-TPWL method

ABSTRACT Numerical simulation is a key technology to improve the development efficiency of low-permeability and tight oil reservoirs. In this paper, in order to improve the speed of reservoir numerical simulation, a complex two phase flow model was presented considering the threshold pressure gradient and stress sensitivity, and the application process of POD-TPWL method is derived and summarized. Furthermore, the computational accuracy and efficiency based on the POD-TPWL method was investigated. The simulation time and error of production data of POD-TPWL method and other methods were statistically analyzed and compared. The results reveal that the POD-TPWL method not only ensures accuracy and stability but also significantly improves computational speed. The calculation time of the full order model is 487 s, the calculation time of the POD method is 284 s, and the calculation time of the POD-TPWL method is 122 s. The calculation speed of the POD-TPWL method is almost 4 times faster than the full order model, the POD-TPWL method is more efficient in the numerical simulation of low permeability nonlinear seepage.

Self‐Triggered Distributed Model Predictive Control via Path Parameter Synchronization

ABSTRACTThis paper investigates the formation tracking problem for multiple mobile robots via self‐triggered distributed model predictive control (DMPC) strategy and path‐parameter communication manner. To ensure the robots follow the desired formation structure along the predefined paths, we establish appropriate tracking error models that form a multi‐agent system. At triggered instants, each agent exchanges a sequence of path parameters representing the robot's position, resolves the optimal control problem (OCP) and subsequently determines the open‐loop phase. Different from existing coordination methodology, the proposed scheme exhibits two essential merits in environments where resources are particularly limited: (1) The tracking task of robots is achieved by designing an appropriate OCP under the DMPC scheme, and the formation task of robots is achieved through the synchronization of one‐dimensional path parameters instead of the multi‐dimensional state information, which demands less communication load; (2) The incorporation of the self‐triggered scheduler acquires the desired control performance with less calculation time, thereby relieving the computational and communication costs. Sufficient conditions are proposed to guarantee the recursive feasibility of the OCP and the closed‐loop stability. Simulation results illustrate the validity of the proposed control algorithm.

Entropy of difference works similarly to permutation entropy for the assessment of anesthesia and sleep EEG despite the lower computational effort.

EEG monitoring during anesthesia or for diagnosing sleep disorders is a common standard. Different approaches for measuring the important information of this biosignal are used. The most often and efficient one for entropic parameters is permutation entropy as it can distinguish the vigilance states in the different settings. Due to high calculation times, it has mostly been used for low orders, although it shows good results even for higher orders. Entropy of difference has a similar way of extracting information from the EEG as permutation entropy. Both parameters and different algorithms for encoding the associated patterns in the signal are described. The runtimes of both entropic measures are compared, not only for the needed encoding but also for calculating the value itself. The mutual information that both parameters extract is measured with the AUC for a linear discriminant analysis classifier. Entropy of difference shows a smaller calculation time than permutation entropy. The reduction is much larger for higher orders, some of them can even only be computed with the entropy of difference. The distinguishing of the vigilance states between both measures is similar as the AUC values for the classification do not differ significantly. As the runtimes for the entropy of difference are smaller than for the permutation entropy, even though the performance stays the same, we state the entropy of difference could be a useful method for analyzing EEG data. Higher orders of entropic features may also be investigated better and more easily.

CALCULATING THE INFLOW TO TUYEN QUANG RESERVOIR BY HEC-HMS MODEL USING DIFFERENT LULC MAPS AND BASIN DIVISIONS

For mathematical models in general and hydrological models in particular, the accuracy of input data and the detail in using that data greatly affect the calculation results. For each specific requirement, how detailed the input data needed to ensure the accuracy while still meeting the requirements of real-time tasks is an issue that needs to be surveyed and researched. In this paper, the authors use HEC-HMS model with two types of LULC (Land use-Land cover) maps and different ratios of basin division to calculate Tuyen Quang reservoir inflow for August 2023 and July 2024 floods. The results show that the Jaxa LULC map gives better results than the Microsoft and Esri LULC map and divides Tuyen Quang basin into 29 sub-basins is more suitable than 09 and 49 sub-basins. From there, the influence of LULC map as well as the ratio of basin division on the accuracy and calculation time are commented.

Rapid prediction model of terahertz transmission in hypersonic plasma sheath under different flight speeds for different vehicle types

Abstract This work clarifies the systematic relationship and difference mechanism between flight speed, plasma sheath and terahertz transmission under different vehicle types by joint simulation model of hypersonic plasma flow and improved scattering matrix method. Significant differences in plasma sheath and terahertz transmission characteristics are observed in different vehicle types. Radio Attenuation Measurement C (RAM C) vehicle has a larger collision frequency and sheath thickness, resulting in higher terahertz attenuation than Hypersonic International Flight Research Experimentation (HIFiRE) vehicle. With the increase of flight speed, electron density, collision frequency and terahertz attenuation of the two different types of vehicles all show a significant increase, and the sheath thickness shows an opposite trend. However, the impact of flight speed on HIFiRE vehicle is much smaller than that on RAM C vehicle, which means that flight parameters have higher control accuracy for RAM C vehicle. On this basis, the systematic relationship between plasma sheath distribution and flight speed is further determined, and a rapid prediction model for terahertz transmission attenuation of different types of vehicle is developed based on a large amount of plasma sheath data. The rapid prediction model greatly reduces the calculation time and resources compared with traditional numerical methods, and its related prediction coefficients show significant differences on different vehicle types.

Modeling and design of linear induction motors using a reluctance network method

The methods of modeling and designing of Linear Induction Motors (LIM) are considered as the most important element of competition among manufacturers of this category of motors. Although, the majority of manufacturers employ finite element-based methods to achieve more accurate design. However, these methods still suffer from a longer computation time. Moreover, the Finite Element Method (FEM) require very significant and expensive computing equipment. Researchers have been created a number of analysis techniques to solve this conundrum and expedite computation, but the accuracy of the findings is still below acceptable bounds. In this work, we propose the modeling and design of the LIM using the Reluctance Network Method (RNM) in order to reduce the calculation time and improve the accuracy of the results. sing the COMSOL Multiphysics software, a comparative analysis with the FEM is introduced in order to verify the outcomes of the previous one. Compared to finite elements, the results enabled a computation time reduction of 27 hours. The proposed RNM-based methodology demonstrates the potential to enhance the speed and accuracy of LIM modeling and design, which could provide a competitive advantage for manufacturers in the industry. The enhanced analysis provides a more comprehensive interpretation of the results, highlighting both the technical achievements and practical implications of using RNM for LIM modeling. The key takeaway is that while RNM shows slightly lower accuracy compared to FEM (87% vs 88%), it offers a significant advantage in computation time (77% reduction) while maintaining acceptable accuracy for practical applications.

Dynamic Allocation Strategy for the Car Rental Industry with Multiple Rental Channels

This paper addresses the rental car allocation problem in which a car rental company rents its cars through various channels. This study proposes a constrained model based on the nested-allocation structure to allocate the rental cars to the car rental system to maximize the total rental revenues. The nested allocation strategy uses the concept of whether the number of sales accumulated to a certain level exceeds a threshold corresponding to that sharer. This approach allows the quota of low-profit channels to support the leasing demand of high-profit channels at any time, thereby increasing revenue. The proposed model can dynamically adjust the nested strategy as the dynamic programming model. However, it avoids the issues of ample storage space and long calculation time commonly encountered by the dynamic programming model. Computational results show that the proposed nested approach substantially outperforms the traditional exclusive allocation approach.

Map-Matching Algorithm Based on Hidden Markov and Constraint Value Pruning

Map matching is the process of matching global positioning system (GPS) trajectory data with map data. Its purpose is to determine the actual route of the moving object. Because of factors such as positioning devices and the environment, the GPS trajectory data obtained may not be accurate. In location-based services, map matching can be used to address the accuracy and reliability issues of GPS location data. There are currently many map-matching algorithms, for example, spatio-temporal-based (STD) matching algorithm, improved interactive voting-based map-matching (IIVMM) algorithm, and turning-point-based (TPB) offline map-matching algorithm, but existing algorithms have some shortcomings, such as low matching accuracy on complex roads or low sampling rates, and routing calculation time bottlenecks. Therefore, this paper proposes a fast matching algorithm based on constrained value pruning that is suitable for complex roads. The algorithm considers the multi-directional features within the road and uses secondary calculations to determine candidate points, improving the accuracy of candidate point selection. Additionally, two pruning strategies based on constrained values are introduced to reduce the majority of the routing calculation process and improve the matching efficiency. Finally, comparative experiments are conducted on a real trajectory dataset. The results show that, compared with STD, IIVMM, and TPB algorithms, the algorithm accuracy is improved by about 2% to 4%, and the running time is reduced by about 30%.