A Form-Finding Method for Branching Structures Based on Dynamic Relaxation

The paper proposes the comparative evaluation of sequential and parallel methods for identifying measurements of nearby objects. The problem statement is choosing the method for identifying measurements of nearby objects. The decision rule for identifying the results of radio engineering measurements of the coordinates of objects is obtained. The decision rules for identifying objects by sequential and parallel methods under various conditions are obtained. The cases of absence and presence of false marks from nearby objects are considered. The task of choosing serial or parallel methods for identifying measurements from nearby objects was set. The comparative evaluation of serial and parallel measurement identification methods is provided. As an indicator of the effectiveness of the methods, we chosen the probability of identification error. We estimated the probability of identification error depending on the relative average distance between objects in the absence of false measurements and in their presence. It is determined that the probability of an identification error when using the parallel identification method is less than when using the sequential identification method. This gain increases as the average relative distance between objects decreases. Based on the analysis of methods for identifying measurement results, it was found that the most appropriate identification method is a parallel method for identifying measurement results. The efficiency of the method increases with decreasing relative average distance between objects. Keywords— evaluation, sequential method, parallel Method, identification, measurement, nearby object, hypothesis

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“…The likelihood function is calculated for each trajectory's fork. The main disadvantage of the [14] is the significant computational complexity.…”

Section: Literature Review and Problem Statementmentioning

confidence: 99%

Comparative Evaluation of Sequential and Parallel Methods for Identifying Measurements of Nearby Objects

Khudov¹,

Lohachov²,

Karlov³

et al. 2022

IJETAE

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“…Al. [6] note that another non-Bayesian approach could be the branching method. The essence of this method is as follows.…”

Section: Literature Review and Problem Statementmentioning

confidence: 99%

“…The methods [5][6] can be classified as non-Bayesian sequential strobe methods. These methods have proved to be effective when tracking a small number of objects, provided there is a large distance between objects, a low level of interference (a small number of false marks), and high thresholds in primary processing devices.…”

Section: Literature Review and Problem Statementmentioning

confidence: 99%

“…These methods have proved to be effective when tracking a small number of objects, provided there is a large distance between objects, a low level of interference (a small number of false marks), and high thresholds in primary processing devices. The methods [5][6] work at distance of up to 250-300 km with a distance between objects of 1-2 km.…”

Section: Literature Review and Problem Statementmentioning

confidence: 99%

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The Method for Identification of Radars Measurements of Nearby Objects Tracking

Khudov¹,

Рубан²,

Pievtsov³

et al. 2021

IJETAE

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— The paper proposes the method for identification of radars measurements of nearby objects tracking. The method for identification of radars measurements of nearby objects tracking, in contrast to the known ones, assumes the next. Solving the optimization problem of searching for a hypothesis of joint identification of objects and measurements. The solution is optimal according to Bayes' criterion. The solution of the optimization problem of joint identification of objects and measurements is reduced to the assignment problem with the subsequent choice of a hypothesis. The choice of hypothesis is presented in the form of an identification matrix. The presence of background objects in the viewing area is taken into account. The procedure for enumerating hypotheses is rather cumbersome even with a small number of objects (10-12 objects). Therefore, the subject of further research is to find ways to reduce the computational costs of solving the optimization problem. Keywords— method, identification, radar, measurement, nearby object, tracking, hypothesis

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“…In the field of the numerical creation of reasonable forms for branching structure, scholars also focus on two directions: form-finding and structural optimization techniques. Typical form-finding methods include the graphic statics [35], the inverted hanging recursive method [12,36], the force density method [37], the element-clustered method [38,39], the quasi-mechanism method [40], and others. The methods based on optimization techniques include bi-directional evolutionary structural optimization (BESO) [41], extended evolutionary structural optimization (EESO) [42], sensitivity analysis [43], and others.…”

Section: Introductionmentioning

confidence: 99%

An Integrated Shape Optimization Method for Hybrid Structure Consisting of Branch and Free-Form Surface

Wang,

Cui,

Jiang

2023

Applied Sciences

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Branching and free-form structures are widely used in large-span buildings. Their shapes are the main factors that affect their mechanical performances. Many studies have been carried out on the morphology of single structural systems, but less on hybrid structures. However, both of them often appear in the same building. In order to reflect the cooperative bearing of substructures in the optimization process of branch-supported free-form surface structures, this paper proposes a holistic shape optimization method. The proposed method extracts design variables based on the structural modeling process, and uses the coordinates in the parametric domain to realize a mathematical description of the positional relationship between substructures. Then, the sensitivity analysis method is used to adjust the position of design variables to reduce the overall strain energy, realizing the integrated shape optimization of this hybrid structure. The effectiveness of the method is validated through several numerical examples. The results show that the overall stiffness of the optimized structure has been significantly improved, and the process of integrated optimization is more convenient. Furthermore, the way of adjusting design variables directly affects the shape and mechanical performance of the optimized structure. This feature serves as a valuable design tool that can provide multiple feasible solutions for architectural and structural design.

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A Form-Finding Method for Branching Structures Based on Dynamic Relaxation

Cited by 4 publications

References 13 publications

Comparative Evaluation of Sequential and Parallel Methods for Identifying Measurements of Nearby Objects

Comparative Evaluation of Sequential and Parallel Methods for Identifying Measurements of Nearby Objects

The Method for Identification of Radars Measurements of Nearby Objects Tracking

An Integrated Shape Optimization Method for Hybrid Structure Consisting of Branch and Free-Form Surface

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