Research Article
A Dynamic Frictionless Contact Problem with Adhesion in Thermo-elasto-viscoplasticity
Issue:
Volume 9, Issue 1, April 2024
Pages:
1-13
Received:
25 October 2023
Accepted:
5 December 2023
Published:
5 February 2024
Abstract: The present paper is devoted to the study a dynamic problem describing a frictionless contact between a thermo- elasto-viscoplastic body and an adhesive foundation. The constitutive law includes a temperature effect described by the first order evolution equation. The contact is modelled with a normal compliance condition involving adhesion effect of contact surfaces. The adhesion is modelled with a surface variable, the bonding field whose evolution is described by a first order differential equation. A variational formulation for the problem is given as a system involving the displacement field, the bonding field and the temperature field. The existence and the uniqueness of the weak solution are established. The proof is based on evolution equation with monotone operators, differential equations and fixed point theorem.
Abstract: The present paper is devoted to the study a dynamic problem describing a frictionless contact between a thermo- elasto-viscoplastic body and an adhesive foundation. The constitutive law includes a temperature effect described by the first order evolution equation. The contact is modelled with a normal compliance condition involving adhesion effect ...
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Research Article
Complexity of Some Types of Cyclic Snake Graphs
Basma Mohamed*,
Mohamed Amin
Issue:
Volume 9, Issue 1, March 2024
Pages:
14-22
Received:
5 December 2023
Accepted:
26 December 2023
Published:
20 February 2024
Abstract: The number of spanning trees in graphs (networks) is a crucial invariant, and it is also an important measure of the reliability of a network. Spanning trees are special subgraphs of a graph that have several important properties. First, T must span G, which means it must contain every vertex in graph G, if T is a spanning tree of graph G. T needs to be a subgraph of G, second. Stated differently, any edge present in T needs to be present in G as well. Third, G is the same as T if each edge in T is likewise present in G. In path-finding algorithms like Dijkstra's shortest path algorithm and A* search algorithm, spanning trees play an essential part. In those approaches, spanning trees are computed as component components. Protocols for network routing also take advantage of it. In numerous techniques and applications, minimum spanning trees are highly beneficial. Computer networks, electrical grids, and water networks all frequently use them. They are also utilized in significant algorithms like the min-cut max-flow algorithm and in graph issues like the travelling salesperson problem. In this paper, we use matrix analysis and linear algebra techniques to obtain simple formulas for the number of spanning trees of certain kinds of cyclic snake graphs.
Abstract: The number of spanning trees in graphs (networks) is a crucial invariant, and it is also an important measure of the reliability of a network. Spanning trees are special subgraphs of a graph that have several important properties. First, T must span G, which means it must contain every vertex in graph G, if T is a spanning tree of graph G. T needs ...
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Research Article
On the Performance of Some Estimation Methods in Models with Heteroscedasticity and Autocorrelated Disturbances (A Monte-Carlo Approach)
Olufemi Aderemi Ayansola*,
Adebowale Olusola Adejumo
Issue:
Volume 9, Issue 1, March 2024
Pages:
23-31
Received:
3 December 2023
Accepted:
25 December 2023
Published:
2 April 2024
Abstract: The proliferation of panel data studies has been greatly motivated by the availability of data and capacity for modelling the complexity of human behaviour than a single cross-section or time series data and these led to the rise of challenging methodologies for estimating the data set. It is pertinent that, in practice, panel data are bound to exhibit autocorrelation or heteroscedasticity or both. In view of the fact that the presence of heteroscedasticity and autocorrelated errors in panel data models biases the standard errors and leads to less efficient results. This study deemed it fit to search for estimator that can handle the presence of these twin problems when they co- exists in panel data. Therefore, robust inference in the presence of these problems needs to be simultaneously addressed. The Monte-Carlo simulation method was designed to investigate the finite sample properties of five estimation methods: Between Estimator (BE), Feasible Generalized Least Square (FGLS), Maximum Estimator (ME) and Modified Maximum Estimator (MME), including a new Proposed Estimator (PE) in the simulated data infected with heteroscedasticity and autocorrelated errors. The results of the root mean square error and absolute bias criteria, revealed that Proposed Estimator in the presence of these problems is asymptotically more efficient and consistent than other estimators in the class of the estimators in the study. This is experienced in all combinatorial level of autocorrelated errors in remainder error and fixed heteroscedastic individual effects. For this reason, PE has better performance among other estimators.
Abstract: The proliferation of panel data studies has been greatly motivated by the availability of data and capacity for modelling the complexity of human behaviour than a single cross-section or time series data and these led to the rise of challenging methodologies for estimating the data set. It is pertinent that, in practice, panel data are bound to exh...
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