Local Maximum Entropy Shape Functions Based FE-EFGM Coupling

In this paper, a new method for coupling the finite element method (FEM)and the element-free Galerkin method (EFGM) is proposed for linear elastic and geometrically nonlinear problems using local maximum entropy shape functions in theEFG zone of the problem domain. These shape functions possess a weak Kroneckerdelta property at the boundaries which provides a natural way to couple the EFGand the FE regions as compared to the use of moving least square basis functions.In this new approach, there is no need for interface/transition elements between theEFG and the FE regions or any other special treatment for shape function continuity across the FE-EFG interface. One- and two-dimensional linear elastic and two-dimensional geometrically nonlinear benchmark numerical examples are solved by the new approach to demonstrate the implementation and performance of the current approach

Optimal utilization of frequency ancillary services in modern power systems

The widespread global adoption of wind energy sources has established a significant presence in the existing power grid. However, the massive integration of intermittent wind energy poses forecasting errors, prompting the need for supplementary reserves from conventional energy sources with increased operational expenses and carbon emissions. Hence, to facilitate the seamless operation of large-scale wind-integrated power grids, it is imperative to harness the potential of renewable energy sources and leverage flexible loads to deliver power-balancing services. In this research, dynamic real-time power dispatch strategies have been developed for the Automatic Generation Control (AGC) system to integrate the reserve capacities of conventional generation units and wind power plants and utilize the demand response capabilities of flexible loads for power balancing services. A comprehensive power system grid model was developed in DigSilent PowerFactory software, consisting of coal-based energy systems, wind energy systems, gas turbines, and cold storage units as flexible loads. The study is divided into different case studies to assess the impact of each scenario on system operation in mitigating the forecasting errors of wind power plants. Further, a comparative analysis was performed to illustrate the effectiveness of each case study. The analysis showed that Case Study III, where reserves are provided by coal energy systems and cold storage units, yielded the highest reduction in Positive Regulation (PR) and Negative Regulation (NR) errors, at 89.0% and 94.15%, respectively. Conversely, Case Study IV demonstrated the least reduction in errors, with 67.82% in PR and 78.41% in NR. However, it indicates that reserves can be supplied from wind energy systems and flexible loads without the support of conventional power plants

A novel Multi-permittivity Cylindrical Dielectric Resonator Antenna for Wideband Applications

In this paper, a novel multi-permittivity cylindrical dielectric resonator antenna for wideband application is presented. The multi-permittivity cylinder is formed by combining two different permittivity material sectors in such a way that each sector (with constant permittivity) is 90 degree apart. A direct microstrip line coupling terminated with T-stub at the open end is used to excite the multi-permittivity cylindrical dielectric resonator. The angular position of the multi sector dielectric resonator with respect to the longitudinal axis of the microstrip line and length of the additional strip at the open end of the feeding circuit is key parameters for wideband operation of the antenna. By optimizing all parameters of the proposed antenna, wideband impedance bandwidth of 56% (12.1 GHz - 21.65 GHz) is achieved. The average gain of the antenna throughout the bandwidth is 5.9 dB with good radiation properties in both E-plane and H-plane. A well matched simulation and experimental results show that the antenna is suitable for wideband applications

Enhancing Grid Operation with Electric Vehicle Integration in Automatic Generation Control

Wind energy has been recognized as a clean energy source with significant potential for reducing carbon emissions. However, its inherent variability poses substantial challenges for power system operators due to its unpredictable nature. As a result, there is an increased dependence on conventional generation sources to uphold the power system balance, resulting in elevated operational costs and an upsurge in carbon emissions. Hence, an urgent need exists for alternative solutions that can reduce the burden on traditional generating units and optimize the utilization of reserves from non-fossil fuel technologies. Meanwhile, vehicle-to-grid (V2G) technology integration has emerged as a remedial approach to rectify power capacity shortages during grid operations, enhancing stability and reliability. This research focuses on harnessing electric vehicle (EV) storage capacity to compensate for power deficiencies caused by forecasting errors in large-scale wind energy-based power systems. A real-time dynamic power dispatch strategy is developed for the automatic generation control (AGC) system to integrate EVs and utilize their reserves optimally to reduce reliance on conventional power plants and increase system security. The results obtained from this study emphasize the significant prospects associated with the fusion of EVs and traditional power plants, offering a highly effective solution for mitigating real-time power imbalances in large-scale wind energy-based power systems

A19/B6: A new Lanczos-type algorithm and its implementation

Lanczos-type algorithms are mostly derived using recurrence relationships between formal orthogonal polynomials. Various recurrence relations between these polynomials can be used for this purpose. In this paper, we discuss recurrence relations A 19 and B 6 for the choice Ui ( x ) = P(1)i(x), where Ui is an auxiliary family of polynomials of exact degree i. This leads to new Lanczos-type algorithm A19=B6 that shows superior stability when compared to existing algorithms of the same type. This new algorithm is derived and described here. Computational results obtained with it are compared to those of the most robust algorithms of this type namely A12, A new 12 A5=B10 and A8=B10 on the same test problems. These results are included

Z-TCAM: An SRAM-based Architecture for TCAM

published_or_final_versio

Risk Factors of Diarrhoea in Malnourished Children Under Age of 5 Years

Background: Acute infectious enteritis remains one of the commonest causes of death among infants and children in developing countries. Acute enteritis is defined as a loss of stool consistency with pasty or liquid stools, and/or an increase in stool frequency to more than three stools in 24 hours with or without fever or vomiting. Human survival depends on the secretion and reabsorption of fluid and electrolytes in the intestinal tract. The objective of the study is to evaluate the risk factors of diarrhoea in children under age of 5 years. Methodology: It was an observational study. Study was completed in about six months. Non-probability purposive sampling technique was used. In this study, 270 samples were taken from Diarrheal ward of The Children Hospital Lahore, Pakistan. Results: In this study, out of 270 patients, 58.52% were males and 41.48% were females. 90.37% patients were vaccinated. 54.81% had weaning history. 91.85% patients had feeding history. 29.26% had blood in stool. 96.67% patients were dehydrated. 95.56% patients had loose watery diarrhoea. 62.96% patients used boiled water. 58.52% patients consumed less than half litre of water, 30.00% patients consumed 1 litre of water and 11.48% patients consumed > 1 litre of water. 49.18% patients had proper hygiene. 38.15% mothers of patients were well educated. 40.37% patients had model household condition. 57.41% patients lived in rural area and 42.59% patients lived in urban area. Conclusion: The variation in the level of diarrheal morbidity was well explained by maternal education, income, personal hygiene, refuse disposal system and the effect of health extension programme

Three-dimensional nonlinear micro/meso-mechanical response of the fibre-reinforced polymer composites

A three-dimensional multi-scale computational homogenisation framework is developed for the prediction of nonlinear micro/meso-mechanical response of the fibre-reinforced polymer (FRP) composites. Two dominant damage mechanisms, i.e. matrix elasto-plastic response and fibre–matrix decohesion are considered and modelled using a non-associative pressure dependent paraboloidal yield criterion and cohesive interface elements respectively. A linear-elastic transversely isotropic material model is used to model yarns/fibres within the representative volume element (RVE). A unified approach is used to impose the RVE boundary conditions, which allows convenient switching between linear displacement, uniform traction and periodic boundary conditions. The computational model is implemented within the framework of the hierarchic finite element, which permits the use of arbitrary orders of approximation. Furthermore, the computational framework is designed to take advantage of distributed memory high-performance computing. The accuracy and performance of the computational framework are demonstrated with a variety of numerical examples, including unidirectional FRP composite, a composite comprising a multi-fibre and multi-layer RVE, with randomly generated fibres, and a single layered plain weave textile composite. Results are validated against the reference experimental/numerical results from the literature. The computational framework is also used to study the effect of matrix and fibre–matrix interfaces properties on the homogenised stress–strain responses