The rapid transition toward renewable-dominated energy systems has transformed microgrids (MGs) into highly interconnected cyber-physical systems (CPSs), where advanced communication, intelligent control, and inverter-based resources enhance operational flexibility while introducing unprecedented security vulnerabilities. This paper presents a comprehensive review of cyber-physical security and resilience enhancement strategies for MGs by establishing a unified framework that integrates attack scenarios, detection methodologies, and defense mechanisms. The evolving threat landscape is systematically analyzed, including false data injection, denial-of-service, spoofing, replay, and coordinated hybrid attacks targeting communication infrastructures, control layers, and physical power dynamics. Furthermore, existing detection approaches are critically reviewed and categorized into model-based, statistical, artificial intelligence and machine learning-based, physics-informed, and digital twin-enabled frameworks. Particular attention is given to emerging techniques such as deep learning, reinforcement learning, graph neural networks, federated learning, and physics-informed neural networks, highlighting their potential and limitations under nonlinear and uncertain inverter-dominated operating conditions. Defense and resilience strategies are investigated through secure communication, adaptive control, redundancy, attack mitigation, self-healing operation, and recovery-oriented approaches. The review further emphasizes the importance of real-time validation platforms and digital twins for predictive risk assessment and autonomous cyber-physical resilience management. Finally, key research challenges are identified, including scalability, explainability of intelligent security models, realistic hardware-in-the-loop validation, standardized resilience metrics, and the development of integrated physics–AI frameworks for future secure and adaptive MGs.
Abstract This study evaluates concrete in which natural aggregates (NAs) are replaced by electric arc furnace (EAF) slag siderurgical aggregate (SA), with partial cement replacement by silica fume and reinforcement using steel and polypropylene fibers. Mechanical tests (compressive and flexural) at 7, 28, and 90 days and microstructural analyses (SEM/EDS) of the interfacial transition zone (ITZ) were conducted. Optimal mixes containing 8% silica fume and 0.6% fiber volume exhibited an average ITZ thickness reduction from 27.8 ± 3.2 μ m (control) to 15.4 ± 2.1 μ m ( n = 20 fields), and compressive strength gains of up to 21% at 28 days (and up to 30% at 90 days for SA-C-100 mixes). Statistical significance was assessed using one-way ANOVA. These results demonstrate the synergistic effect of SA, silica fume, and fibers on densifying the ITZ and improving flexural toughness, and provide practical recommendations for mass concrete applications.
Introduction and Objectives: Ti-6242 alloy is highly regarded in additive manufacturing due to its excellent thermal resistance. Titanium laser-based additively manufactured components, however, often require post-heat treatments because of their high solidification rate and formation of undesirable phases. The aim of this study is to investigate the effects of annealing heat treatment on the microstructure and mechanical properties of Ti-6242 specimens fabricated by laser powder bed fusion method. Materials and Methods: Annealing heat treatments were conducted at three temperatures of 950, 1005, and 1050 ℃ for holding times of 1, 3, 5, and 7 hours. The resulting microstructure, phase composition, and mechanical properties were characterized using optical and scanning electron microscopy, X-ray diffraction, and shear punch testing. Results: The as-built microstructure consisted of columnar primary β grains with colonies of metastable martensitic α′. Heat treatment led to decomposition of α′ and formation of more stable α and β phases. At 1005 and 1050 °C, the microstructure transformed from columnar to equiaxed, whereas at 950 °C, the columnar structure was retained. Williamson–Hall plots obtained from XRD patterns revealed a reduction in the lattice microstrain of heat treated samples compared with the as-built one. The applied heat treatment, improved both ultimate shear strength and ductility of the samples. The highest ultimate shear strength (761 MPa) and normalized displacement (0.638) were achieved at 1005 °C. Conclusion: Appropriate heat treatment leads to a more stable microstructure, reduction in lattice microstrain, and transformation of the columnar structure to an equiaxed one. This process could simultaneously enhance the ultimate shear strength and ductility compared to the as-built sample.
In (Hashemi and Kapur, 2025), we proposed an algorithm for converting a given Gröbner basis into a Gröbner basis with respect to another term ordering. A recent counterexample due to Heisel and Lauritzen (2025) shows that the presented algorithm is not correct as stated. In this short note, we identify the precise source of the failure, propose a corrected variant of the algorithm and prove that it returns, in finitely many steps, a Gröbner basis with respect to the target term ordering.
