Defence Research and Development Laboratory

Abstract Non-destructive evaluation techniques are increasingly applied to estimate the buckling load of shell structures without inducing failure. This study employs the force-stiffness (F-s) method to evaluate the buckling load of oblate ellipsoidal shells subjected to external pressure. Experiments on five steel shells with comparable R/t ratios are conducted, recording pressure, strains, and crown deflections up to failure. Using deflection data up to 80% of the buckling load, the F-s technique predicts buckling with ~90% accuracy, while incorporating crown strain data improves accuracy to ~95%. All shells fail within a pressure range of 2.7-3.4 MPa. The method is further validated on 3D-printed aluminum shells, showing promising consistency, though additional testing is required to refine accuracy. Finally, the F-s approach is demonstrated for real-time prediction of a large-scale shell, nearly three times larger than the experimental models, highlighting its scalability and potential for structural applications.

The essence and main characteristics of electronic attack (EA) are examined, as well as its place in the electronic warfare (EW). The main elements of EA are examined, such as jamming, spoofing and electronic neutralization of enemy radio devices. A definition and the main terms for software-defined radio (SDR) are given. The architecture and main characteristics of SDR are examined. A prototype of SDR is made and demonstrated for the purpose of proving the concept.

In solid propellant rocket motors, the design of grain port geometry primarily dictates the motor ballistic performance. The flexibility offered by the spatial variation of the port shape on motor performance is often discounted due to the requirement of complex mandrel shapes along with their associated manufacturing issues coupled with propellant processing constraints. Literature data indicate improvement in motor volumetric loading and stability by planned distribution of burn surface area along motor length. This paper deals with the realization and testing of a subscale motor with central finocyl-based grain geometry. A novel method of casting complex grain shapes in solid rocket motors using the wax mandrel technique is discussed. The wax mandrel preparation, propellant casting procedure, and wax mandrel removal setup are elaborated. Static testing results of the subscale motor with central finocyl port geometry are also presented as proof-of-concept. This work has demonstrated the feasibility of realizing solid rocket motor grains using the wax mandrel technique, which further enables realization of complex grain designs necessary to meet various mission requirements.

Good practices in artificial intelligence (AI) model validation are key for achieving trustworthy AI. Within the cancer imaging domain, attracting the attention of clinical and technical AI enthusiasts, this work discusses current gaps in AI validation strategies, examining existing practices that are common or variable across technical groups (TGs) and clinical groups (CGs). The work is based on a set of structured questions encompassing several AI validation topics, addressed to professionals working in AI for medical imaging. A total of 49 responses were obtained and analysed to identify trends and patterns. While TGs valued transparency and traceability the most, CGs pointed out the importance of explainability. Among the topics where TGs may benefit from further exposure are stability and robustness checks, and mitigation of fairness issues. On the other hand, CGs seemed more reluctant towards synthetic data for validation and would benefit from exposure to cross-validation techniques, or segmentation metrics. Topics emerging from the open questions were utility, capability, adoption and trustworthiness. These findings on current trends in AI validation strategies may guide the creation of guidelines necessary for training the next generation of professionals working with AI in healthcare and contribute to bridging any technical-clinical gap in AI validation. RELEVANCE STATEMENT: This study recognised current gaps in understanding and applying AI validation strategies in cancer imaging and helped promote trust and adoption for interdisciplinary teams of technical and clinical researchers. KEY POINTS: Clinical and technical researchers emphasise interpretability, externalvalidation with diverse data, and biasawarenessin AI validation for cancer imaging. In cancer imaging AI research, clinical researchers prioritise explainability, whiletechnical researchers focus ontransparency and traceability, and see potential insynthetic datasets. Researchers advocate for greater homogenisation of AI validation practices in cancer imaging.

Most modern spacecraft systems rely on pyrotechnically actuated separation mechanisms to achieve stage separation events. These systems are associated with a very high level of pyro shock, which is detrimental to many sensors and delicate electronic packages. The current research focuses on designing and implementing a system that minimizes pyro shock levels during separation events. This study investigates developing and validating a low-shock gas generator system for stage separation mechanisms. The proposed gas generator cartridge has been used in stage separation hardware, and the shock levels were compared to that of the pyro cartridge actuated stage separation event. The shock levels and the shock response spectrum for gas generator and pyro cartridges were plotted and compared. The gas generator cartridge has demonstrated a significant drop in the shock levels. This comprehensive methodology with stage separation hardware using a gas generator cartridge demonstrates the system's effectiveness in reducing shock levels, ensuring improved performance, and repeatability in practical applications. The results highlight the potential of the proposed approach to enhance operational efficiency by lowering shock levels to a significant order in stage separation mechanisms in aerospace systems.

Digital marketing is rapidly changing, with new methods using technology to engage consumers replacing old ones. This research study covers cutting-edge marketing tactics that can improve consumer engagement, including artificial intelligence in marketing, data analytics for personalised marketing, and marketing research and practice. This study examines new marketing applications to determine if they improve customer interactions and business success. The paper reviews relevant literature, proposes a rigorous research strategy, and discusses sampling data results. The collected data are based on 500 consumer surveys, 20 individual interviews with marketing professionals, and secondary data comprising industry reports and scholarly articles. The data was analysed using statistical analysis software, AI-driven analytics software, and data visualisation tools. This utilised a robust pool of data to provide a comprehensive overview of consumer engagement with digital marketing and their perspectives on the use of AI and other personalisation methods. The current report concludes by considering the prospects for future marketing and how these concepts can be further advanced as technology continues to evolve.