Numerical simulation of the interaction of elements of active protection with metal barriers

Radchenko, P. A.; Батуев, С. П.; Радченко, А. В.

doi:10.1063/1.5007593

Cited by 2 publications

(1 citation statement)

References 4 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…19 Unfortunately, these polymerizations open to air are not well controlled or afford only low molecular weights resulting from termination events. [20][21] On this basis, the development of a controlled cationic polymerization that can be run at ambient temperature without the need for purified reagents and the use of an inert atmosphere remains a grand challenge.…”

mentioning

confidence: 99%

Controlled Cationic Polymerization: Single-Component Initiation under Ambient Conditions

et al. 2019

View full text Add to dashboard Cite

Cationic polymerizations provide a valuable strategy for preparing macromolecules with excellent control but are inherently sensitive to impurities and commonly require rigorous reagent purification, low temperatures, and strictly anhydrous reaction conditions. By using pentacarbomethoxycyclopentadiene (PCCP) as the single-component initiating organic acid, we found that a diverse library of vinyl ethers can be controllably polymerized under ambient conditions. Additionally, excellent chain-end fidelity is maintained even without rigorous monomer purification. We hypothesize that a tight ion complex between the PCCP anion and the oxocarbenium ion chain end prevents chain-transfer events and enables a polymerization with living characteristics. Furthermore, terminating the polymerization with functional nucleophiles allows for chain-end functionalization in high yields.

show abstract

mentioning

confidence: 99%

Controlled Cationic Polymerization: Single-Component Initiation under Ambient Conditions

et al. 2019

View full text Add to dashboard Cite

show abstract

Vulnerability Assessment of Ground Vehicle Systems Enabled With Active Protection Systems (Aps) Through Surrogate Modeling

Kulkarni,

Babu,

Kankanalapalli

et al. 2024

SAE Technical Paper Series

View full text Add to dashboard Cite

<title>ABSTRACT</title> Analytical performance assessment of Active Protection Systems (APS) and the vulnerability assessment of ground vehicles using classical physics-based modeling and simulations has many challenges. Also, modeling many of the factors involved in the interaction during Hard-Kill (HK) of the incoming threat with a countermeasure and the resulting outcomes are quite complex and have varied effects on the survivability of the vehicle. Therefore, relying only on deterministic solutions, are time consuming and computationally cost prohibitive. This effort is focused on changing this paradigm by researching for a suitable machine learning algorithm which takes in simulation data from high fidelity physics-based models as training data. Through decomposition, interpolation and reconstruction techniques, surrogate models can be constructed using the simulation data. These surrogate models can then be used for a quick assessment (fraction of a second compared to a day per simulation) during Analysis of Alternatives (AoA), and Vehicle Protection Systems (VPS) trade studies. <bold>Citation:</bold> Kumar B Kulkarni, Venkatesh Babu, Sanjay Kankanalapalli, Aditya Vipradas, P Jayakumar Ph.D. and Ravi Thyagarajan Ph. D., “Vulnerability assessment of ground vehicle systems enabled with Active Protection Systems (APS) through surrogate modeling,” In <italic>Proceedings of the Ground Vehicle Systems Engineering and Technology Symposium</italic> (GVSETS), NDIA, Novi, MI, Aug. 15-17, 2023.

show abstract

Numerical simulation of the interaction of elements of active protection with metal barriers

Cited by 2 publications

References 4 publications

Controlled Cationic Polymerization: Single-Component Initiation under Ambient Conditions

Controlled Cationic Polymerization: Single-Component Initiation under Ambient Conditions

Vulnerability Assessment of Ground Vehicle Systems Enabled With Active Protection Systems (Aps) Through Surrogate Modeling

Contact Info

Product

Resources

About