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In order to achieve multi-objective optimization design of ballistics and improve the power of weapons, an optimization model for the internal ballistic simulation design of the propellant charge was established. Based on the requirements of artillery ballistic performance, the model took several influences into account, such as type, charge mass (ω) and web thickness (2e1). The objective function was composed of muzzle velocity (v0), maximum chamber pressure (pm), relative burnout point (ηk) equations. The computational program used recursive algorithm to calculate and select reasonable charge results by looping the internal ballistics and optimization design equation sets. 105 mm artillery and 122 mm artillery were selected as examples to optimize the charge design. The results show that compared with the existing charging scheme, the loading scheme optimized by the model can reduce the relative burnout point of 105 mm artillery by 0.21 in the case of the muzzle velocity, and the maximum chamber pressure have a little difference. The maximum chamber pressure of the 122 mm artillery reduces by 2.83% while the muzzle velocity increases by 1.13%.

Microsecond-scale congestion events, known as microbursts, are a main cause of packet loss and poor application performance in today's datacenters. Given the low network utilization in datacenters, one would expect packet deflection, in-situ re-routing of packets that arrive at a full buffer to a different port, to effectively prevent packet loss. However, if deployed naively, deflection leads to excessive packet re-ordering, exacerbated congestion, and head-of-the-line blocking in switch buffers. In this study, we resolve the above challenges by selectively deflecting the packets that cause persistent congestion in the network. To enable this, we augment the end-host network stacks with a transport-independent extension that tracks and marks flows with their remaining bytes. Our in-network deflection component uses the flow size information to re-route packets from flows with more data to send. Finally, an extension to the receive-side of end-host stacks retrieves the correct ordering of packets before passing them to transport and higherlevel protocols. We evaluate our design, Vertigo, under diverse datacenter workloads and show that it is effective in managing microbursts under light and heavy loads and when combined with various congestion control algorithms. For example, in a leaf-spine network under 85% load, Vertigo reduces the mean incast query completion times by 3.5x, 3.3x, 5x compared to ECMP, DRILL, and DIBS when using TCP, 3x, 3.5x, 4.5x alongside DCTCP, and 43x, 33x, 16x when using Swift, respectively.