Sentence examples for weight of fire from inspiring English sources

Exact(8)

One proposal was made to replace the 240-millimeter guns turrets with single 305 mm turrets to create an "all-big-gun" ship, like the British battleship HMS Dreadnought, but this was rejected as it would have raised the displacement above the 18,000-metric ton limit and the slower-firing 305-millimeter guns would have reduced the volume and weight of fire to an unacceptable degree.

We thought there was no one firing back because of the weight of fire.

The weight of fire from the three cruisers prevented them from closing to torpedo range and they scored no hits.

The Americans expended 1,400 rounds at a range of between 45-270 m; however, the weight of fire was insufficient to halt the assaulting force.

Most sections had to brave the full weight of fire from small arms, mortars, artillery, and interlocking fields of heavy machine gun fire.

Since the end of World War I, German divisions had had their artillery spread out amongst their component regiments, which made it difficult to bring the maximum weight of fire to bear on any one point.

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Similar(52)

For instance, the report notes that the floors in 125 of the city's 223 fire stations are buckling under the weight of modern fire engines.

The cost includes a design that complies with Caltrans since the bridge is in that agency's right of way, and with fire code requirements, such as being able to handle the weight of a fire engine.

For much of Saturday afternoon the white shirt held sway over black, the world's best team in retreat under the weight of English fire.

Thermogravimetric analysis (TGA) including derivative plots showed that boric acid and APP enhance the residual weight of intumescent fire retardant coating.

A successful classification of the prefectures of Greece (in forest fire risk zones) was performed by the expert system by comparing the produced fuzzy expected intervals to each other and by using a supervised machine learning algorithm that assigns a certain weight of forest fire risk to each prefecture (Machine Learning, John Wiley and Sons, 1995).

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