How the “perfect storm” was created for Mercedes F1 woes




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After George Russell and Lewis Hamilton qualified sixth and seventh at the Bahrain Grand Prix of the 2023 Formula 1 season, Mercedes director This is Wolff, stated that the team needed to change their design direction. It has now been revealed that senior team officials, drivers and engineers took part in an intense meeting on Tuesday after the race at the Sakhir circuit to address the situation.

Asked by Motorsport.com to detail the talks, the Austrian said it had turned out to be “an interesting process” as the Silver Arrows realized their ability to limit the porpoising in the troubled W13 had given him false hope about how far they could go, and that created a “perfect storm.”

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The head of those of the star said: “Many, big and good meetings are taking place in the team. It is a quite interesting process because last year we had the perfect storm, with a car that was improving and then you start to question the concept of the car less than you really should.

“Now we have to show that we are not happy with where we have arrived,” he continued. “Overall we’re not happy with the amount of downforce, the mechanical balance, and that never comes alone. All those meetings are giving us clarity and making us focus on what we need to do to turn things around quickly.” .

Those words coincide with what Russell commented before the Saudi Arabian Grand Prix, who put the race in which he achieved victory as the reason why they went “a bit of a wrong way”. Wolff added that it is proving that the German team was wrong in its philosophy, and that its design will not surpass its rivals, both Red Bull and Ferrari, as they had previously expected.

That led the Austrian to conclude that Mercedes had a “bad guide” for the data and CFD simulations: “We tried very hard to make it work, because the data we have extrapolated showed us that it worked. We were proven wrong, it’s very simple, and you can see that the three fastest cars, including Ferrari, have a similar concept of how they generate performance, very different from ours.

“At a certain point, we came to the conclusions that we were wrong,” he said. “We’re still looking at why we did it, because we followed the data and what the simulations are telling us, and in that case, we got the data wrong. All of us who were involved in the decision-making process came to that conclusion, we couldn’t keep it up.”

“We really try to stick to it and we don’t want, under any circumstances, to go in one direction saying, ‘we’re going to make that work no matter what,’ because it doesn’t work,” he explained. “I don’t want to waste any more time, and neither do my teammates.”


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