New Release Books by Jon Falk

IBM® Storwize® HyperSwap® is a response to increasing demand for continuous application availability, minimizing downtime in the event of an outage, and non disruptive migrations. IT centers with IBM i can take full advantage of the HyperSwap solution. In this IBM RedpaperTM publication, we provide instructions to implement Storwize HyperSwap with IBM i. We also describe some business continuity scenarios in this area, including solutions with HyperSwap and IBM i Live Partition Mobility, and a solution with HyperSwap and IBM PowerHA® for IBM i.

An inside look at the University of Michigan's football program from the man who was the team's equipment manager for more than four decades Forty years ago, Michigan equipment manager Jon Falk began his legacy, becoming a living encyclopedia of Michigan football tradition and history. Hired by Bo Schembechler in 1974, the now retired Falk shares his firsthand, inside stories from in the locker room, on the sideline, and on the road with one of college football's most storied institutions. He may not be as well known as the Big House or the Little Brown Jug, but among coaches, players, and a good portion of the Michigan football faithful, Jon Falk has fashioned a lively legend of his own. Falk's recollections connect the past and present to highlight the importance of the relationships created during the best four years of any college player's life and it's those relationships that drive the Wolverines to success.

Jon Falk is a living encyclopedia of Michigan football tradition and history, and these firsthand, inside stories reveal the priceless experiences of the coaches and players who made it happen. He’s not as well known as the Big House itself or even the Little Brown Jug, but among coaches, players, and a good portion of the Michigan football faithful, Jon Falk has forged a colorful legend of his own. While games are won and lost on the field, it’s in the locker room where stories are told, friendships are made, and memories are created during the best four years of any college player’s life.

We used a shelterbelt turbulent flow model to simulate a variety of natural and artificial barriers. A two-row tree shelterbelt was simulated by the model. Its drag coefficient was modified until it reached its optimum value; that is, where its velocity field best matched observations. The pressure field matched the observations well under these conditions, so the modifications to the drag coefficient were physically consistent with theory. The model output captured the general characteristics of the observed wind field (upwind wind reduction, overspeeding zone, quiet zone, and wake zone). The model's biases were too much wind speed reduction in the near lee of the shelterbelt and wind speed recovery too close to the shelterbelt. Similar performance was noted in the model performance around an artificial thick barrier, consisting of artificial Christmas trees. We attempted to use the model to simulate fences and other "infinitely thin" barriers. While the model assumes that barriers have a finite thickness, it was able to approximate thin barriers by using fine grid spacing. The model was again able to accurately simulate the observed wind field, though the same biases applied in this case. In the case of multiple barriers, the model captured the fine-scale fluctuations and the array wind field, but tended to slowly increase the wind speed after each successive barrier, which was not seen in the observations. Simulations of shelterbelts with degraded leaf area density showed that the distribution of plant matter within a shelterbelt is not as important as the total amount of plant matter or the shelterbelt's height in determining the shelter effect. Modifying the configuration of the shelterbelt (making the windward edge denser and the leeward edge looser, and vice versa) also had minimal influence on the shelter effect.