Alex Schreyer's Blog, Projects, Books, and More
It is here! After a bit of a wait, Google (formerly @Last software) released SketchUp 6 – again in a free-for-all and a professional version. Here is the official announcement. Upgrades (at least for US customers) are free and there’s a nifty wizard to accomplish a smooth upgrade. Sketchy view in SketchUp 6 using one […] Read more..
I got frustrated when my Outlook 2002 ran out of holidays December 2005. Searching around the internet I found some pages explaining how it is done. Holidays (or any kinds of "all-day" type events can be collected in a formatted text file and then simply imported into Outlook with one click. If you want to […] Read more..
This is a small change that I applied to the WordPress theme on this site. It changes the header image every month. If you like to use this, put the following tag into your header or modify any image in any template- (php-file) on your site.
The DOWEL program is a finite-element modeler for dowel-type connections (e.g. nails, bolts, lag screws) in wood-wood, wood-steel or any other type of connection material configuration. The underlying model has even been used for pile modeling in soil. It calculates load-displacement curves for monotonic and cyclic loading applictions and plots deformed shapes at predefined displacement steps. Material inputs consist of basic material embedment data. All material data is stored in a database that can be appended by the user.
The objective of this study was to investigate the monotonic and cyclic behaviour of different kinds of slender dowel-type fasteners. To accomplish this, four types of fasteners were tested in a series of 73 monotonic and cyclic tests. All tests used either one or two slotted-in steel plates in PARALLAM®, a Parallel Strand Lumber (PSL) product.
This program allows the user to take an Excel spreadsheet with any type of calculation data (no matter how complex) and optimize a calculation outcome (e.g. total cost) using a Genetic Algorithm approach. Genetic algorithms (GAs) are based on biological principles of evolution and provide an interesting alternative to “classic” gradient-based optimization methods.