Nels Madsen

Infrared Thermography As A Control For The Welding Process

A feasibility study was performed to determine if infrared thermography could be used to detect perturbations in the arc welding process that result in defects. Data were gathered using an infrared camera with a resolution of 0.2°C, which was trained on the molten metal pool during welding. Several defects were then intentionally induced, and the resulting thermal images were preserved on film. These images revealed that different types of weld defects induce different characteristic changes in the thermal image by detectably altering the temperature field around the weld. These perturbations in the temperature field can be used to identify and locate defects such as arc misalignment, plate gap, puddle impurities, etc. Macrostructural examinations permitted investigations into the relationships between weld puddle penetration depth and the temperature field. Using computer-aided processing of these thermal images, we expect that the welding process can be controlled to a higher degree than is presently possible.

The relation between anthropometric and physiological variables and bat velocity of high-school baseball players before and after 12 weeks of training.

Szymanski, DJ, Szymanski, JM, Schade, RL, Bradford, TJ, McIntyre, JS, DeRenne, C, and Madsen, NH. The relation between anthropometric and physiological variables and bat velocity of high school baseball players before and after 12 weeks of training. J Strength Cond Res 24(11): 2933-2943, 2010-The purpose of this article was to investigate the relation between anthropometric and physiological variables to linear bat swing velocity (BV) of 2 groups of high-school baseball players before and after completing a 12-week periodized resistance exercise program. Participants were randomly assigned to 1 of 2 training groups using a stratified sampling technique. Group 1 (n = 24) and group 2 (n = 25) both performed a stepwise periodized resistance exercise program and took 100 swings a day, 3 d·wk−1, for 12 weeks with their normal game bat. Group 2 performed additional rotational and full-body medicine ball exercises 3 d·wk−1 for 12 weeks. Fourteen variables were measured or calculated before and after 12 weeks of training. Anthropometric and physiological variables tested were height, body mass, percent body fat, lean body mass (LBM), dominant torso rotational strength (DTRS) and nondominant torso rotational strength (NDTRS), sequential hip-torso-arm rotational strength measured by a medicine ball hitters throw (MBHT), estimated 1 repetition maximum parallel squat (PS) and bench press (BP), vertical jump (VJ), estimated peak power, angular hip velocity (AHV), and angular shoulder velocity (ASV). The baseball-specific skill of linear BV was also measured. Statistical analysis indicated a significant moderately high positive relationship (p ≤ 0.05) between prelinear BV and pre-NDTRS for group 1, pre-LBM, DTRS, NDTRS, peak power, and ASV for group 2; moderate positive relationship between prelinear BV and preheight, LBM, DTRS, peak power, BP, PS, and ASV for group 1, preheight, body mass, MBHT, BP, and PS for group 2. Significantly high positive relationships were indicated between postlinear BV and post-NDTRS for group 1, post-DTRS and NDTRS for group 2; moderately high positive relationships between postlinear BV and post-LBM, DTRS, peak power, BP, and PS for group 1, postheight, LBM, VJ, peak power for group 2; moderate positive relationships between postlinear BV and postheight, body mass, MBHT, and VJ for group 1, postbody mass, MBHT, BP, PS, and ASV for group 2. Significantly low positive relationships were indicated between prelinear BV and prebody mass, MBHT, and VJ for group 1, pre-VJ and AHV for group 2; postlinear BV and post-AHV for group 2. These data show that significant relationships do exist between height, body mass, LBM, rotational power, rotational strength, lower body power, upper and lower body strength, AHV, and ASV to linear BV of high-school baseball players. Strength coaches may want to consider using this information when designing a resistance training program for high-school baseball players. Those recruiting or scouting baseball players may want to use this information to further develop ways of identifying talented players. However, one should be cautious when interpreting this information when designing strength training programs for high-school baseball players to increase linear BV.

Automatic Welding: Infrared Sensors for Process Control

A feasibility study was performed to determine if infrared thermography could be used to detect perturbations in the arc welding process which result in defects. Data were gathered using an infrared camera with a resolution of.2C which was trained on the molten metal pool during welding. Several defects were then intentionally induced and the resulting thermal images were preserved on film. These images revealed that different types of weld defects induce different characteristic changes in the thermal image by detectably altering the temperature field around the weld. These perturbations in the temperature field can be used to identify and locate defects such as arc misalignment, plate gap, puddle impurities etc. Macrostructural examinations permitted investigations into the relationships between weld puddle penetration depth and the temperature field. Using computer aided processing of these thermal images, it is expected that the welding process can be controlled to a higher degree than is presently possible.

Statics with MATLAB

Engineering mechanics involves the development of mathematical models of the physical world. Statics addresses the forces acting on and in mechanical objects and systems. Statics with MATLAB develops an understanding of the mechanical behavior of complex engineering structures and components using MATLAB to execute numerical calculations and to facilitate analytical calculations.MATLAB is presented and introduced as a highly convenient tool to solve problems for theory and applications in statics. Included are example problems to demonstrate the MATLAB syntax and to also introduce specific functions dealing with statics. These explanations are reinforced through figures generated with MATLAB and the extra material available online which includes the special functions described.This detailed introduction and application of MATLAB to the field of statics makes Statics with MATLAB a useful tool for instruction as well as self study, highlighting the use of symbolic MATLAB for both theory and applications to find analytical and numerical solutions

Operation with Vectors

Vectors are quantities that require the specification of magnitude, orientation, and sense. The characteristics of a vector are the magnitude, the orientation, and the sense. The magnitude of a vector is specified by a positive number and a unit having appropriate dimensions. No unit is stated if the dimensions are those of a pure number. The orientation of a vector is specified by the relationship between the vector and given reference lines and/or planes. The sense of a vector is specified by the order of two points on a line parallel to the vector . Orientation and sense together determine the direction of a vector. The line of action of a vector is a hypothetical infinite straight line collinear with the vector. Displacement, velocity, and force are examples of vectors quantities.

Moments, Couples, Equipollent Systems

The moment of a vector \(\mathbf v \), whose line of action passes through a point \(B\), about a point \(A\) is the vector

Centers of Mass

Figure 3.1 shows a set of \(n\) points \(P_i\), \( \{S\}=\{P_1,\,P_2,\ldots ,P_n\}=\{P_i\}_{i=1,2,\ldots ,n}. \) The position vector of a point \(P_i\) relative to an arbitrarily selected reference point \(O\) is \(\mathbf{r }_{P_i}\). A scalar \(s_i\) associated with \(P_i\) for example the mass \(m_i\) of a particle situated at \(P_i\). The first moment of a point \(P_i\) with respect to a point \(O\) is the vector \(\mathbf M _i=s_i\,\mathbf{r }_{P_i}\). The scalar \(s_i\) is called the strength of \(P_i\)

Virtual Work and Stability

A particle in static equilibrium position is considered, Fig. 6.1a. The static equilibrium position of the particle is determined by the forces that act on it. The virtual displacement, \(\delta \mathbf{r}\), is any arbitrary small displacement away from this natural position and consistent with the system constraints.

Analytical Determination of Higher Buckling Modes for Unimodal Optimal Columns

ABSTRACT Recent results have revived interest in the problem of determining the optimal shape of clamped-clamped columns. The bimodal behavior of certain cases has drawn particular attention. In this paper a revised formulation of the problem is used. This formulation permits the determination of the optimal design in the unimodal range in a simpler form than was previously available. The equations governing higher buckling modes of unimodal optimal clamped-clamped columns are posed and solved in series form. The onset of bimodal behavior is determined analytically. Earlier numerical results are confirmed and increased in accuracy.