Prediction of Stress Correction Factor for Welded Joints Using Response Surface Models

While performing fatigue reliability analysis of the butt-welded joints it is vital to estimate the Stress Concentration Factor (SCF) at these joints. A common approach adopted by industry to estimate the SCF at weld toes is to perform Finite Element Analysis (FEA) of the welded joints for different pipe sizes, flanges, valves etc. The SCF are calculated for each size by separately when required and are very time consuming. Although FEA is known for its accurate SCF calculation, but due to its high computational expense and time-consumption, SCF evaluation for different parameters makes the aforementioned method quite laborious. As an alternative response surface models (RSM) may be used for accurate estimation of SCF. The two basic steps in constructing a RSM are training and testing. The first corresponds to fitting a model to the intelligently chosen training points, while the second step involves comparing the predictions of the RSM to the actual response. This paper examines the applicability of 12 different RSMs for estimating SCF. The training and testing data is generated using FEA in ANSYS. In order to compare the accuracy of the RSMs, three metrics, namely, Root Mean Square Error (RMSE), Maximum Absolute Error (AAE), and Explained Variance Score (EVS) are used. A case study illustrating the applicability of the proposed approach is also presented.

OPTIMIZATION DESIGN OF ALU FOAM-FILLED S-SHAPE SQUARE TUBE UNDER AXIAL DYNAMIC LOADING

This paper presents finite element simulation of the crash behavior and the energy absorption characteristics of S-shape square tubes which were fully or partially filled with aluminum foams. Base on the numerical results, it is found that, the density, the length of the filled foam and the thickness of tube directly affect the specific energy absorption (SEA) and peak crushing force (PCF) of the S-shape tubes. In this paper, the multi-objective particle swarm optimization (MOPSO) algorithm is employed to seek for optimal designs for the partial foam-filled S-shape tubes (PFSTs) and the full foam-filled S-shape tubes (FFSTs) with various design parameters such as the density, the length of filled foam and the thickness of tube, where response surface models are established to formulation SEA and PCF. The optimization results showed the energy absorption capability per unit mass of the PFSTs is more powerful than that of the FFSTs while the PCF constrained under the same level.

Optimization and Modeling of Slightly Acidic Electrolyzed Water for the Clean-in-Place Process in Milking Systems

To find an environmentally friendly and energy efficient alternative to acidic detergent for a milking system clean-in-place (CIP) process, this study investigated the feasibility of applying slightly acidic electrolyzed water (SAEW) alone to wash the system by cleaning soiled stainless steel (304) pipes, rubber gaskets, and PVC milk hoses, which were used in the milking system. The results showed that SAEW with appropriate parameters could achieve the same or even better hygienic effects compared with commercial detergent. Using response surface models, the SAEW parameters required to clean stainless steel were optimized at 9.9 min for the treatment time, 37.8 °C for the water temperature, and 60 mg/L for the available chlorine concentration; and were 14.4 min, 29.6 °C, and 60 mg/L for rubber gasket and PVC samples, respectively. After washing with the optimized parameter combination, bacteria and adenosine triphosphate on the three materials were almost non-detectable, indicating that SAEW has the potential to replace acidic detergents in CIP milking systems.