A New Approach For Calculating Inherent Strain and Distortion in Additive Manufacturing of Metal Parts

Additive manufacturing (AM) of metallic parts is widely utilized for industrial applications. However, quality issues of the printed parts, including part distortion and cracks caused by high temperature and fast cooling, result in high residual stress. This is a challenge that limits the industry acceptance of AM. To overcome this challenge, a numerical modeling method for predicting part distortion at the design stage plays an important role, and enables design engineers to remove failures before printing, as well as determine the optimal printing process parameters to minimize part deformation. This research proposes an inherent strain-based part deformation prediction method. To determine the inherent strain (IS) value, a micro-scale model for analyzing the temperature distribution is constructed. The IS value is calculated from the temperature gradient. Then, the IS value is used for determining the part deformation. The proposed methodology has been developed and evaluated, using a 316L stainless steel cantilever beam, in both simulations and experimental results.

Fast Prediction for Resistance Spot Welding Deformation Using Inherent Strain Method and Nugget Model

In a car body, there exist thousands of resistance spot welds, which may induce large deformation during the manufacturing process. Therefore, it is expected that automotive industries will develop a method and a computing system for the fast and simple prediction of its deformation. Although the inherent strain method has been used for the fast prediction of arc welding deformation, it has not been applied to resistance spot welding so far. Additionally, the electrical-thermal-mechanical coupling analysis for the deformation induced by resistance spot welding is complicated and much more time-consuming. Therefore, in this study, a nugget model of the resistance spot weld has been developed, and the inherent strain method is extended for use in the fast prediction of resistance spot welding deformation. In addition, the deformation of a vehicle part with 23 resistance spot welds was efficiently predicted within around 90 min using the inherent strain method, displaying good accuracy compared with the measurement.

Variability of Beta-Lactam Broth Microdilution for Pseudomonas aeruginosa

Antimicrobial susceptibility testing for Pseudomonas aeruginosa is critical to determine suitable treatment options. Commercial susceptibility tests are typically calibrated against the reference method, broth microdilution (BMD). Imprecision of minimum inhibitory concentrations (MICs) obtained by BMD for the same isolate on repeat testing is known to exist. Factors that impact the extent of variability include concentration of the inoculum, operator effects, contents of the media, inherent strain properties, and the testing process or materials. We evaluated the variability of BMD for anti-pseudomonal beta-lactams (aztreonam, cefepime, ceftazidime, meropenem, piperacillin-tazobactam, ceftazidime-avibactam, ceftolozane-tazobactam) tested against a collection of P. aeruginosa isolates. Multiple replicate BMD tests were performed and MICs were compared to assess reproducibility, including the impact of the inoculum and operator. Overall, essential agreement (EA) was ≥ 90% for all beta-lactams tested. Absolute agreement (AA) was as low as 70% for some beta-lactams. Variability from the inoculum and operators impacted the reproducibility of MICs. Piperacillin-tazobactam exhibited the highest degree of variability with 74% AA and 94%% EA. The implications of MIC variability are extensive as the MIC is essential for multiple facets of microbiology, such as the development of new compounds and susceptibility tests, dose optimization and pharmacokinetic/pharmacodynamic (PK/PD) targets for individual patients.