The variability of the material properties of steel from different suppliers causes problems in achieving the required surface quality after turning. Therefore, the manufacturer needs to estimate the resulting quality before starting production, especially if it is an expensive, small-batch production from stainless steel. Predictive models will make it possible to estimate the surface roughness from the mechanical properties of steel and thus support decision making about supplier selection or acceptance of a material supply. This research presents a step-by-step decision-making procedure, which enables the trained staff to make quick decisions based on commonly available information in the Mill Test Certificate (MTC). A new multivariate second-order polynomial model and feedforward backpropagation artificial neural network (ANN) models have been developed using input variables from the MTC: Tensile Strength, Yield Strength, Elongation, and Hardness. Models were used to enhance the methodological robustness in formulating the decision if the predicted surface roughness is outside the required range, even before accepting the delivery. Both models can accurately predict surface roughness, while the ANN model is more accurate than the polynomial model; however, the predictive model is sensitive to the accuracy of the input data, and the model’s prediction is valid only under precisely defined conditions.

This study aimed to evaluate the static response of prestressed reinforced concrete beams strengthened in their flexure and shear properties using different strengthening techniques, steel plates, and externally bonded woven carbon fiber fabric (WCFF). The experimental work involved testing twenty large-scale prestressed reinforced concrete beams with a length of 3000 mm, and cross-sections measuring 400 mm in height and 200 mm in breadth were cast in the factory and tested in the laboratory. Four beams without prestressing served as the reference beams; two unbonded pre-tensioned beams served as the control beams, and the remaining fourteen beams were strengthened with steel plates and externally bonded woven carbon fiber fabric (WCFF). Eight of the beams were strengthened with 4 mm thick steel plates and tested under a monotonically increasing load with manual readings recorded. The remaining six beams were strengthened with 0.5 mm thick WCFF and tested under a monotonically increasing load with manual readings recorded. The variables considered included the strengthening techniques (FRP composite sheets, steel plates), the types of strengthening (slices, U-shaped), and the flexural and shear capacities of the strengthened beams. All the implemented strengthening techniques yielded enhancements in both the flexural and shear strength outcomes of the beams compared to their respective controls. The most significant increase in load capacity, whether in terms of ultimate load or first crack load, for the prestressed concrete beams’ flexure properties occurred when strengthening with U-shaped steel plates. Additionally, the greatest reduction in deflection at the point of reaching the maximum load for the prestressed concrete beams, in terms of their flexure properties, was observed when strengthening with U-shaped steel plates. Similarly, the maximum load increase for the prestressed concrete beams, in terms of their shear properties, was achieved through strengthening with U-shaped woven carbon fiber fabric wrapping. Furthermore, a finite element model was created to simulate various experimental specimens. The finite element model’s results exhibited harmony with the experimental results, affirming the efficacy of the presented finite element model.

The purpose of the present study is three-fold. Firstly, it attempts to describe the bake hardening (BH) behavior of selected interstitial free (IF) and dual phase (DP) steels. Secondly, it predicts the BH behavior of the IF DX 51D and DP 500 HCT 590X plates of steel, and thirdly studies material failure prevention in scholarly sources. The research is aimed at investigating the increasing steel strength during the BH of these two high-strength sheets of steel used for outer vehicle body parts. Samples of steel were pre-strained to 1%, 2%, and 5% and then baked at 140–220 °C for 10 to 30 min. The BH effect was determined from three factors: pre-strain, baking temperature, and baking time. Research has shown that increasing the yield strength by the BH effect is predictable. Therefore, the number of experiments could be reduced for the investigation of BH effect for other kinds of IF and DP steels. The literature study of the hailstone failure reveals that the knowledge of BH steels behavior helps to calculate the steel supplier´s failure mode effect analysis (FMEA) risk priority number.