Process - Property Correlation of Friction Stir Welding of Marine Grade Aluminium Alloy 5083 Using Finite Element Analysis

In this article, a 3D finite element based thermo-mechanical model for friction stir welding (FSW) of a marine-grade aluminium alloy 5083 is proposed. The model demonstrates the thermal evaluation and the distribution of residual stresses and strains under the variation of process variables. The temperature profile of the weld joint during the FSW process and the mechanical properties of the joints are also experimentally evaluated. The necessary calibration of the model for the correct implementation of the thermal loading, mechanical loading, and boundary conditions was performed using the experimental results. The model simulation and experimental results are analyses in view of the process-property correlation study. The residual stress was evaluated along, and across the weld, centreline referred as longitudinal and transverse residual stresses, respectively. The magnitude of longitudinal residual stress is noted 60-80% higher than that of the transverse direction. The longitudinal residual stress generated a tensile oval shaped stress region around the tool shoulder confined to a maximum distance of about 25mm from the axis of the tool along the weld line. It encompasses the weld-nugget to thermo-mechanically affected zone (TMAZ), while the parent metal region is mostly experiences the compressive residual stresses. However, the transverse residual stress region appears like wing shaped region spread out in both the advancing and retreating side of the weld and occupying approximately double the area as compared to the longitudinal residual stresses. Overall, the study revealed a corelation between the FSW process variables such as welding speed and the tool rotational speed with the residual stress and the mechanical properties of the joint.

Optimization of process-property relations of 3D printed ceramics using extrusion-based additive manufacturing

The capability and applicability of additive manufacturing have mesmerized the entire manufacturing world. One major technique of additive manufacturing is extrusion-based additive manufacturing (EAM), which has been recently employed for the rapid production of ceramic components, among other applications. This study focused on establishing the process-property relations for extrusion-based additively manufactured ceramics, namely Alumina (Al2O3) and Zirconia (ZrO2), and then optimization of the relations to get the desired mechanical properties for applicability. Extrusion-based additive manufacturing was used to obtain the ceramic sample parts from ceramic-binder mixtures and by subsequent post-processing. The process parameters chosen for the study were extrusion velocity and part orientation whereas the mechanical properties selected were hardness and flexural strength. Extrusion velocity was varied at three levels i.e. 7.5 mm/s, 12.5 mm/s and 17.5 mm/s. Two levels selected for part orientation were horizontal and vertical. The design of experiments technique was used to establish the process-property relations by highlighting the most significant process parameters affecting the selected mechanical properties. Optimization was achieved by highlighting those levels of significant process parameters that provided the desired values of mechanical properties. Part orientation came out to be a significant factor affecting both the hardness and flexural strength of the two ceramics whereas extrusion velocity was found to be insignificant for both mechanical properties. Among the two levels of part orientation, vertical orientation samples showed higher values of hardness while horizontal samples showed higher flexural strength thus, aiding in the optimization of the process-property relations.

Evaluation of mechanical property predictions of refill Friction Stir Spot Welding joints via machine learning regression analyses on DoE data

The high-potential of lightweight components consisting of similar or dissimilar materials can be exploited by Solid-State Joining techniques. Whereas defects such as pores and hot cracking are often an issue in fusion-based joining processes, via solid-state joining processes they can be avoided to enable high-quality welds. To define an optimal process window for obtaining anticipated joint properties, numerous time and cost consuming experiments are usually required. Building a predictive model based on regression analysis enables the identification and quantification of process-property relationships. On the one hand, mechanical property and performance predictions based on specific process parameters are needed, on the other hand, inverse determination of required process parameters for reaching desired properties or performances are demanded. If these relations are obtained, optimized process parameter sets can be identified while vast numbers of required experiments can be reduced, as underlying physical mechanisms are utilized. In this study, different regression analysis algorithms, such as linear regression, decision trees and random forests, are applied to the refill Friction Stir Spot Welding process for establishing correlations between process parameters and joint properties. Experimental data sets used for training and testing are based on a Box-Behnken Design of Experiments (DoE) and additional test experiments, respectively. The machine-learning based regression analyses are benchmarked against linear regression and DoE statistics. The results illustrate a decryption of relationships along the process-property chain and its deployment to predict mechanical properties governed by process parameters.

Digital mapping of erosion degree of soils using the factor - property and factor - process - property models (the south of the Central Russian upland)

Soil degradation resulting from water erosion poses a serious threat to food and environmental security, therefore the research of soil erosion features and soil erosion mapping do not lose their relevance. The paper presents the results of large-scale digital mapping of the erosion degree of the arable soils in the Prokhorovsky district of the Belgorod region (85 thousand hectares), based on two approaches: (1) linking the factors of erosion-accumulative processes and the erosion degree of soil directly (factor -property model), and (2) due to imitation erosion model WaTEM/SEDEM (factor - process - property model). The inclusion of the process component into the digital soil mapping algorithm allows taking into account not only the spatial but also the temporal soil erosion features. It was revealed that the agricultural development of the Prokhorovsky district was primarily carried out on lands that are weakly prone to erosion, with the rate of erosion almost two times lower than on younger arable lands. As a result, the soil erosion maps, based on the factor - process - property model, with and without taking into account the duration of agricultural use, largely correspond to each other. Dominant soil categories (the map pixel corresponds to one soil taxa - noneroded and slightly eroded, medium, highly eroded), mapping by factor -property and factor - process - property models, have a high degree of correspondence to each other (prediction identity for 90% of pixels), while the soil combinations (the map pixel has information on the proportion of soils with different erosion degrees of soil) more significant (identity for less than 60% of pixels). The areas of zonal, erosion-zonal, and weakly eroded soil combinations differ 1.5-2 times, in the direction of a greater degree of soil erosion on the factor - process - property map.

Serial Eviction Filing: Civil Courts, Property Management, and the Threat of Displacement

Drawing on over 8 million eviction court records from twenty-eight states, this study shows the role that eviction filings play in extracting monetary sanctions from tenants. In so doing, it documents an unanticipated feature of housing insecurity: serial eviction filings. Serial eviction filings occur when a property manager files to evict the same household repeatedly from the same address. Almost half of all eviction filings in our sample are associated with serial filings. Combining multivariate analysis with in-depth interviews conducted with thirty-three property managers and ten attorneys and court officials, we document the dynamics and consequences of serial eviction filings. When legal environments expedite the eviction process, property managers use the housing court to collect rent and late fees, passing costs on to tenants. Serial eviction filings exacerbate tenants’ housing cost burden and compromise their ability to find future housing. Using tract-level rent and filing fees, we estimate that each eviction filing translates into approximately $180 in fines and fees for the typical renter household, raising their monthly housing cost by 20%. The study challenges existing views of eviction as a discrete event concentrated among poor renters. Rather, it may be better conceived of as a routinized, drawn-out process affecting a broader segment of the rental market and entailing consequences beyond displacement.