Machining induces severe plastic deformation (SPD) in the chip and on the surface to stimulate dramatic microstructural transformations which can often result in a manufactured component with a fine-grained surface. The aim of this paper is to study the one-to-one mappings between the thermomechanics of deformation during chip formation and an array of resulting microstructural characteristics in terms of central deformation parameters–strain, strain-rate, temperature, and the corresponding Zener–Hollomon (ZH) parameter. Here, we propose a generalizable rate-strain-microstructure (RSM) framework for relating the deformation parameters to the resulting deformed grain size and interface characteristics. We utilize Oxley’s model to calculate the strain and strain-rate for a given orthogonal machining condition which was also validated using digital imaging correlation-based deformation field characterization. Complementary infrared thermography in combination with a modified-Oxley’s analysis was utilized to characterize the temperature in the deformation zone where the SPD at high strain-rates is imposed. These characterizations were utilized to delineate a suitable RSM phase-space composed of the strain as one axis and the ZH parameter as the other. Distinctive one-to-one mappings of various microstructures corresponding to an array of grain sizes and grain boundary distributions onto unique subspaces of this RSM space are shown. Building on the realization that the microstructure on machined surfaces is closely related to the chip microstructure derived from the primary deformation zone, this elucidation is expected to offer a reliable approach for controlling surface microstructures from orthogonal machining.

Background: Newcastle disease (ND) is an economically important viral disease affecting the poultry industry. In Kerala, a state in South India, incidences of ND in commercial and backyard poultry have been reported. But a systematic statewide study on the prevalence of the disease has not been carried out. Objectives: A cross-sectional survey was performed to detect the presence of Newcastle disease virus (NDV) in suspect cases and among apparently healthy commercial flocks and backyard poultry, in the state and to identify risk factors for NDV infection. Methods: Real-time reverse transcription-PCR (RT-PCR) was used to detect the M gene of NDV in choanal swabs and tissue samples collected from live and dead birds, respectively and the results were statistically analysed. Results: The predominant clinical signs of the examined birds included mild respiratory signs, huddling together and greenish diarrhoea. Nervous signs in the form of torticollis were noticed in birds in some of the affected flocks. On necropsy, many birds had haemorrhages in the proventriculus and caecal tonsils which were suggestive of ND. Of the 2079 samples tested, 167 (8.0%) were positive for the NDV M-gene by RT-PCR. Among 893 samples collected from diseased flocks, 129 (14.5%), were positive for M gene with pairwise relative risk (RR) of 15.6 as compared to apparently healthy flocks where 6 out of 650 (0.9%) samples were positive. All positive samples were from poultry; none of the ducks, pigeons, turkey and wild birds were positive. Commercial broilers were at higher risk of infection than commercial layers (RR: 4.5) and backyard poultry (RR: 4.9). Similarly, birds reared under intensive housing conditions were at a higher risk of being infected as compared to those reared under semi-intensive (RR: 6.7) or backyard housing (RR: 2.1). Multivariable analysis indicated that significantly higher risk of infection exists during migratory season and during ND outbreaks occurring nearby. Further, lower risk was observed with flock vaccination and backyard or semi-intensive housing when compared to intensive housing. When the M gene positive samples were tested by RT-PCR to determine whether the detected NDV were mesogenic/velogenic, 7 (4.2%) were positive. Conclusions: In Kerala, NDV is endemic in poultry with birds reared commercially under intensive rearing systems being affected the most. The outcome of this study also provides a link between epidemiologic knowledge and the development of successful disease control measures. Statistical analysis suggests that wild bird migration season and presence of migratory birds influences the prevalence of the virus in the State. Further studies are needed to genotype and sub-genotype the detected viruses and to generate baseline data on the prevalence of NDV strains, design better detection strategies, and determine patterns of NDV transmission across domestic poultry and wild bird populations in Kerala.