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Prakash, Aditya

Publications and source records attributed to Prakash, Aditya.

Data Mining Critical Infrastructure Systems: Models and Tools

Critical infrastructures (CIs) such as power, water, transportation, and telecommunication are highly complex interacting systems that are vital to national security, economy and public life. They play an important role in several core urban computing challenges. Advances in computing resources and techniques have led to enormous progress in developing intelligent frameworks for analyzing these large heterogeneous systems. In this article, we survey state-of-the-art and foundational work in this upcoming area from a data mining perspective. We discuss basic concepts of CIs, their properties, impacts on them due to natural or human-caused disturbances and different computational methodologies used for modeling and understanding their behavior. We also discuss recent work that specifically deals with two critical sectors of CIs, namely power and transportation systems. Lastly, we also describe several existing tools and methods that are used to facilitate decision making for domain operators, enable efficient and faster disaster response for federal and state agencies and help improve the security and resiliency of these CIs.

97 MATHEMATICS AND COMPUTING↗

Effect of Zener–Holloman Parameter on the Prior Austenite Grain size in a 12Cr-10Ni Precipitation-Hardenable Stainless Steel

Hot isothermal plane strain compression (PSC) tests were carried out on a 12Cr-10Ni martensitic precipitation-hardenable (PH) stainless steel, in the temperature range of 750-1050 °C, to study microstructural evolution during large strain deformation. The nature of stress–strain curves varies with Zener–Holloman parameter (Z) with specimens deformed at high Z showing steady-state behavior and those deformed at lower Z showing flow softening. Prior austenite grain size (PAGS), d, exhibited a strong correlation to Z showing a bilinear behavior represented as: d = (1803.9)Z{sup −0.094} for high Z deformation and d = (1456.2)Z{sup −0.058} for low Z deformation. Based on the above study, it is recommended to thermomechanically process 12Cr-10Ni steel at Z ≥ 10{sup 22} for obtaining products with good strength–toughness balance.

36 MATERIALS SCIENCE↗

Optimization of hot workability and microstructure control in a 12Cr-10Ni precipitation hardenable stainless steel: An approach using processing maps

Highlights: • Deformation processing map was developed for a 12Cr10Ni precipitation hardenable martensitic stainless steel and optimized hot working parameters were suggested to obtain defect free products. • The ‘stable’ domain of the processing maps were correlated to the dynamic recrystallization in the austenite phase and further confirmed by detailed microstructural investigations. • The DRx domain showed a refinement of the martensite packet size and of the prior transformation austenite grain size, essential to obtain the desired mechanical properties. - Abstract: Optimization of hot working parameters and corresponding microstructure control were explored in a 12Cr-10Ni precipitation hardenable martensitic stainless steel. From hot compression tests, 1073–1373 K (800°–1100 °C) and five (0.001–10 s{sup −1}) different strain rates, processing maps were developed, and various domains of microstructure evolution (in the austenite phase) were identified. The stable domain of the processing maps appeared to indicate dynamic recrystallization (DRx) in the austenite phase: as evident by the appearance of inflection point in the strain hardening rate versus flow stress plots. The suspected DRx domain was further confirmed by detailed microstructural investigations of the respective water-quenched specimens. The DRx domain showed a refinement of the martensite packet size and of the prior transformation austenite grain size. The later was shown with optical microstructure and reconstructed (modelled) microtexture data of the prior austenite grains. Additionally, the DRx domain showed a significant difference in activation energy as estimated from appropriate constitutive modelling.

36 MATERIALS SCIENCE↗