B. Basaran

Energy harvesting using martensite variant reorientation mechanism in a NiMnGa magnetic shape memory alloy

Magnetic shape memory alloys demonstrate significant potential for harvesting waste mechanical energy utilizing the Villari effect. In this study, a few milliwatts of power output are achieved taking advantage of martensite variant reorientation mechanism in Ni51.1Mn24Ga24.9 single crystals under slowly fluctuating loads (10Hz) without optimization in the power conversion unit. Effects of applied strain range, bias magnetic field, and loading frequency on the voltage output are revealed. Anticipated power outputs under moderate frequencies are predicted showing that the power outputs higher than 1W are feasible.

Stress-induced martensite to austenite phase transformation in Ni2MnGa magnetic shape memory alloys

The effects of temperature on the stress-induced variant reorientation process and the possibility to trigger stress-induced martensite to austenite phase transformation in Ni2MnGa single crystals were investigated under compression. It is revealed that, as the temperature decreases, both the critical stress (under 16?kG magnetic field) and the critical magnetic field levels (under ?1?MPa) for martensite variant reorientation increase. Magnetic-field-induced strain is also found to increase with temperature. Near the austenite start temperature, it is possible to attain stress-induced martensite to austenite transformation under constant magnetic field. A thermodynamical guideline is introduced to explain the conditions for ?stress-induced martensite to austenite transformation? in Ni2MnGa alloys. It is concluded that, when magnetocrystalline anisotropy energy is large enough, stress-induced martensite to austenite transformation can be achieved within a narrow temperature range below austenite start temperature.

Constitutive modeling of magneto-mechanical coupling response of magnetic field-induced phase transformations in NiMnCoIn magnetic shape memory alloys

The unique characteristic of magnetic field induced phase transformation of NiMnCoIn magnetic shape memory alloys (MSMAs) lies in the generation of large transformation strains under high constant stress levels. Motivated by experiments, a constitutive model is proposed to take into account magnetic field induced phase transformation from austenitic to martensitic phase. The working principle of such materials is described by the deformation of continua due to mechanical and magnetic forces. The cross coupling of mechanical and magnetic variables is captured by introducing nonlinear kinematics. In the present work, microstructure dependence of martensitic phase transformation is taken into account by introducing internal variables into the model. The constitutive response is derived in a consistent thermodynamic way.

Constitutive Modeling of Magneto-Thermo-Mechanical Response of Field-Induced Phase Transformations in NiMnCoIn Magnetic Shape Memory Alloys

In this work we model the magnetic field induced phase transformation (FIPT) of magnetic shape memory alloys (MS-MAs). The working principle of such materials is described by the cross coupling of mechanical, thermal and magnetic fields. The Thermo-magneto-mechanical constitutive equations are derived in a thermodynamic consistent way. A 3-D stress-field-temperature phase diagram is constructed using the model. The model is calibrated from the experimental data and the model predictions are compared with experimental results.Copyright

Constitutive Modeling of Magnetic Field-Induced Phase Transformation in NiMnCoIn Magnetic Shape Memory Alloys

In this work we model the magnetic field induced phase transformation (FIPT) of magnetic shape memory alloys (MSMAs). The working principle of such materials is described by the deformation of continua due to mechanical and magnetic forces. The cross coupling of mechanical and magnetic variables is captured by introducing nonlinear kinematics. The mechanical and magnetic constitutive equations are derived by a thermodynamic consistent way. Finally, the model prediction followed by model calibration is compared with the experimental results.Copyright