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Publications by Ian M. Howard
Parametric Design-Based Modal Damped Vibrational Piezoelectric Energy Harvesters With Arbitrary Proof Mass Offset: Numerical and Analytical Validations
Mechanical Systems and Signal Processing
Control
Systems Engineering
Signal Processing
Mechanical Engineering
Civil
Structural Engineering
Computer Science Applications
Aerospace Engineering
Comparative Numerical Studies of Electromechanical Finite Element Vibration Power Harvester Approaches of a Piezoelectric Unimorph
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Coupled Electromechanical Numerical Modelling of Piezoelectric Vibration Energy Harvesters
Annals of DAAAM and Proceedings of the International DAAAM Symposium
Control
Systems Engineering
Industrial
Mechanical Engineering
Electronic Engineering
Manufacturing Engineering
Computer Science Applications
Electrical
Flexible and Robust Piezoelectric Polymer Nanocomposites Based Energy Harvesters
High-Performance Piezoelectric Energy Harvesters and Their Applications
Joule
Energy
Piezoelectric Energy Harvesting With Parametric Uncertainty
Smart Materials and Structures
Mechanics of Materials
Electronic Engineering
Signal Processing
Condensed Matter Physics
Materials Science
Civil
Molecular Physics,
Structural Engineering
Electrical
Atomic
Optics
On the Performance Improvement of Piezoelectric Energy Harvesters
International Journal of Mechanical Engineering and Robotics Research
Control
Systems Engineering
Artificial Intelligence
Mechanical Engineering
Issues in Mathematical Modeling of Piezoelectric Energy Harvesters
Smart Materials and Structures
Mechanics of Materials
Electronic Engineering
Signal Processing
Condensed Matter Physics
Materials Science
Civil
Molecular Physics,
Structural Engineering
Electrical
Atomic
Optics
Manufacture and Characterisation of Piezoelectric Broadband Energy Harvesters Based on Asymmetric Bistable Cantilever Laminates
Ferroelectrics
Optical
Electronic
Condensed Matter Physics
Magnetic Materials
Figure of Merit Comparison of PP-based Electret and PVDF-based Piezoelectric Polymer Energy Harvesters
Bayesian Framework to Quantify Uncertainties in Piezoelectric Energy Harvesters
