S. E. Haaland

Bio: S. E. Haaland is an academic researcher from Norwegian Institute of Technology. The author has contributed to research in topics: Darcy friction factor formulae & Open-channel flow. The author has an hindex of 1, co-authored 1 publications receiving 790 citations.

Autonomous Soft Robotic Fish Capable of Escape Maneuvers Using Fluidic Elastomer Actuators.

Abstract: In this work we describe an autonomous soft-bodied robot that is both self-contained and capable of rapid, continuum-body motion. We detail the design, modeling, fabrication, and control of the soft fish, focusing on enabling the robot to perform rapid escape responses. The robot employs a compliant body with embedded actuators emulating the slender anatomical form of a fish. In addition, the robot has a novel fluidic actuation system that drives body motion and has all the subsystems of a traditional robot onboard: power, actuation, processing, and control. At the core of the fish's soft body is an array of fluidic elastomer actuators. We design the fish to emulate escape responses in addition to forward swimming because such maneuvers require rapid body accelerations and continuum-body motion. These maneuvers showcase the performance capabilities of this self-contained robot. The kinematics and controllability of the robot during simulated escape response maneuvers are analyzed and compared wit...

Recent advances in application of nanofluids in heat transfer devices: A critical review

Abstract: This paper presents a critical review of heat transfer applications of nanofluids. The effects of nanoparticle concentration, size, shape, and nanofluid flow rate on Nusselt number, heat transfer coefficient, thermal conductivity, thermal resistance, friction factor and pressure drop from numerous studies reported recently are presented. Effects of various geometric parameters on heat transfer enhancement of system using nanofluids have also been reviewed. Heat transfer devices covered in this paper include radiators, circular tube heat exchangers, plate heat exchangers, shell and tube heat exchangers and heat sinks. Various correlations used for experimental validation or developed in reviewed studies are also compiled, compared and analyzed. The pros and cons associated to the applications of nanofluids in heat transfer devices are presented in details to determine the future direction of research in this arena.

A symbolic data-driven technique based on evolutionary polynomial regression

Abstract: This paper describes a new hybrid regression method that combines the best features of conventional numerical regression techniques with the genetic programming symbolic regression technique. The key idea is to employ an evolutionary computing methodology to search for a model of the system/process being modelled and to employ parameter estimation to obtain constants using least squares. The new technique, termed Evolutionary Polynomial Regression (EPR) overcomes shortcomings in the GP process, such as computational performance; number of evolutionary parameters to tune and complexity of the symbolic models. Similarly, it alleviates issues arising from numerical regression, including difficulties in using physical insight and over-fitting problems. This paper demonstrates that EPR is good, both in interpolating data and in scientific knowledge discovery. As an illustration, EPR is used to identify polynomial formulae with progressively increasing levels of noise, to interpolate the Colebrook-White formula for a pipe resistance coefficient and to discover a formula for a resistance coefficient from experimental data.