Farzad Ahmadkhanlou

Optimum cost design of reinforced concrete slabs using neural dynamics model

For structural optimization algorithms to find widespread usage among practicing engineering they must be formulated as cost optimization and applied to realistic structures subjected to the actual constraints of commonly used design codes such as the ACI code. In this article, a general formulation is presented for cost optimization of single- and multiple-span RC slabs with various end conditions (simply supported, one end continuous, both ends continuous, and cantilever) subjected to all the constraints of the ACI code. The problem is formulated as a mixed integer-discrete variable optimization problem with three design variables: thickness of slab, steel bar diameter, and bar spacing. The solution is obtained in two stages. In the first stage, the neural dynamics model of Adeli and Park is used to obtain an optimum solution assuming continuous variables. Next, the problem is formulated as a mixed integer-discrete optimization problem and solved using a perturbation technique in order to find practical values for the design variables. Practicality, robustness, and excellent convergence properties of the algorithm are demonstrated by application to four examples.

The development of variably compliant haptic systems using magnetorheological fluids

In this study the authors develop haptic systems for telerobotic surgery. In order to model the full range of tactile force exhibited from an MR damper a microstructural, kinetic theory-based model of Magnetorheological (MR) fluids has been developed. Microscale constitutive equations relating flow, stress, and particle orientation are produced. The model developed is fully vectorial and relationships between the stress tensor and the applied magnetic field vector are fully exploited. The higher accuracy of the model in this regard gives better force representations of highly compliant objects. This model is then applied in force feedback control of single degree of freedom (SDOF) and two degrees of freedom (2DOF) systems. Carbonyl iron powders with different particle sizes mixed with silicone oils with different viscosities are used to make several sample MR fluids. These MR fluid samples are then used in three different designed MR dampers. A State feedback control algorithm is employed to control a SDOF system and tracking a 2-D profile path using a special innovative MR force feedback joystick. The results indicate that the MR based force feedback dampers can be used as effective haptic devices. The systems designed and constructed in this paper can be extended to a three degree of freedom force feedback system appropriate for telerobotic surgery.

A magnetorheological fluid-based controllable active knee brace

High customization costs and reduction of natural mobility put current rehabilitative knee braces at a disadvantage. A resolution to this problem is to integrate a Magnetorheological (MR) fluid-based joint into the system. A MR joint will allow patients to apply and control a resistive torque to knee flexion and extension. The resistance torque can also be continuously adjusted as a function of extension angle and patient strength (or as a function of time), which is currently impossible with state of the art rehabilitative knee braces. A novel MR fluid-based controllable knee brace is designed and prototyped in this research. The device exhibits large resistive torque in the on-state and low resistance in the offstate. The controllable variable stiffness, compactness, and portability of the system make it a proper alternative to current rehabilitative knee braces.

An Improved Model for Magnetorheological Fluid-Based Actuators and Sensors:

The resistance to flow of magnetorheological (MR) fluids is greatly increased by the application of a magnetic field. At present, most devices exploiting this MR fluid behavior are pistons executing straight-line motion. The MR fluids in these devices are subjected to shear flow, and are modeled by either the Bingham plastic or Herschel-Buckley models, both 1D, phenomenological continuum-level forms relating strain rate, magnetic field magnitude, and stress magnitude, and fit to continuum-level empirical measurements. We employ a multiscale model of the MR fluid introduced in an earlier paper, which integrates nanoscale behavior over a mesoscale volume to deduce continuum properties. This approach replaces many of the phenomenological features of the Bingham plastic and Herschel-Buckley models with first principles, and isolates those few phenomenological features that remain into a single scalar term. The model is compared to the Bingham plastic and Herschel-Buckley models, assessing each model’s ability to capture the experimentally measured mechanical response of a particular MR fluid-based damper to specified magnetic fields. The result of this comparison is that, our model possesses the flexibility to best match the measured behavior of the MR fluid device observed in our experiments, with fewer required experimental measurements.

Modeling and Control of Single and Two Degree of Freedom Magnetorheological Fluid-based Haptic Systems for Telerobotic Surgery

In this study, the authors develop haptic systems for telerobotic surgery exploiting MR fluids for semiactive force feedback. To investigate the full range of tactile force exhibited by a particular MR damper design, a microstructural 3D kinetic theory-based model of MR fluids has been developed. In this model, microscale constitutive equations relate flow, stress, and particle orientation. The higher accuracy of the model in this regard gives better force representations of highly compliant objects. In this article, the model is utilized in force-feedback control of both a SDOF system and a 2DOF system. A state-feedback control algorithm is employed to track both the SDOF system, and the 2DOF system using specially designed MR force-feedback joysticks. The results demonstrate that the MR fluid-based force-feedback joysticks can be used effectively as haptic devices. It is also observed that both SDOF and 2DOF systems are nearly transparent in replicating the stiffness of different external objects, due to the light weight of the semiactive system and controller implementation.

A magnetorheological fluid based orthopedic active knee brace

The disadvantage of current knee braces ranges from high cost for customization to a loss in physical mobility and limited rehabilitative value. One approach to solving this problem is to use a Magnetorheological (MR) device to make the knee brace have a controllable resistance. Our design solution is to replace the manufacturers joint with an rotary MR fluid based shear damper. The device is designed based on a maximum yield stress, a corresponding magnetic field, a torque and the MR fluid viscosity. The analytical and experimental results show the advantages and the feasibility of using the proposed MR based controllable knee braces.

Microstructural Analysis and Control of Magneto-Rheological Fluid

Characteristic phenomenological behavior of MR fluids is typically modeled by Bingham’s equation, which has no fundamental connection to the microstructure of MR fluid and the fully coupled mechanical-electrical-magnetic equations. In this paper microstructurally, kinetic theory-based model of MR fluids (consisting of micro-sized ferrous particles suspended in a Newtonian fluid) are developed. For modeling these composite systems, dumbbell models in which two beads joined by an elastic connector are investigated. In these models the distributed forces from the carrier fluid and from the magnetic field on the suspended particle are idealized as being localized on beads. Microscale constitutive equations relating flow, stress, and particle orientation are produced by integrating the coupled equations governing forces, flow, and orientation over a representative volume of particles and carrier fluid. Coefficients in the constitutive equations are specified not by a fit to macroscale experimental flow measurement but rather in terms of primitive measurements of particle microstructure, carrier fluid, viscosity and density, and temperature. These new models for MR fluids are three dimensional and applicable to any flow geometry, while the Bingham plastic model is in general applicable only to shear flow. The models in this paper reduce to forms similar to Bingham’s model in a simple shear flow, but with coefficients which arise from fundamental electromagnetic considerations and microstructural features such as geometrical, magnetic and mechanical characterization of the particles, quantities measured primitively from the carrier fluid, magnetic field and temperature.Copyright

Hybrid Lithium-ion/Ultracap energy storage systems for plug-in hybrid electric vehicles

Battery technologies to maximize power density and energy density simultaneously are not commercially feasible. The use of bi-directional DC-DC converter allows use of multiple energy storage systems, and the flexible DC-link voltages can enhance the system efficiency and reduce component sizing. In this paper we have conducted vehicle level study and modeling to quantify the benefit of bi-directional DC-DC converter in hybrid energy storage systems for vehicles. The goal of this study is to reduce the overall cost of plug-in hybrid electric vehicle (PHEV) and demonstrate high power density and efficiency by hybrid energy storage system, including a Lithium-ion battery, an Ultracap, and two DC-DC converters. The simulation results show the PHEV with hybrid energy storage system has better performance over the conventional PHEV. The hybrid energy storage system allows the best utilization of Ultracap and battery technologies for both high power density and high energy density.

Local and global optimization of exportable vehicle power based smart microgrid

This paper investigates the technical feasibility of a smart microgrid that includes (i) exportable vehicle power system (EVPS) units, (ii) Auxiliary Power Supply (APU) units, and (iii) utility distribution system. The Cognitive Power Management (CPM) of the microgrid is introduced based on the availability of communications, to optimize operation of the overall microgird system in terms of fuel consumption. The CPM uses CAN based communications and forms the “intelligence” of the microgrid. The primary objective of this study is to provide strategies for the local and global optimal fuel consumption of the combined EVPS and APU units. To highlight the salient performance features of the cognitive microgrid, a comparison between a conventional microgrid control strategy and the cognitive power management based microgird is also performed.

All-printed smart structures: a viable option?

The last two decades have seen evolution of smart materials and structures technologies from theoretical concepts to physical realization in many engineering fields. These include smart sensors and actuators, active damping and vibration control, biomimetics, and structural health monitoring. Recently, additive manufacturing technologies such as 3D printing and printed electronics have received attention as methods to produce 3D objects or electronic components for prototyping or distributed manufacturing purposes. In this paper, the viability of manufacturing all-printed smart structures, with embedded sensors and actuators, will be investigated. To this end, the current 3D printing and printed electronics technologies will be reviewed first. Then, the plausibility of combining these two different additive manufacturing technologies to create all-printed smart structures will be discussed. Potential applications for this type of all-printed smart structures include most of the traditional smart structures where sensors and actuators are embedded or bonded to the structures to measure structural response and cause desired static and dynamic changes in the structure.