Global efficiency of innovative rotational mold directly heated by thermal fluid

The article is focused on analysis of global efficiency of new mold for rotational molding of plastic parts, being directly heated by thermal fluid. The overall efficiency is based on several items such as reduction of cycle time, better uniformity of heating-cooling and low energy consumption. The new tool takes advantage of additive fabrication and electroforming for making the optimal manifold and cavity shell of the mold. Experimental test of a prototype mold was carried out on an experimental rotational molding machine, developed for this purpose, measuring wall temperature, and internal air temperature, with and without plastic material inside. Results were compared with conventional mold heated into an oven and to theoretical simulations done by Computational Fluid Dynamic software (CFD). The analysis represents considerable improvement of cycle time related to conventional methods (heated by oven) and better thermal uniformity to conventional procedures by direct heating of oil with external channels. In addition to thermal analysis an energetic efficiency study was done. POLYM. ENG. SCI., 52:1998-2005, 2012. © 2012 Society of Plastics Engineers Copyright © 2012 Society of Plastics Engineers.

Model reduction for nonlinear aeroelasticity using the Discrete Empirical Interpolation Method

A novel surrogate model is proposed in lieu of computational fluid dynamic (CFD) code for fast nonlinear aerodynamic modeling. First, a nonlinear function is identified on selected interpolation points defined by discrete empirical interpolation method (DEIM). The flow field is then reconstructed by a least square approximation of flow modes extracted by proper orthogonal decomposition (POD). The proposed model is applied in the prediction of limit cycle oscillation for a plunge/pitch airfoil and a delta wing with linear structural model, results are validate against a time accurate CFD-FEM code. The results show the model is able to replicate the aerodynamic forces and flow fields with sufficient accuracy while requiring a fraction of CFD cost.

Footbridge system identification using wireless inertial measurement units for force and response measurements

With the main focus on safety, design of structures for vibration serviceability is often overlooked or mismanaged, resulting in some high profile structures failing publicly to perform adequately under human dynamic loading due to walking, running or jumping. A standard tool to inform better design, prove fitness for purpose before entering service and design retrofits is modal testing, a procedure that typically involves acceleration measurements using an array of wired sensors and force generation using a mechanical shaker. A critical but often overlooked aspect is using input (force) to output (response) relationships to enable estimation of modal mass, which is a key parameter directly controlling vibration levels in service.

This paper describes the use of wireless inertial measurement units (IMUs), designed for biomechanics motion capture applications, for the modal testing of a 109 m footbridge. IMUs were first used for an output-only vibration survey to identify mode frequencies, shapes and damping ratios, then for simultaneous measurement of body accelerations of a human subject jumping to excite specific vibrations modes and build up bridge deck accelerations at the jumping location. Using the mode shapes and the vertical acceleration data from a suitable body landmark scaled by body mass, thus providing jumping force data, it was possible to create frequency response functions and estimate modal masses.

The modal mass estimates for this bridge were checked against estimates obtained using an instrumented hammer and known mass distributions, showing consistency among the experimental estimates. Finally, the method was used in an applied research application on a short span footbridge where the benefits of logistical and operational simplicity afforded by the highly portable and easy to use IMUs proved extremely useful for an efficient evaluation of vibration serviceability, including estimation of modal masses.

Data-Driven Dynamic Modeling of Coupled Thermal and Electric Outputs of Microturbines

Microturbines are among the most successfully commercialized distributed energy resources, especially when they are used for combined heat and power generation. However, the interrelated thermal and electrical system dynamic behaviors have not been fully investigated. This is technically challenging due to the complex thermo-fluid-mechanical energy conversion processes which introduce multiple time-scale dynamics and strong nonlinearity into the analysis. To tackle this problem, this paper proposes a simplified model which can predict the coupled thermal and electric output dynamics of microturbines. Considering the time-scale difference of various dynamic processes occuring within microturbines, the electromechanical subsystem is treated as a fast quasi-linear process while the thermo-mechanical subsystem is treated as a slow process with high nonlinearity. A three-stage subspace identification method is utilized to capture the dominant dynamics and predict the electric power output. For the thermo-mechanical process, a radial basis function model trained by the particle swarm optimization method is employed to handle the strong nonlinear characteristics. Experimental tests on a Capstone C30 microturbine show that the proposed modeling method can well capture the system dynamics and produce a good prediction of the coupled thermal and electric outputs in various operating modes.

Identification of Microturbine Model for Long-term Dynamic Analysis of Distribution Networks

As one of the most successfully commercialized distributed energy resources, the long-term effects of microturbines (MTs) on the distribution network has not been fully investigated due to the complex thermo-fluid-mechanical energy conversion processes. This is further complicated by the fact that the parameter and internal data of MTs are not always available to the electric utility, due to different ownerships and confidentiality concerns. To address this issue, a general modeling approach for MTs is proposed in this paper, which allows for the long-term simulation of the distribution network with multiple MTs. First, the feasibility of deriving a simplified MT model for long-term dynamic analysis of the distribution network is discussed, based on the physical understanding of dynamic processes that occurred within MTs. Then a three-stage identification method is developed in order to obtain a piecewise MT model and predict electro-mechanical system behaviors with saturation. Next, assisted with the electric power flow calculation tool, a fast simulation methodology is proposed to evaluate the long-term impact of multiple MTs on the distribution network. Finally, the model is verified by using Capstone C30 microturbine experiments, and further applied to the dynamic simulation of a modified IEEE 37-node test feeder with promising results.

Data-Driven Dynamic Prediction of Interrelated Heat and Electric Outputs of Microturbines

Microturbines are among the most successfully commercialized distributed energy resources, especially when they are used for combined heat and power generation. However, the interrelated thermal and electrical system dynamic behaviors have not been fully investigated. This is technically challenging due to the complex thermo-fluid-mechanical energy conversion processes which introduce multiple time-scale dynamics and strong nonlinearity into the analysis. To tackle this problem, this paper proposes a simplified model which can predict the coupled thermal and electric output dynamics of microturbines. Considering the time-scale difference of various dynamic processes occuring within microturbines, the electromechanical subsystem is treated as a fast quasi-linear process while the thermo-mechanical subsystem is treated as a slow process with high nonlinearity. A three-stage subspace identification method is utilized to capture the dominant dynamics and predict the electric power output. For the thermo-mechanical process, a radial basis function model trained by the particle swarm optimization method is employed to handle the strong nonlinear characteristics. Experimental tests on a Capstone C30 microturbine show that the proposed modeling method can well capture the system dynamics and produce a good prediction of the coupled thermal and electric outputs in various operating modes.

Direct Field Measurement of the Dynamic Amplification in a Bridge

In this paper, the level of dynamics, as described by the Assessment Dynamic Ratio (ADR), is measured directly through a field test on a bridge in the United Kingdom. The bridge was instrumented using fiber optic strain sensors and piezo-polymer weigh-in-motion sensors were installed in the pavement on the approach road. Field measurements of static and static-plus-dynamic strains were taken over 45 days. The results show that, while dynamic amplification is large for many loading events, these tend not to be the critical events. ADR, the allowance that should be made for dynamics in an assessment of safety, is small.