Simplified model for prediction of compressive strength of alkali-activated natural pozzolans

The assessment of pozzolanic activity is essential for estimating the reaction of a material as pozzolan. Natural pozzolans can be activated and condensed with sodium silicate in an alkaline environment to synthesize high performance cementitious construction materials with low environmental impact. In this paper, the pozzolanic activities of five natural pozzolans are studied. The correlation between type and chemical composition of natural pozzolan, which affects the formation of the geopolymer gel phase, both for the calcined and untreated natural pozzolans, have been reviewed. The improvement in pozzolanic properties was studied following heat treatment including calcinations and/or elevated curing temperature by using alkali solubility, and compressive strength tests. A model was developed to allow prediction of the alkali-activated pozzolan strength versus their chemical compositions, alkali solubility, and crystallinity.

External circuit system effects on chlorine plasma instabilities

The effects of the external circuit on plasma instabilities in all inductive plasma source are investigated. The instabilities are found to be asymmetric with respect to the circuit input impedance. A simplified model of the antenna-plasnia coupling provides an explanation of the asymetry.

Physical Models of Wind Instruments : A Generalized Excitation Coupled with a Modular Tube Simulation Platform

To develop real-time simulations of wind instruments, digital waveguides filters can be used as an efficient representation of the air column. Many aerophones are shaped as horns which can be approximated using conical sections. Therefore the derivation of conical waveguide filters is of special interest. When these filters are used in combination with a generalized reed excitation, several classes of wind instruments can be simulated. In this paper we present the methods for transforming a continuous description of conical tube segments to a discrete filter representation. The coupling of the reed model with the conical waveguide and a simplified model of the termination at the open end are described in the same way. It turns out that the complete lossless conical waveguide requires only one type of filter.Furthermore, we developed a digital reed excitation model, which is purely based on numerical integration methods, i.e., without the use of a look-up table.

A theoretical examination of known and hypothetical clathrate hydrate materials

The recent synthesis of a new hydrogen binary hydrate with the sH structure has highlighted the potential storage capabilities of water clathrates [T. A. Strobel, C. A. Koh, and E. D. Sloan, J. Phys. Chem. B 112, 1885 (2008) and A. R. C. Duarte, A. Shariati, L. J. Rovetto, and C. J. Peters, J. Phys. Chem. B 112, 1888 (2008)]. In this work, the absorption of hydrogen and the promoters used in the experimental work are considered using a simplified model for the host-guest interaction, which allows one to understand the stabilizing effects of multiple help molecules. Two further hypothetical clathrates, which are isostructural with known zeolite structures, are also investigated. It is shown that the energy gained by absorbing adamantane into these two frameworks is far greater than that gained upon absorption of adamantane into the sH structure. Hence, a clathrate with the same topology as the DDR (Sigma 1) zeolite may be synthesizable with adamantane and hydrogen as guest molecules as, in the conditions explored here, this phase appears to be more stable than the sH structure. (C) 2009 American Institute of Physics. [DOI: 10.1063/1.3142503]

Manufacturing at double the speed

The speed of manufacturing processes today depends on a trade-off between the physical processes of production, the wider system that allows these processes to operate and the co-ordination of a supply chain in the pursuit of meeting customer needs. Could the speed of this activity be doubled? This paper explores this hypothetical question, starting with examination of a diverse set of case studies spanning the activities of manufacturing. This reveals that the constraints on increasing manufacturing speed have some common themes, and several of these are examined in more detail, to identify absolute limits to performance. The physical processes of production are constrained by factors such as machine stiffness, actuator acceleration, heat transfer and the delivery of fluids, and for each of these, a simplified model is used to analyse the gap between current and limiting performance. The wider systems of production require the co-ordination of resources and push at the limits of human biophysical and cognitive limits. Evidence about these is explored and related to current practice. Out of this discussion, five promising innovations are explored to show examples of how manufacturing speed is increasing—with line arrays of point actuators, parallel tools, tailored application of precision, hybridisation and task taxonomies. The paper addresses a broad question which could be pursued by a wider community and in greater depth, but even this first examination suggests the possibility of unanticipated innovations in current manufacturing practices.

Linking Parametric CAD with Adjoint Surface Sensitivities

The goal of this work is to present an efficient CAD-based adjoint process chain for calculating parametric sensitivities (derivatives of the objective function with respect to the CAD parameters) in timescales acceptable for industrial design processes. The idea is based on linking parametric design velocities (geometric sensitivities computed from the CAD model) with adjoint surface sensitivities. A CAD-based design velocity computation method has been implemented based on distances between discrete representations of perturbed geometries. This approach differs from other methods due to the fact that it works with existing commercial CAD packages (unlike most analytical approaches) and it can cope with the changes in CAD model topology and face labeling. Use of the proposed method allows computation of parametric sensitivities using adjoint data at a computational cost which scales with the number of objective functions being considered, while it is essentially independent of the number of design variables. The gradient computation is demonstrated on test cases for a Nozzle Guide Vane (NGV) model and a Turbine Rotor Blade model. The results are validated against finite difference values and good agreement is shown. This gradient information can be passed to an optimization algorithm, which will use it to update the CAD model parameters.

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.

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.

Judging Time Intevals using a model of perceptuo-motor control

Estimating a time interval and temporally coordinating movements in space are fundamental skills, but the relationships between these different forms of timing, and the neural processes that they incur, are not well understood. While different theories have been proposed to account for time perception, time estimation, and the temporal patterns of coordination, there are no general mechanisms which unify these various timing skills. This study considers whether a model of perceptuo-motor timing, the tau(GUIDE), can also describe how certain judgements of elapsed time are made. To evaluate this, an equation for determining interval estimates was derived from the tau(GUIDE) model and tested in a task where participants had to throw a ball and estimate when it would hit the floor. The results showed that in accordance with the model, very accurate judgements could be made without vision (mean timing error -19.24 msec), and the model was a good predictor of skilled participants' estimate timing. It was concluded that since the tau(GUIDE) principle provides temporal information in a generic form, it could be a unitary process that links different forms of timing.

Real-time estimation of battery internal temperature based on a simplified thermoelectric model

Li-ion batteries have been widely used in the EVs, and the battery thermal management is a key but challenging part of the battery management system. For EV batteries, only the battery surface temperature can be measured in real-time. However, it is the battery internal temperature that directly affects the battery performance, and large temperature difference may exist between surface and internal temperatures, especially in high power demand applications. In this paper, an online battery internal temperature estimation method is proposed based on a novel simplified thermoelectric model. The battery thermal behaviour is first described by a simplified thermal model, and battery electrical behaviour by an electric model. Then, these two models are interrelated to capture the interactions between battery thermal and electrical behaviours, thus offer a comprehensive description of the battery behaviour that is useful for battery management. Finally, based on the developed model, the battery internal temperature is estimated using an extended Kalman filter. The experimental results confirm the efficacy of the proposed method, and it can be used for online internal temperature estimation which is a key indicator for better real-time battery thermal management.

Simplified theory of wideband spectra of liquid H2O and D2O (from 0 to 1000 cm(-1)) due to reorienting polar and vibrating H-bonded water molecules

A semi-phenomenological molecular model is presented, which is capable of describing with the use of analytical formulae, the wideband dielectric(1) and far-infrared spectra of ordinary and heavy water. In the model the vector of a dipole moment is presented as a sum of two components. The absolute value of the first one is constant; the second one changes harmonically with time. The key aspect of this work is consideration of FIR spectra due to the second component. In the context of the modified hybrid model presented in the work, reorientation of the dipoles in the rectangular potential well is considered, as a result of which the librational (near 700 cm (-1)) and translational (near 200 cm (-1)) absorption bands and the microwave Debye relaxation spectrum arise. It is shown that the time-dependent part of a dipole moment contributes most to the translational band, the relevant mechanism is taken to be stretching vibration of the H-bonded molecules. Previous linear-response molecular models were unsuccessful in describing this band (in heavy water) in terms of the complex dielectric permittivity. The spatial and time scales characteristic of water are estimated. (C) 2002 Elsevier Science B.V. All rights reserved.

Neuromuscular and biomechanical factors codetermine the solution to motor redundancy in rhythmic multijoint arm movement

How the CNS deals with the issue of motor redundancy remains a central question for motor control research. Here we investigate the means by which neuromuscular and biomechanical factors interact to resolve motor redundancy in rhythmic multijoint arm movements. We used a two-df motorised robot arm to manipulate the dynamics of rhythmic flexion-extension (FE) and supination-pronation (SP) movements at the elbow-joint complex. Participants were required to produce rhythmic FE and SP movements, either in isolation, or in combination (at the phase relationship of their choice), while we recorded the activity of key bi-functional muscles. When performed in combination, most participants spontaneously produced an in-phase pattern of coordination in which flexion is synchronised with supination. The activity of the Biceps Brachii (BB), the strongest arm muscle which also has the largest moment arms in both flexion and supination was significantly higher for FE and SP performed in combination than in isolation, suggesting optimal exploitation of the mechanical advantage of this muscle. In a separate condition, participants were required to produce a rhythmic SP movement while a rhythmic FE movement was imposed by the motorised robot. Simulations based upon a musculoskeletal model of the arm demonstrated that in this context, the most efficient use of the force-velocity relationship of BB requires that an anti-phase pattern of coordination (flexion synchronized with pronation) be produced. In practice, the participants maintained the in-phase behavior, and BB activity was higher than for SP performed in isolation. This finding suggests that the neural organisation underlying the exploitation of bifunctional muscle properties, in the natural context, constrains the system to maintain the

A model for radiation-induced bystander effects, with allowance for spatial position and the effects of cell turnover

Bystander effects, whereby cells that are not directly exposed to ionizing radiation exhibit adverse biological effects, have been observed in a number of experimental systems. A novel stochastic model of the radiation-induced bystander effect is developed that takes account of spatial location, cell killing and repopulation. The ionizing radiation dose- and time-responses of this model are explored, and it is shown to exhibit pronounced downward curvature in the high dose-rate region, similar to that observed in many experimental systems, reviewed in the paper. It is also shown to predict the augmentation of effect after fractionated delivery of dose that has been observed in certain experimental systems. It is shown that the generally intractable solution of the full stochastic system can be considerably simplified by assumption of pairwise conditional dependence that varies exponentially over time. (C) 2004 Elsevier Ltd. All rights reserved.