Modelling metal cutting using modern ductile fracture mechanics: Quantitative explanations for some longstanding problems

The assumption that negligible work is involved in the formation of new surfaces in the machining of ductile metals, is re-examined in the light of both current Finite Element Method (FEM) simulations of cutting and modern ductile fracture mechanics. The work associated with separation criteria in FEM models is shown to be in the kJ/m2 range rather than the few J/m2 of the surface energy (surface tension) employed by Shaw in his pioneering study of 1954 following which consideration of surface work has been omitted from analyses of metal cutting. The much greater values of surface specific work are not surprising in terms of ductile fracture mechanics where kJ/m2 values of fracture toughness are typical of the ductile metals involved in machining studies. This paper shows that when even the simple Ernst–Merchant analysis is generalised to include significant surface work, many of the experimental observations for which traditional ‘plasticity and friction only’ analyses seem to have no quantitative explanation, are now given meaning. In particular, the primary shear plane angle φ becomes material-dependent. The experimental increase of φ up to a saturated level, as the uncut chip thickness is increased, is predicted. The positive intercepts found in plots of cutting force vs. depth of cut, and in plots of force resolved along the primary shear plane vs. area of shear plane, are shown to be measures of the specific surface work. It is demonstrated that neglect of these intercepts in cutting analyses is the reason why anomalously high values of shear yield stress are derived at those very small uncut chip thicknesses at which the so-called size effect becomes evident. The material toughness/strength ratio, combined with the depth of cut to form a non-dimensional parameter, is shown to control ductile cutting mechanics. The toughness/strength ratio of a given material will change with rate, temperature, and thermomechanical treatment and the influence of such changes, together with changes in depth of cut, on the character of machining is discussed. Strength or hardness alone is insufficient to describe machining. The failure of the Ernst–Merchant theory seems less to do with problems of uniqueness and the validity of minimum work, and more to do with the problem not being properly posed. The new analysis compares favourably and consistently with the wide body of experimental results available in the literature. Why considerable progress in the understanding of metal cutting has been achieved without reference to significant surface work is also discussed.

Failure of a control strategy for a hybrid air-conditioning and wind catchers/towers system at Bluewater shopping malls in Kent

Purpose – To evaluate the control strategy for a hybrid natural ventilation wind catchers and air-conditioning system and to assess the contribution of wind catchers to indoor air environments and energy savings if any. Design/methodology/approach – Most of the modeling techniques for assessing wind catchers performance are theoretical. Post-occupancy evaluation studies of buildings will provide an insight into the operation of these building components and help to inform facilities managers. A case study for POE was presented in this paper. Findings – The monitoring of the summer and winter month operations showed that the indoor air quality parameters were kept within the design target range. The design control strategy failed to record data regarding the operation, opening time and position of wind catchers system. Though the implemented control strategy was working effectively in monitoring the operation of mechanical ventilation systems, i.e. AHU, did not integrate the wind catchers with the mechanical ventilation system. Research limitations/implications – Owing to short-falls in the control strategy implemented in this project, it was found difficult to quantify and verify the contribution of the wind catchers to the internal conditions and, hence, energy savings. Practical implications – Controlling the operation of the wind catchers via the AHU will lead to isolation of the wind catchers in the event of malfunctioning of the AHU. Wind catchers will contribute to the ventilation of space, particularly in the summer months. Originality/value – This paper demonstrates the value of POE as indispensable tool for FM professionals. It further provides insight into the application of natural ventilation systems in building for healthier indoor environments at lower energy cost. The design of the control strategy for natural ventilation and air-conditioning should be considered at the design stage involving the FM personnel.

A conceptual design of a wireless sensor actuator system for optimising energy and well-being in a building

This article presents a prototype model based on a wireless sensor actuator network (WSAN) aimed at optimizing both energy consumption of environmental systems and well-being of occupants in buildings. The model is a system consisting of the following components: a wireless sensor network, `sense diaries', environmental systems such as heating, ventilation and air-conditioning systems, and a central computer. A multi-agent system (MAS) is used to derive and act on the preferences of the occupants. Each occupant is represented by a personal agent in the MAS. The sense diary is a new device designed to elicit feedback from occupants about their satisfaction with the environment. The roles of the components are: the WSAN collects data about physical parameters such as temperature and humidity from an indoor environment; the central computer processes the collected data; the sense diaries leverage trade-offs between energy consumption and well-being, in conjunction with the agent system; and the environmental systems control the indoor environment.

Efficient fuzzy control of a rotary inverted pendulum based on LQR mapping

This paper develops fuzzy methods for control of the rotary inverted pendulum, an underactuated mechanical system. Two control laws are presented, one for swing up and another for the stabilization. The pendulum is swung up from the vertical down stable position to the upward unstable position in a controlled trajectory. The rules for the swing up are heuristically written such that each swing results in greater energy build up. The stabilization is achieved by mapping a stabilizing LQR control law to two fuzzy inference engines, which reduces the computational load compared with using a single fuzzy inference engine. The robustness of the balancing control is tested by attaching a bottle of water at the tip of the pendulum.

Multi-agent building control in shared environment

Multi-agent systems have been adopted to build intelligent environment in recent years. It was claimed that energy efficiency and occupants' comfort were the most important factors for evaluating the performance of modem work environment, and multi-agent systems presented a viable solution to handling the complexity of dynamic building environment. While previous research has made significant advance in some aspects, the proposed systems or models were often not applicable in a "shared environment". This paper introduces an ongoing project on multi-agent for building control, which aims to achieve both energy efficiency and occupants' comfort in a shared environment.

An enhanced relay-enabled medium access control protocol for wireless ad hoc networks

In this paper we propose an enhanced relay-enabled distributed coordination function (rDCF) for wireless ad hoc networks. The idea of rDCF is to use high data rate nodes to work as relays for the low data rate nodes. The relay helps to increase the throughput and lower overall blocking time of nodes due to faster dual-hop transmission. rDCF achieves higher throughput over IEEE 802.11 distributed coordination function (DCF). The protocol is further enhanced for higher throughput and reduced energy. These enhancements result from the use of a dynamic preamble (i.e. using short preamble for the relay transmission) and also by reducing unnecessary overhearing (by other nodes not involved in transmission). We have modeled the energy consumption of rDCF, showing that rDCF provides an energy efficiency of 21.7% at 50 nodes over 802.11 DCF. Compared with the existing rDCF, the enhanced rDCF (ErDCF) scheme proposed in this paper yields a throughput improvement of 16.54% (at the packet length of 1000 bytes) and an energy saving of 53% at 50 nodes.

Modelling energy consumption of relay-enabled MAC protocols in ad hoc networks

To enhance the throughput of ad hoc networks, dual-hop relay-enabled transmission schemes have recently been proposed. Since in ad hoc networks throughput is normally related to their energy consumption, it is important to examine the impact of using relay-enabled transmissions on energy consumption. In this paper, we present an analytical energy consumption model for dual-hop relay-enabled medium access control (MAC) protocols. Based on the recently reported relay-enabled distributed coordination function (rDCF), we have shown the efficacy of the proposed analytical model. This is a generalized model and can be used to predict energy consumption in saturated relay-enabled ad hoc networks via energy decomposition. This is helpful in designing MAC protocols for cooperative communications and it is shown that using a relay results not only in a better throughput but also better energy efficiency.

Modeling energy consumption of dual-hop relay based MAC protocols in ad hoc networks

Given that the next and current generation networks will coexist for a considerable period of time, it is important to improve the performance of existing networks. One such improvement recently proposed is to enhance the throughput of ad hoc networks by using dual-hop relay-based transmission schemes. Since in ad hoc networks throughput is normally related to their energy consumption, it is important to examine the impact of using relay-based transmissions on energy consumption. In this paper, we present an analytical energy consumption model for dual-hop relay-based medium access control (MAC) protocols. Based on the recently reported relay-enabled Distributed Coordination Function (rDCF), we have shown the efficacy of the proposed analytical model. This is a generalized model and can be used to predict energy consumption in saturated relay-based ad hoc networks. This model can predict energy consumption in ideal environment and with transmission errors. It is shown that using a relay results in not only better throughput but also better energy efficiency. Copyright (C) 2009 Rizwan Ahmad et al.

Optimal kinematic control of an autonomous underwater vehicle

This note investigates the motion control of an autonomous underwater vehicle (AUV). The AUV is modeled as a nonholonomic system as any lateral motion of a conventional, slender AUV is quickly damped out. The problem is formulated as an optimal kinematic control problem on the Euclidean Group of Motions SE(3), where the cost function to be minimized is equal to the integral of a quadratic function of the velocity components. An application of the Maximum Principle to this optimal control problem yields the appropriate Hamiltonian and the corresponding vector fields give the necessary conditions for optimality. For a special case of the cost function, the necessary conditions for optimality can be characterized more easily and we proceed to investigate its solutions. Finally, it is shown that a particular set of optimal motions trace helical paths. Throughout this note we highlight a particular case where the quadratic cost function is weighted in such a way that it equates to the Lagrangian (kinetic energy) of the AUV. For this case, the regular extremal curves are constrained to equate to the AUV's components of momentum and the resulting vector fields are the d'Alembert-Lagrange equations in Hamiltonian form.

Design of a minimum variance multiple input-multiple output neuro self-tuning proportional-integral-derivative controller for non-linear dynamic systems

In this study a minimum variance neuro self-tuning proportional-integral-derivative (PID) controller is designed for complex multiple input-multiple output (MIMO) dynamic systems. An approximation model is constructed, which consists of two functional blocks. The first block uses a linear submodel to approximate dominant system dynamics around a selected number of operating points. The second block is used as an error agent, implemented by a neural network, to accommodate the inaccuracy possibly introduced by the linear submodel approximation, various complexities/uncertainties, and complicated coupling effects frequently exhibited in non-linear MIMO dynamic systems. With the proposed model structure, controller design of an MIMO plant with n inputs and n outputs could be, for example, decomposed into n independent single input-single output (SISO) subsystem designs. The effectiveness of the controller design procedure is initially verified through simulations of industrial examples.

Design, implementation and testing of an intelligent knowledge-based system for the supervisory control of a hot rolling mill

This paper describes the design, implementation and testing of an intelligent knowledge-based supervisory control (IKBSC) system for a hot rolling mill process. A novel architecture is used to integrate an expert system with an existing supervisory control system and a new optimization methodology for scheduling the soaking pits in which the material is heated prior to rolling. The resulting IKBSC system was applied to an aluminium hot rolling mill process to improve the shape quality of low-gauge plate and to optimise the use of the soaking pits to reduce energy consumption. The results from the trials demonstrate the advantages to be gained from the IKBSC system that integrates knowledge contained within data, plant and human resources with existing model-based systems. (c) 2005 Elsevier Ltd. All rights reserved.

A model of intelligent building energy management for the indoor environment

People's interaction with the indoor environment plays a significant role in energy consumption in buildings. Mismatching and delaying occupants' feedback on the indoor environment to the building energy management system is the major barrier to the efficient energy management of buildings. There is an increasing trend towards the application of digital technology to support control systems in order to achieve energy efficiency in buildings. This article introduces a holistic, integrated, building energy management model called `smart sensor, optimum decision and intelligent control' (SMODIC). The model takes into account occupants' responses to the indoor environments in the control system. The model of optimal decision-making based on multiple criteria of indoor environments has been integrated into the whole system. The SMODIC model combines information technology and people centric concepts to achieve energy savings in buildings.

Redox control of light-induced charge separation in a transition metal cluster: photochemistry of a methyl viologen-substituted [Os-3(CO)10(a-diimine)] cluster

Sub)picosecond transient absorption (TA) and time-resolved infrared (TRIR) spectra of the cluster [OS3(CO)(10-) (AcPy-MV)](2+) (the clication AcPy-MV = Acpy-MV2+ = [2-pyridylacetimine-N-(2-(1'-methyl-4,4'-bipyridine-1,1'-diium-1-yl) ethyl)] (PF6)(2)) (1(2+)) reveal that photoinduced electron transfer to the electron-accepting 4,4'-bipyridine-1,1'diium (MV2+) moiety competes with the fast relaxation of the initially populated sigmapi* excited state of the cluster to the ground state and/or cleavage of an Os-Os bond. The TA spectra of cluster 12 in acetone, obtained by irradiation into its lowest-energy absorption band, show the characteristic absorptions of the one-electron-reduced MV*(+) unit at 400 and 615 nm, in accordance with population of a charge-separated (CS) state in which a cluster-core electron has been transferred to the lowest pi* orbital of the remote MV2+ unit. This assignment is confirmed by picosecond TRIR spectra that show a large shift of the pilot highest-frequency nu(CO) band of 1(2+) by ca. +40 cm(-1), reflecting the photooxidation of the cluster core. The CS state is populated via fast (4.2 x 10(11) s(-1)) and efficient (88%) oxidative quenching of the optically populated sigmapi* excited state and decays biexponentially with lifetimes of 38 and 166 ps (1:2:1 ratio) with a complete regeneration of the parent cluster. About 12% of the cluster molecules in the sigmapi* excited state form long-lived open-core biradicals. In strongly coordinating acetonitrile, however, the cluster core-to-MV2+ electron transfer in cluster 12+ results in the irreversible formation of secondary photoproducts with a photooxidized cluster core. The photochemical behavior of the [Os-3(CO)(10)(alpha-diimine-MV)](2+) (donor-acceptor) dyad can be controlled by an externally applied electronic bias. Electrochemical one-electron reduction of the MV2+ moiety prior to the irradiation reduces its electron-accepting character to such an extent that the photoinduced electron transfer to MV*+ is no longer feasible. Instead, the irradiation of reduced cluster 1(.)+ results in the reversible formation of an open-core zwitterion, the ultimate photoproduct also observed upon irradiation of related nonsubstituted clusters [Os-3(CO)(10)(alpha-diimine)] in strongly coordinating solvents such as acetonitrile.

Kinetic energy analysis of the response of the Atlantic meridional overturning circulation to CO2-forced climate change

Atmosphere–ocean general circulation models (AOGCMs) predict a weakening of the Atlantic meridional overturning circulation (AMOC) in response to anthropogenic forcing of climate, but there is a large model uncertainty in the magnitude of the predicted change. The weakening of the AMOC is generally understood to be the result of increased buoyancy input to the north Atlantic in a warmer climate, leading to reduced convection and deep water formation. Consistent with this idea, model analyses have shown empirical relationships between the AMOC and the meridional density gradient, but this link is not direct because the large-scale ocean circulation is essentially geostrophic, making currents and pressure gradients orthogonal. Analysis of the budget of kinetic energy (KE) instead of momentum has the advantage of excluding the dominant geostrophic balance. Diagnosis of the KE balance of the HadCM3 AOGCM and its low-resolution version FAMOUS shows that KE is supplied to the ocean by the wind and dissipated by viscous forces in the global mean of the steady-state control climate, and the circulation does work against the pressure-gradient force, mainly in the Southern Ocean. In the Atlantic Ocean, however, the pressure-gradient force does work on the circulation, especially in the high-latitude regions of deep water formation. During CO2-forced climate change, we demonstrate a very good temporal correlation between the AMOC strength and the rate of KE generation by the pressure-gradient force in 50–70°N of the Atlantic Ocean in each of nine contemporary AOGCMs, supporting a buoyancy-driven interpretation of AMOC changes. To account for this, we describe a conceptual model, which offers an explanation of why AOGCMs with stronger overturning in the control climate tend to have a larger weakening under CO2 increase.

Neural network enhanced generalised minimum variance self-tuning controller for nonlinear discrete-time systems

A neural network enhanced self-tuning controller is presented, which combines the attributes of neural network mapping with a generalised minimum variance self-tuning control (STC) strategy. In this way the controller can deal with nonlinear plants, which exhibit features such as uncertainties, nonminimum phase behaviour, coupling effects and may have unmodelled dynamics, and whose nonlinearities are assumed to be globally bounded. The unknown nonlinear plants to be controlled are approximated by an equivalent model composed of a simple linear submodel plus a nonlinear submodel. A generalised recursive least squares algorithm is used to identify the linear submodel and a layered neural network is used to detect the unknown nonlinear submodel in which the weights are updated based on the error between the plant output and the output from the linear submodel. The procedure for controller design is based on the equivalent model therefore the nonlinear submodel is naturally accommodated within the control law. Two simulation studies are provided to demonstrate the effectiveness of the control algorithm.