Development of predictive models for cement stabilized soils

Factors that affect the engineering properties of cement stabilized soils such as strength are discussed in this paper using data on these factors. The selected factors studied in this paper are initial soil water content, grain size distribution, organic matter content, binder dosage, age and curing temperature, which has been collated from a number of international deep mixing projects. Some resulting correlations from this data are discussed and presented. The concept of Artificial Neural Networks and its applicability in developing predictive models for deep mixed soils is presented and discussed using a subset of the collated data. The results from the neural network model were found to emulate the known trends and reasonable estimates of strength as a function of the selected variables were obtained. © 2012 American Society of Civil Engineers.

Introduction to the development of an information management system for soil mix technology using artificial neural networks

This paper introduces current work in collating data from different projects using soil mix technology and establishing trends using artificial neural networks (ANNs). Variation in unconfined compressive strength as a function of selected soil mix variables (e.g., initial soil water content and binder dosage) is observed through the data compiled from completed and on-going soil mixing projects around the world. The potential and feasibility of ANNs in developing predictive models, which take into account a large number of variables, is discussed. The main objective of the work is the management and effective utilization of salient variables and the development of predictive models useful for soil mix technology design. Based on the observed success in the predictions made, this paper suggests that neural network analysis for the prediction of properties of soil mix systems is feasible. © ASCE 2011.

What kind of friction model is needed to predict brake squeal?

Predictive models of friction-induced vibration have proved elusive despite decades of research. There are many mechanisms that can cause brake squeal; friction coupled systems can be highly sensitive to small perturbations; and the dynamic properties of friction at the contact zone seem to be poorly understood. This paper describes experimental and theoretical work aimed at identifying the key ingredients of a predictive model. A large-scale experiment was carried out to identify squeal initiations using a pin-on-disc test rig: approximately 30,000 squeal initiations were recorded, covering a very wide range of frequencies. The theoretical model allows for completely general linear systems coupled at a single sliding point by friction: squeal is predicted using a linearised stability analysis. Results will be presented that show that almost all observed squeal events can be predicted within this model framework, but that some subsets require innovative friction modelling: predictions are highly dependent on the particular choice of friction model and its associated parameters. Copyright © 2012 by ASME.

What kind of friction model is needed to predict brake squeal?

Predictive models of friction-induced vibration have proved elusive despite decades of research. There are many mechanisms that can cause brake squeal; friction coupled systems can be highly sensitive to small perturbations; and the dynamic properties of friction at the contact zone seem to be poorly understood. This paper describes experimental and theoretical work aimed at identifying the key ingredients of a predictive model. A large-scale experiment was carried out to identify squeal initiations using a pin-on-disc test rig: approximately 30,000 squeal initiations were recorded, covering a very wide range of frequencies. The theoretical model allows for completely general linear systems coupled at a single sliding point by friction: squeal is predicted using a linearised stability analysis. Results will be presented that show that almost all observed squeal events can be predicted within this model framework, but that some subsets require innovative friction modelling: predictions are highly dependent on the particular choice of friction model and its associated parameters. Copyright © 2012 by ASME.

Linear quadratic game and non-cooperative predictive methods for potential application to modelling driver-AFS interactive steering control

This paper is concerned with the modelling of strategic interactions between the human driver and the vehicle active front steering (AFS) controller in a path-following task where the two controllers hold different target paths. The work is aimed at extending the use of mathematical models in representing driver steering behaviour in complicated driving situations. Two game theoretic approaches, namely linear quadratic game and non-cooperative model predictive control (non-cooperative MPC), are used for developing the driver-AFS interactive steering control model. For each approach, the open-loop Nash steering control solution is derived; the influences of the path-following weights, preview and control horizons, driver time delay and arm neuromuscular system (NMS) dynamics are investigated, and the CPU time consumed is recorded. It is found that the two approaches give identical time histories as well as control gains, while the non-cooperative MPC method uses much less CPU time. Specifically, it is observed that the introduction of weight on the integral of vehicle lateral displacement error helps to eliminate the steady-state path-following error; the increase in preview horizon and NMS natural frequency and the decline in time delay and NMS damping ratio improve the path-following accuracy. © 2013 Copyright Taylor and Francis Group, LLC.

Predictive techniques for turbulent oscillatory flows

The prediction of turbulent oscillatory flow at around transitional Reynolds numbers is considered for an idealized electronics system. To assess the accuracy of turbulence models, comparison is made with measurements. A stochastic procedure is used to recover instantaneous velocity time traces from predictions. This procedure enables more direct comparison with turbulence intensity measurements which have not been filtered to remove the oscillatory flow component. Normal wall distances, required in some turbulence models, are evaluated using a modified Poisson equation based technique. A range of zero, one and two equation turbulence models are tested, including zonal and a non-linear eddy viscosity models. The non-linear and zonal models showed potential for accuracy improvements.

Assessing boost-assist options for turbocharged engines using 1-D engine simulation and model predictive control

Delivering acceptable low end torque and good transient response is a significant challenge for all turbocharged engines. As downsized gasoline engines and Diesel engines make up a larger and larger proportion of the light-duty engines entering the market, the issue takes on greater significance. Several schemes have been proposed to improve torque response in highly boosted engines, including the use of electrical assist turbochargers and compressed air assist. In this paper we examine these methods with respect to their effectiveness in improving transient response and their relative performance along with some of the practical considerations for real world application. Results shown in this paper are from 1-D simulations using the Ricardo WAVE software package. The simulation model is based on a production light-duty Diesel engine modified to allow the introduction of compressed air at various points in the air-path as well as direct torque application to the turbocharger shaft (such as might be available from an electrical assist turbocharger). Whilst the 1-D simulation software provides a suitable environment for investigating the various boost assistance options, the overall air path performance also depends upon the control system. The introduction of boost assistance complicates the control in two significant ways: the system may run into constraints (such as compressor surge) that are not encountered in normal operation and the assistance introduces an additional control input. Production engine controllers are usually based on gain-scheduled PID control and extensive calibration. For this study, the non-linear nature of the engine together with the multiple configurations considered and the slower than real-time execution of 1-D models makes such an approach time consuming. Moreover, an ad-hoc approach would leave some doubt as to the fairness of comparisons between the different boost-assist options. Model Predictive Control has been shown to offer a convenient approach to controlling the 1-D simulations in a close to optimal manner for a typical Diesel VGT-EGR air path configuration. We show that the same technique can be applied to all the considered assistance methods with only modest calibration effort required. Copyright © 2012 SAE International.

Model based control for closed loop testing of 1-D engine simulation models

1-D engine simulation models are widely used for the analysis and verification of air-path design concepts and prediction of the resulting engine transient response. The latter often requires closed loop control over the model to ensure operation within physical limits and tracking of reference signals. For this purpose, a particular implementation of Model Predictive Control (MPC) based on a corresponding Mean Value Engine Model (MVEM) is reported here. The MVEM is linearised on-line at each operating point to allow for the formulation of quadratic programming (QP) problems, which are solved as the part of the proposed MPC algorithm. The MPC output is used to control a 1-D engine model. The closed loop performance of such a system is benchmarked against the solution of a related optimal control problem (OCP). As an example this study is focused on the transient response of a light-duty car Diesel engine. For the cases examined the proposed controller implementation gives a more systematic procedure than other ad-hoc approaches that require considerable tuning effort. © 2012 IFAC.