Prediction of cutting forces is very important for the design of cutting tools and for process planning. This paper presents a fuzzy modelling method of cutting forces based on subtractive clustering. The subtractive clustering combined with the least-square algorithm identifies the fuzzy prediction model directly from the information obtained from the sensors. In the micro-milling experimental...

The hysteretic nonlinear dependence of pre-sliding friction force on displacement is modeled using different physics-based and black-box approaches including various Maxwell-slip models, NARX models, neural networks, nonparametric (local) models and dynamical networks. The efficiency and accuracy of these identification methods is compared for an experimental time series where the observed fric...

Fundamental barriers to advancing weather and climate diagnosis and prediction on time-scales from days to years are partly attributable to gaps in knowledge and the limited capability of contemporary operational and research numerical prediction systems to represent precipitating convection and its multiscale organization, particularly in the tropics. In this regard improvements in convective ...

Statistical methods for evaluating the predictive capability of computational models are tested and illustrated for a Sandia National Laboratories case study pertaining to the degradation of polyurethane foam in a thermal environment. A newly developed computational model of this phenomenon is compared to a suite of nine experiments. The statistical analysis focuses on characterizing prediction...

The prediction of the structures and interactions of biological macromolecules at the atomic level and the design of new structures and interactions are critical tests of our understanding of the interatomic interactions that underlie molecular biology. Equally important, the capability to accurately predict and design macromolecular structures and interactions would streamline the interpretati...

The Aero Repair and Overhaul industry is facing an increasing challenge of prediction and scheduling of engine overhauls to remain competitive in a complex business arena. An appropriate technology solution is required to achieve efficient schedules while satisfying multiple opposing constraints in a highly dynamic environment. In this paper, we describe Overhaul Prediction and Scheduling, an a...

In this paper, we propose a method to predict the block error rate performance of the wireless links in OFDM communication systems. Our approach relies on a performance prediction methodology that uses the mean mutual information per coded bit as quality measure. We make a simplification within this methodology such that, contrary to existing approaches, our method needs the generation and stor...

A methodology combining molecular structure represented by fragments, and artificial neural network (ANN) was applied for the prediction of a new acetylcholinesterase (AChE; EC 3.1.1.7) reactivator. We searched for a new structure of the AChE reactivator with the capability of reactivating AChE inhibited by almost all actual nerve agents. For this purpose, we have tested in vitro seventeen pote...

This paper presents an improved reaching law, and a sliding mode speed controller, based on the improved reaching law and grey prediction compensator, is presented for an Electro-Hydraulic Velocity Servo System. The proposed control strategy can forecast and reject the disturbances and parameter variations. This system has a fast response and a good disturbance rejection capability. The numeric...

Performance predictions of component assemblies and obtaining performance properties from these predictions are a crucial success factor for component based systems. The number of methods and tools has been developed that analyze the performance of software systems. These methods and tools aim at helping software engineers by providing them with the capability to understand design trade-offs an...