Modeling the full-range deformation behaviors of materials under complex loading and conditions is a significant challenge for constitutive relations (CRs) modeling. We propose general encoder-decoder deep learning framework that can model high-dimensional stress-strain data histories with robustness universal capability. The employs an encoder to project input information (e.g., history, condi...

this study aims at presenting a numerical model for predicting grout flow and penetration length into the jointed rock mass using universal distinct element code (udec). the numerical model is validated using practical data and analytical method for grouting process. input data for the modeling, including geomechanical parameters along with grout properties, were obtained from a case study. the...

Estimation of a camera pose (position and orientation) from an image, given a 3d model of the world, is a topic of great interest in many current fields of research. When aiming for a model based pose estimation approach, several questions arise: What is the model? How do we acquire a model? How is the image linked to the model? How is a pose computed and verified using the latter information? ...

We present a new approach that enables investors to seek a reasonably robust policy for portfolio selection in the presence of rare but high-impact realization of moment uncertainty. In practice, portfolio managers face diffculty in seeking a balance between relying on their knowledge of a reference financial model and taking into account possible ambiguity of the model. Based on the concept of...

A control-oriented identification and uncertainty estimation approach from input-output data is presented, for use in the design of control systems for paper machines. The application of this approach is demonstrated on a high fidelity simulator. An estimate of the process model along with the uncertainty bounds that describe the confidence limits of the model, consistent with the robust contro...

Dynamic optimization allows for the determination of the upper bound of achievable performance in the operation of continuous chemical processes in transient operationwhich often results from load or grade changes. Performance assessment can rely on the computation of optimal trajectories for selected scenarios which properly reflect the operational envelope. Realistic industrial problems, howe...

Architectural design spaces of microprocessors are often exponentially large with respect to the pending processor parameters. To avoid simulating all configurations in the design space, machine learning and statistical techniques have been utilized to build regression models for characterizing the relationship between architectural configurations and responses (e.g., performance or power consu...