Non-intrusive on-the-fly data race detection using execution replay

This paper presents a practical solution for detecting data races in parallel programs. The solution consists of a combination of execution replay (RecPlay) with automatic on-the-fly data race detection. This combination enables us to perform the data race detection on an unaltered execution (almost no probe effect). Furthermore, the usage of multilevel bitmaps and snooped matrix clocks limits the amount of memory used. As the record phase of RecPlay is highly efficient, there is no need to switch it off, hereby eliminating the possibility of Heisenbugs because tracing can be left on all the time.Comment: In M. Ducasse (ed), proceedings of the Fourth International Workshop on Automated Debugging (AAdebug 2000), August 2000, Munich. cs.SE/001003

Modeling deep-bed grain drying using Comsol Multiphysics

CFD simulations were carried out to predict the convective heat and mass transfer coefficients in the rice bed, and correlations were developed for the convective heat and mass transfer coefficients as a function of drying air flow rate. The developed correlations were used to extend the coupled CFD and diffusion model developed by ElGamal et al. (2013) for thinlayer rice drying to volumetric heat and mass transfer in a deep-bed of rice. All mathematical models were solved using the Comsol Multiphysics® simulation program v4.3 (Comsol Inc, Palo Alto), which uses the finite element method to solve the model equations. The model was used to predict the air temperature, as well as the grain moisture content and temperature at different locations of the dryer during the drying process. The theoretical predictions of moisture and temperature profiles inside a deep-bed of rice were verified by experimental data from literature

Multi-scale model for heat and mass transfer during rice drying

Grain drying is a simultaneous heat and moisture transfer problem. The modeling of such a problem is of significance in understanding and controlling the drying process. The main goal of this study was to predict the heat and mass transfer processes during deep-bed rice drying. To achieve this, first, CFD simulations were carried out to analyze the external flow and temperature fields at steady-state for a control volume of a stationary rice bed. The model was used to predict the convective heat and mass transfer coefficients in the rice bed, and correlations were developed for the convective heat and mass transfer coefficients as a function of drying air flow rate. Then, the coupled CFD and diffusion model developed by ElGamal, Ronsse, Radwan & Pieters (2013) to investigate the heat and mass transfer for thin-layer drying of rice was extended to volumetric heat and mass transfer in a deep-bed of rice using the predicted heat and mass transfer coefficients. All models were solved numerically using the finite element method. The model was used to predict the air temperature, as well as the grain moisture content and temperature at different locations of the dryer during the drying process. The theoretical predictions of moisture and temperature profiles inside a deep-bed of rice were verified by experimental data from literature. The average mean relative deviation values for the prediction of grain moisture content varied between 1.00 to 3.13%

Execution replay and debugging

As most parallel and distributed programs are internally non-deterministic -- consecutive runs with the same input might result in a different program flow -- vanilla cyclic debugging techniques as such are useless. In order to use cyclic debugging tools, we need a tool that records information about an execution so that it can be replayed for debugging. Because recording information interferes with the execution, we must limit the amount of information and keep the processing of the information fast. This paper contains a survey of existing execution replay techniques and tools.Comment: In M. Ducasse (ed), proceedings of the Fourth International Workshop on Automated Debugging (AADebug 2000), August 2000, Munich. cs.SE/001003

Simulations of propelling and energy harvesting articulated bodies via vortex particle-mesh methods

The emergence and understanding of new design paradigms that exploit flow induced mechanical instabilities for propulsion or energy harvesting demands robust and accurate flow structure interaction numerical models. In this context, we develop a novel two dimensional algorithm that combines a Vortex Particle-Mesh (VPM) method and a Multi-Body System (MBS) solver for the simulation of passive and actuated structures in fluids. The hydrodynamic forces and torques are recovered through an innovative approach which crucially complements and extends the projection and penalization approach of Coquerelle et al. and Gazzola et al. The resulting method avoids time consuming computation of the stresses at the wall to recover the force distribution on the surface of complex deforming shapes. This feature distinguishes the proposed approach from other VPM formulations. The methodology was verified against a number of benchmark results ranging from the sedimentation of a 2D cylinder to a passive three segmented structure in the wake of a cylinder. We then showcase the capabilities of this method through the study of an energy harvesting structure where the stocking process is modeled by the use of damping elements

A global coating quality model for top-spray fluidized beds: spray sub model

Fluidized beds are amongst others used in industrial applications for coating particles. Little research has been performed in developing a quality model for a coating process. A quality model is able to predict the quality of the process in terms of coating thickness and uniformity and the occurrence of unwanted side-effects, including agglomeration, attrition and spray loss. The quality of the coating process in a fluidized bed is largely determined by the spray characteristics and the particle motion. A new quality model was developed for the coating process in a top-spray fluidized bed. The first step in the development of the new model was the creation of an accurate spray sub-model that describes the movement and the heat and mass balances of the droplets in the coating process. The second step was the creation of a particle sub-model that describes the movement and the heat and mass balances of the particles in the fluidized bed. The third and final step will be the development of the global coating quality model by combining the spray and the particle sub model. Experimental validation of the spray sub-model has already been carried out and is presented in this paper