Asif Khalak

Investigation of relative effects of mass and damping in vortex-induced vibration of a circular cylinder

Abstract An experimental study of vortex-induced vibration of a circular cylinder was conducted in a unique experimental facility especially designed for low mass and low damping. In this low mass-damping regime, two separate regions of the high amplitude response curve were identified, which we label “upper” and “lower” branches of response. A systematic study including twelve responses was performed to determine the effect of separately varying the nondimensional mass and varying the nondimensional damping. It seems apparent over the range of our present investigation that the mass - damping (the product of mass and damping) collapses well the amplitude of response, indicating two distinct amplitude curves, rather than the single, unique relationship previously supposed.

Near-optimal assembly for shotgun sequencing with noisy reads

Recent work identified the fundamental limits on the information requirements in terms of read length and coverage depth required for successful de novo genome reconstruction from shotgun sequencing data, based on the idealistic assumption of no errors in the reads (noiseless reads). In this work, we show that even when there is noise in the reads, one can successfully reconstruct with information requirements close to the noiseless fundamental limit. A new assembly algorithm, X-phased Multibridging, is designed based on a probabilistic model of the genome. It is shown through analysis to perform well on the model, and through simulations to perform well on real genomes.

FinisherSC: a repeat-aware tool for upgrading de novo assembly using long reads.

UNLABELLED We introduce FinisherSC, a repeat-aware and scalable tool for upgrading de novo assembly using long reads. Experiments with real data suggest that FinisherSC can provide longer and higher quality contigs than existing tools while maintaining high concordance. AVAILABILITY AND IMPLEMENTATION The tool and data are available and will be maintained at http://kakitone.github.io/finishingTool/ CONTACT : dntse@stanford.edu SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.

Influence of prognostic health management on logistic supply chain

In this paper, we discuss the problem of determining performance metrics for preemptive condition-based maintenance, also referred to as prognostic health maintenance (PHM). This performance is tightly coupled to the properties of the logistics supply chain. Further, the optimal supply chain design is, in fact, sensitive to the capabilities of the PHM system. We formulate this joint optimization problem, which can be shown to be equivalent to a shortest path problem (SPP). The properties of the solution elucidate the design tradeoffs in using damage prediction technologies in the overall health management solution

Real-time Probabilistic Forecasting of Wear Degradation using a Macro-scale Physical Model

Friction and wear processes have their origins in the surface interactions between solid materials with many dynamically important details at the microscale. These details such as the structure of surface roughness, etc. may be framed in terms of macro parameters, but there is necessarily a degree of abstraction and uncertainty in this description. As such, wear models tend to have a significant degree of uncertainty. Moreover, since the physics of contact wear as well as the relevant parameters are uncertain, the damage may be multi-modal and tends to take non-Gaussian Forms. In this work, we address these issues by combining the following elements: a macro-scale physical model of the material wear process under sliding and/or rolling contact, and a rapid algorithm to compute probabilistically valid, non- Gaussian forecasts of the wear. The current state estimate is made using a predictor-corrector method that combines a previous prediction with new sensor information. Based on an input loading forecast (which may be probabilistic), we use the wear model to compute a probability distribution for incremental damage over a time horizon of interest, such as the remaining life of the device of interest. The macro-scale, physics-based wear models are analytic, making the computation of incremental damage very rapid. Combining these incremental probability estimates into a single probability distribution for the future remaining life may be done in realtime using a novel probabilistic damage accumulation algorithm. This algorithm accelerates the probability calculations without making approximations of Gaussianity by operating in the Fourier domain. We apply this approach to the problem of predicting the wear profile of a lead screw actuator accounting for uncertainty in the external demands on the system using a physics-based model for the actuator connected to a 3 degree-of-freedom flight simulator.

Experimental Evaluation of Air Injection for Actuation of Rotating Stall in a Low Speed, Axial Fan

This paper presents an experimental investigation of the effects of air injection on the rotating stall instability in a low speed axial compressor. Two experiments concerning air injection were tried. The first experiment used a continuous forcing perpendicular to the flow in the same or opposite direction of the tip velocity. The results show a dramatic difference between the two directions, with opposite direction forcing causing a significant increase in performance, and same direction forcing causing a significant decrease in performance. This result contradicts the Emmons stall propagation model. The second experiment investigated the differences with respect to different frequencies of air injection, with the injector pointed at the fan, parallel to the flow. We found that the change in the compressor characteristic in the unstalled region was highly dependent upon the forcing frequency with the maximum change occurring near the frequency of stall.Copyright