Modeling and simulation of JP-8 fuel based hybrid solid oxide fuel cell system

Solid Oxide Fuel Cells (SOFC) are solid state energy conversion devices that operate at high temperatures (800 to 1000 ±C). Their inherent advantage of fuel flexibility, tolerance to impurities, faster chemical kinetics with non precious catalyst materials and capability of supporting bottoming cycle components make them an attractive proposition for energy generation in comparison to other fuel cell technologies. To assist the advancement of this technology, this work develops dynamic, computer-based, mathematical models of an Auto-thermal reformer (ATR) based SOFC system with Jet Propellant-8 as the fuel to the ATR. Limitations in the existing models of SOFC systems lie in handling of complex hydrocarbon mixtures and also in simulating start up conditions. Although experimental data necessary to model these accurately is currently not available, this work puts forth a structured method for model development and management. Hierarchical libraries are developed herein, allowing easy modification of the models on multiple levels for simulation of various SOFC system configurations, which can help in improving accuracy as and when experimental data is accessible. The comprehensive model consists of submodels for individual components, namely, the fuel cell stack, an ATR reformer, boiler, mixer, heat exchangers, pump, blower, and bottoming cycle components like Stirling engine. Essential dynamics such as heat transfer, chemical kinetics, electrochemistry, thermodynamics and pressure dynamics can be analyzed through the simulation results. In addition, the model will also capture phase change phenomenon in the form of boiling, vaporization and condensation to incorporate liquid hydrocarbon and water

Chronic Nerve Interfacing Utilizing Graft-Embedded Regenerative Macro-Sieve Electrodes

Custom-designed macro-sieve electrodes represent a novel means of facilitating chronic high specificity nerve stimulation needed to control distal nerve musculature and restore sensorimotor function. Implantation of these electrodes requires the transection of the nerve, which has shown to disrupt muscle fiber distribution. This present study assesses the feasibility of implementing these electrodes in an end-to-side nerve graft. The macro-sieve electrodes were fabricated and micro-surgically implanted into 3.2 cm nerve autografts harvested from the sciatic nerve of 12 male Lewis rats. Electrode-enabled nerve grafts were micro-surgically implanted in an end-to-side manner into donor rat sciatic nerves without the need for a transection of the host nerve. The nerve interface was assessed by selectively stimulating regenerated nerve tissue via implanted sieve electrodes while simultaneously mapping evoked muscle activation and force production at 3 months post-operatively. Micro-surgical implantation of nerve grafts and conduit-based nerve grafts into the sciatic nerve of healthy male rats of 3 months resulted in robust axonal regeneration. The electrode-enabled nerve grafts implanted in the sciatic nerve of healthy male rats showed signs of axonal regeneration through the macro-sieve electrode. Electrophysiological assessment showed preservation of motor function 3 months post-operatively

Performance Evaluation of Sparse Matrix Multiplication Kernels on Intel Xeon Phi

Intel Xeon Phi is a recently released high-performance coprocessor which features 61 cores each supporting 4 hardware threads with 512-bit wide SIMD registers achieving a peak theoretical performance of 1Tflop/s in double precision. Many scientific applications involve operations on large sparse matrices such as linear solvers, eigensolver, and graph mining algorithms. The core of most of these applications involves the multiplication of a large, sparse matrix with a dense vector (SpMV). In this paper, we investigate the performance of the Xeon Phi coprocessor for SpMV. We first provide a comprehensive introduction to this new architecture and analyze its peak performance with a number of micro benchmarks. Although the design of a Xeon Phi core is not much different than those of the cores in modern processors, its large number of cores and hyperthreading capability allow many application to saturate the available memory bandwidth, which is not the case for many cutting-edge processors. Yet, our performance studies show that it is the memory latency not the bandwidth which creates a bottleneck for SpMV on this architecture. Finally, our experiments show that Xeon Phi's sparse kernel performance is very promising and even better than that of cutting-edge general purpose processors and GPUs

REPP-H: runtime estimation of power and performance on heterogeneous data centers

Modern data centers increasingly demand improved performance with minimal power consumption. Managing the power and performance requirements of the applications is challenging because these data centers, incidentally or intentionally, have to deal with server architecture heterogeneity [19], [22]. One critical challenge that data centers have to face is how to manage system power and performance given the different application behavior across multiple different architectures.This work has been supported by the EU FP7 program (Mont-Blanc 2, ICT-610402), by the Ministerio de Economia (CAP-VII, TIN2015-65316-P), and the Generalitat de Catalunya (MPEXPAR, 2014-SGR-1051). The material herein is based in part upon work supported by the US NSF, grant numbers ACI-1535232 and CNS-1305220.Peer ReviewedPostprint (author's final draft

RePP-C: runtime estimation of performance-power with workload consolidation in CMPs

Configuration of hardware knobs in multicore environments for meeting performance-power demands constitutes a desirable feature in modern data centers. At the same time, high energy efficiency (performance per watt) requires optimal thread-to-core assignment. In this paper, we present the runtime estimator (RePP-C) for performance-power, characterized by processor frequency states (P-states), a wide range of sleep intervals (Cl-states) and workload consolidation. We also present a schema for frequency and contention-aware thread-to-core assignment (FACTS) which considers various thread demands. The proposed solution (RePP-C) selects a given hardware configuration for each active core to ensure that the performance-power demands are satisfied while using the scheduling schema (FACTS) for mapping threads-to-cores. Our results show that FACTS improves over other state-of-the-art schedulers like Distributed Intensity Online (DIO) and native Linux scheduler by 8.25% and 37.56% in performance, with simultaneous improvement in energy efficiency by 6.2% and 14.17%, respectively. Moreover, we prove the usability of RePP-C by predicting performance and power for 7 different types of workloads and 10 different QoS targets. The results show an average error of 7.55% and 8.96% (with 95% confidence interval) when predicting energy and performance respectively.This work has been partially supported by the European Union FP7 program through the Mont-Blanc-2 project (FP7-ICT-610402), by the Ministerio de Economia y Competitividad under contract Computacion de Altas Prestaciones VII (TIN2015-65316-P), and the Departament d’Innovacio, Universitats i Empresa de la Generalitat de Catalunya, under project MPEXPAR: Models de Programacio i Entorns d’Execucio Paral.lels (2014-SGR-1051).Peer ReviewedPostprint (author's final draft

An overview of pharmacodynamic modelling, ligand-binding approach and its application in clinical practice

AbstractThe study of the magnitude and variation of drug response is defined as pharmacodynamics (PDs). PD models examine plasma concentration and effect relationship. It can predict the archetypal effect (E) of a drug as a function of the drug concentration (C) and estimate an unknown PD parameter (θpd). The PD models have been described as fixed, linear, log-linear, Emax, sigmoid Emax, and indirect PD response. Ligand binding model is an example of a PD model that works on the underpinning PD principle of a drug, eliciting its pharmacological effect at the receptor site. The pharmacological effect is produced by the drug binding to the receptor to either activate or antagonise the receptor. Ligand binding models describe a system of interacting components, i.e. the interaction of one or more ligands with one or more binding sites. The Emax model is the central method that provides an empirical justification for the concentration/dose-effect relationship. However, for ligand binding models justification is provided by theory of receptor occupancy. In essence, for ligand binding models, the term fractionaloccupancy is best used to describe the fraction of receptors occupied at a particular ligand concentration. It is stated that the fractionaloccupancy=occupiedbindingsites/totalbindingsites, which means the effect of a drug should depend on the fraction of receptors that are occupied. In the future, network-based systems pharmacology models using ligand binding principles could be an effective way of understanding drug-related adverse effects. This will facilitate and strengthen the development of rational drug therapy in clinical practice