Entropy generation for forced convection in a porous saturated circular tube with uniform wall temperature

A numerical study is reported to investigate both the First and the Second Law of Thermodynamics for thermally developing forced convection in a circular tube filled by a saturated porous medium, with uniform wall temperature, and with the effects of viscous dissipation included. A theoretical analysis is also presented to study the problem for the asymptotic region applying the perturbation solution of the Brinkman momentum equation reported by (K. Hooman, K., A.A. Ranjbar-Kani, A perturbation based analysis to investigate forced convection in a porous saturated tube, Journal of Computational and Applied Mathematics 162 (2) (2004) 411–419.). Expressions are reported for the temperature profile, the Nusselt number, the Bejan number, and the dimensionless entropy generation rate in the asymptotic region. Numerical results are found to be in good agreement with theoretical counterparts.     

Error propagation analysis using FPGA-based SEU-fault injection

Error propagation analysis is one of the main objectives of fault injection experiments. This analysis helps designers to detect design mistakes and to provide effective mechanisms for fault tolerant systems. However, error propagation analysis requires that the chosen fault injection technique provides a high degree of observability (i.e., the ability to observe the internal values and events of a circuit after a fault is injected). Simulation-based fault injection provides a high observability adequate for error propagation analysis. However, the performance of the simulation-based technique is inadequate to handle today’s hardware complexity. As an alternative, FPGA-based fault injection can be used to accelerate the fault injection experiments, but the communication time needed for observing the circuit behavior from outside of the FPGA imposes severe limitations on the observability. In this paper, an observation technique for FPGA-based fault injection is proposed which significantly reduces the communication time as compared with previous scan-based observation techniques. Furthermore, this paper describes a SEU-fault injection technique based on a chain of parallel registers which reduces the time needed for injecting SEU faults as compared to the previous scan-based fault-injection techniques. As a case study, a 32-bit pipelined processor has been used in the fault injection experiments. The experimental results show that when a high degree of observability is required (e.g., error propagation analysis), the proposed fault injection technique is over 1166 times faster than simulation-based fault injection, whereas the traditional scan-based technique can achieve only a speedup of about 2–3 – which means that the proposed technique is about 500 times faster than the traditional scan-based technique. Such results are supported by theoretical performance analysis. This speed increase has been achieved without excessive increase in FPGA resource overhead, for example, the FPGA overhead of the proposed technique is only 2  3% higher than that of the traditional scan-based technique.     

Effects of viscous heating,fluid property variation,velocity slip,and temperature jump on convection through parallel plate and circular microchannels

Theoretical results, based on perturbation techniques, are presented for fully developed, both hydrodynamically and thermally, forced convection in both parallel plate and circular microchannels subject to isoflux wall boundary condition. Scaling effects, including variable property, viscous dissipation, velocity slip, and temperature jump, are studied for flow of both gases and liquids. The interactions between the aforementioned effects, due to temperature-dependence of the fluid properties that couples the momentum and thermal energy equation, are also examined in detail.     

A new criterion to design reactive coal stockpiles

This paper proposes a new criterion to design the self-heating coal stockpiles. The generated heat can be removed if air is blown to the self-heating stockpile. At the same time, introducing more air to the system boosts the aforementioned chemical reactions. Hence, there is a tradeoff between the two opposing effects. Monitoring such a tradeoff, which pinpoints both qualitatively and quantitatively the safe characteristics (geometry, porosity, and permeability) of a stockpile, can be referred to as a design criterion to be implemented in industry. In order to validate the application of the newly-proposed criterion, two independent numerical solvers are used being a FORTRAN code and the commercially available software CFD-ACE. Different key parameters including approaching wind speed, porosity, and permeability are examined. Finally, application of energy flux vectors for convection visualization is also illustrated for a more comprehensive analysis of the problem.     

Application of high porosity metal foams as air-cooled heat exchangers to high heat load removal systems

A numerical study has been conducted to investigate the fluid flow and heat transfer of an air-cooled metal foam heat exchanger under the high speed laminar jet confined by two parallel walls for which the range of the Reynolds number is 600–1000. Two independent numerical solvers were used and cross-validated being a FORTRAN code and the commercially available software CFD-ACE. The effects of local thermal non-equilibrium, thermal dispersion, porosity, and pore density on the heat transfer augmentation are examined for different Reynolds numbers. Application of energy flux vectors, for convection visualization, is also illustrated for a more comprehensive analysis of the problem. Finally, the performance of the metal foam heat exchanger is compared to that of conventional finned design. It is observed that the heat removal rate can be greatly improved at almost no excess cost.     

FPGA-based Monte Carlo simulation for fault tree analysis

The reliability analysis of critical systems is often performed using fault-tree analysis. Fault trees are analyzed using analytic approaches or Monte Carlo simulation. The usage of the analytic approaches is limited in few models and certain kinds of distributions. In contrast to the analytic approaches, Monte Carlo simulation can be broadly used. However, Monte Carlo simulation is time-consuming because of the intensive computations. This is because an extremely large number of simulated samples may be needed to estimate the reliability parameters at a high level of confidence.In this paper, a tree model, called Time-to-Failure tree, has been presented, which can be used to accelerate the Monte Carlo simulation of fault trees. The time-to-failure tree of a system shows the relationship between the time to failure of the system and the times to failures of its components. Static and dynamic fault trees can be easily transformed into time-to-failure trees. Each time-to-failure tree can be implemented as a pipelined digital circuit, which can be synthesized to a field programmable gate array (FPGA). In this way, Monte Carlo simulation can be significantly accelerated. The performance analysis of the method shows that the speed-up grows with the size of the fault trees. Experimental results for some benchmark fault trees show that this method can be about 471 times faster than software-based Monte Carlo simulation.     

Hydrodynamic modeling of traffic jams in intracellular transport in axons

Irregularities in intracellular traffic in axons caused by mutations of molecular motors may lead to “traffic jams”, which often result in swelling of axons causing such neurodegenerative diseases as Alzheimer's disease and Down syndrome. Hence, it is of particular interest to mathematically model the formation of traffic jams in axons. This paper adopts the hydrodynamic continuity equations for intracellular transport of organelles as developed by Smith and Simmons [D.A. Smith, R.M. Simmons, Models of motor-assisted transport of intracellular particles, Biophysical Journal 80 (2001) 45–68.] whereas the Kerner and Konhäuser [B.S. Kerner, P. Konhäuser, Cluster effect in initially homogeneous traffic flow, Physical Review E 48 (1993), R2335–R2338.] model for traffic jams in highway traffic is applied to predict the velocity field. It is observed that combination of the two sets of equations can comprehensively predict the traffic jams in axons without the need to any additional assumption or modification.     

Emulating switch-level models of CMOS circuits

This paper presents a method for emulating switch-level models of CMOS circuits using FPGAs. In this method, logic gates are used to model switch-level circuits without any abstraction. In contrast to the abstraction methods for which transistors are grouped together to form gates, in this method, gates are grouped together to form the switch models of transistors. The method presented in this paper, unlike the abstraction methods, can emulate many important features of switch-level models, such as bi-directional signal propagation and variations in driving strength. In order to attain a better utilization of FPGA resources a mixed-mode emulation approach has been used. In this approach parts of the circuit are emulated at the switch-level while the remaining parts of the circuit are emulated at the gate-level. The experimental results show that the presented emulation-based approach could be significantly faster than existing simulation-based approaches. The analytical performance estimation shows that the speed-up grows with the circuit size and is workload dependent.     

Optimal tuning of fuzzy parameters for structural motion control using multiverse optimizer

In recent years, there is an increasing interest in optimization of structural control algorithms. Fuzzy logic controller is one of the most common and versatile control algorithms that is generally formulated based on the human knowledge and expert. Human knowledge and experience do not yield optimal control responses for a given structure, and tuning of the fuzzy parameters is necessary. This paper focuses on the optimization of a fuzzy controller applied to a seismically excited nonlinear building. In the majority of cases, this problem is formulated based on the linear behavior of the structure; however, in this paper, objective functions and the evaluation criteria are considered with respect to the nonlinear responses of the structures. Multiverse optimizer is a novel nature‐inspired optimization algorithm that is based on the three concepts of cosmology as white hole, black hole, and wormhole. This algorithm has fast convergence rate and can be utilized in continuous and discrete optimization problems. In this paper, the multiverse optimizer is considered as the optimization algorithm for optimization of the fuzzy controller. The performance of the selected algorithm is compared with eight different optimization algorithms. The results prove that the selected algorithm is able to provide very competitive results.