E-Nanocluster : thermal design for the heat extraction from a computer cluster based on Raspberry Pi 2’s single board computers

A computer cluster is a group of interconnected computers. They work as a single supercomputer that can run simulations and operations that require big computational calculations. A computer cluster has several applications from climatological predictions and astrological applications to molecular simulations. On the other hand, the Raspberry Pi 2 is a computer with the size of a credit card but with a high performance. At the Escola Tècnica i Superior d’Enginyeria Industrial de Barcelona (Spain) was born the idea of building a small computer cluster for small research centres and universities by using a hundred Raspberry Pi 2 boards: The E-Nanocluster. The E-Nanocluster requires a series of projects that delve into different branches of the engineering science. This particular project is the first one and it focus on the heat extraction and the structure design of the cluster. The structure of this document follows all the steps that bring the cluster from a simple idea to a real solution. First there is a presentation of the main characteristics of the computer clusters and the Raspberry Pi 2 boards and then is analysed the state of the art of the actual heat extraction systems in computers. Once the best system is chosen, it is provided a basic design for the cluster. From that design is developed an adaptable thermal and fluidic model made with Microsoft Office Spreadsheet. This model calculates in just a few seconds which is the fan power required for the correct heat extraction. All the parameters such as the air temperature, heat sink characteristics or the power generated can be modified. With this model it is done a sensibility analysis for optimizing the solution by minimizing the cost and the space of the machine. After that, it has been done a Computational Fluid Dynamic (CFD) simulation to verify the model. The CFD program used has been SolidWorks Flow Simulation. Finally, there is an analysis of the environmental impact, the budget of the project and a plan for the next projects that should be done for bringing the E-Nanocluster to life

A CFD results-based reduced-order model for latent heat thermal energy storage systems with macro-encapsulated PCM

Macro-encapsulation of phase change material (PCM) is a promising approach to overcome a serious drawback of many latent heat thermal energy storage systems (LHTESSs): their low thermal power. Simulations are often used to support the design of these storage systems, but the simulation of the charging process of such an LHTESS with detailed CFD models is too computationally expensive. To obtain information about the behavior of a complete LHTESS, highly simplified system simulation models are usually applied. A new approach to create a reduced-order model is herein presented that aims to increase the accuracy of these system simulation models. The first step consists of performing a set of detailed CFD simulations of one capsule with different boundary conditions. The results are written into look-up tables that contain the charging power of one capsule as a function of the enthalpy stored and the boundary conditions. These look-up tables are then implemented into the reduced-order model. The temporal mean deviation of the energy content in the storage unit between experiments and the reduced-order model is only 5 % and the simulation time of the fastest reduced-order model was 5 s, while the CFD simulations took up to about two weeks on a workstation. Finally, for the conditions tested, the heat transfer fluid (HTF) does not have to be included in the CFD simulation, but can be replaced by a properly defined convective boundary condition. The capsule wall, however, needs to be included in the CFD model (especially for capsule wall materials with a distinctively higher thermal conductivity than the PCM) to account for the heat flow towards the bottom of the capsule supporting close contact melting.Andreas König-Haagen is grateful for the financial support of the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Grant no KO 6286/1-1/444616738. Moritz Faden is grateful for the financial support of the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under grant no. BR 1713/20-2. This work was partially funded by the ENEDI Research Group (IT1730-22) and by the Spanish Ministry of Science and Innovation (MICINN) through the STES4D research project (TED2021-131061B-C32)

High-performance cluster computing, algorithms, implementations and performance evaluation for computation-intensive applications to promote complex scientific research on turbulent flows

Large-scale high-performance computing is a very rapidly growing field of research that plays a vital role in the advance of science, engineering, and modern industrial technology. Increasing sophistication in research has led to a need for bigger and faster computers or computer clusters, and high-performance computer systems are themselves stimulating the redevelopment of the methods of computation. Computing is fast becoming the most frequently used technique to explore new questions. We have developed high-performance computer simulation modeling software system on turbulent flows. Five papers are selected to present here from dozens of papers published in our efforts on complex software system development and knowledge discovery through computer simulations. The first paper describes the end-to-end computer simulation system development and simulation results that help understand the nature of complex shelterbelt turbulent flows. The second paper deals specifically with high-performance algorithm design and implementation in a cluster of computers. The third paper discusses the twelve design processes of parallel algorithms and software system as well as theoretical performance modeling and characterization of cluster computing. The fourth paper is about the computing framework of drag and pressure coefficients. The fifth paper is about simulated evapotranspiration and energy partition of inhomogeneous ecosystems. We discuss the end-to-end computer simulation system software development, distributed parallel computing performance modeling and system performance characterization. We design and compare several parallel implementations of our computer simulation system and show that the performance depends on algorithm design, communication channel pattern, and coding strategies that significantly impact load balancing, speedup, and computing efficiency. For a given cluster communication characteristics and a given problem complexity, there exists an optimal number of nodes. With this computer simulation system, we resolved many historically controversial issues and a lot of important problems

Numerical predictions of laminar and turbulent forced convection: Lattice Boltzmann simulations using parallel libraries

This paper presents the performance comparison of various parallel lattice Boltzmann codes for simulation of incompressible laminar convection in 2D and 3D channels. Five different parallel libraries namely; matlabpool, pMatlab, GPU-Matlab, OpenMP and OpenMP+OpenMPI were used to parallelize the serial lattice Boltzmann method code. Domain decomposition method was adopted for parallelism for 2D and 3D uniform lattice grids. Bhatnagar-Gross-Krook approximation with lattice types D2Q9, D2Q19 and D2Q5, D2Q6 were considered to solve 2D and 3D fluid flow and heat transfer respectively. Parallel computations were conducted on a workstation and an IBM HPC cluster with 32 nodes. Laminar forced convection in a 2D and turbulent forced convection in a 3D channels was considered as a test case. The performance of parallel LBM codes was compared with serial LBM code. Results show that for a given problem, parallel simulations using matlabpool and pMatlab library perform almost equal. Parallel simulations using C language with OpenMP libraries were 10 times faster than simulations involving Matlab parallel libraries. Parallel simulations with OpenMP+OpenMPI were 0.35 times faster than the reported parallel lattice Boltzmann method code in the literature

Applications Of A Time-Dependent Polar Ionosphere Model For Radio Modification Experiments

Thesis (Ph.D.) University of Alaska Fairbanks, 2010A time-dependent self-consistent ionosphere model (SLIM) has been developed to study the response of the polar ionosphere to radio modification experiments, similar to those conducted at the High-Frequency Active Auroral Research Program (HAARP) facility in Gakona, Alaska. SCIM solves the ion continuity and momentum equations, coupled with average electron and ion gas energy equations; it is validated by reproducing the diurnal variation of the daytime ionosphere critical frequency, as measured with an ionosonde. Powerful high-frequency (HF) electromagnetic waves can drive naturally occurring electrostatic plasma waves, enhancing the ionospheric reflectivity to ultra-high frequency (UHF) radar near the HF-interaction region as well as heating the electron gas. Measurements made during active experiments are compared with model calculations to clarify fundamental altitude-dependent physical processes governing the vertical composition and temperature of the polar ionosphere. The modular UHF ionosphere radar (MUIR), co-located with HAARP, measured HF-enhanced ion-line (HFIL) reflection height and observed that it ascended above its original altitude after the ionosphere had been HF-heated for several minutes. The HFIL ascent is found to follow from HF-induced depletion of plasma surrounding the F-region peak density layer, due to temperature-enhanced transport of atomic oxygen ions along the geomagnetic field line. The lower F-region and topside ionosphere also respond to HF heating. Model results show that electron temperature increases will lead to suppression of molecular ion recombination rates in the lower F region and enhancements of ambipolar diffusion in the topside ionosphere, resulting in a net enhancement of slant total electron content (TEC); these results have been confirmed by experiment. Additional evidence for the model-predicted topside ionosphere density enhancements via ambipolar diffusion is provided by in-situ measurements of ion density and vertical velocity over HAARP made by a Defense Meteorological Satellite Program (DMSP) satellite