Matching Items (4)
Description
With the ever-increasing demand for high-end services, technological companies have been forced to operate on high performance servers. In addition to the customer services, the company's internal need to store and manage huge amounts of data has also increased their need to invest in High Density Data Centers. As a result, the performance to size of the data center has increased tremendously. Most of the consumed power by the servers is emitted as heat. In a High Density Data Center, the power per floor space area is higher compared to the regular data center. Hence the thermal management of this type of data center is relatively complicated.
Because of the very high power emission in a smaller containment, improper maintenance can result in failure of the data center operation in a shorter period. Hence the response time of the cooler to the temperature rise of the servers is very critical. Any delay in response will constantly lead to increased temperature and hence the server's failure.
In this paper, the significance of this delay time is understood by performing CFD simulation on different variants of High Density Modules using ANSYS Fluent. It was found out that the delay was becoming longer as the size of the data center increases. But the overload temperature, ie. the temperature rise beyond the set-point became lower with the increase in data center size. The results were common for both the single-row and the double-row model. The causes of the increased delay are accounted and explained in detail manner in this paper.
Because of the very high power emission in a smaller containment, improper maintenance can result in failure of the data center operation in a shorter period. Hence the response time of the cooler to the temperature rise of the servers is very critical. Any delay in response will constantly lead to increased temperature and hence the server's failure.
In this paper, the significance of this delay time is understood by performing CFD simulation on different variants of High Density Modules using ANSYS Fluent. It was found out that the delay was becoming longer as the size of the data center increases. But the overload temperature, ie. the temperature rise beyond the set-point became lower with the increase in data center size. The results were common for both the single-row and the double-row model. The causes of the increased delay are accounted and explained in detail manner in this paper.
ContributorsRamaraj, Dinesh Balaji (Author) / Gupta, Sandeep (Thesis advisor) / Hermann, Marcus (Committee member) / Huang, Huei-Ping (Committee member) / Arizona State University (Publisher)
Created2015
Description
The exhaust system is an integral part of any internal combustion engine. A well- designed exhaust system efficiently removes exhaust gasses expelled from the cylinders. If tuned for performance purposes, the exhaust system can also exhibit scavenging and supercharging characteristics. This project reviews the major components of an exhaust system and discusses the proper design techniques necessary to utilize the performance boosting potential of a tuned exhaust system for a four-stroke engine. These design considerations are then applied to Arizona State University's Formula SAE vehicle by comparing the existing system to a properly tuned system. An inexpensive testing method, developed specifically for this project, is used to test the effectiveness of the current design. The results of the test determined that the current design is ineffective at scavenging neighboring pipes of exhaust gasses and should be redesigned for better performance.
ContributorsKnutsen, Jeffrey Scott (Author) / Huang, Huei-Ping (Thesis director) / Steele, Bruce (Committee member) / Barrett, The Honors College (Contributor) / Mechanical and Aerospace Engineering Program (Contributor)
Created2014-05
Description
Formula SAE is a student design competition where students design and fabricate a formula-style racecar to race in a series of events against schools from around the world. It gives students of all majors the ability to use classroom theory and knowledge in a real world application. The general guidelines for the prototype racecars is for the students to use four-stroke, Otto cycle piston engines with a displacement of no greater than 610cc. A 20mm air restrictor downstream the throttle limits the power of the engines to under 100 horsepower. A 178-page rulebook outlines the remaining restrictions as they apply to the various vehicle systems: vehicle dynamics, driver interface, aerodynamics, and engine. Vehicle dynamics is simply the study of the forces which affect wheeled vehicles in motion. Its primary components are the chassis and suspension system. Driver interface controls everything that the driver interacts with including steering wheel, seat, pedals, and shifter. Aerodynamics refers to the outside skin of the vehicle which controls the amount of drag and downforce on the vehicle. Finally, the engine consists of the air intake, engine block, cooling system, and the exhaust. The exhaust is one of the most important pieces of an engine that is often overlooked in racecar design. The purpose of the exhaust is to control the removal of the combusted air-fuel mixture from the engine cylinders. The exhaust as well as the intake is important because they govern the flow into and out of the engine's cylinders (Heywood 231). They are especially important in racecar design because they have a great impact on the power produced by an engine. The higher the airflow through the cylinders, the larger amount of fuel that can be burned and consequently, the greater amount of power the engine can produce. In the exhaust system, higher airflow is governed by several factors. A good exhaust design gives and engine a higher volumetric efficiency through the exhaust scavenging effect. Volumetric efficiency is also affected by frictional losses. In addition, the system should ideally be lightweight, and easily manufacturable. Arizona State University's Formula SAE racecar uses a Honda F4i Engine from a CBR 600 motorcycle. It is a four cylinder Otto cycle engine with a 600cc displacement. An ideal or tuned exhaust system for this car would maximize the negative gauge pressure during valve overlap at the ideal operating rpm. Based on the typical track layout for the Formula SAE design series, an ideal exhaust system would be optimized for 7500 rpm and work well in the range
ContributorsButterfield, Brandon Michael (Author) / Huang, Huei-Ping (Thesis director) / Trimble, Steven (Committee member) / Mechanical and Aerospace Engineering Program (Contributor) / Materials Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
This dissertation introduces FARCOM (Fortran Adaptive Refiner for Cartesian Orthogonal Meshes), a new general library for adaptive mesh refinement (AMR) based on an unstructured hexahedral mesh framework. As a result of the underlying unstructured formulation, the refinement and coarsening operators of the library operate on a single-cell basis and perform in-situ replacement of old mesh elements. This approach allows for h-refinement without the memory and computational expense of calculating masked coarse grid cells, as is done in traditional patch-based AMR approaches, and enables unstructured flow solvers to have access to the automated domain generation capabilities usually only found in tree AMR formulations.
The library is written to let the user determine where to refine and coarsen through custom refinement selector functions for static mesh generation and dynamic mesh refinement, and can handle smooth fields (such as level sets) or localized markers (e.g. density gradients). The library was parallelized with the use of the Zoltan graph-partitioning library, which provides interfaces to both a graph partitioner (PT-Scotch) and a partitioner based on Hilbert space-filling curves. The partitioned adjacency graph, mesh data, and solution variable data is then packed and distributed across all MPI ranks in the simulation, which then regenerate the mesh, generate domain decomposition ghost cells, and create communication caches.
Scalability runs were performed using a Leveque wave propagation scheme for solving the Euler equations. The results of simulations on up to 1536 cores indicate that the parallel performance is highly dependent on the graph partitioner being used, and differences between the partitioners were analyzed. FARCOM is found to have better performance if each MPI rank has more than 60,000 cells.
The library is written to let the user determine where to refine and coarsen through custom refinement selector functions for static mesh generation and dynamic mesh refinement, and can handle smooth fields (such as level sets) or localized markers (e.g. density gradients). The library was parallelized with the use of the Zoltan graph-partitioning library, which provides interfaces to both a graph partitioner (PT-Scotch) and a partitioner based on Hilbert space-filling curves. The partitioned adjacency graph, mesh data, and solution variable data is then packed and distributed across all MPI ranks in the simulation, which then regenerate the mesh, generate domain decomposition ghost cells, and create communication caches.
Scalability runs were performed using a Leveque wave propagation scheme for solving the Euler equations. The results of simulations on up to 1536 cores indicate that the parallel performance is highly dependent on the graph partitioner being used, and differences between the partitioners were analyzed. FARCOM is found to have better performance if each MPI rank has more than 60,000 cells.
ContributorsBallesteros, Carlos Alberto (Author) / Herrmann, Marcus (Thesis advisor) / Adrian, Ronald (Committee member) / Chen, Kangping (Committee member) / Huang, Huei-Ping (Committee member) / Lopez, Juan (Committee member) / Arizona State University (Publisher)
Created2019