Preliminary study of the effects of vortex generators in ultralight aircraft

Analysis of vortex generator's behavior and performance of flight tests in a given ultra-light aircraft model.- Theoretical study and state of the art of use of these devices. - Flow simulation across a given lifting surface with and without VGs. - Analysis of vortex generator’s performance in different configurations for given conditions.- Practical application: testing vortex generators into an experimental ultra-light aircraft and performing in-flight tests

Mixing multi-core CPUs and GPUs for scientific simulation software

Recent technological and economic developments have led to widespread availability of multi-core CPUs and specialist accelerator processors such as graphical processing units (GPUs). The accelerated computational performance possible from these devices can be very high for some applications paradigms. Software languages and systems such as NVIDIA's CUDA and Khronos consortium's open compute language (OpenCL) support a number of individual parallel application programming paradigms. To scale up the performance of some complex systems simulations, a hybrid of multi-core CPUs for coarse-grained parallelism and very many core GPUs for data parallelism is necessary. We describe our use of hybrid applica- tions using threading approaches and multi-core CPUs to control independent GPU devices. We present speed-up data and discuss multi-threading software issues for the applications level programmer and o er some suggested areas for language development and integration between coarse-grained and ne-grained multi-thread systems. We discuss results from three common simulation algorithmic areas including: partial di erential equations; graph cluster metric calculations and random number generation. We report on programming experiences and selected performance for these algorithms on: single and multiple GPUs; multi-core CPUs; a CellBE; and using OpenCL. We discuss programmer usability issues and the outlook and trends in multi-core programming for scienti c applications developers

Off-line computing for experimental high-energy physics

The needs of experimental high-energy physics for large-scale computing and data handling are explained in terms of the complexity of individual collisions and the need for high statistics to study quantum mechanical processes. The prevalence of university-dominated collaborations adds a requirement for high-performance wide-area networks. The data handling and computational needs of the different types of large experiment, now running or under construction, are evaluated. Software for experimental high-energy physics is reviewed briefly with particular attention to the success of packages written within the discipline. It is argued that workstations and graphics are important in ensuring that analysis codes are correct, and the worldwide networks which support the involvement of remote physicists are described. Computing and data handling are reviewed showing how workstations and RISC processors are rising in importance but have not supplanted traditional mainframe processing. Examples of computing systems constructed within high-energy physics are examined and evaluated

ASCR/HEP Exascale Requirements Review Report

This draft report summarizes and details the findings, results, and recommendations derived from the ASCR/HEP Exascale Requirements Review meeting held in June, 2015. The main conclusions are as follows. 1) Larger, more capable computing and data facilities are needed to support HEP science goals in all three frontiers: Energy, Intensity, and Cosmic. The expected scale of the demand at the 2025 timescale is at least two orders of magnitude -- and in some cases greater -- than that available currently. 2) The growth rate of data produced by simulations is overwhelming the current ability, of both facilities and researchers, to store and analyze it. Additional resources and new techniques for data analysis are urgently needed. 3) Data rates and volumes from HEP experimental facilities are also straining the ability to store and analyze large and complex data volumes. Appropriately configured leadership-class facilities can play a transformational role in enabling scientific discovery from these datasets. 4) A close integration of HPC simulation and data analysis will aid greatly in interpreting results from HEP experiments. Such an integration will minimize data movement and facilitate interdependent workflows. 5) Long-range planning between HEP and ASCR will be required to meet HEP's research needs. To best use ASCR HPC resources the experimental HEP program needs a) an established long-term plan for access to ASCR computational and data resources, b) an ability to map workflows onto HPC resources, c) the ability for ASCR facilities to accommodate workflows run by collaborations that can have thousands of individual members, d) to transition codes to the next-generation HPC platforms that will be available at ASCR facilities, e) to build up and train a workforce capable of developing and using simulations and analysis to support HEP scientific research on next-generation systems.Comment: 77 pages, 13 Figures; draft report, subject to further revisio

Capacity optimization of battery-generator hybrid power system: Toward minimizing maintenance cost in expeditionary basecamp/operational energy applications

Low and transient load condition are known to have deleterious impact on the efficiency and health of diesel generators (DGs). Extensive operation under such loads reduces fuel consumption and energy conversion efficiency, and contribute to diesel engine degradation, damage, or catastrophic failure. Non-ideal loads are prevalent in expeditionary base camps that support contingency operations in austere environments or remote locations where grid electricity is either non-existent or inaccessible. The impact of such loads on DGs exacerbates already overburdened basecamp energy logistics requirements. There is a need, therefore, to eliminate or prevent the occurrence of non-ideal loads. Although advances in diesel engine technologies have improved their performance, DGs remain vulnerable to the consequences of non-ideal loads and inherent inefficiencies of combustion. The mechanisms through which DGs respond to and mitigate non-ideal loads are also mechanically stressful and energy-intensive. Thus, this research investigated the idea of using batteries to prevent DGs from encountering non-ideal loads, as a way to reduce basecamp energy logistics requirements. Using a simple semi-empirical approach, the study modeled and simulated a battery-DG hybrid system under various load conditions. The simulation allowed for synthesis of design space in which specified battery and generator capacity can achieve optimal savings in fuel consumption and maintenance cost. Results show that a right-sized battery-diesel generator system allows for more than 50% cost savings relative to a standalone generator