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An Empirically Based Stochastic Turbulence Simulator with Temporal Coherence for Wind Energy Applications

In this dissertation, we develop a novel methodology for characterizing and simulating nonstationary, full-field, stochastic turbulent wind fields.

In this new method, nonstationarity is characterized and modeled via temporal coherence, which is quantified in the discrete frequency domain by probability distributions of the differences in phase between adjacent Fourier components.

The empirical distributions of the phase differences can also be extracted from measured data, and the resulting temporal coherence parameters can quantify the occurrence of nonstationarity in empirical wind data.

This dissertation (1) implements temporal coherence in a desktop turbulence simulator, (2) calibrates empirical temporal coherence models for four wind datasets, and (3) quantifies the increase in lifetime wind turbine loads caused by temporal coherence.

The four wind datasets were intentionally chosen from locations around the world so that they had significantly different ambient atmospheric conditions.

The prevalence of temporal coherence and its relationship to other standard wind parameters was modeled through empirical joint distributions (EJDs), which involved fitting marginal distributions and calculating correlations.

EJDs have the added benefit of being able to generate samples of wind parameters that reflect the characteristics of a particular site.

Lastly, to characterize the effect of temporal coherence on design loads, we created four models in the open-source wind turbine simulator FAST based on the \windpact turbines, fit response surfaces to them, and used the response surfaces to calculate lifetime turbine responses to wind fields simulated with and without temporal coherence.

The training data for the response surfaces was generated from exhaustive FAST simulations that were run on the high-performance computing (HPC) facilities at the National Renewable Energy Laboratory.

This process was repeated for wind field parameters drawn from the empirical distributions and for wind samples drawn using the recommended procedure in the wind turbine design standard \iec.

The effect of temporal coherence was calculated as a percent increase in the lifetime load over the base value with no temporal coherence.

AGOCS – Accurate Google Cloud Simulator Framework

This paper presents the Accurate Google Cloud Simulator (AGOCS) – a novel high-fidelity Cloud workload simulator based on parsing real workload traces, which can be conveniently used on a desktop machine for day-to-day research. Our simulation is based on real-world workload traces from a Google Cluster with 12.5K nodes, over a period of a calendar month. The framework is able to reveal very precise and detailed parameters of the executed jobs, tasks and nodes as well as to provide actual resource usage statistics. The system has been implemented in Scala language with focus on parallel execution and an easy-to-extend design concept. The paper presents the detailed structural framework for AGOCS and discusses our main design decisions, whilst also suggesting alternative and possibly performance enhancing future approaches. The framework is available via the Open Source GitHub repository.

A Research of Resource Scheduling Algorithm Based on Hadoop

With the development of electronic devices, more and more mobile clients are connected to the Internet and they generate massive data every day. We live in an age of “Big Data”, and every day we generate hundreds of million magnitude data. By analyzing the data and making prediction, we can carry out better development plan. Unfortunately, traditional computation framework cannot meet the demand, so the Hadoop would be put forward. First the paper introduces the background and development status of Hadoop, compares the MapReduce in Hadoop 1.0 and YARN in Hadoop 2.0, and analyzes the advantages and disadvantages of them. Because the resource management module is the core role of YARN, so next the paper would research about the resource allocation module including the resource management, resource allocation algorithm, resource preemption model and the whole resource scheduling process from applying resource to finishing allocation. Also it would introduce the FIFO Scheduler, Capacity Scheduler, and Fair Scheduler and compare them. The main work has been done in this paper is researching and analyzing the Dominant Resource Fair algorithm of YARN, putting forward a maximum resource utilization algorithm based on Dominant Resource Fair algorithm. The paper also provides a suggestion to improve the unreasonable facts in resource preemption model. Emphasizing “fairness” during resource allocation is the core concept of Dominant Resource Fair algorithm of YARM. Because the cluster is multiple users and multiple resources, so the user’s resource request is multiple too. The DRF algorithm would divide the user’s resources into dominant resource and normal resource. For a user, the dominant resource is the one whose share is highest among all the request resources, others are normal resource. The DRF algorithm requires the dominant resource share of each user being equal. But for these cases where different users’ dominant resource amount differs greatly, emphasizing “fairness” is not suitable and can’t promote the resource utilization of the cluster. By analyzing these cases, this thesis puts forward a new allocation algorithm based on DRF. The new algorithm takes the “fairness” into consideration but not the main principle. Maximizing the resource utilization is the main principle and goal of the new algorithm. According to comparing the result of the DRF and new algorithm based on DRF, we found that the new algorithm has more high resource utilization than DRF. The last part of the thesis is to install the environment of YARN and use the Scheduler Load Simulator (SLS) to simulate the cluster environment.

SMILE: Simulator for Maryland Imitation Learning Environment

As robot imitation learning is beginning to replace conventional hand-coded approaches in programming robot behaviors, much work is focusing on learning from the actions of demonstrators. We hypothesize that in many situations, procedural tasks can be learned more effectively by observing object behaviors while completely ignoring the demonstrator's motions. To support studying this hypothesis and robot imitation learning in general, we built a software system named SMILE that is a simulated 3D environment. In this virtual environment, both a simulated robot and a user-controlled demonstrator can manipulate various objects on a tabletop. The demonstrator is not embodied in SMILE, and therefore a recorded demonstration appears as if the objects move on their own. In addition to recording demonstrations, SMILE also allows programing the simulated robot via Matlab scripts, as well as creating highly customizable objects for task scenarios via XML. This report describes the features and usages of SMILE.

A noise simulator for eLISA: Migrating LISA Pathfinder knowledge to the eLISA mission

We present a new technical simulator for the eLISA mission, based on state space modeling techniques and developed in MATLAB. This simulator computes the coordinate and velocity over time of each body involved in the constellation, i.e. the spacecraft and its test masses, taking into account the different disturbances and actuations. This allows studying the contribution of instrumental noises and system imperfections on the residual acceleration applied on the TMs, the latter reflecting the performance of the achieved free-fall along the sensitive axis. A preliminary version of the results is presented.

A rolling-gliding wear simulator for the investigation of tribological material pairings for application in total knee arthroplasty

Background: Material wear testing is an important technique in the development and evaluation of materials for use in implant for total knee arthroplasty. Since a knee joint induces a complex rolling-gliding movement, standardised material wear testing devices such as Pin-on-Disc or Ring-on-Disc testers are suitable to only a limited extent because they generate pure gliding motion only.Methods: A rolling-gliding wear simulator was thus designed, constructed and implemented, which simulates and reproduces the rolling-gliding movement and loading of the knee joint on specimens of simplified geometry. The technical concept was to run a base-plate, representing the tibia plateau, against a pivoted cylindrical counter-body, representing one femur condyle under an axial load. A rolling movement occurs as a result of the friction and pure gliding is induced by limiting the rotation of the cylindrical counter-body. The set up also enables simplified specimens handling and removal for gravimetrical wear measurements. Long-term wear tests and gravimetrical wear measurements were carried out on the well known material pairings: cobalt chrome-polyethylene, ceramic-polyethylene and ceramic-ceramic, over three million motion cycles to allow material comparisons to be made.Results: The observed differences in wear rates between cobalt-chrome on polyethylene and ceramic on polyethylene pairings were similar to the differences of published data for existing material-pairings. Test results on ceramic-ceramic pairings of different frontal-plane geometry and surface roughness displayed low wear rates and no fracture failures.Conclusions: The presented set up is able to simulate the rolling-gliding movement of the knee joint, is easy to use, and requires a minimum of user intervention or monitoring. It is suitable for long-term testing, and therefore a useful tool for the investigation of new and promising materials which are of interest for application in knee joint replacement implants. © 2010 Richter et al; licensee BioMed Central Ltd.

A Hardware Implementation of a Run-Time Scheduler for Reconfigurable Systems

New generation embedded systems demand high performance, efficiency and flexibility. Reconfigurable hardware can provide all these features. However the costly reconfiguration process and the lack of management support have prevented a broader use of these resources. To solve these issues we have developed a scheduler that deals with task-graphs at run-time, steering its execution in the reconfigurable resources while carrying out both prefetch and replacement techniques that cooperate to hide most of the reconfiguration delays. In our scheduling environment task-graphs are analyzed at design-time to extract useful information. This information is used at run-time to obtain near-optimal schedules, escaping from local-optimum decisions, while only carrying out simple computations. Moreover, we have developed a hardware implementation of the scheduler that applies all the optimization techniques while introducing a delay of only a few clock cycles. In the experiments our scheduler clearly outperforms conventional run-time schedulers based on As-Soon-As-Possible techniques. In addition, our replacement policy, specially designed for reconfigurable systems, achieves almost optimal results both regarding reuse and performance.

A Hardware Task-Graph Scheduler for Reconfigurable Multi-tasking Systems

Reconfigurable hardware can be used to build a multitasking system where tasks are assigned to HW resources at run-time according to the requirements of the running applications. These tasks are frequently represented as direct acyclic graphs and their execution is typically controlled by an embedded processor that schedules the graph execution. In order to improve the efficiency of the system, the scheduler can apply prefetch and reuse techniques that can greatly reduce the reconfiguration latencies. For an embedded processor all these computations represent a heavy computational load that can significantly reduce the system performance. To overcome this problem we have implemented a HW scheduler using reconfigurable resources. In addition we have implemented both prefetch and replacement techniques that obtain as good results as previous complex SW approaches, while demanding just a few clock cycles to carry out the computations. We consider that the HW cost of the system (in our experiments 3% of a Virtex-II PRO xc2vp30 FPGA) is affordable taking into account the great efficiency of the techniques applied to hide the reconfiguration latency and the negligible run-time penalty introduced by the scheduler computations.

Development of a cargo screening process simulator: a first approach

The efficiency of current cargo screening processes at sea and air ports is largely unknown as few benchmarks exists against which they could be measured. Some manufacturers provide benchmarks for individual sensors but we found no benchmarks that take a holistic view of the overall screening procedures and no benchmarks that take operator variability into account. Just adding up resources and manpower used is not an effective way for assessing systems where human decision-making and operator compliance to rules play a vital role. Our aim is to develop a decision support tool (cargo-screening system simulator) that will map the right technology and manpower to the right commodity-threat combination in order to maximise detection rates. In this paper we present our ideas for developing such a system and highlight the research challenges we have identified. Then we introduce our first case study and report on the progress we have made so far.

Multi-sensor Cloud and Aerosol Retrieval Simulator and Its Applications

Executing a cloud or aerosol physical properties retrieval algorithm from controlled synthetic data is an important step in retrieval algorithm development. Synthetic data can help answer questions about the sensitivity and performance of the algorithm or aid in determining how an existing retrieval algorithm may perform with a planned sensor. Synthetic data can also help in solving issues that may have surfaced in the retrieval results. Synthetic data become very important when other validation methods, such as field campaigns,are of limited scope. These tend to be of relatively short duration and often are costly. Ground stations have limited spatial coverage whilesynthetic data can cover large spatial and temporal scales and a wide variety of conditions at a low cost. In this work I develop an advanced cloud and aerosol retrieval simulator for the MODIS instrument, also known as Multi-sensor Cloud and Aerosol Retrieval Simulator (MCARS). In a close collaboration with the modeling community I have seamlessly combined the GEOS-5 global climate model with the DISORT radiative transfer code, widely used by the remote sensing community, with the observations from the MODIS instrument to create the simulator. With the MCARS simulator it was then possible to solve the long standing issue with the MODIS aerosol optical depth retrievals that had a low bias for smoke aerosols. MODIS aerosol retrieval did not account for effects of humidity on smoke aerosols. The MCARS simulator also revealed an issue that has not been recognized previously, namely,the value of fine mode fraction could create a linear dependence between retrieved aerosol optical depth and land surface reflectance. MCARS provided the ability to examine aerosol retrievals against “ground truth” for hundreds of thousands of simultaneous samples for an area covered by only three AERONET ground stations. Findings from MCARS are already being used to improve the performance of operational MODIS aerosol properties retrieval algorithms. The modeling community will use the MCARS data to create new parameterizations for aerosol properties as a function of properties of the atmospheric column and gain the ability to correct any assimilated retrieval data that may display similar dependencies in comparisons with ground measurements.

Variable-spectrum solar simulator

The invention relates to a variable-spectrum solar simulator for characterising photovoltaic systems. The simulator can be used to obtain a spectrum adjusted to the solar spectrum, both for a standard spectrum or a real spectrum adjusted to local irradiation conditions. The simulator also allows the spatial-angular characteristics of the sun to be reproduced. The invention comprises: a broad-spectrum light source, the flux from which is emitted through an aperture; an optical system which collimates the primary source; a system which disperses the beam chromatically; an optical system which forms an image of the dispersed primary source at a given position, at which a spatial mask is placed in order to filter the received irradiance spectrally; an optical system which captures the filtered spectrum and returns, mixes and concentrates same in a secondary source with the desired spectral, angular, and spatial characteristics; an optical system which collimates the secondary source such that it reproduces the angular characteristics of the sun; and a control system.

Power network in the loop : subsystem testing using a switching amplifier

“Hardware in the Loop” (HIL) testing is widely used in the automotive industry. The sophisticated electronic control units used for vehicle control are usually tested and evaluated using HIL-simulations. The HIL increases the degree of realistic testing of any system. Moreover, it helps in designing the structure and control of the system under test so that it works effectively in the situations that will be encountered in the system. Due to the size and the complexity of interaction within a power network, most research is based on pure simulation. To validate the performance of physical generator or protection system, most testing is constrained to very simple power network. This research, however, examines a method to test power system hardware within a complex virtual environment using the concept of the HIL. The HIL testing for electronic control units and power systems protection device can be easily performed at signal level. But performance of power systems equipments, such as distributed generation systems can not be evaluated at signal level using HIL testing. The HIL testing for power systems equipments is termed here as ‘Power Network in the Loop’ (PNIL). PNIL testing can only be performed at power level and requires a power amplifier that can amplify the simulation signal to the power level. A power network is divided in two parts. One part represents the Power Network Under Test (PNUT) and the other part represents the rest of the complex network. The complex network is simulated in real time simulator (RTS) while the PNUT is connected to the Voltage Source Converter (VSC) based power amplifier. Two way interaction between the simulator and amplifier is performed using analog to digital (A/D) and digital to analog (D/A) converters. The power amplifier amplifies the current or voltage signal of simulator to the power level and establishes the power level interaction between RTS and PNUT. In the first part of this thesis, design and control of a VSC based power amplifier that can amplify a broadband voltage signal is presented. A new Hybrid Discontinuous Control method is proposed for the amplifier. This amplifier can be used for several power systems applications. In the first part of the thesis, use of this amplifier in DSTATCOM and UPS applications are presented. In the later part of this thesis the solution of network in the loop testing with the help of this amplifier is reported. The experimental setup for PNIL testing is built in the laboratory of Queensland University of Technology and the feasibility of PNIL testing has been evaluated using the experimental studies. In the last section of this thesis a universal load with power regenerative capability is designed. This universal load is used to test the DG system using PNIL concepts. This thesis is composed of published/submitted papers that form the chapters in this dissertation. Each paper has been published or submitted during the period of candidature. Chapter 1 integrates all the papers to provide a coherent view of wide bandwidth switching amplifier and its used in different power systems applications specially for the solution of power systems testing using PNIL.

Hybrid system simulation of computer control applications over communication networks

Discrete event-driven simulations of digital communication networks have been used widely. However, it is difficult to use a network simulator to simulate a hybrid system in which some objects are not discrete event-driven but are continuous time-driven. A networked control system (NCS) is such an application, in which physical process dynamics are continuous by nature. We have designed and implemented a hybrid simulation environment which effectively integrates models of continuous-time plant processes and discrete-event communication networks by extending the open source network simulator NS-2. To do this a synchronisation mechanism was developed to connect a continuous plant simulation with a discrete network simulation. Furthermore, for evaluating co-design approaches in an NCS environment, a piggybacking method was adopted to allow the control period to be adjusted during simulations. The effectiveness of the technique is demonstrated through case studies which simulate a networked control scenario in which the communication and control system properties are defined explicitly.