189 research outputs found
Experimental application of a dynamic observer to capture and predict the dynamics of a flat-plate boundary layer
No full textThe recent approach, proposed by Guzman-Inigo et al. \cite{GuzmanInigo2014}, using System Identification to derive a Reduced Order Model from snapshots of a flow is applied to a transitional boundary layer growing over a flat-plate. It is shown that such an approach can indeed be applied to experimental PIV snapshots. Using a proper learning dataset and a proper local sensor, it is shown that the evolution of boundary layer can be properly estimated from the time evolution of the local probe and with no more than ten POD modes for the Reduced Order Model. The influence of the various parameters on the efficiency of the system identification technique is discussed
Addressing the challenges of climate change risks and adaptation in coastal areas: A review
No full textClimate change is and will continue altering the world's coasts, which are the most densely populated and economically active areas on earth and home for highly valuable ecosystems. While there is considerable relevant research, in the authors' experience this problem remains challenging for coastal engineering. This paper reviews important challenges in this respect and identifies three key actions to address them: (a) refocusing traditional practice towards more climate-aware approaches; (b) developing more comprehensive risk frameworks that include the multi-dimensionality and non-stationarity of their components and consideration of uncertainty; and (c) building bridges between risk assessment and adaptation theory and practice. We conclude that the way forward includes numerous activities including increased observations; the attribution of coastal impacts to their drivers; enhanced climate projections and their integration into impact models; more impact assessments at the local scale; dynamic projections of spatially-distributed exposure and vulnerability; and the exploration of inherently adaptive options. Given the complexity of the possible solutions, more practical guidance is required.Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Coastal Engineerin
Odoardo Fialetti (1573-c.1638): the interrelation of Venetian art and anatomy, and his importance in England
No full textBolognese artist Odoardo Fialetti (1573 – c.1638) is a fascinating figure upon which curiously little work has been done. Though he is a rarely discussed pupil of Tintoretto, Fialetti’s oeuvre is vast (some 55 known paintings and approximately 450 prints) and incredibly diverse. His work encompasses religious subjects, portraits, books on drawing and sport, maps, and illustration for treatises on city defences, literary texts, and anatomy. His work was influential for several hundred years after his death, not only in Venice and northern Italy, but also in France where his designs were used as decoration on faïence produced at Nevers, and England, where his paintings were much admired at court. Fialetti’s close association with Sir Henry Wotton, and the careful copy of his drawing book made by Alexander Browne in the mid-seventeenth century, attest to his impact on the formation of an Italianate sensibility in the appreciation of the visual arts in Early Modern England. In the realm of science, Fialetti’s influence can be deduced from his drawings of curiously animated cadavers in detailed landscapes to those of future generations of anatomists and illustrators throughout Europe. Because of the diverse associations and projects throughout his career, the study of Fialetti is inherently interdisciplinary, encompassing the history of art, history of science and history of the Venetian book trade, as well as crossing geographical boundaries in linking Venetian art and English tastes of the late renaissance and early baroque. Through examination of his extant oeuvre, as well as discussion of lost work, I aim to recognise Fialetti’s status as an artist responding to contemporary artistic debates (disegno versus colorito), a changing cultural climate and the burgeoning importance of the printed medium
How Does John Taylor the Water-Poet Break the mould of 17th century poetry
No full textThe dominant view of poetry in the early 17th century was ‘poetry, imagined as the product of an aristocratic social ethos, sustained and policed the social boundaries that defined ‘equals or near equals in social status. Writing private poetry was thus an act of social classification’ (Wendy Wall, The Imprint of Gender , Cornell University Press 1993 p. 13). Much poetry from this period was therefore circulated in manuscript form, and sometimes published posthumously. Even among the poets who did publish in their lifetime, such as Ben Jonson, considerable effort was put into making their work appear sufficiently literary
Providing Green SLAs in High Performance Computing Clouds
No full textDemand for clean products and services is increasing as society is becoming increasingly aware of climate change. In response, many enterprises are setting explicit sustainability goals and implementing initiatives to reduce carbon emissions. Quantification and disclosure of such goals and initiatives have become important marketing tools. As enterprises and individuals shift their workloads to the cloud, this drive toward quantification and disclosure will lead to demand for quantifiable green cloud services. Thus, we argue that cloud providers should offer a new class of green service, in addition to existing (energy-sourceoblivious) services. This new class would provide their clients with explicit service-level agreements (which we call Green SLAs) for the percentage of renewable energy used to run their workloads.Technical report DCS-TR-70
Quantifying and Improving I/O Predictability in Virtualized Systems
No full textVirtualization enables the consolidation of virtual machines (VMs) to increase the utilization of physical servers in Infrastructure-as-a-Service (IaaS) cloud providers. Unfortunately, our quantification of storage I/O performance across a range of workloads, virtual machine monitor (VMM) architectures, approaches to storage virtualization, and storage devices shows widespread performance unpredictability in the face of consolidation. Surprisingly, the use of solid-state drives (SSDs) can exacerbate the problem. Since many users may desire consistent performance, we argue that IaaS cloud providers should provide a class of predictable-performance service in addition to their existing (predictability-oblivious) services. Thus, we propose and evaluate VirtualFence, a storage system that provides predictable performance for this new class of service. VirtualFence uses three main techniques: (1) non-work-conserving time-division I/O scheduling, (2) a small SSD cache in front of a much larger hard disk drive (HDD), and (3) space-partitioning of both the SSD cache and the HDD. Our evaluation of a prototype VirtualFence implemented in the Xen VMM shows that VirtualFence improves predictability significantly. More fundamentally, our evaluation illustrates the tradeoff between predictability and performance. We conclude that current VMMs are far from providing predictability. Systems like VirtualFence can remedy this problem, while allowing the cloud provider to select an appropriate compromise between performance and predictability.Technical report DCS-TR-69
GreenCassandra: Using Renewable Energy in Distributed Structured Storage Systems
No full textOn-site generation of renewable (“green”) energy can help to significantly reduce grid (“brown”) energy consumption, and correspondingly the carbon footprint, of datacenters. However, it is challenging to use green energy generated from sources such as solar and wind because energy production is variable. In this paper, we investigate how to manage an interactive service, where response time is a critical performance metric, to maximize the benefits of green energy produced from these sources. Specifically, we design, prototype, and evaluate a distributed structured storage system, GreenCassandra, which is representative of a class of important subsystems underlying many interactive cloud services. Our proposed approach predicts the production of solar energy, and then controls the number of active nodes to manage energy consumption while respecting a response time SLA. When green energy is available, GreenCassandra may activate extra servers to build up slack with respect to the SLA. When using brown energy, GreenCassandra deactivates servers to reduce energy consumption, leveraging any built-up performance slack, while observing constraints imposed by the SLA. Evaluations show that GreenCassandra can use a heuristic green-energy-aware policy to decrease brown energy consumption and cost by up to 28% and 29%, respectively. Further, these savings are very close to those achievable by an optimizationbased policy that has perfect knowledge of future workload and green energy production.Technical report DCS-TR-71
ApproxHadoop: Bringing Approximations to MapReduce Frameworks
No full textResearch has shown that approximate computing is effective at reducing the resource requirements, computation time, and/or energy consumption of large-scale computing. In this paper, we We propose and evaluate a framework for creating and running approximation-enabled MapReduce programs. Specifically, we propose approximation mechanisms that fit naturally into the MapReduce paradigm, including input data sampling, task dropping, and accepting and running a precise and a user-defined approximate version of the MapReduce code. We then show how to leverage statistical theories to compute error bounds for popular classes of MapReduce programs when approximating with input data sampling and/or task dropping. We implement the proposed mechanisms and error bound estimations in a prototype system called ApproxHadoop. Our evaluation uses MapReduce applications from different domains, including data analytics, scientific computing, video encoding, and machine learning. Our results show that ApproxHadoop can significantly reduce application execution time and/or energy consumption when the user is willing to tolerate small errors. For example, ApproxHadoop can reduce runtimes by up to 32× when the user can tolerate an error of 1% with 95% confidence. We conclude that our framework and system can make approximation easily accessible to many application domains using the MapReduce model.Technical report DCS-TR-70
Cost-Aware Building of Cloud Services Powered by Renewable Energy
No full textInterest in powering datacenters at least partially using on-site renewable sources, e.g. solar or wind, has been growing. In fact, researchers have studied distributed services comprising networks of such “green” datacenters, and load distribution approaches that “follow the renewables” to maximize their use. Unfortunately, the prior works have not considered where to site such a network for efficient production of renewable energy, while minimizing both datacenter and renewable plant building costs. Moreover, researchers have not built real load management systems for follow-the-renewables services. Thus, in this paper, we propose a framework, optimization problem, and solution approach for siting and provisioning green datacenters for a follow-the-renewables HPC cloud service. We illustrate the location selection tradeoffs by quantifying the minimum cost of achieving different amounts of renewable energy. Finally, we design and implement a system capable of migrating virtual machines across the green datacenters to follow the renewables. Among other interesting results, we demonstrate that one can build green HPC cloud services at a relatively low additional cost compared to existing servicesTechnical report DCS-TR-70
- …
