47 research outputs found
Domain Specific Instruction Set Extensions
No full textOver the past years, a considerable amount of effort has been devoted to the definition and implementation of techniques for the optimization and acceleration of applications on various computing platforms. Among these techniques, the extension of a given instruction-set architecture with custom instructions has become a common approach. Custom instructions effectively reduce the dynamic instruction count, which, in turn, leads to increase in performance and reduction in power consumption. Traditionally, existing techniques address Instruction-Set Extension (ISE) on a per-application basis. Anyhow, when many applications have to be considered at the same time, ISE on a per-application basis is, clearly, less effective, as the custom instructions have often limited re-utilization across applications. To overcome this problem, we propose a new framework for the automatic generation of domain-specific ISEs. Experimental results show that, the proposed framework, evaluated on a number of applications from various domains, can effectively generate domain-specific instructions with high utilization factor across the targeted applications. At the same time, the generated instructions reduce the instruction count, 45% on average and upto 80% in special cases. This, in turn, can lead to considerable improvements in performance and reduction of power consumption.Parallel and Distributed SystemsComputer EngineeringElectrical Engineering, Mathematics and Computer Scienc
Focused laser spike dewetting as a method to probe rheology of polymer thin films
No full textThin polymer films whose thickness ranges from fractions of a nanometer to several micrometers have been in high demand over the past few years in several industries. Their high surface area to volume ratio and the potential for low-cost processing with minimal material usage while fulfilling purpose requirements make them very useful. However, these films behave differently from bulk materials and majority of polymer fabrication processes involve polymer flow. Hence the study of polymer thin film rheology becomes crucial. Bulk measurement of rheology is well established, but it has disadvantages in that it requires a lot of material and may not capture thin film physics. Previous studies have demonstrated dewetting of thin polymer films to study film material stability and properties. This study seeks to use focused laser spike (FLaSk) dewetting as a method to probe rheology of thin material films. The method is used to extract materials properties of three thin films – Polystyrene (PS), Poly –4–hydroxystyrene (PHS) and N, N′-Bis (3 – methylphenyl)–N, N′-diphenylbenzidine (TPD) having different glass transition temperatures,M.S.Includes bibliographical referencesby Adithya Sridha
Open-Domain Aspect-Opinion Co-Mining with Double-Layer Span Extraction
No full textThe aspect-opinion extraction tasks extract aspect terms and opinion terms from reviews. The supervised extraction methods achieve state-of-the-art performance but require large-scale human-annotated training data. Thus, they are restricted for open-domain tasks due to the lack of training data. This work addresses this challenge and simultaneously mines aspect terms, opinion terms, and their correspondence in a joint model. We propose an Open-Domain Aspect-Opinion Co-Mining (ODAO) method with a Double-Layer span extraction framework. Instead of acquiring human annotations, ODAO first generates weak labels for unannotated corpus by employing rules-based on universal dependency parsing. Then, ODAO utilizes this weak supervision to train a double-layer span extraction framework to extract aspect terms (ATE), opinion terms (OTE), and aspect-opinion pairs (AOPE). ODAO applies canonical correlation analysis as an early stopping indicator to avoid the model over-fitting to the noise to tackle the noisy weak supervision. ODAO applies a self-training process to gradually enrich the training data to tackle the weak supervision bias issue. We conduct extensive experiments and demonstrate the power of the proposed ODAO. The results on four benchmark datasets for aspect-opinion co-extraction and pair extraction tasks show that ODAO can achieve competitive or even better performance compared with the state-of-the-art fully supervised methods.This proceeding is published as Mohna Chakraborty, Adithya Kulkarni, and Qi Li. 2022. Open-Domain Aspect-Opinion Co-Mining with Double-Layer Span Extraction. In Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD '22). Association for Computing Machinery, New York, NY, USA, 66–75. https://doi.org/10.1145/3534678.3539386. © 2022 Copyright held by the owner/author(s). This work is licensed under a Creative Commons Attribution International 4.0 License
A new coupled modelling framework for turbine inflow generation: mesoscale-synthetic turbulence
No full textAt the mercy of strong winds, high wind shear, unstable boundary layer and anomalous atmospheric conditions, stands a wind turbine designed to produce sustainable power under harsh conditions. The field of wind energy is a promising prospect for a sustainable future. Diverse research towards the improvement of a wind turbine’s capability and cost is currently the focus of the wind energy industry. With higher wind turbines being designed every day, various challenges and limitations of the current state-of-the-art surface; anomalous atmospheric conditions, structural integrity and cost.The goal of this thesis is to extend the approach to design a site-specific wind turbine considering an anomalous atmospheric condition. By coupling a mesoscale model with a stochastic turbulence function, a wind field capable of depicting a particular atmospheric condition is created. Using an aeroelastic solver the resulting loads on a wind turbine can be simulated. The methodology uses Weather, Research and Forecasting (WRF) model to re-create an event of low-level jet identified at the met mast of FINO-1, off coast Germany. The wind profile is coupled with a stochastic turbulence function designed at FINO-1 to be used as wind field for the aeroelastic solver, FAST.A literature survey identified a multitude of approaches used for simulating a low-level jet and analyse the loads on a wind turbine, the majority of which indicate high computational costs and contrived re-creations of the event. Thus, the challenge was to identify a near-realistic event creation with low computational costs. Therefore, coupling a low-resolution mesoscale model to create the event with a site-specific stochastic turbulence function is used to analyse loads on a wind turbine. Meteorological data analysis at FINO-1 led to the identification of three case studies of low-level jets under varied stability conditions of the atmosphere. The case studies are compared with the International Electrotechnical Commission (IEC) standard’s, IEC – 61400 – Ed3; IEC Kaimal and IEC Great Planes Low Level Jet (GPLLJ) spectrum. For cases with high stability, on an average proposed model predicts 21% higher stress on blade root and 27% higher at the tower top and base in comparison to IEC GPLLJ and 15% and 30% lower in comparison to IEC Kaimal, respectively. Similarly, under unstable conditions, proposed model predicts similar loads on the blade root, 7% lower loads at the tower top and base in comparison to IEC GPLLJ and 30% higher loads for blade root and tower top and base in comparison to IEC Kaimal. Comparing these results with literature on high stability loading higher loads are expected under these conditions.Concluding, this project developed a model framework to analyse anomalous atmospheric phenomena on a wind turbine specific to a site with low computational costs. While the capabilities of the model have been successfully showcased, only a partial validation on a benchmark case has been carried out. Therefore, going forward a full physical validation of the model for its accuracy for its target applications is recommended.Electrical Engineering | Sustainable Energy Technolog
Aerodynamic assessment of sub-scale aircraft model: A multi-fidelity approach
No full textNovel designs like the Flying-V, Prandtl-Plane and Blended Wing-Body show promise towards sustainable aviation. In the preliminary design phase, Sub-scale Flight Test (SFT) is a reliable method to get insight into the flight behavior of these designs. The effectiveness and value provided by SFT depends on the similitude between the SFT model and the full-scale aircraft. The method ofcomputational scaling is a state-of-the-art method into designing SFT models, that maximizes the similitude. However, this method is often infeasible because of large computational costs. Of the various analyses in this methodology, the aerodynamic analysis is computationally most expensive. Therefore, this research developed a multi-fidelity approach for the assessment of aerodynamiccharacteristics of SFT model. The approach utilized a blend of Reynolds- Averaged Navier-Stokes (RANS) and 3D-Panel Method (3DPM). This provided a good tradeoff between accuracy and computational cost, making the method of computational scaling a feasible method into design of SFT models.Aerospace Engineerin
Evaluating the feasibility of studying propeller-wing interaction through ground-based high-speed experimental taxi-tests: A numerical study comparing a propeller powered aircraft in cruising free-flight with high-speed taxiing
No full textThe Dutch Electric Aviation Centre possesses and uses a Cessna Skymaster 337F as an experimental flying testbed to help gain knowledge to aid the transition towards hybrid/ electric aviation. The interaction between the rear propeller slipstream and the horizontal tail has been likened to the interaction of propeller-wing configurations seen on larger regional aircraft. The DEAC intends to study this interaction through ground-based high-speed taxi-tests before any flight tests. By doing so, tests are conducted in a safer and more accessible environment without the need for re-certification, albeit, with changes to both testing environment and aircraft operational settings. This numerical study focused on evaluating the feasibility of such a testing approach to help gain an insight and better prepare for experiments. RANS CFD studies were performed on a simplified self-designed and developed half-airplane half-propeller model of the aircraft in ground-run configuration and free-flight configuration. In this stead-state simulation, the propellers were treated as actuator disks and had a specified constant pressure rise. Vortices being shed from the fuselage and interacting with the tail were discovered. The uncertainties due to the chosen simplifications, the neglect of twin contra-rotating propeller swirls, and the fact that the formation and evolution of the wake vortices, and their interaction with both the rear propeller and the horizontal tail are inherently unsteady effects, precludes a definitive conclusion. A more detailed numerical model is required to address the situation and evaluate the feasibility of this approach.Dutch Electric Aviation CenterAerospace Engineerin
Optimal Charging Strategies for Electric Vehicle Fleets
No full textElectric vehicles are a fast-growing market in the automotive sector. In addition, the widespread use of renewable energy to power electric vehicles makes them sustainable, with considerably low greenhouse gas emissions. As a result, service providers are switching to fleets of electric vehicles to promote environmental sustainability. However, unlike conventional vehicles, EVs require unique infrastructure to charge them. This leads to some technical and economic challenges. Therefore, intelligent charging strategies are needed to charge EV fleets optimally.The thesis primarily focuses on minimizing the energy and battery degradation costs for a fleet operator using different charging strategies. To accomplish this objective, a joint optimization technique is used to solve the problem. The method used is an optimal exchange problem that works by clearing market constraints. Specifically, an ADMM-based distributed charging problem is used for charging the EV fleet. The algorithm is implemented for different charger power levels for the different strategies to analyze the difference in energy and battery degradation costs. Furthermore, a variable charger allocation method is proposed to charge the EV fleet.Mechanical Engineering | Systems and Contro
Decision Support for Port Investments: A Real Options Approach
No full textExpansions for future demand? How much capacity will be required? Until when the decision can be postponed? When to expand? What should be the magnitude of expansion? What is the position of such an investment? These are the kind of questions which a port authority is subjected to while making a decision to expand or develop a port. The decision to invest in the expansion of the port is based on the anticipation of the market in future. The port authorities try to bridge the gap between “What the port is doing?” and “What the port should be doing?”. The choice of timing and expansion is of extreme importance as it allows the port authority to ensure that the project is financially viable and at the same time they achieve its objectives. During the feasibility stages, while making these decisions, a static discounted cash flow (DCF) model is used to calculate the financial outcomes of the expansion plans. However, such a model gives an impression that the decision-maker is obliged to the expansion decisions and cannot delay or alter their scale of investments. However, the reality is otherwise, the decision-maker is an active manager, who adapts the development/expansion plans to the changes based on the project progress. The current study presents an alternative to the Predict and Control approach of the static DCF model. This is done using Real Options Analysis(ROA). Within the scope of the research, a conceptual framework for ROA for port decision making was derived. The conceptual framework is translated into a mathematical numerical model for a test case in Southeast Africa. The numerical model values the option of multi-stage capacity expansion for the port. Focus is maintained on incorporating flexibility “on” infrastructure based on timing and magnitude under the uncertainty of demand. Through the use of stochastic processes, Monte Carlo simulations, solution algorithm and sensitivity analysis a total of 96 strategies have been evaluated.Through the analysis of results, it was understood that flexibility has a monetary value when the expansions are done using multi-stage sequential methodologies. Sequential expansions allow the port authority to gain more information based on which the supply can be adapted. In the short term, rather than installing extra capacity, optimising the current operations has a greater benefit for the port authority. While for the long term, the port authority should hold their flexible options until the boundary value wherein the probability of pay-offs exceeding the initial capital expenditures drastically reduce. The option value was seen to be influenced the time until expiration, lead times, number of stages of expansion, modal split factor and dwelling times. ROA was seen to be more of a decision support tool to understand the position of the investment rather than a financial valuation model
Towards domain-specific Instruction-Set Generation
No full textOver the past years, a considerable amount of effort has been devoted to the definition and implementation of techniques for the optimization and acceleration of applications on various (reconfigurable) computing platforms. Among these techniques, the extension of a given instruction-set architecture with custom instructions has become a common approach. Custom instructions effectively reduce the dynamic instruction count, which, in turn, leads to an increase in performance. Traditionally, existing techniques address Instruction-Set Extension (ISE) on a per-application basis. Anyhow, when many applications have to be considered at the same time, ISE on a per-application basis is, clearly, less effective, as the custom instructions have, often, limited re-utilization across applications. To overcome this problem, we propose a new framework for the automatic generation of domain-specific ISEs. Experimental results show that, the proposed framework, evaluated on a number of applications from various domains, can effectively generate domain-specific instructions with high utilization factor across the targeted applications. At the same time, the generated instructions dramatically reduce the instruction count, 50% on average and upto 95% in special cases. This, in turn, can lead to a considerable improvement in performance
