Review of low-temperature vapour power cycle engines with quasi-isothermal expansion

External combustion heat cycle engines convert thermal energy into useful work. Thermal energy resources include solar, geothermal, bioenergy, and waste heat. To harness these and maximize work output, there has been a renaissance of interest in the investigation of vapour power cycles for quasi-isothermal (near constant temperature) instead of adiabatic expansion. Quasi-isothermal expansion has the advantage of bringing the cycle efficiency closer to the ideal Carnot efficiency, but it requires heat to be transferred to the working fluid as it expands. This paper reviews various low-temperature vapour power cycle heat engines with quasi-isothermal expansion, including the methods employed to realize the heat transfer. The heat engines take the form of the Rankine cycle with continuous heat addition during the expansion process, or the Stirling cycle with a condensable vapour as working fluid. Compared to more standard Stirling engines using gas, the specific work output is higher. Cryogenic heat engines based on the Rankine cycle have also been enhanced with quasi-isothermal expansion. Liquid flooded expansion and expander surface heating are the two main heat transfer methods employed. Liquid flooded expansion has been applied mainly in rotary expanders, including scroll turbines; whereas surface heating has been applied mainly in reciprocating expanders. © 2014 Elsevier Ltd.

The design and validation of an optical coherence tomography-based classification system for focal vitreomacular traction

PurposeTo develop and validate a classification system for focal vitreomacular traction (VMT) with and without macular hole based on spectral domain optical coherence tomography (SD-OCT), intended to aid in decision-making and prognostication.MethodsA panel of retinal specialists convened to develop this system. A literature review followed by discussion on a wide range of cases formed the basis for the proposed classification. Key features on OCT were identified and analysed for their utility in clinical practice. A final classification was devised based on two sequential, independent validation exercises to improve interobserver variability.ResultsThis classification tool pertains to idiopathic focal VMT assessed by a horizontal line scan using SD-OCT. The system uses width (W), interface features (I), foveal shape (S), retinal pigment epithelial changes (P), elevation of vitreous attachment (E), and inner and outer retinal changes (R) to give the acronym WISPERR. Each category is scored hierarchically. Results from the second independent validation exercise indicated a high level of agreement between graders: intraclass correlation ranged from 0.84 to 0.99 for continuous variables and Fleiss' kappa values ranged from 0.76 to 0.95 for categorical variables.ConclusionsWe present an OCT-based classification system for focal VMT that allows anatomical detail to be scrutinised and scored qualitatively and quantitatively using a simple, pragmatic algorithm, which may be of value in clinical practice as well as in future research studies.

Benchmarking of distributed computing engines spark and GraphLab for big data analytics

In this paper we evaluate and compare two representativeand popular distributed processing engines for large scalebig data analytics, Spark and graph based engine GraphLab. Wedesign a benchmark suite including representative algorithmsand datasets to compare the performances of the computingengines, from performance aspects of running time, memory andCPU usage, network and I/O overhead. The benchmark suite istested on both local computer cluster and virtual machines oncloud. By varying the number of computers and memory weexamine the scalability of the computing engines with increasingcomputing resources (such as CPU and memory). We also runcross-evaluation of generic and graph based analytic algorithmsover graph processing and generic platforms to identify thepotential performance degradation if only one processing engineis available. It is observed that both computing engines showgood scalability with increase of computing resources. WhileGraphLab largely outperforms Spark for graph algorithms, ithas close running time performance as Spark for non-graphalgorithms. Additionally the running time with Spark for graphalgorithms over cloud virtual machines is observed to increaseby almost 100% compared to over local computer clusters.

Towards next generation vertical search engines

As the Web evolves unexpectedly fast, information grows explosively. Useful resources become more and more difficult to find because of their dynamic and unstructured characteristics. A vertical search engine is designed and implemented towards a specific domain. Instead of processing the giant volume of miscellaneous information distributed in the Web, a vertical search engine targets at identifying relevant information in specific domains or topics and eventually provides users with up-to-date information, highly focused insights and actionable knowledge representation. As the mobile device gets more popular, the nature of the search is changing. So, acquiring information on a mobile device poses unique requirements on traditional search engines, which will potentially change every feature they used to have. To summarize, users are strongly expecting search engines that can satisfy their individual information needs, adapt their current situation, and present highly personalized search results. ^ In my research, the next generation vertical search engine means to utilize and enrich existing domain information to close the loop of vertical search engine's system that mutually facilitate knowledge discovering, actionable information extraction, and user interests modeling and recommendation. I investigate three problems in which domain taxonomy plays an important role, including taxonomy generation using a vertical search engine, actionable information extraction based on domain taxonomy, and the use of ensemble taxonomy to catch user's interests. As the fundamental theory, ultra-metric, dendrogram, and hierarchical clustering are intensively discussed. Methods on taxonomy generation using my research on hierarchical clustering are developed. The related vertical search engine techniques are practically used in Disaster Management Domain. Especially, three disaster information management systems are developed and represented as real use cases of my research work.^

Towards Next Generation Vertical Search Engines

As the Web evolves unexpectedly fast, information grows explosively. Useful resources become more and more difficult to find because of their dynamic and unstructured characteristics. A vertical search engine is designed and implemented towards a specific domain. Instead of processing the giant volume of miscellaneous information distributed in the Web, a vertical search engine targets at identifying relevant information in specific domains or topics and eventually provides users with up-to-date information, highly focused insights and actionable knowledge representation. As the mobile device gets more popular, the nature of the search is changing. So, acquiring information on a mobile device poses unique requirements on traditional search engines, which will potentially change every feature they used to have. To summarize, users are strongly expecting search engines that can satisfy their individual information needs, adapt their current situation, and present highly personalized search results. In my research, the next generation vertical search engine means to utilize and enrich existing domain information to close the loop of vertical search engine's system that mutually facilitate knowledge discovering, actionable information extraction, and user interests modeling and recommendation. I investigate three problems in which domain taxonomy plays an important role, including taxonomy generation using a vertical search engine, actionable information extraction based on domain taxonomy, and the use of ensemble taxonomy to catch user's interests. As the fundamental theory, ultra-metric, dendrogram, and hierarchical clustering are intensively discussed. Methods on taxonomy generation using my research on hierarchical clustering are developed. The related vertical search engine techniques are practically used in Disaster Management Domain. Especially, three disaster information management systems are developed and represented as real use cases of my research work.

RAGE Reusable Game Software Components and Their Integration into Serious Game Engines

This paper presents and validates a methodology for integrating reusable software components in diverse game engines. While conforming to the RAGE com-ponent-based architecture described elsewhere, the paper explains how the interac-tions and data exchange processes between a reusable software component and a game engine should be implemented for procuring seamless integration. To this end, a RAGE-compliant C# software component providing a difficulty adaptation routine was integrated with an exemplary strategic tile-based game “TileZero”. Implementa-tions in MonoGame, Unity and Xamarin, respectively, have demonstrated successful portability of the adaptation component. Also, portability across various delivery platforms (Windows desktop, iOS, Android, Windows Phone) was established. Thereby this study has established the validity of the RAGE architecture and its un-derlying interaction processes for the cross-platform and cross-game engine reuse of software components. The RAGE architecture thereby accommodates the large scale development and application of reusable software components for serious gaming.

Designing low-emission aero-engines using adjoint methods

The aim of this work is to investigate an efficient CAD based adjoint process chain for calculating sensitivities of the objective function to the CAD parameter in time scales acceptable for industrial design processes.

Emission Control in Diesel Engines by Alcohol Fumigation, 1990

Exhaust emissions from diesel engines are a substantial source of air pollution in this country. In recognition of this fact, the Environmental Protection Agency has issued strict new regulations due to take effect -in 1991 and 1994 that will drastically reduce the amount of some pollutants these engines will be allowed to emit. The technology is not currently available to produce diesel engines that can meet these regulations without large penalties in engine performance and efficiency. One technique that offers promise of being able to reduce emissions from both existing engines and new engines is alcohol fumigation.

Conception optimale d’une chaîne de traction électrique pour une voiture de type Formule SAE

La Formule SAE (Society of Automotive Engineers) est une compétition étudiante consistant en la conception et la fabrication d’une voiture de course monoplace. De nombreux événements sont organisés à chaque année au cours desquels plusieurs universités rivalisent entre elles lors d’épreuves dynamiques et statiques. Celles-ci comprennent l’évaluation de la conception, l’évaluation des coûts de fabrication, l’accélération de la voiture, etc. Avec plus de 500 universités participantes et des événements annuels sur tous les continents, il s’agit de la plus importante compétition d’ingénierie étudiante au monde. L’équipe ULaval Racing a participé pendant plus de 20 ans aux compétitions annuelles réservées aux voitures à combustion. Afin de s’adapter à l’électrification des transports et aux nouvelles compétitions destinées aux voitures électriques, l’équipe a conçu et fabriqué une chaîne de traction électrique haute performance destinée à leur voiture 2015. L’approche traditionnelle employée pour concevoir une motorisation électrique consiste à imposer les performances désirées. Ces critères comprennent l’inclinaison maximale que la voiture doit pouvoir gravir, l’autonomie désirée ainsi qu’un profil de vitesse en fonction du temps, ou tout simplement un cycle routier. Cette approche n’est malheureusement pas appropriée pour la conception d’une traction électrique pour une voiture de type Formule SAE. Ce véhicule n’étant pas destiné à la conduite urbaine ou à la conduite sur autoroute, les cycles routiers existants ne sont pas représentatifs des conditions d’opération du bolide à concevoir. Ainsi, la réalisation de ce projet a nécessité l’identification du cycle d’opération routier sur lequel le véhicule doit opérer. Il sert de point de départ à la conception de la chaîne de traction composée des moteurs, de la batterie ainsi que des onduleurs de tension. L’utilisation d’une méthode de dimensionnement du système basée sur un algorithme d’optimisation génétique, suivie d’une optimisation locale couplée à une analyse par éléments-finis a permis l’obtention d’une solution optimale pour les circuits de type Formule SAE. La chaîne de traction conçue a été fabriquée et intégrée dans un prototype de voiture de l’équipe ULaval Racing lors de la saison 2015 afin de participer à diverses compétitions de voitures électriques.

Development of variable displacement oil pump for internal combustion engines

In the last years the need to develop more environmentally friendly and efficient cars as led to the development of several technologies to improve the performance of internal combustion engines, a large part of the innovations are focused in the auxiliary systems of the engine, including, the oil pump, this is an element of great importance in the dynamics of the engine as well a considerable energy consumer. Most solutions for oil pumps to this day are fixed displacement, for medium and high speeds, the pump flow rate is higher than the needs of the engine, this excess flow leads to the need for recirculation of the fluid which represents a waste of energy. Recently, technological advances in this area have led to the creation of variable displacement oil pumps, these have become a 'must have' due to the numerous advantages they bring, although the working principle of vane or piston pumps is relatively well known, the application of this technology for the automotive industry is new and brings new challenges. The focus of this dissertation is to develop a new concept of variable displacement system for automotive oil pumps. The main objective is to obtain a concept that is totally adaptable to existing solutions on the market (engines), both dimensionally as in performance specifications, having at the same time an innovative mechanical system for obtaining variable displacement. The developed design is a vane pump with variable displacement going in line with existing commercial solutions, however, the variation of the eccentricity commonly used to provide an variable displacement delivery is not used, the variable displacement is achieved without varying the eccentricity of the system but with a variation of the length of the pumping chamber. The principle of operation of the pump is different to existing solutions while maintaining the ability to integrate standard parts such as control valves and mechanical safety valves, the pump is compatible with commercial solutions in terms of interfaces for connection between engine systems and pump. A concept prototype of the product was obtained in order to better evaluate the validity of the concept. The developed concept represents an innovation in oil pumps design, being unique in its mechanical system for variable displacement delivery.

An Acoustic Analysis of Valveless Pulsejet Engines

Valveless pulsejets are extremely simple aircraft engines; essentially cleverly designed tubes with no moving parts. These engines utilize pressure waves, instead of machinery, for thrust generation, and have demonstrated thrust-to-weight ratios over 8 and thrust specific fuel consumption levels below 1 lbm/lbf-hr – performance levels that can rival many gas turbines. Despite their simplicity and competitive performance, they have not seen widespread application due to extremely high noise and vibration levels, which have persisted as an unresolved challenge primarily due to a lack of fundamental insight into the operation of these engines. This thesis develops two theories for pulsejet operation (both based on electro-acoustic analogies) that predict measurements better than any previous theory reported in the literature, and then uses them to devise and experimentally validate effective noise reduction strategies. The first theory analyzes valveless pulsejets as acoustic ducts with axially varying area and temperature. An electro-acoustic analogy is used to calculate longitudinal mode frequencies and shapes for prescribed area and temperature distributions inside an engine. Predicted operating frequencies match experimental values to within 6% with the use of appropriate end corrections. Mode shapes are predicted and used to develop strategies for suppressing higher modes that are responsible for much of the perceived noise. These strategies are verified experimentally and via comparison to existing models/data for valveless pulsejets in the literature. The second theory analyzes valveless pulsejets as acoustic systems/circuits in which each engine component is represented by an acoustic impedance. These are assembled to form an equivalent circuit for the engine that is solved to find the frequency response. The theory is used to predict the behavior of two interacting pulsejet engines. It is validated via comparison to experiment and data in the literature. The technique is then used to develop and experimentally verify a method for operating two engines in anti-phase without interfering with thrust production. Finally, Helmholtz resonators are used to suppress higher order modes that inhibit noise suppression via anti-phasing. Experiments show that the acoustic output of two resonator-equipped pulsejets operating in anti-phase is 9 dBA less than the acoustic output of a single pulsejet.

Using interaction data for improving the offline and online evaluation of search engines

This thesis investigates how web search evaluation can be improved using historical interaction data. Modern search engines combine offline and online evaluation approaches in a sequence of steps that a tested change needs to pass through to be accepted as an improvement and subsequently deployed. We refer to such a sequence of steps as an evaluation pipeline. In this thesis, we consider the evaluation pipeline to contain three sequential steps: an offline evaluation step, an online evaluation scheduling step, and an online evaluation step. In this thesis we show that historical user interaction data can aid in improving the accuracy or efficiency of each of the steps of the web search evaluation pipeline. As a result of these improvements, the overall efficiency of the entire evaluation pipeline is increased. Firstly, we investigate how user interaction data can be used to build accurate offline evaluation methods for query auto-completion mechanisms. We propose a family of offline evaluation metrics for query auto-completion that represents the effort the user has to spend in order to submit their query. The parameters of our proposed metrics are trained against a set of user interactions recorded in the search engine’s query logs. From our experimental study, we observe that our proposed metrics are significantly more correlated with an online user satisfaction indicator than the metrics proposed in the existing literature. Hence, fewer changes will pass the offline evaluation step to be rejected after the online evaluation step. As a result, this would allow us to achieve a higher efficiency of the entire evaluation pipeline. Secondly, we state the problem of the optimised scheduling of online experiments. We tackle this problem by considering a greedy scheduler that prioritises the evaluation queue according to the predicted likelihood of success of a particular experiment. This predictor is trained on a set of online experiments, and uses a diverse set of features to represent an online experiment. Our study demonstrates that a higher number of successful experiments per unit of time can be achieved by deploying such a scheduler on the second step of the evaluation pipeline. Consequently, we argue that the efficiency of the evaluation pipeline can be increased. Next, to improve the efficiency of the online evaluation step, we propose the Generalised Team Draft interleaving framework. Generalised Team Draft considers both the interleaving policy (how often a particular combination of results is shown) and click scoring (how important each click is) as parameters in a data-driven optimisation of the interleaving sensitivity. Further, Generalised Team Draft is applicable beyond domains with a list-based representation of results, i.e. in domains with a grid-based representation, such as image search. Our study using datasets of interleaving experiments performed both in document and image search domains demonstrates that Generalised Team Draft achieves the highest sensitivity. A higher sensitivity indicates that the interleaving experiments can be deployed for a shorter period of time or use a smaller sample of users. Importantly, Generalised Team Draft optimises the interleaving parameters w.r.t. historical interaction data recorded in the interleaving experiments. Finally, we propose to apply the sequential testing methods to reduce the mean deployment time for the interleaving experiments. We adapt two sequential tests for the interleaving experimentation. We demonstrate that one can achieve a significant decrease in experiment duration by using such sequential testing methods. The highest efficiency is achieved by the sequential tests that adjust their stopping thresholds using historical interaction data recorded in diagnostic experiments. Our further experimental study demonstrates that cumulative gains in the online experimentation efficiency can be achieved by combining the interleaving sensitivity optimisation approaches, including Generalised Team Draft, and the sequential testing approaches. Overall, the central contributions of this thesis are the proposed approaches to improve the accuracy or efficiency of the steps of the evaluation pipeline: the offline evaluation frameworks for the query auto-completion, an approach for the optimised scheduling of online experiments, a general framework for the efficient online interleaving evaluation, and a sequential testing approach for the online search evaluation. The experiments in this thesis are based on massive real-life datasets obtained from Yandex, a leading commercial search engine. These experiments demonstrate the potential of the proposed approaches to improve the efficiency of the evaluation pipeline.

Effects of infiltration pressure on mechanical properties of Al–12Si/graphite composites for piston engines

In this work results for the flexural strength and the thermal properties of interpenetrated graphite preforms infiltrated with Al-12wt%Si are discussed and compared to those for packed graphite particles. To make this comparison relevant, graphite particles of four sizes in the range 15–124 μm, were obtained by grinding the graphite preform. Effects of the pressure applied to infiltrate the liquid alloy on composite properties were investigated. In spite of the largely different reinforcement volume fractions (90% in volume in the preform and around 50% in particle compacts) most properties are similar. Only the Coefficient of Thermal Expansion is 50% smaller in the preform composites. Thermal conductivity of the preform composites (slightly below 100 W/m K), may be increased by reducing the graphite content, alloying, or increasing the infiltration pressure. The strength of particle composites follows Griffith criterion if the defect size is identified with the particle diameter. On the other hand, the composites strength remains increasing up to unusually high values of the infiltration pressure. This is consistent with the drainage curves measured in this work. Mg and Ti additions are those that produce the most significant improvements in performance. Although extensive development work remains to be done, it may be concluded that both mechanical and thermal properties make these materials suitable for the fabrication of piston engines.

MODELING OF TRANSFER PATH FOR DETERMINATION OF COMBUSTION AND NOISE METRICS ON DIESEL ENGINES

Determination of combustion metrics for a diesel engine has the potential of providing feedback for closed-loop combustion phasing control to meet current and upcoming emission and fuel consumption regulations. This thesis focused on the estimation of combustion metrics including start of combustion (SOC), crank angle location of 50% cumulative heat release (CA50), peak pressure crank angle location (PPCL), and peak pressure amplitude (PPA), peak apparent heat release rate crank angle location (PACL), mean absolute pressure error (MAPE), and peak apparent heat release rate amplitude (PAA). In-cylinder pressure has been used in the laboratory as the primary mechanism for characterization of combustion rates and more recently in-cylinder pressure has been used in series production vehicles for feedback control. However, the intrusive measurement with the in-cylinder pressure sensor is expensive and requires special mounting process and engine structure modification. As an alternative method, this work investigated block mounted accelerometers to estimate combustion metrics in a 9L I6 diesel engine. So the transfer path between the accelerometer signal and the in-cylinder pressure signal needs to be modeled. Depending on the transfer path, the in-cylinder pressure signal and the combustion metrics can be accurately estimated - recovered from accelerometer signals. The method and applicability for determining the transfer path is critical in utilizing an accelerometer(s) for feedback. Single-input single-output (SISO) frequency response function (FRF) is the most common transfer path model; however, it is shown here to have low robustness for varying engine operating conditions. This thesis examines mechanisms to improve the robustness of FRF for combustion metrics estimation. First, an adaptation process based on the particle swarm optimization algorithm was developed and added to the single-input single-output model. Second, a multiple-input single-output (MISO) FRF model coupled with principal component analysis and an offset compensation process was investigated and applied. Improvement of the FRF robustness was achieved based on these two approaches. Furthermore a neural network as a nonlinear model of the transfer path between the accelerometer signal and the apparent heat release rate was also investigated. Transfer path between the acoustical emissions and the in-cylinder pressure signal was also investigated in this dissertation on a high pressure common rail (HPCR) 1.9L TDI diesel engine. The acoustical emissions are an important factor in the powertrain development process. In this part of the research a transfer path was developed between the two and then used to predict the engine noise level with the measured in-cylinder pressure as the input. Three methods for transfer path modeling were applied and the method based on the cepstral smoothing technique led to the most accurate results with averaged estimation errors of 2 dBA and a root mean square error of 1.5dBA. Finally, a linear model for engine noise level estimation was proposed with the in-cylinder pressure signal and the engine speed as components.