1,720,974 research outputs found
2.3 MW Biomass Steam Power Plant: Experimental and Thermodynamic Analysis
No full textThe present paper shows the experimental and numerical analysis of a biomass plant from maximum power of 2.3 MW. This is a classical Steam Power Plant with a maximum pressure of 48 bar and a turbine inlet temperature of about 430 °C at the design point. The size is significantly smaller than the mean of this type of system, but maintains a relative high value (about 22.9%) of the Global Electric Efficiency.
The analysis was conducted using experimental data, collected directly on the Power Plant, at the Design Point, and thus validating thermodynamic models.
The difficulty in collecting the experimental data of this type of system, is mainly due to the enormous variability of the lower heating value of biomass, which involves a large variability of the load and then the operating parameters. Combustion simulation was validated by experimental data (Flue gas temperature, air flow, fuel flow) and the results allowed the evaluation of the biomass composition that is within the range reported in the literature.
Different Plant configurations were, numerically, evaluated to plug the power fluctuations due to variability of biomass. A 100 kWe Natural Gas fuelled Micro-Gas Turbine (MGT) was numerically connected to the Biomass Steam Power Plant (BSPP) to evaluate the benefits on the power fluctuations and on the Global Electric Efficiency. A MGT thermodynamic scheme has been developed and, properly, validated with experimental data from literature. It is designed to send the hot gases coming from the exit of the MGT in the combustion chamber of the main system, thus creating a MGT-ST Power Plant. Analysis of the results of this coupling has noticed an improvement in terms of efficiency and operational stability
Experimental Data and Thermodynamic Analysis of Biomass Steam Power Plant with Two Different Configurations Plant
No full textThis paper presents an experimental and numerical analysis of a biomass plant with a maximum power of 2.3 mw. The plant is significantly smaller than the average size of this type of system [1][2][3][4], but maintains a relatively high global electric efficiency (approximately 22.9%). The analysis used experimental data, collected directly from the power plant, at the design point, and thus validates the thermodynamic models. A combustion simulation was validated by experimental data (flue gas temperature, air flow, fuel flow), and the results the biomass composition that is within the range reported in the literature [5]. The integration with the steam plant biomass was achieved by combining the hot exhaust gases [6][7] together with the biomass in the main combustion chamber of the plant. The results showed that the efficiency of the energy conversion was extremely high, higher than that from incinerating CDR, and thus, biomass at a high humidity can be disposed of in a gasifier
Efficiency and Cost Optimization of a Regenerative Organic Rankine Cycle Power Plant through the Multi-Objective Approach
No full textMulti-objective optimization could be, in the industrial sector, a fundamental strategic approach for defining the target design specifications and operating parameters of new competitive products for the market, especially in renewable energy and energy savings fields. Vector optimization mostly enabled the determination of a set of optimal solutions characterized by different costs, sizes, efficiencies and other key features. The designer can subsequently select the solution with the best compromise between the objective functions for the specific application and constraints. In this paper, a multi-objective optimization problem addressing an Organic Rankine Cycle system is solved with consideration for the electric efficiency and overall heat exchangers area as quantities that should be optimized. In fact, considering that the overall capital cost of the ORC system is dominated by the cost of the heat exchangers rather than that of the pump and turbine, this area is related to the cost of the plant and so it was used to indirectly optimize the economic system performance. For this reason, although cost data have not been used, the heat exchangers area was used as a second objective function to minimize the plant cost. Pareto optimal solutions highlighted a trade-off between the two conflicting objective functions. Octamethyltrisiloxane (MDM) was considered organic working fluid, while the following input parameters were used as decision variables: minimum and maximum pressure of the thermodynamic cycle; superheating and subcooling temperature; and regenerator heat exchanger efficiency. Four different solutions belonging to the Pareto optimal front were selected and analyzed. These solutions are characterized by a range of the electric efficiency between 14.1% and 18.9% and overall heat exchangers area from 446 m2 to 1079 m2
Evaluating the potential of quantum machine learning in cybersecurity: A case-study on PCA-based intrusion detection systems
Full text linkQuantum computing promises to revolutionize our understanding of the limits of computation, and its implications in cryptography have long been evident. Today, cryptographers are actively devising post-quantum solutions to counter the threats posed by quantum-enabled adversaries. Meanwhile, quantum scientists are innovating quantum protocols to empower defenders. However, the broader impact of quantum computing and quantum machine learning (QML) on other cybersecurity domains still needs to be explored. In this work, we investigate the potential impact of QML on cybersecurity applications of traditional ML. First, we explore the potential advantages of quantum computing in machine learning problems specifically related to cybersecurity. Then, we describe a methodology to quantify the future impact of fault-tolerant QML algorithms on real-world problems. As a case study, we apply our approach to standard methods and datasets in network intrusion detection, one of the most studied applications of machine learning in cybersecurity. Our results provide insight into the conditions for obtaining a quantum advantage and the need for future quantum hardware and software advancements
A Gasification System for the Disposal of Industrial Waste and Energy Generation: Experimentation and Thermodynamic Analysis
No full textThe present paper shows the thermodynamic analysis of a gasification system, which is currently used for the recovery of metals from contaminated substances of organic origin (waste of mechanical process, rolling, cold-drawn, tins, multi-coupled materials, tetra, etc. .), and that, in this paper, is extended to the energy recovery and disposal of Paper Industry Waste. The interest in pyrolysis and gasification is justified because these processes go over the traditional combustion systems of biomass and waste.
In this system the inert ambient is supported by the smoke coming from the combustion of natural gas and it is possible to schematize it into a line of heat treatment and in a flue gas cleaning occurring after the combustion.
Using the results of different experimental tests a thermodynamic and thermo-chemical analysis is carried out. Starting from the energy and mass balances on the entire system and on the each component, the balance of the gasification reactions is verified
Quantum algorithms for SVD-based data representation and analysis
Full text linkThis paper narrows the gap between previous literature on quantum linear algebra and practical data analysis on a quantum computer, formalizing quantum procedures that speed-up the solution of eigenproblems for data representations in machine learning. The power and practical use of these subroutines is shown through new quantum algorithms, sublinear in the input matrix’s size, for principal component analysis, correspondence analysis, and latent semantic analysis. We provide a theoreti- cal analysis of the run-time and prove tight bounds on the randomized algorithms’ error. We run experiments on multiple datasets, simulating PCA’s dimensionality reduction for image classification with the novel routines. The results show that the run-time parameters that do not depend on the input’s size are reasonable and that the error on the computed model is small, allowing for competitive classification performances
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
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