1,731 research outputs found

    Combustion characteristics of several types of biofuel in a diesel engine

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    Interesovanje za alternativna goriva koja bi se koristila za pogon motora sus je veoma veliko u čitavom svetu. Zato se istraživanja vezana za ovu problematiku vrše u mnogim vodećim svetskim laboratorijama za motore. Razlog ovog interesovanja su dostupnost ovakvih goriva, povoljne ekološke karakteristike i pozitivan uticaj na ekonomije zemalja koje ovakva goriva mogu da proizvode. U predmetnom radu se daje deo rezulta veoma kompleksnih i dugotrajnih istraživanja dinamike procesa sagorevanja kod dizel motora pogonjenog metilestrima biljnih ulja i to otpadnog palminog jestivog ulja, sojinog ulja i ulja uljane repice. Poređenje promena u radnom procesu motora, pre svega procesu sagorevanja, je vršeno pri sinhronizovanom radu motora na uobičajenim standardnim dizel gorivom mineralnog porekla. Analizom zakona (toka) sagorevanja svakog pojedinačnog goriva, utvrđeno je da postoje razlike koje nisu velikog karaktera, iz čega se može zaključiti da su goriva proizvedena iz biljnih ulja, a po važećem standardu, veoma kvalitetna goriva za pogon dizel motora. Ovo daje mogućnost naročito poljoprivrednim gazdinstvima da samostalno proizvode deo potrebnog goriva sa sopstvenih zemljišnih parcela uz uslov da poseduju odgovarajuću opremu za proizvodnju biodizela.Alternative propulsion fuels for diesel engines were highlights for a variety of research activities within a large number of R&D labs in the world. Curiosity, as well as basic interest in alternative fuel has been immense because of its reproducibility, renewability, as well as good ecological characteristics. Another reason for this interest is a favorable impact on the economies of the countries engaged in their production, by processing that kind of bio fuel. This paper presents the results of testing and research of the three types of alternative fuel gained from bio oil. Analyses and comparison of the dynamics of combustion process of these alternative fuels were done in relation to the reference diesel fuel. Burning process of methyl esters rapeseed (RME100), soya oil (SME100), waste cooking palm oil (PME100), as well as of regular Euro diesel fuel were investigated. It was found that these fuels were highly usable in diesel engines if they had been produced according to a proper standard procedure under standard EN 14214. The application of bio fuel is also very interesting for the propulsion of agricultural engines and machinery, because it enables the individual farming of bio fuel products necessary for the appropriate own machinery

    NASA SBIR abstracts of 1992, phase 1 projects

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    The objectives of 346 projects placed under contract by the Small Business Innovation Research (SBIR) program of the National Aeronautics and Space Administration (NASA) are described. These projects were selected competitively from among proposals submitted to NASA in response to the 1992 SBIR Program Solicitation. The basic document consists of edited, non-proprietary abstracts of the winning proposals submitted by small businesses. The abstracts are presented under the 15 technical topics within which Phase 1 proposals were solicited. Each project was assigned a sequential identifying number from 001 to 346, in order of its appearance in the body of the report. Appendixes to provide additional information about the SBIR program and permit cross-reference of the 1992 Phase 1 projects by company name, location by state, principal investigator, NASA Field Center responsible for management of each project, and NASA contract number are included

    NASA SBIR abstracts of 1991 phase 1 projects

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    The objectives of 301 projects placed under contract by the Small Business Innovation Research (SBIR) program of the National Aeronautics and Space Administration (NASA) are described. These projects were selected competitively from among proposals submitted to NASA in response to the 1991 SBIR Program Solicitation. The basic document consists of edited, non-proprietary abstracts of the winning proposals submitted by small businesses. The abstracts are presented under the 15 technical topics within which Phase 1 proposals were solicited. Each project was assigned a sequential identifying number from 001 to 301, in order of its appearance in the body of the report. Appendixes to provide additional information about the SBIR program and permit cross-reference of the 1991 Phase 1 projects by company name, location by state, principal investigator, NASA Field Center responsible for management of each project, and NASA contract number are included

    Combustion characteristics of several types of biofuel in a diesel engine

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    Alternative propulsion fuels for diesel engines were highlights for a variety of research activities within a large number of R&D labs in the world. Curiosity, as well as basic interest in alternative fuel has been immense because of its reproducibility, renewability, as well as good ecological characteristics. Another reason for this interest is a favorable impact on the economies of the countries engaged in their production, by processing that kind of bio fuel. This paper presents the results of testing and research of the three types of alternative fuel gained from bio oil. Analyses and comparison of the dynamics of combustion process of these alternative fuels were done in relation to the reference diesel fuel. Burning process of methyl esters rapeseed (RME100), soya oil (SME100), waste cooking palm oil (PME100), as well as of regular euro diesel fuel were investigated. It was found that these fuels were highly usable in diesel engines if they had been produced according to a proper standard procedure under standard EN 14214. The application of bio fuel is also very interesting for the propulsion of agricultural engines and machinery, because it enables the individual farming of bio fuel products necessary for the appropriate own machinery

    Small business innovation research. Abstracts of completed 1987 phase 1 projects

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    Non-proprietary summaries of Phase 1 Small Business Innovation Research (SBIR) projects supported by NASA in the 1987 program year are given. Work in the areas of aeronautical propulsion, aerodynamics, acoustics, aircraft systems, materials and structures, teleoperators and robotics, computer sciences, information systems, spacecraft systems, spacecraft power supplies, spacecraft propulsion, bioastronautics, satellite communication, and space processing are covered

    Controls and Measurements of KU Engine Test Cells for Biodiesel, SynGas, and Assisted Biodiesel Combustion

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    This thesis is comprised of three unique data acquisition and controls (CDAQ) projects. Each of these projects differs from each other; however, they all include the concept of testing renewable or future fuel sources. The projects were the following: University of Kansas's Feedstock-to-Tailpipe Initiative's Synthesis Gas Reforming rig, Feedstock-to-Tailpipe Initiative's Biodiesel Single Cylinder Test Stand, and a unique Reformate Assisted Biodiesel Combustion architecture. The main responsibility of the author was to implement, develop and test CDAQ systems for the projects. For the Synthesis Gas Reforming rig, this thesis includes a report that summarizes the analysis and solution of building a controls and data acquisition system for this setup. It describes the purpose of the sensors selected along with their placement throughout the system. Moreover, it includes an explanation of the planned data collection system, along with two models describing the reforming process useful for system control. For the Biodiesel Single Cylinder Test Stand, the responsibility was to implement the CDAQ system for data collection. This project comprised a variety of different sensors that are being used collect the combustion characteristics of different biodiesel formulations. This project is currently being used by other graduates in order to complete their projects for subsequent publication. For the Reformate Assisted Biodiesel Combustion architecture, the author developed a reformate injection system to test different hydrogen and carbon monoxide mixtures as combustion augmentation. Hydrogen combustion has certain limiting factors, such as pre-ignition in spark ignition engines and inability to work as a singular fuel in compression ignition engines. To offset these issues, a dual-fuel methodology is utilized by injecting a hydrogen/carbon monoxide mixture into the intake stream of a diesel engine operating on biodiesel. While carbon monoxide does degrade some of the desirable properties of hydrogen, it acts partially like a diluent in order to prevent pre-ignition from occurring. The result of this mixture addition allows the engine to maintain power while reducing biodiesel fuel consumption with a minimal NOx emissions increase

    Machine learning based adaptive soft sensor for flash point inference in a refinery realtime process

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    In industrial control processes, certain characteristics are sometimes difficult to measure by a physical sensor due to technical and/or economic limitations. This fact is especially true in the petrochemical industry. Some of those quantities are especially crucial for operators and process safety. This is the case for the automotive diesel Flash Point Temperature (FT). Traditional methods for FT estimation are based on the study of the empirical inference between flammability properties and the denoted target magnitude. The necessary measures are taken indirectly by samples from the process and analyzing them in the laboratory, this process implies time (can take hours from collection to flash temperature measurement) and thus make it very difficult for real-time monitorization, which in fact results in security and economical losses. This study defines a procedure based on Machine Learning modules that demonstrate the power of real-time monitorization over real data from an important international refinery. As input, easily measured values provided in real-time, such as temperature, pressure, and hydraulic flow are used and a benchmark of different regressive algorithms for FT estimation is presented. The study highlights the importance of sequencing preprocessing techniques for the correct inference of values. The implementation of adaptive learning strategies achieves considerable economic benefits in the productization of this soft sensor. The validity of the method is tested in the reality of a refinery. In addition, real-world industrial data sets tend to be unstable and volatile, and the data is often affected by noise, outliers, irrelevant or unnecessary features, and missing data. This contribution demonstrates with the inclusion of a new concept, called an adaptive soft sensor, the importance of the dynamic adaptation of the conformed schemes based on Machine Learning through their combination with feature selection, dimensional reduction, and signal processing techniques. The economic benefits of applying this soft sensor in the refinery's production plant and presented as potential semi-annual savings.This work has received funding support from the SPRI-Basque Gov- ernment through the ELKARTEK program (OILTWIN project, ref. KK- 2020/00052)

    Recent advances in the characterization of gaseous and liquid fuels by vibrational spectroscopy

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    Date of Acceptance: 20/04/2015 Acknowledgments The author would like to thank Thomas Seeger, Alfred Leipertz, Florian Zehentbauer, Stella Corsetti, David McGloin, and Kristina Noack for fruitful discussions over the past decade. Special thanks to Lynda Cromwell and Andrew Williamson for proofreading the manuscriptPeer reviewedPublisher PD

    Online boiler convective heat exchanger monitoring: a comparison of soft sensing and data-driven approaches

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    Online monitoring supports plant reliability and performance management by providing real time information about the condition of equipment. However, the intricate geometries and harsh operating environment of coal fired power plant boilers inhibit the ability to do online measurements of all process related variables. A low-cost alternative lies in the possibility of using knowledge about boiler operation to extract information about its condition from standard online process measurements. This approach is evaluated with the aim of enhancing online condition monitoring of a boiler’s convective pass heat exchanger network by respectively using a soft sensor and a data-driven method. The soft sensor approach is based on a one-dimensional thermofluid process model which takes measurements as inputs and calculates unmeasured variables as outputs. The model is calibrated based on design information. The data-driven method is one developed specifically in this study to identify unique fault signatures in measurement data to detect and quantify changes in unmeasured variables. The fault signatures are initially constructed using the calibrated one-dimensional thermofluid process model. The benefits and limitations of these methods are compared at the hand of a case study boiler. The case study boiler has five convective heat exchanger stages, each composed of four separate legs. The data-driven method estimates the average conduction thermal resistance of individual heat exchanger legs and the flue gas temperature at the inlet to the convective pass. In addition to this, the soft sensor estimates the average fluid variables for individual legs throughout the convective pass and therefore provides information better suited for condition prognosis. The methods are tested using real plant measurements recorded during a period which contained load changes and on-load heat exchanger cleaning events. The cleaning event provides some basis for validating the results because the qualitative changes of some unmeasured monitored variables expected during this event are known. The relative changes detected by both methods are closely correlated. The data-driven method is computationally less expensive and easily implementable across different software platforms once the fault signatures have been obtained. Fault signatures are easily trainable once the model has been developed. The soft sensors require the continuous use of the modelling software and will therefore be subject to licencing constraints. Both methods offer the possibility to enhance the monitoring resolution of modern boilers without the need to install any additional measurements. Implementation of these monitoring frameworks can provide a simple and low-cost contribution to optimized boiler performance and reliability management
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