Experimental and Numerical Analysis of Ethanol Fueled HCCI Engine

Presently, the research on the homogeneous charge compression ignition (HCCI) engines has gained importance in the field of automotive power applications due to its superior efficiency and low emissions compared to the conventional internal combustion (IC) engines. In principle, the HCCI uses premixed lean homogeneous charge that auto-ignites volumetrically throughout the cylinder. The homogeneous mixture preparation is the main key to achieve high fuel economy and low exhaust emissions from the HCCI engines. In the recent past, different techniques to prepare homogeneous mixture have been explored. The major problem associated with the HCCI is to control the auto-ignition over wide range of engine operating conditions. The control strategies for the HCCI engines were also explored. This dissertation investigates the utilization of ethanol, a potential major contributor to the fuel economy of the future. Port fuel injection (PFI) strategy was used to prepare the homogeneous mixture external to the engine cylinder in a constant speed, single cylinder, four stroke air cooled engine which was operated on HCCI mode. Seven modules of work have been proposed and carried out in this research work to establish the results of using ethanol as a potential fuel in the HCCI engine. Ethanol has a low Cetane number and thus it cannot be auto-ignited easily. Therefore, intake air preheating was used to achieve auto-ignition temperatures. In the first module of work, the ethanol fueled HCCI engine was thermodynamically analysed to determine the operating domain. The minimum intake air temperature requirement to achieve auto-ignition and stable HCCI combustion was found to be 130 °C. Whereas, the knock limit of the engine limited the maximum intake air temperature of 170 °C. Therefore, the intake air temperature range was fixed between 130-170 °C for the ethanol fueled HCCI operation. In the second module of work, experiments were conducted with the variation of intake air temperature from 130-170 °C at a regular interval of 10 °C. It was found that, the increase in the intake air temperature advanced the combustion phase and decreased the exhaust gas temperature. At 170 °C, the maximum combustion efficiency and thermal efficiency were found to be 98.2% and 43% respectively. The NO emission and smoke emissionswere found to be below 11 ppm and 0.1% respectively throughout this study. From these results of high efficiency and low emissions from the HCCI engine, the following were determined using TOPSIS method. They are (i) choosing the best operating condition, and (ii) which input parameter has the greater influence on the HCCI output. In the third module of work, TOPSIS - a multi-criteria decision making technique was used to evaluate the optimum operating conditions. The optimal HCCI operating condition was found at 70% load and 170 °C charge temperature. The analysis of variance (ANOVA) test results revealed that, the charge temperature would be the most significant parameter followed by the engine load. The percentage contribution of charge temperature and load were63.04% and 27.89% respectively. In the fourth module of work, the GRNN algorithm was used to predict the output parameters of the HCCI engine. The network was trained, validated, and tested with the experimental data sets. Initially, the network was trained with the 60% of the experimental data sets. Further, the validation and testing of the network was done with each 20% data sets. The validation results predicted that, the output parameters those lie within 2% error. The results also showed that, the GRNN models would be advantageous for network simplicity and require less sparse data. The developed new tool efficiently predicted the relation between the input and output parameters. In the fifth module of work, the EGR was used to control the HCCI combustion. An optimum of 5% EGR was found to be optimum, further increase in the EGR caused increase in the hydrocarbon (HC) emissions. The maximum brake thermal efficiency of 45% was found for 170 °C charge temperature at 80% engine load. The NO emission and smoke emission were found to be below 10 ppm and 0.61% respectively. In the sixth module of work, a hybrid GRNN-PSO model was developed to optimize the ethanol-fueled HCCI engine based on the output performance and emission parameters. The GRNN network interpretive of the probability estimate such that it can predict the performance and emission parameters of HCCI engine within the range of input parameters. Since GRNN cannot optimize the solution, and hence swarm based adaptive mechanism was hybridized. A new fitness function was developed by considering the six engine output parameters. For the developed fitness function, constrained optimization criteria were implemented in four cases. The optimum HCCI engine operating conditions for the general criteria were found to be 170 °C charge temperature, 72% engine load, and 4% EGR. This model consumed about 60-75 ms for the HCCI engine optimization. In the last module of work, an external fuel vaporizer was used to prepare the ethanol fuel vapour and admitted into the HCCI engine. The maximum brake thermal efficiency of 46% was found for 170 °C charge temperature at 80% engine load. The NO emission and smoke emission were found to be below 5 ppm and 0.45% respectively. Overall, it is concluded that, the HCCI combustion of sole ethanol fuel is possible with the charge heating only. The high load limit of HCCI can be extended with ethanol fuel. High thermal efficiency and low emissions were possible with ethanol fueled HCCI to meet the current demand

Object Tracking with Multiple Instance Learning and Gaussian Mixture Model

Recently, Multiple Instance Learning (MIL) technique has been introduced for object tracking\linebreak applications, which has shown its good performance to handle drifting problem. While some instances in positive bags not only contain objects, but also contain the background, it is not reliable to simply assume that each feature of instances in positive bags obeys a single Gaussian distribution. In this paper, a tracker based on online multiple instance boosting has been developed, which employs Gaussian Mixture Model (GMM) and single Gaussian distribution respectively to model features of instances in positive and negative bags. The differences between samples and the model are integrated into the process of updating the parameters for GMM. With the Haar-like features extracted from the bags, a set of weak classifiers are trained to construct a strong classifier, which is used to track the object location at a new frame. And the classifier can be updated online frame by frame. Experimental results have shown that our tracker is more stable and efficient when dealing with the illumination, rotation, pose and appearance changes

Mining taxation in Sierra Leone

This dissertation explores why mineral revenue has been low in Sierra Leone. My approach to answering this question changed during the fieldwork, because of my interactions with key stakeholders in the mining sector. The discussions I had with the parties concerned and the documents I was able to access (some outside of the public domain) provided very useful information about the industry. I examine how politics has affected the mining sector. In essence, governments and politicians aspiring to power try hard to gain influence over the mining sector to get control over rents. They then use it for their own interests. In a range of ways, this undermines important institutions and public revenue. I then explore, in more detail, the factors through which pervasive politicization of mining, and corruption, have undermined public revenue. The overarching conclusion from this research is that low mining revenue is due to poor governance and corruption. I suggest that improving institutional capacity in the public sector and strengthening the role of parliament and civil society organizations must, therefore, constitute the cornerstone of the feasible reforms needed to raise revenue to the treasury. Though these proposed changes are not the entire solution, they could make a significant contribution to ensuring the right agreements are negotiated and implemented, ultimately increasing the government's share of the rents generated

Diverse Voices: Middle Years Students’ Insights into Life in Inclusive Classrooms

Thirty-one middle school students (grades 4–7) were interviewed at length about their perspectives regarding academic and social inclusion of students with disabilities; the barriers they perceive to a compassionate, inclusive learning community; and what they believe helps overcome these barriers. In discussing the inclusion of students with disabilities, participants were eloquent in their empathy for the challenges students with disabilities faced, while also articulating barriers to their willingness to include students with disabilities in their academic life based on pressures of the current school system, such as grades and pace, and the stigma associated with the presence of an educational assistant

Social Support, Substance Use, and Mental Health Services Utilization Among African Americans

Mental illness is more prevalent among African Americans than their Non-Hispanic White counterparts; however, this population is less inclined to receive behavioral treatment. The purpose of this study was to examine the association between perceived social support, substance use, and gender with mental health care services utilization among African Americans. The social ecological model and social support theory grounded this study. The research design was a quantitative cross-sectional analysis of the 2016 Behavioral Risk Factor Surveillance Survey. The sample consisted of 486,3030 African American adults that represented the U.S. population using weighted estimates. The overall logistic regression models for the 3 research questions were significant (p = .000). Controlling for sociodemographic factors, logistic regression analyses indicated that receiving emotional and social support predicted (OR=2.294) use of mental health care services in the last 12 months. Similarly, not using substances in the prior 30 days (OR=1.309) and being female (OR=2.562) predicted use of mental health care services in the last 12 months. The findings from this study may be used to increase awareness among mental health providers to refer African Americans to emotional and social support resources. The findings may lead to positive social change through the development of interventions for those who use substances and for men

Robust Correlation Tracking for UAV with Feature Integration and Response Map Enhancement

Recently, correlation filter (CF)-based tracking algorithms have attained extensive interest in the field of unmanned aerial vehicle (UAV) tracking. Nonetheless, existing trackers still struggle with selecting suitable features and alleviating the model drift issue for online UAV tracking. In this paper, a robust CF-based tracker with feature integration and response map enhancement is proposed. Concretely, we develop a novel feature integration method that comprehensively describes the target by leveraging auxiliary gradient information extracted from the binary representation. Subsequently, the integrated features are utilized to learn a background-aware correlation filter (BACF) for generating a response map that implies the target location. To mitigate the risk of model drift, we introduce saliency awareness in the BACF framework and further propose an adaptive response fusion strategy to enhance the discriminating capability of the response map. Moreover, a dynamic model update mechanism is designed to prevent filter contamination and maintain tracking stability. Experiments on three public benchmarks verify that the proposed tracker outperforms several state-of-the-art algorithms and achieves a real-time tracking speed, which can be applied in UAV tracking scenarios efficiently

Factors Affecting Work Performance During the COVID-19 Pandemic: An Empirical Study from Indonesia

The purpose of this study is to assess the impact of the principal’s democratic leadership style, teacher competency, work discipline, and work environment on teacher performance during the pandemic. Using the proportional random sampling strategy, a sample of 468 respondents consisted of kindergarten teachers, elementary school teachers, junior high school teachers, junior high school teachers, and high school/vocational school teachers. The study revealed that the principal’s democratic leadership style, teacher competence, work discipline, and work environment substantially impact teacher performance. However, the principal’s democratic leadership style does not affect teacher performance, whereas teacher competence, work discipline, and work environment have a minor impact on teacher performance. Furthermore, during the COVID-19 pandemic, work discipline is the most critical variable influencing teacher performance. The findings of this study suggest that the principal’s democratic leadership style, teacher competence, work discipline, and work environment have a positive impact on teacher performance during the pandemic. During the COVID-19 pandemic, work discipline is the most important variable influencing teacher performance. Considering that democratic leadership has no effect on teacher performance and that this leadership style is widely used by school principals in the world of education, it is assumed that there is no effect on teacher performance

Evaluating Testing Strategies for Identifying Youths With HIV Infection and Linking Youths to Biomedical and Other Prevention Services

Importance: Most human immunodeficiency virus (HIV)-infected youths are unaware of their serostatus (approximately 60%) and therefore not linked to HIV medical or prevention services. The need to identify promising and scalable approaches to promote uptake of HIV testing among youths at risk is critical. Objective: To evaluate a multisite HIV testing program designed to encourage localized HIV testing programs focused on self-identified sexual minority males and to link youths to appropriate prevention services after receipt of their test results. Design, Setting, and Participants: Testing strategies were evaluated using an observational design during a 9-month period (June 1, 2015, through February 28, 2016). Testing strategies were implemented by 12 adolescent medicine HIV primary care programs and included targeted testing, universal testing, or a combination. Data were collected from local youth at high risk of HIV infection and, specifically, sexual minority males of color. Main Outcomes and Measures: Proportion of sexual minority males and sexual minority males of color tested, proportion of previously undiagnosed HIV-positive youths identified, and rates of linkage to prevention services. Results: A total of 3301 youths underwent HIV testing. Overall, 35 (3.6%) of those who underwent universal testing in primary care clinical settings, such as emergency departments and community health centers, were sexual minority males (35 [3.6%] were males of color) compared with 236 (46.7%) (201 [39.8%] were males of color) who were tested through targeted testing and 693 (37.8%) (503 [27.4%] were males of color) through combination efforts. Identification of new HIV-positive cases varied by strategy: 1 (0.1%) via universal testing, 39 (2.1%) through combination testing, and 16 (3.2%) through targeted testing. However, when targeted tests were separated from universal testing results for sites using a combined strategy, the rate of newly identified HIV-positive cases identified through universal testing decreased to 1 (0.1%). Rates of new HIV-positive cases identified through targeted testing increased to 49 (6.3%). Youths who tested through targeted testing (416 [85.1%]) were more likely to link successfully to local HIV prevention services, including preexposure prophylaxis, compared with those who underwent universal testing (328 [34.1%]). Conclusions and Relevance: The findings suggest that community-based targeted approaches to HIV testing are more effective than universal screening for reaching young sexual minority males (especially males of color), identifying previously undiagnosed HIV-positive youths, and linking HIV-negative youths to relevant prevention services. Targeted, community-based HIV testing strategies hold promise as a scalable and effective means to identify high-risk youths who are unaware of their HIV status