The thesis addresses the economic impacts of construction safety in Greece. The research involved the development of a methodology for determining the overall costs of safety, namely the sum of the costs of accidents and the costs of safety management failures (with or without accident) including image cost. Hitherto, very little work has been published on the cost of accidents in practical case studies. Moreover, to the author’s belief, no research has been published that seeks to determine in real cases the costs of prevention. The methodology developed is new, transparent, and capable of being replicated and adapted to other employment sectors and to other countries. The methodology was applied to three construction projects in Greece to test the safety costing methodology and to offer some preliminary evidence on the business case for safety. The survey work took place between 1999 and 2001 and involved 27 months of costing work on site. The study focuses on the overall costs of safety that apply to the main (principal) contractor. The methodology is supported by 120 discrete cost categories, and systematic criteria for determining which costs are included (counted) in the overall cost of safety. A quality system (in compliance with ISO9000 series) was developed to support the work and ensure accuracy of data gathering. The results of the study offer some support for the business case for safety. Though they offer good support for the economics of safety as they demonstrate need for cost effectiveness. Subject to important caveats, those projects that appeared to manage safety more cost-effectively achieved the lowest overall safety cost. Nevertheless, results are significantly lower than of other published works for two main reasons; first costs due to damages with no potential to injury were not included and second only costs to main constructor were considered. Study’s results are discussed and compared with other publish works.

<p>Manufacturing today is increasingly competitive and every organization around the world is looking to decrease costs. Maintenance costs generated an average of 28 percent of total manufacturing cost at the Fiat Chrysler Indiana Transmission Plant One in 2018, states Rex White, Head Maintenance Planner at Fiat Chrysler (2018). Maintenance is a supportive expense that does not generate a profit, which makes maintenance an attractive expense to decrease. The cost for components and skilled labor are expensive; however, the downtime is exponentially a larger threat to production cost. One most feared scenarios within a manufacturing facility is that one machine takes down several as it backs up the entire production process.</p><p>The three major types of maintenance are reactive, preventive, and predictive. The research project focused on applying the principles of predictive maintenance to the Fiat Chrysler facilities in Indiana. The report explains the techniques and principles of applying the technology currently available to reduce downtime and maintenance cost. The predictive maintenance procedures and saving are compared with reactive and preventive methods to determine a value of return. The report will examine the benefits of using the Internet of Things technology to create autonomous self-diagnosing smart machines. The predictive maintenance plan in this research illustration will introduce health check equipment used to implement longer lasting machine components. In conclusion, the project developed out an entire predictive maintenance plan to reduce downtime and maintenance costs.<br></p><p></p><br>

This thesis documents the design, manufacture and testing of a passive and non-invasive micro-scale planar particle-from-fluid filter for segregating cell types from a homogeneous suspension. The microfluidics system can be used to separate spermatogenic cells from testis biopsy samples, providing a mechanism for filtrate retrieval for assisted reproduction therapy. The system can also be used for point-of-service diagnostics applications for hospitals, lab-on-a-chip pre-processing and field applications such as clinical testing in the third world. Various design concepts are developed and manufactured, and are assessed based on etched structure morphology, robustness to variations in the manufacturing process, and design impacts on fluid flow and particle separation characteristics. Segregation was measured using image processing algorithms that demonstrate efficiency is more than 55% for 1 µl volumes at populations exceeding 1 x 107. the technique supports a significant reduction in time over conventional processing, in the separation and identification of particle groups, offering a potential reduction in the associated cost of the targeted procedure. The thesis has developed a model of quasi-steady wetting flow within the micro channel and identifies the forces across the system during post-wetting equalisation. The model and its underlying assumptions are validated empirically in microfabricated test structures through a novel Micro-Particle Image Velocimetry technique. The prototype devices do not require ancillary equipment nor additional filtration media, and therefore offer fewer opportunities for sample contamination over conventional processing methods. The devices are disposable with minimal reagent volumes and process waste. Optimal processing parameters and production methods are identified with any improvements that could be made to enhance their performance in a number of identified potential applications.

In W. E. B. Du Bois’ The Souls of Black Folk there is a story entitled “Of the Coming of John” that features two boys named John, one black from a poor family, the other white from a wealthy family. As the two are away at college each family awaits ‘of the coming of John,’ the title is also a reference to maturity because black John becomes disillusioned with race relations as he is awakened to the injustices that seemed so normal. Like black John, I too went to college far away from my hometown, developed a heightened awareness of society’s racism, and retained a desire to return home to teach youth in my community. And like black John, I want to teach by implementing a pedagogy that promotes equity for black Americans amid inequitable conditions.<div><br></div><div>The research problem addressed in this study relates to the absence of sociopolitical teaching practices in K-12 engineering education, which I argue is necessary for equitable inclusion of underrepresented racial/ethnic minorities in general, and black males in particular. Black Americans are plagued by racial inequities that transcend all domains of societal living (e.g., economics, education, health, etc.); this lamentable reality is the direct result of historical disenfranchisement of this racial group within the United States. Therefore, engineering must be taught with pertinence to the social, political, and cultural realities of the pupils. This self-study was an investigation into my story of living as a black male and studying engineering, and how my experience (along with my sociological understanding of other black males) shaped the way I taught engineering to black boys. Critical autoethnography was used to articulate the cultural and experiential knowledge that guided my instructional methods. Black Critical Theory, an offshoot of Critical Race Theory, served as one theoretical framework for this study because it centralizes the prevalence of anti-blackness as a lens to understand the experiences of black citizens. African American Male Theory is a complementary framework as it takes a broader ecological perspective to analyze the experiences of black male citizens. Taken together, these frameworks reveal the distinct features of American life negotiated by black males.<br></div><div><br></div><div>Resultantly, my life events led me to merge black racial identity, black politics, and the dynamics surrounding the education of black boys to teach K-12 engineering within a critical race pedagogical framework. I was socialized to be present and authentic among the people I want to lead and serve, hence, my devotion to community-engage scholarship. I grew tired of watching educators give-up on black students or become volatile, therefore, I spent time with the hyper-marginalized to build up the requisite resilience to avoid dysfunctional teaching and a cynical demeanor. I have felt undervalued and left-out in some classroom experiences, so I prioritize connecting with students over presenting content. I’ve witnessed engineering educators ostracize and belittle students unwilling to assimilate to its cultural norms, contrarily, I taught black boys with the goal of making engineering relatable to them, not vice versa.<br></div>

No description available.

No description available.

This thesis presents the design, development and testing of a new film cooling hole geometry, the converging slot-hole or console. Both the thermal and aerodynamic performance were measured, using the adiabatic effectiveness and heat transfer coefficient, and aerodynamic loss respectively, to quantify performance. Comparative measurements were made, by testing conventional film cooling hole shapes in parallel with the console experiments. The CFD code, Fluent, was used to predict the performance of the initial design concept before it was manufactured. Initial performance measurements in incompressible flow were performed in a low speed wind tunnel at an engine representative Reynolds number based on mainstream flow and hole diameter. For these experiments, the coolant to mainstream density ratio was approximately unity, and the cooling performance was measured over a flat plate. The console was tested in parallel with cylindrical holes, a slot and fan-shaped holes, all of which had equal throat area per unit width. The heat transfer performance was measured at steady state using thermochromic liquid crystals sprayed onto a flat plate heater. The aerodynamic performance of the holes was measured by traversing the boundary layer 50 cylindrical hole diameters downstream of the injection location with a pitot probe. Engine representative measurements of the console performance were made in a transonic annular cascade that simulates the three-dimensional flow in the gas turbine. The Reynolds and Mach numbers were representative of engine conditions, and the coolant flow was made aerodynamically and thermodynamically similar to engine conditions by matching both the momentum flux and density ratios. This was achieved by using a heavy foreign gas with the composition of 30.2% SF6 and 69.8% Ar by weight, which simulates the coolant to mainstream density ratio of 1.78, and has a ratio of specific heats of 1.4. The performance of a nozzle guide vane with rows of fan-shaped holes was compared with an NGV with a film cooling configuration designed with rows of consoles replacing rows of fan-shaped holes. The heat transfer performance was measured using a modified step change transient liquid crystal technique. The aerodynamic performance was measured using a four hole probe traverse downstream of the NGV. The heat transfer performance of the console was found to be similar to or slightly lower than the performance of fan-shaped holes. The most significant benefit of the console was found to be the aerodynamic performance, with a loss due to film cooling of only 20% of the loss due to film cooling of the rows of fan-shaped holes measured at engine representative conditions.

<div>Thermoelectric (TE) devices are useful in niche applications that require reliability and durability, including energy harvesters for sensors, cooling electronics, and power generation at high temperatures. Assessing, optimizing, and implementing materials into practical TE devices and systems have been difficult theoretical and engineering problems. The goal of this research is to develop a first-principles informed approach to analyze thermoelectric materials for potential practical applications.</div><div>TE materials and devices are traditionally quantified using a material figure of merit (FOM), zT, and device FOM, ZT. Using full numerical descriptions of band structures and solutions to the Boltzmann transport equation (BTE) in the relaxation time approximation (RTA), we examine how band convergence may or may not increase zT depending on the relative strength of intra- and inter-band scattering. We compute zT vs. a generalized TE quality factor (b-factor) and examine a dozen complex TE materials showing none exceeds the performance of a simple, parabolic energy band. In fact, a plot of zT vs. b-factor appears to be universal. We test this conclusion based on RTA solutions to the BTE using a simple treatment of scattering against more rigorous first-principles approaches. </div><div>In addition, we theoretically assess a low-cost TE oxide (2H-CuAlO₂), which has durability at high temperatures and is earth abundant, making it attractive for applications. Finally, with an eye towards minimizing the $cost/kW-hr of thermoelectric energy generation, we discuss our approach to a few specific high temperature environments and discuss their viability as practical system level applications.</div>

<div>Agricultural machinery is critical in modern farming. With continuous technological advancements in farm machinery, farm machines have evolved from simple mechanical machines to cyberphysical systems that contain rich sources of multimodal sensor data. Effective acquisition and analyses of these data have become essential but challenging tasks in revealing machine-centric and logistical insights to researchers and farmers.</div><div><br></div><div>In this dissertation, theses challenge are addressed in two parts. The first part demonstrates successful development and deployment of two open-source telematic devices for collecting machine network, geospatial, and video data. The first, ISOBlue 2.0, was designed to be a logger of both GPS and CAN data with wireless data streaming capabilities. The second, ISOBlue HD, an extension of ISOBlue 2.0, was configured to behave as a network server that interfaced with external cameras for automatic video recording of machine operation contexts. These devices were deployed in a variety of machines in different farming activities. A total of over 1 TB of multimodal machinery data were collected.<br></div><div><br></div><div>The second part presents three problems that focus on analyzing primarily GPS track data collected from past wheat harvests. The first poses an activity classification problem. It involved clustering a 3D feature set generated from both GPS and CAN data from a combine using the Density-Based Spatial Clustering of Applications with Noise algorithm. The<br>resultant clusters between on-road and in-field data samples as well as normal and anomalous activities. The second problem concentrates on combine unloading event detections using GPS tracks of multiple combines in 16 harvest sessions. The identified events from a novel algorithm that couples Interacting Multiple Models filtering and composite rules were utilized to estimate the total yield for each session. The estimated yields had an overall accuracy of over 90% when comparing to the actual weight ticket records. Lastly, two instantaneous metrics, instantaneous area capacity and swath utilization, were proposed and estimated using GPS tracks of multiple combines in 7 different fields during various harvest years. A novel algorithm was created for estimating instantaneous actual harvested area and swath utilization. This enabled exact computations of instantaneous metrics as oppose to conventional rough estimates of area capacity. Harvest performances were evaluated both temporally and geospatially by machines and years. It was discovered that three contributing factors that lead to high area capacity were wide header attachments, high harvesting speed, and uniform harvesting patterns. Moreover, it was found that the benefit of a wider header might diminish if the harvesting speed was low.<br></div>

<p>The manufacturing industry widely employs sound monitoring inspired by the ability of operators that can detect problems based on the sounds that machines emit. This monitoring serves as an integral component for predictive maintenance and productivity estimation. To facilitate real-time monitoring, edge devices are employed to manage and collect sound data. A streamlined Convolutional Neural Network (CNN) model was proposed, designed to execute all necessary computations for predictions, taking into consideration the limited computational resources of edge devices. Comparative analysis with renowned CNN models, namely VGG16, VGG19, ResNet-50, and YAMNet, reveals that the proposed CNN model is highly effective in event prediction from sound classification. Remarkably, the proposed model only required 2% of the prediction time as compared to the slowest and most complex model, while preserving an overall prediction accuracy of 98.9%. To balance the minor accuracy trade-off due to the simplicity of the proposed CNN architecture, an algorithm based on the First-In, First-Out (FIFO) queue system was developed. This method led to a reduction in the prediction error rate by up to 25% within a certain interval between the queue elements, in contrast to systems that do not implement this algorithm. The input feature adopted was the normalized Log-Mel spectrum with a duration of one second. A grid search method was utilized for hyperparameter tuning, with the aim of identifying the optimal hyperparameter combination within the constraints of the simplified CNN model architecture. To substantiate the real-time monitoring performance and superiority of the proposed CNN model, the same workflow was applied to the grain leg and plasma cutting machine using sound data collected from each. The results affirmed that the combination of the proposed CNN model and the developed algorithm exhibited exceptional performance under real-world conditions. In conclusion, for real-time monitoring that employs edge devices, the usage of a simplified CNN model and a customized algorithm is advocated to ensure continuous real-time monitoring devoid of errors or network instability.  </p>