Analysis of competitiveness level in an industrial company using a continuous improvement based approach

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Removal of BrO3 − from drinking water samples using newly developed agricultural waste-based activated carbon and its determination by ultra-performance liquid chromatography-mass spectrometry

Activated carbon was prepared from date pits via chemical activation with H3PO4. The effects of activating agent concentration and activation temperature on the yield and surface area were studied. The optimal activated carbon was prepared at 450 °C using 55 % H3PO4. The prepared activated carbon was characterized by Fourier transform infrared spectroscopy, scanning electron microscopy, thermogravimetric-differential thermal analysis, and Brunauer, Emmett, and Teller (BET) surface area. The prepared date pit-based activated carbon (DAC) was used for the removal of bromate (BrO3 −). The concentration of BrO3 − was determined by ultra-performance liquid chromatography-mass tandem spectrometry (UPLC-MS/MS). The experimental equilibrium data for BrO3 − adsorption onto DAC was well fitted to the Langmuir isotherm model and showed maximum monolayer adsorption capacity of 25.64 mg g−1. The adsorption kinetics of BrO3 − adsorption was very well represented by the pseudo-first-order equation. The analytical application of DAC for the analysis of real water samples was studied with very promising results.

Fabrication of Mg foams for biomedical applications by means of a replica method based upon spherical carbon particles

Interest in Mg foams is increasing due to their potential use as biomaterials. Fabrication methods determine to a great extent their structure and, in some cases, may pollute the foam. In this work Mg foams are fabricated by a replica method that uses as skeleton packed spheres of active carbon, a material widely utilized in medicine. After Mg infiltration, carbon particles are eliminated by an oxidizing heat treatment. The latter covers Mg with MgO which improves performance. In particular, oxidation retards degradation of the foam, as the polarization curves of the Mg foam with and without oxide indicate. The sphericity and regularity of C particles allows control of the structure of the produced open-cell foams.

A SCR Model based on Reactor and Engine Experimental Studies for a Cu-zeolite Catalyst

A NOx reduction efficiency higher than 95% with NH3 slip less than 30 ppm is desirable for heavy-duty diesel (HDD) engines using selective catalytic reduction (SCR) systems to meet the US EPA 2010 NOx standard and the 2014-2018 fuel consumption regulation. The SCR performance needs to be improved through experimental and modeling studies. In this research, a high fidelity global kinetic 1-dimensional 2-site SCR model with mass transfer, heat transfer and global reaction mechanisms was developed for a Cu-zeolite catalyst. The model simulates the SCR performance for the engine exhaust conditions with NH3 maldistribution and aging effects, and the details are presented. SCR experimental data were collected for the model development, calibration and validation from a reactor at Oak Ridge National Laboratory (ORNL) and an engine experimental setup at Michigan Technological University (MTU) with a Cummins 2010 ISB engine. The model was calibrated separately to the reactor and engine data. The experimental setup, test procedures including a surrogate HD-FTP cycle developed for transient studies and the model calibration process are described. Differences in the model parameters were determined between the calibrations developed from the reactor and the engine data. It was determined that the SCR inlet NH3 maldistribution is one of the reasons causing the differences. The model calibrated to the engine data served as a basis for developing a reduced order SCR estimator model. The effect of the SCR inlet NO2/NOx ratio on the SCR performance was studied through simulations using the surrogate HD-FTP cycle. The cumulative outlet NOx and the overall NOx conversion efficiency of the cycle are highest with a NO2/NOx ratio of 0.5. The outlet NH3 is lowest for the NO2/NOx ratio greater than 0.6. A combined engine experimental and simulation study was performed to quantify the NH3 maldistribution at the SCR inlet and its effects on the SCR performance and kinetics. The uniformity index (UI) of the SCR inlet NH3 and NH3/NOx ratio (ANR) was determined to be below 0.8 for the production system. The UI was improved to 0.9 after installation of a swirl mixer into the SCR inlet cone. A multi-channel model was developed to simulate the maldistribution effects. The results showed that reducing the UI of the inlet ANR from 1.0 to 0.7 caused a 5-10% decrease in NOx reduction efficiency and 10-20 ppm increase in the NH3 slip. The simulations of the steady-state engine data with the multi-channel model showed that the NH3 maldistribution is a factor causing the differences in the calibrations developed from the engine and the reactor data. The Reactor experiments were performed at ORNL using a Spaci-IR technique to study the thermal aging effects. The test results showed that the thermal aging (at 800°C for 16 hours) caused a 30% reduction in the NH3 stored on the catalyst under NH3 saturation conditions and different axial concentration profiles under SCR reaction conditions. The kinetics analysis showed that the thermal aging caused a reduction in total NH3 storage capacity (94.6 compared to 138 gmol/m3), different NH3 adsorption/desorption properties and a decrease in activation energy and the pre-exponential factor for NH3 oxidation, standard and fast SCR reactions. Both reduction in the storage capability and the change in kinetics of the major reactions contributed to the change in the axial storage and concentration profiles observed from the experiments.

Comparison of Computer-Based and Optical Face Recognition Paradigms

The main objectives of this thesis are to validate an improved principal components analysis (IPCA) algorithm on images; designing and simulating a digital model for image compression, face recognition and image detection by using a principal components analysis (PCA) algorithm and the IPCA algorithm; designing and simulating an optical model for face recognition and object detection by using the joint transform correlator (JTC); establishing detection and recognition thresholds for each model; comparing between the performance of the PCA algorithm and the performance of the IPCA algorithm in compression, recognition and, detection; and comparing between the performance of the digital model and the performance of the optical model in recognition and detection. The MATLAB © software was used for simulating the models. PCA is a technique used for identifying patterns in data and representing the data in order to highlight any similarities or differences. The identification of patterns in data of high dimensions (more than three dimensions) is too difficult because the graphical representation of data is impossible. Therefore, PCA is a powerful method for analyzing data. IPCA is another statistical tool for identifying patterns in data. It uses information theory for improving PCA. The joint transform correlator (JTC) is an optical correlator used for synthesizing a frequency plane filter for coherent optical systems. The IPCA algorithm, in general, behaves better than the PCA algorithm in the most of the applications. It is better than the PCA algorithm in image compression because it obtains higher compression, more accurate reconstruction, and faster processing speed with acceptable errors; in addition, it is better than the PCA algorithm in real-time image detection due to the fact that it achieves the smallest error rate as well as remarkable speed. On the other hand, the PCA algorithm performs better than the IPCA algorithm in face recognition because it offers an acceptable error rate, easy calculation, and a reasonable speed. Finally, in detection and recognition, the performance of the digital model is better than the performance of the optical model.

DYNAMIC MODEL BASED STATE ESTIMATION IN A HEAVY DUTY DIESEL AFTERTREATMENT SYSTEM FOR ONBOARD DIAGNOSTICS AND CONTROLS

Estimating un-measurable states is an important component for onboard diagnostics (OBD) and control strategy development in diesel exhaust aftertreatment systems. This research focuses on the development of an Extended Kalman Filter (EKF) based state estimator for two of the main components in a diesel engine aftertreatment system: the Diesel Oxidation Catalyst (DOC) and the Selective Catalytic Reduction (SCR) catalyst. One of the key areas of interest is the performance of these estimators when the catalyzed particulate filter (CPF) is being actively regenerated. In this study, model reduction techniques were developed and used to develop reduced order models from the 1D models used to simulate the DOC and SCR. As a result of order reduction, the number of states in the estimator is reduced from 12 to 1 per element for the DOC and 12 to 2 per element for the SCR. The reduced order models were simulated on the experimental data and compared to the high fidelity model and the experimental data. The results show that the effect of eliminating the heat transfer and mass transfer coefficients are not significant on the performance of the reduced order models. This is shown by an insignificant change in the kinetic parameters between the reduced order and 1D model for simulating the experimental data. An EKF based estimator to estimate the internal states of the DOC and SCR was developed. The DOC and SCR estimators were simulated on the experimental data to show that the estimator provides improved estimation of states compared to a reduced order model. The results showed that using the temperature measurement at the DOC outlet improved the estimates of the CO , NO , NO2 and HC concentrations from the DOC. The SCR estimator was used to evaluate the effect of NH3 and NOX sensors on state estimation quality. Three sensor combinations of NOX sensor only, NH3 sensor only and both NOX and NH3 sensors were evaluated. The NOX only configuration had the worst performance, the NH3 sensor only configuration was in the middle and both the NOX and NH3 sensor combination provided the best performance.

An Investigation of Waste Glass-Based Geopolymers Supplemented with Alumina

An increased consideration of sustainability throughout society has resulted in a surge of research investigating sustainable alternatives to existing construction materials. A new binder system, called a geopolymer, is being investigated to supplement ordinary portland cement (OPC) concrete, which has come under scrutiny because of the CO2 emissions inherent in its production. Geopolymers are produced from the alkali activation of a powdered aluminosilicate source by an alkaline solution, which results in a dense three-dimensional matrix of tetrahedrally linked aluminosilicates. Geopolymers have shown great potential as a building construction material, offering similar mechanical and durability properties to OPC. Additionally, geopolymers have the added value of a considerably smaller carbon footprint than OPC. This research considered the compressive strength, microstructure and composition of geopolymers made from two types of waste glass with varying aluminum contents. Waste glass shows great potential for mainstream use in geopolymers due to its chemical and physical homogeneity as well as its high content of amorphous silica, which could eliminate the need for sodium silicate. However, the lack of aluminum is thought to negatively affect the mechanical performance and alkali stability of the geopolymer system. Mortars were designed using various combinations of glass and metakaolin or fly ash to supplement the aluminum in the system. Mortar made from the high-Al glass (12% Al2O3) reached over 10,000 psi at six months. Mortar made from the low-Al glass (<1% Al2O3) did not perform as well and remained sticky even after several weeks of curing, most likely due to the lack of Al which is believed to cause hardening in geopolymers. A moderate metakaolin replacement (25-38% by mass) was found to positively affect the compressive strength of mortars made with either type of glass. Though the microstructure of the mortar was quite indicative of mechanical performance, composition was also found to be important. The initial stoichiometry of the bulk mixture was maintained fairly closely, especially in mixtures made with fine glass. This research has shown that glass has great potential for use in geopolymers, when care is given to consider the compositional and physical properties of the glass in mixture design.

AN INVESTIGATION OF VARIABLE VALVE TIMING EFFECTS ON HCCI ENGINE PERFORMANCE

The Homogeneous Charge Compression Ignition (HCCI) engine is a promising combustion concept for reducing NOx and particulate matter (PM) emissions and providing a high thermal efficiency in internal combustion engines. This concept though has limitations in the areas of combustion control and achieving stable combustion at high loads. For HCCI to be a viable option for on-road vehicles, further understanding of its combustion phenomenon and its control are essential. Thus, this thesis has a focus on both the experimental setup of an HCCI engine at Michigan Technological University (MTU) and also developing a physical numerical simulation model called the Sequential Model for Residual Affected HCCI (SMRH) to investigate performance of HCCI engines. The primary focus is on understanding the effects of intake and exhaust valve timings on HCCI combustion. For the experimental studies, this thesis provided the contributions for development of HCCI setup at MTU. In particular, this thesis made contributions in the areas of measurement of valve profiles, measurement of piston to valve contact clearance for procuring new pistons for further studies of high geometric compression ratio HCCI engines. It also consists of developing and testing a supercharging station and the setup of an electrical air heater to extend the HCCI operating region. The HCCI engine setup is based on a GM 2.0 L LHU Gen 1 engine which is a direct injected engine with variable valve timing (VVT) capabilities. For the simulation studies, a computationally efficient modeling platform has been developed and validated against experimental data from a single cylinder HCCI engine. In-cylinder pressure trace, combustion phasing (CA10, CA50, BD) and performance metrics IMEP, thermal efficiency, and CO emission are found to be in good agreement with experimental data for different operating conditions. Effects of phasing intake and exhaust valves are analyzed using SMRH. In addition, a novel index called Fuel Efficiency and Emissions (FEE) index is defined and is used to determine the optimal valve timings for engine operation through the use of FEE contour maps.

THE EFFECT OF ANNEALING ON AMORPHOUS SILICON BASED SOLAR PHOTOVOLTAIC THERMAL SYSTEM (PV/T) AND APPROPRIATE GLOBAL DISPATCH STRATEGIES

Previous work has shown that high-temperature short-term spike thermal annealing of hydrogenated amorphous silicon (a-Si:H) photovoltaic thermal (PVT) systems results in higher electrical energy output. The relationship between temperature and performance of a-Si:H PVT is not simple as high temperatures during thermal annealing improves the immediate electrical performance following an anneal, but during the anneal it creates a marked drop in electrical performance. In addition, the power generation of a-Si:H PVT depends on both the environmental conditions and the Staebler-Wronski Effect kinetics. In order to improve the performance of a-Si:H PVT systems further, this paper reports on the effect of various dispatch strategies on system electrical performance. Utilizing experimental results from thermal annealing, an annealing model simulation for a-Si:Hbased PVT was developed and applied to different cities in the U.S. to investigate potential geographic effects on the dispatch optimization of the overall electrical PVT systems performance and annual electrical yield. The results showed that spike thermal annealing once per day maximized the improved electrical energy generation. In the outdoor operating condition this ideal behavior deteriorates and optimization rules are required to be implemented.

Determing the Effect of Thermal Treatment Timing on Ultra-High Performance Concrete Beams

The loss of prestressing force over time influences the long-term deflection of the prestressed concrete element. Prestress losses are inherently complex due to the interaction of concrete creep, concrete shrinkage, and steel relaxation. Implementing advanced materials such as ultra-high performance concrete (UHPC) further complicates the estimation of prestress losses because of the changes in material models dependent on curing regime. Past research shows compressive creep is "locked in" when UHPC cylinders are subjected to thermal treatment before being loaded in compression. However, the current precasting manufacturing process would typically load the element (through prestressing strand release from the prestressing bed) before the element would be taken to the curing facility. Members of many ages are stored until curing could be applied to all of them at once. This research was conducted to determine the impact of variable curing times for UHPC on the prestress losses, and hence deflections. Three UHPC beams, a rectangular section, a modified bulb tee section, and a pi-girder, were assessed for losses and deflections using an incremental time step approach and material models specific to UHPC based on compressive creep and shrinkage testing. Results show that although it is important for prestressed UHPC beams to be thermally treated, to "lock in" material properties, the timing of thermal treatment leads to negligible differences in long-term deflections. Results also show that for UHPC elements that are thermally treated, changes in deflection are caused only by external loads because prestress losses are "locked-in" following thermal treatment.

Fiber scaffolds of poly (glycerol-dodecanedioate) and its derivative via electrospinning for neural tissue engineering

Peripheral nerves have demonstrated the ability to bridge gaps of up to 6 mm. Peripheral Nerve System injury sites beyond this range need autograft or allograft surgery. Central Nerve System cells do not allow spontaneous regeneration due to the intrinsic environmental inhibition. Although stem cell therapy seems to be a promising approach towards nerve repair, it is essential to use the distinct three-dimensional architecture of a cell scaffold with proper biomolecule embedding in order to ensure that the local environment can be controlled well enough for growth and survival. Many approaches have been developed for the fabrication of 3D scaffolds, and more recently, fiber-based scaffolds produced via the electrospinning have been garnering increasing interest, as it offers the opportunity for control over fiber composition, as well as fiber mesh porosity using a relatively simple experimental setup. All these attributes make electrospun fibers a new class of promising scaffolds for neural tissue engineering. Therefore, the purpose of this doctoral study is to investigate the use of the novel material PGD and its derivative PGDF for obtaining fiber scaffolds using the electrospinning. The performance of these scaffolds, combined with neural lineage cells derived from ESCs, was evaluated by the dissolvability test, Raman spectroscopy, cell viability assay, real time PCR, Immunocytochemistry, extracellular electrophysiology, etc. The newly designed collector makes it possible to easily obtain fibers with adequate length and integrity. The utilization of a solvent like ethanol and water for electrospinning of fibrous scaffolds provides a potentially less toxic and more biocompatible fabrication method. Cell viability testing demonstrated that the addition of gelatin leads to significant improvement of cell proliferation on the scaffolds. Both real time PCR and Immunocytochemistry analysis indicated that motor neuron differentiation was achieved through the high motor neuron gene expression using the metabolites approach. The addition of Fumaric acid into fiber scaffolds further promoted the differentiation. Based on the results, this newly fabricated electrospun fiber scaffold, combined with neural lineage cells, provides a potential alternate strategy for nerve injury repair.^

Effects of truck traffic on top-down fatigue cracking performance of flexible pavements using a new mechanics-based analysis framework

The mechanics-based analysis framework predicts top-down fatigue cracking initiation time in asphalt concrete pavements by utilising fracture mechanics and mixture morphology-based property. To reduce the level of complexity involved, traffic data were characterised and incorporated into the framework using the equivalent single axle load (ESAL) approach. There is a concern that this kind of simplistic traffic characterisation might result in erroneous performance predictions and pavement structural designs. This paper integrates axle load spectra and other traffic characterisation parameters into the mechanics-based analysis framework and studies the impact these traffic characterisation parameters have on predicted fatigue cracking performance. The traffic characterisation inputs studied are traffic growth rate, axle load spectra, lateral wheel wander and volume adjustment factors. For this purpose, a traffic integration approach which incorporates Monte Carlo simulation and representative traffic characterisation inputs was developed. The significance of these traffic characterisation parameters was established by evaluating a number of field pavement sections. It is evident from the results that all the traffic characterisation parameters except truck wheel wander have been observed to have significant influence on predicted top-down fatigue cracking performance.

Integration of a graph-based model indexer in commercial modelling tools

Softeam has over 20 years of experience providing UML-based modelling solutions, such as its Modelio modelling tool, and its Constellation enterprise model management and collaboration environment. Due to the increasing number and size of the models used by Softeam’s clients, Softeam joined the MONDO FP7 EU research project, which worked on solutions for these scalability challenges and produced the Hawk model indexer among other results. This paper presents the technical details and several case studies on the integration of Hawk into Softeam’s toolset. The first case study measured the performance of Hawk’s Modelio support using varying amounts of memory for the Neo4j backend. In another case study, Hawk was integrated into Constellation to provide scalable global querying of model repositories. Finally, the combination of Hawk and the Epsilon Generation Language was compared against Modelio for document generation: for the largest model, Hawk was two orders of magnitude faster.

An Islanding Detection Method based on Impedance Estimation and Grid Identification for Grid-Tie Distributed Power Generation Systems

Power system policies are broadly on track to escalate the use of renewable energy resources in electric power generation. Integration of dispersed generation to the utility network not only intensifies the benefits of renewable generation but also introduces further advantages such as power quality enhancement and freedom of power generation for the consumers. However, issues arise from the integration of distributed generators to the existing utility grid are as significant as its benefits. The issues are aggravated as the number of grid-connected distributed generators increases. Therefore, power quality demands become stricter to ensure a safe and proper advancement towards the emerging smart grid. In this regard, system protection is the area that is highly affected as the grid-connected distributed generation share in electricity generation increases. Islanding detection, amongst all protection issues, is the most important concern for a power system with high penetration of distributed sources. Islanding occurs when a portion of the distribution network which includes one or more distributed generation units and local loads is disconnected from the remaining portion of the grid. Upon formation of a power island, it remains energized due to the presence of one or more distributed sources. This thesis introduces a new islanding detection technique based on an enhanced multi-layer scheme that shows superior performance over the existing techniques. It provides improved solutions for safety and protection of power systems and distributed sources that are capable of operating in grid-connected mode. The proposed active method offers negligible non-detection zone. It is applicable to micro-grids with a number of distributed generation sources without sacrificing the dynamic response of the system. In addition, the information obtained from the proposed scheme allows for smooth transition to stand-alone operation if required. The proposed technique paves the path towards a comprehensive protection solution for future power networks. The proposed method is converter-resident and all power conversion systems that are operating based on power electronics converters can benefit from this method. The theoretical analysis is presented, and extensive simulation results confirm the validity of the analytical work.

Engineering interfacial silicon dioxide for improved metal-insulator-semiconductor silicon photoanode water splitting performance

Silicon photoanodes protected by atomic layer deposited (ALD) TiO2 show promise as components of water splitting devices that may enable the large-scale production of solar fuels and chemicals. Minimizing the resistance of the oxide corrosion protection layer is essential for fabricating efficient devices with good fill factor. Recent literature reports have shown that the interfacial SiO2 layer, interposed between the protective ALD-TiO2 and the Si anode, acts as a tunnel oxide that limits hole conduction from the photoabsorbing substrate to the surface oxygen evolution catalyst. Herein, we report a significant reduction of bilayer resistance, achieved by forming stable, ultrathin (<1.3 nm) SiO2 layers, allowing fabrication of water splitting photoanodes with hole conductances near the maximum achievable with the given catalyst and Si substrate. Three methods for controlling the SiO2 interlayer thickness on the Si(100) surface for ALD-TiO2 protected anodes were employed: (1) TiO2 deposition directly on an HF-etched Si(100) surface, (2) TiO2 deposition after SiO2 atomic layer deposition on an HF-etched Si(100) surface, and (3) oxygen scavenging, post-TiO2 deposition to decompose the SiO2 layer using a Ti overlayer. Each of these methods provides a progressively superior means of reliably thinning the interfacial SiO2 layer, enabling the fabrication of efficient and stable water oxidation silicon anodes.