Study of the effect of biodiesel fuel on passive oxidation in a catalyzed particulate filter

A 2007 Cummins ISL 8.9L direct-injection common rail diesel engine rated at 272 kW (365 hp) and 317 kW (425 hp) was used to load the filter to 2.2 g/L and passively oxidize particulate matter (PM) within an aftertreatment system consisting of a diesel oxidation catalyst (DOC) and catalyzed particulate filter (CPF). The tests conducted with the engine rated at 365 hp used a 2007 DOC and CPF. The tests conducted with the engine rated at 425 hp used a 2010 DOC and 2007 CPF. Understanding the passive NO2 oxidation kinetics of PM within the CPF allows for reducing the frequency of active regenerations (hydrocarbon injection) and the associated fuel penalties. Modeling the passive oxidation of accumulated PM in the CPF will lead to creating accurate state estimation strategies. The MTU 1-D CPF model will be used to simulate data collected from this study to examine differences in the PM oxidation kinetics when soy methyl ester (SME) biodiesel is used as the source of fuel for the engine, and when the engine is operated at a higher power rating. A test procedure developed by Hutton et al. [1, 2] was modified to improve the ability to model the experimental data and provide additional insight into passively oxidized PM in a partially regenerated CPF. A test procedure was developed to allow PM oxidation rates by NO2 to be determined from engine test cell data. An experimental matrix consisting of CPF inlet temperatures from 250 to 450 °C with varying NOX/PM from 25 to 583and NO2/PM ratios from 5 to 240 was used. SME biodiesel was volumetrically blended with ULSD in 10% (B10) and 20% (B20) portions. This blended fuel was then used to evaluate the effect of biodiesel on passive oxidation rates. Four tests were performed with B10 and four tests with B20. Gathering data to determine the effect of fuel type (ULSD and biodiesel blends) on PM oxidation is the primary goal. The engine used for this testing was then configured to a higher power rating and one of the tests planned was performed. Additional testing is scheduled to take place with ULSD fuel to determine the affect the engine rating has on the PM oxidation. The experimental reaction rates during passive oxidation varied based upon the average CPF temperature, NO2 concentrations, and the NOX/PM ratios for each engine rating and with all fuels. The data analysis requires a high fidelity model that includes NO2 and thermal oxidation mechanisms and back diffusion to determine the details of the PM oxidation process.

Microfluidic fabrication of advanced microcapsules for use in self-healing materials

The proposed work aims to facilitate the development of a microfluidic platform for the production of advanced microcapsules containing active agents which can be the functional constituents of self-healing composites. The creation of such microcapsules is enabled by the unique flow characteristics within microchannels including precise control over shear and interfacial forces for droplet creation and manipulation as well as the ability to form a solid shell either chemically or via the addition of thermal or irradiative energy. Microchannel design and a study of the fluid dynamics and mechanisms for shell creation are undertaken in order to establish a fabrication approach capable of producing healing-agent-containing microcapsules. An in-depth study of the process parameters has been undertaken in order to elucidate the advantages of this production technique including precise control of size (i.e., monodispersity) and surface morphology of the microcapsules. This project also aims to aid the optimization of the mechanical properties as well as healing performance of self-healing composites by studying the effects of the advantageous properties of the as-produced microcapsules. Scale-up of the microfluidic fabrication using parallel devices on a single chip as well as on-chip microcapsule production and shape control will also be investigated. It will be demonstrated that microfluidic fabrication is a versatile approach for the efficient creation of functional microcapsules allowing for superior design of self-healing composites.

IMPACT OF ENGINE CALIBRATION ON PM OXIDATION IN A CATALYZED PARTICULATE FILTER OVER A TRANSIENT CYCLE: A MODELLING STUDY

The combustion strategy in a diesel engine has an impact on the emissions, fuel consumption and the exhaust temperatures. The PM mass retained in the CPF is a function of NO2 and PM concentrations in addition to the exhaust temperatures and the flow rates. Thus the engine combustion strategy affects exhaust characteristics which has an impact on the CPF operation and PM mass retained and oxidized. In this report, a process has been developed to simulate the relationship between engine calibration, performance and HC and PM oxidation in the DOC and CPF respectively. Fuel Rail Pressure (FRP) and Start of Injection (SOI) sweeps were carried out at five steady state engine operating conditions. This data, along with data from a previously carried out surrogate HD-FTP cycle [1], was used to create a transfer function model which estimates the engine out emissions, flow rates, temperatures for varied FRP and SOI over a transient cycle. Four different calibrations (test cases) were considered in this study, which were simulated through the transfer function model and the DOC model [1, 2]. The DOC outputs were then input into a model which simulates the NO2 assisted and thermal PM oxidation inside a CPF. Finally, results were analyzed as to how engine calibration impacts the engine fuel consumption, HC oxidation in the DOC and the PM oxidation in the CPF. Also, active regeneration for various test cases was simulated and a comparative analysis of the fuel penalties involved was carried out.

Advanced Nanostructured Electro-Catalysts for Electricity Generation and Biorenewable Alcohol Conversion

In my Ph.D research, a wet chemistry-based organic solution phase reduction method was developed, and was successfully applied in the preparation of a series of advanced electro-catalysts, including 0-dimensional (0-D) Pt, Pd, Au, and Pd-Ni nanoparticles (NPs), 1-D Pt-Fe nanowires (NWs) and 2-D Pd-Fe nanoleaves (NLs), with controlled size, shape, and morphology. These nanostructured catalysts have demonstrated unique electro-catalytic functions towards electricity production and biorenewable alcohol conversion. The molecular oxygen reduction reaction (ORR) is a long-standing scientific issue for fuel cells due to its sluggish kinetics and the poor catalyst durability. The activity and durability of an electro-catalyst is strongly related with its composition and structure. Based on this point, Pt-Fe NWs with a diameter of 2 - 3 nm were accurately prepared. They have demonstrated a high durability in sulfuric acid due to its 1-D structure, as well as a high ORR activity attributed to its tuned electronic structure. By substituting Pt with Pd using a similar synthesis route, Pd-Fe NLs were prepared and demonstrated a higher ORR activity than Pt and Pd NPs catalysts in the alkaline electrolyte. Recently, biomass-derived alcohols have attracted enormous attention as promising fuels (to replace H2) for low-temperature fuel cells. From this point of view, Pd-Ni NPs were prepared and demonstrated a high electro-catalytic activity towards ethanol oxidation. Comparing to ethanol, the biodiesel waste glycerol is more promising due to its low price and high reactivity. Glycerol (and crude glycerol) was successfully applied as the fuel in an Au-anode anion-exchange membrane fuel cell (AEMFC). By replacing Au with a more active Pt catalyst, simultaneous generation of both high power-density electricity and value-added chemicals (glycerate, tartronate, and mesoxalate) from glycerol was achieved in an AEMFC. To investigate the production of valuable chemicals from glycerol electro-oxidation, two anion-exchange membrane electro-catalytic reactors were designed. The research shows that the electro-oxidation product distribution is strongly dependent on the anode applied potential. Reaction pathways for the electro-oxidation of glycerol on Au/C catalyst have been elucidated: continuous oxidation of OH groups (to produce tartronate and mesoxalate) is predominant at lower potentials, while C-C cleavage (to produce glycolate) is the dominant reaction path at higher potentials.

EVOLUTION OF SELECTED ISOPRENE OXIDATION PRODUCTS IN DARK AQUEOUS AMMONIUM SULFATE

The aqueous phase processing of glyoxylic acid, pyruvic acid, oxalic acid and methylglyoxal was studied simulating dark and radical free atmospheric aqueous aerosol. A novel observation of the cleavage of a carbon-carbon bond in pyruvic acid and glyoxylic acid leading to their decarboxylation was made in the presence of ammonium salts but no decarboxylation was observed from oxalic acid. The empirical rate constants for decarboxylation were determined. The structure of the acid, ionic environment of solution and concentration of species found to affect the decarboxylation process. A tentative set of reaction mechanisms was proposed involving nucleophilic attack by ammonia on the carbonyl carbon leading to fragmentation of the carbon-carbon bond between the carbonyl and carboxyl carbons. Whereas, the formation of high molecular weight organic species was observed in the case of methylglyoxal. The elemental compositions of the species were determined. It was concluded that, additional pathways that are not currently known likely contribute to aqueous phase processing leading to high molecular weight organic species. Under similar conditions in atmospheric aerosol, the aqueous phase processing will markedly impact the physicochemical properties of aerosol.

MODEL UPDATING AND STRUCTURAL HEALTH MONITORING OF HORIZONTAL AXIS WIND TURBINES VIA ADVANCED SPINNING FINITE ELEMENTS AND STOCHASTIC SUBSPACE IDENTIFICATION METHODS

Wind energy has been one of the most growing sectors of the nation’s renewable energy portfolio for the past decade, and the same tendency is being projected for the upcoming years given the aggressive governmental policies for the reduction of fossil fuel dependency. Great technological expectation and outstanding commercial penetration has shown the so called Horizontal Axis Wind Turbines (HAWT) technologies. Given its great acceptance, size evolution of wind turbines over time has increased exponentially. However, safety and economical concerns have emerged as a result of the newly design tendencies for massive scale wind turbine structures presenting high slenderness ratios and complex shapes, typically located in remote areas (e.g. offshore wind farms). In this regard, safety operation requires not only having first-hand information regarding actual structural dynamic conditions under aerodynamic action, but also a deep understanding of the environmental factors in which these multibody rotating structures operate. Given the cyclo-stochastic patterns of the wind loading exerting pressure on a HAWT, a probabilistic framework is appropriate to characterize the risk of failure in terms of resistance and serviceability conditions, at any given time. Furthermore, sources of uncertainty such as material imperfections, buffeting and flutter, aeroelastic damping, gyroscopic effects, turbulence, among others, have pleaded for the use of a more sophisticated mathematical framework that could properly handle all these sources of indetermination. The attainable modeling complexity that arises as a result of these characterizations demands a data-driven experimental validation methodology to calibrate and corroborate the model. For this aim, System Identification (SI) techniques offer a spectrum of well-established numerical methods appropriated for stationary, deterministic, and data-driven numerical schemes, capable of predicting actual dynamic states (eigenrealizations) of traditional time-invariant dynamic systems. As a consequence, it is proposed a modified data-driven SI metric based on the so called Subspace Realization Theory, now adapted for stochastic non-stationary and timevarying systems, as is the case of HAWT’s complex aerodynamics. Simultaneously, this investigation explores the characterization of the turbine loading and response envelopes for critical failure modes of the structural components the wind turbine is made of. In the long run, both aerodynamic framework (theoretical model) and system identification (experimental model) will be merged in a numerical engine formulated as a search algorithm for model updating, also known as Adaptive Simulated Annealing (ASA) process. This iterative engine is based on a set of function minimizations computed by a metric called Modal Assurance Criterion (MAC). In summary, the Thesis is composed of four major parts: (1) development of an analytical aerodynamic framework that predicts interacted wind-structure stochastic loads on wind turbine components; (2) development of a novel tapered-swept-corved Spinning Finite Element (SFE) that includes dampedgyroscopic effects and axial-flexural-torsional coupling; (3) a novel data-driven structural health monitoring (SHM) algorithm via stochastic subspace identification methods; and (4) a numerical search (optimization) engine based on ASA and MAC capable of updating the SFE aerodynamic model.

Advanced luminance control and black offset correction for multi-projector display systems

In order to display a homogeneous image using multiple projectors, differences in the projected intensities must be compensated. In this paper, we present novel approaches to combine and extend existing techniques for edge blending and luminance harmonization to achieve a detailed luminance control. Furthermore, we apply techniques for improving the contrast ratio of multi-segmented displays also to the black offset correction. We also present a simple scheme to involve the displayed context in the correction process to dynamically improve the contrast in brighter images. In addition, we present a metric to evaluate the different methods and their influence on the visual quality.

Development of a novel material flow simulation model for the integration of spatial and process relevant information

Simulation techniques are almost indispensable in the analysis of complex systems. Materials- and related information flow processes in logistics often possess such complexity. Further problem arise as the processes change over time and pose a Big Data problem as well. To cope with these issues adaptive simulations are more and more frequently used. This paper presents a few relevant advanced simulation models and intro-duces a novel model structure, which unifies modelling of geometrical relations and time processes. This way the process structure and their geometric relations can be handled in a well understandable and transparent way. Capabilities and applicability of the model is also presented via a demonstrational example.

The FReedom from Ischemic Events-New Dimensions for Survival (FRIENDS) registry: design of a prospective cohort study of patients with advanced peripheral artery disease.

BACKGROUND Advanced lower extremity peripheral artery disease (PAD), whether presenting as acute limb ischemia (ALI) or chronic critical limb ischemia (CLI), is associated with high rates of cardiovascular ischemic events, amputation, and death. Past research has focused on strategies of revascularization, but few data are available that prospectively evaluate the impact of key process of care factors (spanning pre-admission, acute hospitalization, and post-discharge) that might contribute to improving short and long-term health outcomes. METHODS/DESIGN The FRIENDS registry is designed to prospectively evaluate a range of patient and health system care delivery factors that might serve as future targets for efforts to improve limb and systemic outcomes for patients with ALI or CLI. This hypothesis-driven registry was designed to evaluate the contributions of: (i) pre-hospital limb ischemia symptom duration, (ii) use of leg revascularization strategies, and (iii) use of risk-reduction pharmacotherapies, as pre-specified factors that may affect amputation-free survival. Sequential patients would be included at an index "vascular specialist-defined" ALI or CLI episode, and patients excluded only for non-vascular etiologies of limb threat. Data including baseline demographics, functional status, co-morbidities, pre-hospital time segments, and use of medical therapies; hospital-based use of revascularization strategies, time segments, and pharmacotherapies; and rates of systemic ischemic events (e.g., myocardial infarction, stroke, hospitalization, and death) and limb ischemic events (e.g., hospitalization for revascularization or amputation) will be recorded during a minimum of one year follow-up. DISCUSSION The FRIENDS registry is designed to evaluate the potential impact of key factors that may contribute to adverse outcomes for patients with ALI or CLI. Definition of new "health system-based" therapeutic targets could then become the focus of future interventional clinical trials for individuals with advanced PAD.

Probabilistic approach to cloud and snow detection on Advanced Very High Resolution Radiometer (AVHRR) imagery

Derivation of probability estimates complementary to geophysical data sets has gained special attention over the last years. Information about a confidence level of provided physical quantities is required to construct an error budget of higher-level products and to correctly interpret final results of a particular analysis. Regarding the generation of products based on satellite data a common input consists of a cloud mask which allows discrimination between surface and cloud signals. Further the surface information is divided between snow and snow-free components. At any step of this discrimination process a misclassification in a cloud/snow mask propagates to higher-level products and may alter their usability. Within this scope a novel probabilistic cloud mask (PCM) algorithm suited for the 1 km × 1 km Advanced Very High Resolution Radiometer (AVHRR) data is proposed which provides three types of probability estimates between: cloudy/clear-sky, cloudy/snow and clear-sky/snow conditions. As opposed to the majority of available techniques which are usually based on the decision-tree approach in the PCM algorithm all spectral, angular and ancillary information is used in a single step to retrieve probability estimates from the precomputed look-up tables (LUTs). Moreover, the issue of derivation of a single threshold value for a spectral test was overcome by the concept of multidimensional information space which is divided into small bins by an extensive set of intervals. The discrimination between snow and ice clouds and detection of broken, thin clouds was enhanced by means of the invariant coordinate system (ICS) transformation. The study area covers a wide range of environmental conditions spanning from Iceland through central Europe to northern parts of Africa which exhibit diverse difficulties for cloud/snow masking algorithms. The retrieved PCM cloud classification was compared to the Polar Platform System (PPS) version 2012 and Moderate Resolution Imaging Spectroradiometer (MODIS) collection 6 cloud masks, SYNOP (surface synoptic observations) weather reports, Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) vertical feature mask version 3 and to MODIS collection 5 snow mask. The outcomes of conducted analyses proved fine detection skills of the PCM method with results comparable to or better than the reference PPS algorithm.

Applying the Fuzzy Analytical Hierarchy Process in Cognitive Cities

This paper introduces a mobile application (app) as the first part of an interactive framework. The framework enhances the inter-action between cities and their citizens, introducing the Fuzzy Analytical Hierarchy Process (FAHP) as a potential information acquisition method to improve existing citizen management en-deavors for cognitive cities. Citizen management is enhanced by advanced visualization using Fuzzy Cognitive Maps (FCM). The presented app takes fuzziness into account in the constant inter-action and continuous development of communication between cities or between certain of their entities (e.g., the tax authority) and their citizens. A transportation use case is implemented for didactical reasons.

Applying the fuzzy analytical hierarchy process in digital marketing

The fuzzy analytical network process (FANP) is introduced as a potential multi-criteria-decision-making (MCDM) method to improve digital marketing management endeavors. Today’s information overload makes digital marketing optimization, which is needed to continuously improve one’s business, increasingly difficult. The proposed FANP framework is a method for enhancing the interaction between customers and marketers (i.e., involved stakeholders) and thus for reducing the challenges of big data. The presented implementation takes realities’ fuzziness into account to manage the constant interaction and continuous development of communication between marketers and customers on the Web. Using this FANP framework, the marketers are able to increasingly meet the varying requirements of their customers. To improve the understanding of the implementation, advanced visualization methods (e.g., wireframes) are used.

CO Oxidation on Pt(100): New Insights based on Combined Voltammetric, Microscopic and Spectroscopic Experiments

We present an experimental study of the CO electro-oxidation on Pt(100)-(1 × 1) electrodes employing electrochemical methods in combination with in situ scanning tunneling microscopy (STM) and shell-isolated nanoparticle enhanced Raman spectroscopy (SHINERS). We discussed the nature and stability of the active sites in the preignition region in the presence of dissolved CO (COb) and monitored substrate structure changes during the COb electro-oxidation process. We corroborated that the electro-oxidation kinetics is determined decisively by the history of CO adlayer formation. A new mechanism was proposed for Pt(100) electrode deactivation in the preignition region after excursion of electrode potential to COb ignition region. We believe that this mechanism takes place on Pt surfaces independently on their crystallographic orientation.

Improving Cervical Cancer Nodal Boost Radiation Therapy by Quantifying Uncertainties and Exploring Advanced Radiation Therapy Modalities

Radiation therapy for patients with intact cervical cancer is frequently delivered using primary external beam radiation therapy (EBRT) followed by two fractions of intracavitary brachytherapy (ICBT). Although the tumor is the primary radiation target, controlling microscopic disease in the lymph nodes is just as critical to patient treatment outcome. In patients where gross lymphadenopathy is discovered, an extra EBRT boost course is delivered between the two ICBT fractions. Since the nodal boost is an addendum to primary EBRT and ICBT, the prescription and delivery must be performed considering previously delivered dose. This project aims to address the major issues of this complex process for the purpose of improving treatment accuracy while increasing dose sparing to the surrounding normal tissues. Because external beam boosts to involved lymph nodes are given prior to the completion of ICBT, assumptions must be made about dose to positive lymph nodes from future implants. The first aim of this project was to quantify differences in nodal dose contribution between independent ICBT fractions. We retrospectively evaluated differences in the ICBT dose contribution to positive pelvic nodes for ten patients who had previously received external beam nodal boost. Our results indicate that the mean dose to the pelvic nodes differed by up to 1.9 Gy between independent ICBT fractions. The second aim is to develop and validate a volumetric method for summing dose of the normal tissues during prescription of nodal boost. The traditional method of dose summation uses the maximum point dose from each modality, which often only represents the worst case scenario. However, the worst case is often an exaggeration when highly conformal therapy methods such as intensity modulated radiation therapy (IMRT) are used. We used deformable image registration algorithms to volumetrically sum dose for the bladder and rectum and created a voxel-by-voxel validation method. The mean error in deformable image registration results of all voxels within the bladder and rectum were 5 and 6 mm, respectively. Finally, the third aim explored the potential use of proton therapy to reduce normal tissue dose. A major physical advantage of protons over photons is that protons stop after delivering dose in the tumor. Although theoretically superior to photons, proton beams are more sensitive to uncertainties caused by interfractional anatomical variations, and must be accounted for during treatment planning to ensure complete target coverage. We have demonstrated a systematic approach to determine population-based anatomical margin requirements for proton therapy. The observed optimal treatment angles for common iliac nodes were 90° (left lateral) and 180° (posterior-anterior [PA]) with additional 0.8 cm and 0.9 cm margins, respectively. For external iliac nodes, lateral and PA beams required additional 0.4 cm and 0.9 cm margins, respectively. Through this project, we have provided radiation oncologists with additional information about potential differences in nodal dose between independent ICBT insertions and volumetric total dose distribution in the bladder and rectum. We have also determined the margins needed for safe delivery of proton therapy when delivering nodal boosts to patients with cervical cancer.

The "Catching up" Process of Manufacturing in East Asia

This paper examines the "catching up" process of manufacturing in East Asia within the framework of North and South location. Results of this study indicate that latecomers of the ASEAN Four and China have advanced the "catching up" process. At the same time, second-runners of the Asian NIES have more extensively increased their "catching up" with Japan. Most "catching up" was realized in a very short period in the 1990s, and the advancement of the "catching up" process has moved into various industries from nondurable products to light machinery products. However, it has not yet advanced in heavy machinery such as in the industrial machinery and machine tool industries.