Discrete element methods for asphalt concrete : development and application of user-defined microstructural models and a viscoelastic micromechanical model

As an important Civil Engineering material, asphalt concrete (AC) is commonly used to build road surfaces, airports, and parking lots. With traditional laboratory tests and theoretical equations, it is a challenge to fully understand such a random composite material. Based on the discrete element method (DEM), this research seeks to develop and implement computer models as research approaches for improving understandings of AC microstructure-based mechanics. In this research, three categories of approaches were developed or employed to simulate microstructures of AC materials, namely the randomly-generated models, the idealized models, and image-based models. The image-based models were recommended for accurately predicting AC performance, while the other models were recommended as research tools to obtain deep insight into the AC microstructure-based mechanics. A viscoelastic micromechanical model was developed to capture viscoelastic interactions within the AC microstructure. Four types of constitutive models were built to address the four categories of interactions within an AC specimen. Each of the constitutive models consists of three parts which represent three different interaction behaviors: a stiffness model (force-displace relation), a bonding model (shear and tensile strengths), and a slip model (frictional property). Three techniques were developed to reduce the computational time for AC viscoelastic simulations. It was found that the computational time was significantly reduced to days or hours from years or months for typical three-dimensional models. Dynamic modulus and creep stiffness tests were simulated and methodologies were developed to determine the viscoelastic parameters. It was found that the DE models could successfully predict dynamic modulus, phase angles, and creep stiffness in a wide range of frequencies, temperatures, and time spans. Mineral aggregate morphology characteristics (sphericity, orientation, and angularity) were studied to investigate their impacts on AC creep stiffness. It was found that aggregate characteristics significantly impact creep stiffness. Pavement responses and pavement-vehicle interactions were investigated by simulating pavement sections under a rolling wheel. It was found that wheel acceleration, steadily moving, and deceleration significantly impact contact forces. Additionally, summary and recommendations were provided in the last chapter and part of computer programming codes wree provided in the appendixes.

Comparison of three methods for driven pile capacity

A significant cost for foundations is the design and installation of piles when they are required due to poor ground conditions. Not only is it important that piles be designed properly, but also that the installation equipment and total cost be evaluated. To assist in the evaluation of piles a number of methods have been developed. In this research three of these methods were investigated, which were developed by the Federal Highway Administration, the US Corps of Engineers and the American Petroleum Institute (API). The results from these methods were entered into the program GRLWEAPTM to assess the pile drivability and to provide a standard base for comparing the three methods. An additional element of this research was to develop EXCEL spreadsheets to implement these three methods. Currently the Army Corps and API methods do not have publicly available software and must be performed manually, which requires that data is taken off of figures and tables, which can introduce error in the prediction of pile capacities. Following development of the EXCEL spreadsheet, they were validated with both manual calculations and existing data sets to ensure that the data output is correct. To evaluate the three pile capacity methods data was utilized from four project sites from North America. The data included site geotechnical data along with field determined pile capacities. In order to achieve a standard comparison of the data, the pile capacities and geotechnical data from the three methods were entered into GRLWEAPTM. The sites consisted of both cohesive and cohesionless soils; where one site was primarily cohesive, one was primarily cohesionless, and the other two consisted of inter-bedded cohesive and cohesionless soils. Based on this limited set of data the results indicated that the US Corps of Engineers method more closely compared with the field test data, followed by the API method to a lesser degree. The DRIVEN program compared favorably in cohesive soils, but over predicted in cohesionless material.

Ethanol Production from Hardboard Manufacturing Process Wastewater: Methods for Improving Product Yields from Hemicellulose Hydrolysates

Waste effluents from the forest products industry are sources of lignocellulosic biomass that can be converted to ethanol by yeast after pretreatment. However, the challenge of improving ethanol yields from a mixed pentose and hexose fermentation of a potentially inhibitory hydrolysate still remains. Hardboard manufacturing process wastewater (HPW) was evaluated at a potential feedstream for lignocellulosic ethanol production by native xylose-fermenting yeast. After screening of xylose-fermenting yeasts, Scheffersomyces stipitis CBS 6054 was selected as the ideal organism for conversion of the HPW hydrolysate material. The individual and synergistic effects of inhibitory compounds present in the hydrolysate were evaluated using response surface methodology. It was concluded that organic acids have an additive negative effect on fermentations. Fermentation conditions were also optimized in terms of aeration and pH. Methods for improving productivity and achieving higher ethanol yields were investigated. Adaptation to the conditions present in the hydrolysate through repeated cell sub-culturing was used. The objectives of this present study were to adapt S. stipitis CBS6054 to a dilute-acid pretreated lignocellulosic containing waste stream; compare the physiological, metabolic, and proteomic profiles of the adapted strain to its parent; quantify changes in protein expression/regulation, metabolite abundance, and enzyme activity; and determine the biochemical and molecular mechanism of adaptation. The adapted culture showed improvement in both substrate utilization and ethanol yields compared to the unadapted parent strain. The adapted strain also represented a growth phenotype compared to its unadapted parent based on its physiological and proteomic profiles. Several potential targets that could be responsible for strain improvement were identified. These targets could have implications for metabolic engineering of strains for improved ethanol production from lignocellulosic feedstocks. Although this work focuses specifically on the conversion of HPW to ethanol, the methods developed can be used for any feedstock/product systems that employ a microbial conversion step. The benefit of this research is that the organisms will the optimized for a company's specific system.

Pavement Engineering Problem

Work on a real life pavement engineering problem. This afternoon you will be working with Dr. Yan on the question: How do you make the most cost effective choice between two types of pavement contracting methods?

Magnesium - Tellurium by Powder Methods

Today considerable work is being done in the compressed metal powder field which is gradually ob­taining prominence as a valuable branch of metallurgy. The mass of data, however, has led to many different ideas on the results of sintering.

Oil and Gas Production Methods in Montana

Montana's oil and gas industries aggregate a gross income of over 12,000,000 annually to the state. Oil and gas fields have been thoroughly discussed in liter­ature as to geology, location, production and future possibilities. The specific object of this report has been to compile a comprehensive study of the production methods as they occur.

Measurements of the Magnetic Permeabilities of the Iron-Manganese Alloy System Prepared by the Methods of Powder Metallurgy

Powder metallurgy is a branch of metallurgy which produces metallic compacts in their final forms by means of pressure and heat-treatment from the pow­ders. The products of powder metallurgy are being used in our daily lives quite often. For example, the tungsten wires in the electric bulbs to the silver-tin fillings of our teeth.

Long-Range Pollution Transport: Trans-Atlantic Mechanisms and Lagrangian Modeling Methods

Over the past several decades, it has become apparent that anthropogenic activities have resulted in the large-scale enhancement of the levels of many trace gases throughout the troposphere. More recently, attention has been given to the transport pathway taken by these emissions as they are dispersed throughout the atmosphere. The transport pathway determines the physical characteristics of emissions plumes and therefore plays an important role in the chemical transformations that can occur downwind of source regions. For example, the production of ozone (O3) is strongly dependent upon the transport its precursors undergo. O3 can initially be formed within air masses while still over polluted source regions. These polluted air masses can experience continued O3 production or O3 destruction downwind, depending on the air mass's chemical and transport characteristics. At present, however, there are a number of uncertainties in the relationships between transport and O3 production in the North Atlantic lower free troposphere. The first phase of the study presented here used measurements made at the Pico Mountain observatory and model simulations to determine transport pathways for US emissions to the observatory. The Pico Mountain observatory was established in the summer of 2001 in order to address the need to understand the relationships between transport and O3 production. Measurements from the observatory were analyzed in conjunction with model simulations from the Lagrangian particle dispersion model (LPDM), FLEX-PART, in order to determine the transport pathway for events observed at the Pico Mountain observatory during July 2003. A total of 16 events were observed, 4 of which were analyzed in detail. The transport time for these 16 events varied from 4.5 to 7 days, while the transport altitudes over the ocean ranged from 2-8 km, but were typically less than 3 km. In three of the case studies, eastward advection and transport in a weak warm conveyor belt (WCB) airflow was responsible for the export of North American emissions into the FT, while transport in the FT was governed by easterly winds driven by the Azores/Bermuda High (ABH) and transient northerly lows. In the fourth case study, North American emissions were lofted to 6-8 km in a WCB before being entrained in the same cyclone's dry airstream and transported down to the observatory. The results of this study show that the lower marine FT may provide an important transport environment where O3 production may continue, in contrast to transport in the marine boundary layer, where O3 destruction is believed to dominate. The second phase of the study presented here focused on improving the analysis methods that are available with LPDMs. While LPDMs are popular and useful for the analysis of atmospheric trace gas measurements, identifying the transport pathway of emissions from their source to a receptor (the Pico Mountain observatory in our case) using the standard gridded model output, particularly during complex meteorological scenarios can be difficult can be difficult or impossible. The transport study in phase 1 was limited to only 1 month out of more than 3 years of available data and included only 4 case studies out of the 16 events specifically due to this confounding factor. The second phase of this study addressed this difficulty by presenting a method to clearly and easily identify the pathway taken by only those emissions that arrive at a receptor at a particular time, by combining the standard gridded output from forward (i.e., concentrations) and backward (i.e., residence time) LPDM simulations, greatly simplifying similar analyses. The ability of the method to successfully determine the source-to-receptor pathway, restoring this Lagrangian information that is lost when the data are gridded, is proven by comparing the pathway determined from this method with the particle trajectories from both the forward and backward models. A sample analysis is also presented, demonstrating that this method is more accurate and easier to use than existing methods using standard LPDM products. Finally, we discuss potential future work that would be possible by combining the backward LPDM simulation with gridded data from other sources (e.g., chemical transport models) to obtain a Lagrangian sampling of the air that will eventually arrive at a receptor.

IMPROVING FLOW DISTRIBUTION IN SMALL-SCALE WATER-SUPPLY SYSTEMS THROUGH THE USE OF FLOW-REDUCING DISCS AND METHODS FOR ANALYZING THE EFFECTIVENESS OF SOLAR POWERED PUMPING FOR A DRINKING WATER SUPPLY IN RURAL PANAMA

As continued global funding and coordination are allocated toward the improvement of access to safe sources of drinking water, alternative solutions may be necessary to expand implementation to remote communities. This report evaluates two technologies used in a small water distribution system in a mountainous region of Panama; solar powered pumping and flow-reducing discs. The two parts of the system function independently, but were both chosen for their ability to mitigate unique issues in the community. The design program NeatWork and flow-reducing discs were evaluated because they are tools taught to Peace Corps Volunteers in Panama. Even when ample water is available, mountainous terrains affect the pressure available throughout a water distribution system. Since the static head in the system only varies with the height of water in the tank, frictional losses from pipes and fittings must be exploited to balance out the inequalities caused by the uneven terrain. Reducing the maximum allowable flow to connections through the installation of flow-reducing discs can help to retain enough residual pressure in the main distribution lines to provide reliable service to all connections. NeatWork was calibrated to measured flow rates by changing the orifice coefficient (θ), resulting in a value of 0.68, which is 10-15% higher than typical values for manufactured flow-reducing discs. NeatWork was used to model various system configurations to determine if a single-sized flow-reducing disc could provide equitable flow rates throughout an entire system. There is a strong correlation between the optimum single-sized flow- reducing disc and the average elevation change throughout a water distribution system; the larger the elevation change across the system, the smaller the recommended uniform orifice size. Renewable energy can jump the infrastructure gap and provide basic services at a fraction of the cost and time required to install transmission lines. Methods for the assessment of solar powered pumping systems as a means for rural water supply are presented and assessed. It was determined that manufacturer provided product specifications can be used to appropriately design a solar pumping system, but care must be taken to ensure that sufficient water can be provided to the system despite variations in solar intensity.

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.

Fabrication methods for creating flexible polymer substrate sensor tags

The authors describe the design, fabrication, and testing of a passive wireless sensor platform utilizing low-cost commercial surface acoustic wave filters and sensors. Polyimide and polyethylene terephthalate sheets are used as substrates to create a flexible sensor tag that can be applied to curved surfaces. A microfabricated antenna is integrated on the substrate in order to create a compact form factor. The sensor tags are fabricated using 315 MHz surface acoustic wave filters and photodiodes and tested with the aid of a fiber-coupled tungsten lamp. Microwave energy transmitted from a network analyzer is used to interrogate the sensor tag. Due to an electrical impedance mismatch at the SAW filter and sensor, energy is reflected at the sensor load and reradiated from the integrated antenna. By selecting sensors that change electrical impedance based on environmental conditions, the sensor state can be inferred through measurement of the reflected energy profile. Testing has shown that a calibrated system utilizing this type of sensor tag can detect distinct light levels wireless and passively. The authors also demonstrate simultaneous operation of two tags with different center passbands that detects light. Ranging tests show that the sensor tags can operate at a distance of at least 3.6 m.

Methods of Determining Porosity and Spatter Losses of Arc Welds

The original objective of this project was to determine the effect of varying current intensity and electrode coating composition upon the spatter losses and porosity of arc welds made by alternating current. This subject was suggested by the Welding Research Council of the Engineering Foundation, which is a clearing house for welding research in order to avoid du­plication of work.

An insulin infusion advisory system for type 1 diabetes patients based on non-linear model predictive control methods

In this paper, an Insulin Infusion Advisory System (IIAS) for Type 1 diabetes patients, which use insulin pumps for the Continuous Subcutaneous Insulin Infusion (CSII) is presented. The purpose of the system is to estimate the appropriate insulin infusion rates. The system is based on a Non-Linear Model Predictive Controller (NMPC) which uses a hybrid model. The model comprises a Compartmental Model (CM), which simulates the absorption of the glucose to the blood due to meal intakes, and a Neural Network (NN), which simulates the glucose-insulin kinetics. The NN is a Recurrent NN (RNN) trained with the Real Time Recurrent Learning (RTRL) algorithm. The output of the model consists of short term glucose predictions and provides input to the NMPC, in order for the latter to estimate the optimum insulin infusion rates. For the development and the evaluation of the IIAS, data generated from a Mathematical Model (MM) of a Type 1 diabetes patient have been used. The proposed control strategy is evaluated at multiple meal disturbances, various noise levels and additional time delays. The results indicate that the implemented IIAS is capable of handling multiple meals, which correspond to realistic meal profiles, large noise levels and time delays.

How to Improve the Production Process for interactive TV with semi-formal Methods

The central question for this paper is how to improve the production process by closing the gap between industrial designers and software engineers of television(TV)-based User Interfaces (UI) in an industrial environment. Software engineers are highly interested whether one UI design can be converted into several fully functional UIs for TV products with different screen properties. The aim of the software engineers is to apply automatic layout and scaling in order to speed up and improve the production process. However, the question is whether a UI design lends itself for such automatic layout and scaling. This is investigated by analysing a prototype UI design done by industrial designers. In a first requirements study, industrial designers had created meta-annotations on top of their UI design in order to disclose their design rationale for discussions with software engineers. In a second study, five (out of ten) industrial designers assessed the potential of four different meta-annotation approaches. The question was which annotation method industrial designers would prefer and whether it could satisfy the technical requirements of the software engineering process. One main result is that the industrial designers preferred the method they were already familiar with, which therefore seems to be the most effective one although the main objective of automatic layout and scaling could still not be achieved.

Semantic Methods for Intelligent Distributed Design Environments

Continuous advancements in technology have led to increasingly comprehensive and distributed product development processes while in pursuit of improved products at reduced costs. Information associated with these products is ever changing, and structured frameworks have become integral to managing such fluid information. Ontologies and the Semantic Web have emerged as key alternatives for capturing product knowledge in both a human-readable and computable manner. The primary and conclusive focus of this research is to characterize relationships formed within methodically developed distributed design knowledge frameworks to ultimately provide a pervasive real-time awareness in distributed design processes. Utilizing formal logics in the form of the Semantic Web’s OWL and SWRL, causal relationships are expressed to guide and facilitate knowledge acquisition as well as identify contradictions between knowledge in a knowledge base. To improve the efficiency during both the development and operational phases of these “intelligent” frameworks, a semantic relatedness algorithm is designed specifically to identify and rank underlying relationships within product development processes. After reviewing several semantic relatedness measures, three techniques, including a novel meronomic technique, are combined to create AIERO, the Algorithm for Identifying Engineering Relationships in Ontologies. In determining its applicability and accuracy, AIERO was applied to three separate, independently developed ontologies. The results indicate AIERO is capable of consistently returning relatedness values one would intuitively expect. To assess the effectiveness of AIERO in exposing underlying causal relationships across product development platforms, a case study involving the development of an industry-inspired printed circuit board (PCB) is presented. After instantiating the PCB knowledge base and developing an initial set of rules, FIDOE, the Framework for Intelligent Distributed Ontologies in Engineering, was employed to identify additional causal relationships through extensional relatedness measurements. In a conclusive PCB redesign, the resulting “intelligent” framework demonstrates its ability to pass values between instances, identify inconsistencies amongst instantiated knowledge, and identify conflicting values within product development frameworks. The results highlight how the introduced semantic methods can enhance the current knowledge acquisition, knowledge management, and knowledge validation capabilities of traditional knowledge bases.