University-led innovative and inspirational engineering education

The UK Government and large employers have recognised the skills gap between learners leaving the education system and the requirements of employers. The current system is seen to be failing significant numbers of learners and has been accused of schooling but not educating our young people. University-led technical colleges are one part of the solution being developed to provide outstanding engineering education. This paper focusses on the learning experience that the Aston University Engineering Academy, the first University-led University Technical College (UTC), has created for entrants to the Engineering Academy in September 2012, when it opens in brand new buildings next to the University. The overall aim is to produce technically literate young people that have business and enterprise skills as well as insight into the diverse range of opportunities in Engineering and Technical disciplines. The project has brought University staff and students together with employers and Academy staff to optimise the engineering education that they will receive. The innovative model presented has drawn on research from across the world in the implementation of this new type of school, as well as educational practices from the USA and the Scandinavian countries. The resulting curriculum is authentic and exciting and expands the University model of problem-based learning and placements into the secondary school environment. The benefits of this close partnership for University staff and students, the employers and the Academy staff are expanded on and the paper concludes with a prediction of progression routes from the Academy.

Practice based learning approaches in collaborative design and engineering education:a case study investigation into the benefits of a crossdisciplinary practice based learning strategy

This study explores the ongoing pedagogical development of a number of undergraduate design and engineering programmes in the United Kingdom. Observations and data have been collected over several cohorts to bring a valuable perspective to the approaches piloted across two similar university departments while trialling a number of innovative learning strategies. In addition to the concurrent institutional studies the work explores curriculum design that applies the principles of Co-Design, multidisciplinary and trans disciplinary learning, with both engineering and product design students working alongside each other through a practical problem solving learning approach known as the CDIO learning initiative (Conceive, Design Implement and Operate) [1]. The study builds on previous work presented at the 2010 EPDE conference: The Effect of Personality on the Design Team: Lessons from Industry for Design Education [2]. The subsequent work presented in this paper applies the findings to mixed design and engineering team based learning, building on the insight gained through a number of industrial process case studies carried out in current design practice. Developments in delivery also aligning the CDIO principles of learning through doing into a practice based, collaborative learning experience and include elements of the TRIZ creative problem solving technique [3]. The paper will outline case studies involving a number of mixed engineering and design student projects that highlight the CDIO principles, combined with an external industrial design brief. It will compare and contrast the learning experience with that of a KTP derived student project, to examine an industry based model for student projects. In addition key areas of best practice will be presented, and student work from each mode will be discussed at the conference.

Design software architecture models using ontology

Software architecture plays an essential role in the high level description of a system design, where the structure and communication are emphasized. Despite its importance in the software engineering process, the lack of formal description and automated verification hinders the development of good software architecture models. In this paper, we present an approach to support the rigorous design and verification of software architecture models using the semantic web technology. We view software architecture models as ontology representations, where their structures and communication constraints are captured by the Web Ontology Language (OWL) and the Semantic Web Rule Language (SWRL). Specific configurations on the design are represented as concrete instances of the ontology, to which their structures and dynamic behaviors must conform. Furthermore, ontology reasoning tools can be applied to perform various automated verification on the design to ensure correctness, such as consistency checking, style recognition, and behavioral inference.

Optimization of pavement maintenance and rehabilitation programming using shuffled complex evolution algorithm

The major barrier to practical optimization of pavement preservation programming has always been that for formulations where the identity of individual projects is preserved, the solution space grows exponentially with the problem size to an extent where it can become unmanageable by the traditional analytical optimization techniques within reasonable limit. This has been attributed to the problem of combinatorial explosion that is, exponential growth of the number of combinations. The relatively large number of constraints often presents in a real-life pavement preservation programming problems and the trade-off considerations required between preventive maintenance, rehabilitation and reconstruction, present yet another factor that contributes to the solution complexity. In this research study, a new integrated multi-year optimization procedure was developed to solve network level pavement preservation programming problems, through cost-effectiveness based evolutionary programming analysis, using the Shuffled Complex Evolution (SCE) algorithm.^ A case study problem was analyzed to illustrate the robustness and consistency of the SCE technique in solving network level pavement preservation problems. The output from this program is a list of maintenance and rehabilitation treatment (M&R) strategies for each identified segment of the network in each programming year, and the impact on the overall performance of the network, in terms of the performance levels of the recommended optimal M&R strategy. ^ The results show that the SCE is very efficient and consistent in the simultaneous consideration of the trade-off between various pavement preservation strategies, while preserving the identity of the individual network segments. The flexibility of the technique is also demonstrated, in the sense that, by suitably coding the problem parameters, it can be used to solve several forms of pavement management programming problems. It is recommended that for large networks, some sort of decomposition technique should be applied to aggregate sections, which exhibit similar performance characteristics into links, such that whatever M&R alternative is recommended for a link can be applied to all the sections connected to it. In this way the problem size, and hence the solution time, can be greatly reduced to a more manageable solution space. ^ The study concludes that the robust search characteristics of SCE are well suited for solving the combinatorial problems in long-term network level pavement M&R programming and provides a rich area for future research. ^

Predicting jurors' decisions: The effects of repeated expression and forewarning in civil voir dire

To help lawyers uncover jurors' attitudes and predict verdict, litigation experts recommend that attorneys encourage jurors to repeatedly express their attitudes during voir dire. While social cognitive literature has established that repeated expression of attitudes increases accessibility and behavior predictability, the persuasive twist on the method exercised in trials deserves empirical investigation. Only one study has examined the use of repeated expression within a legal context with the results finding that the tactic increased accessibility, but did not influence the attitude verdict relationship. This dissertation reexamines the ability of civil attitudes to predict verdict in a civil trial and investigates the use of repeated expression as a persuasive tactic utilized by both parties (Plaintiff and Defense) within a civil voir dire in an attempt to increase attitudinal strength, via accessibility, and change attitudes to better predict verdict. This project also explores potential moderators, repetition by the opposing party and the use of a forewarning, to determine their ability to counter the effects of repeated expression on attitudes and verdict.^ This dissertation project asked subjects to take on the role of jurors in a civil case. During the voir dire questioning session, the number of times the participants were solicited to express their attitudes towards litigation crisis by both parties was manipulated (one vs. five). Also manipulated was the inclusion of a forewarning statement from the plaintiff, within which mock jurors were cautioned about the repeated tactics that the defense may use to influence their attitudes. Subsequently, participants engaged in a response latency task which measured the accessibility of their attitudes towards various case-related issues. After reading a vignette of a fictitious personal injury case, participants rendered verdict decisions and responded to an attitude evaluation scale. Exploratory factor analyses, Probit regressions, and path analyses were used to analyze the data. Results indicated that the act of repeated expression influenced both the accessibility and value of litigation crisis attitudes thus increasing the attitude-verdict relationship, but only when only one party engaged in it. Furthermore, the forewarning manipulation did moderate the effect of repeated expression on attitude change and verdict, supporting our hypothesis.^

Experimental analysis of soil and dust stabilizers for controlling displacement of contaminated soils by wind tunnel experiments

During the remediation of burial grounds at the US Department of Energy's (DOE's) Hanford Site in Washington State, the dispersion of contaminated soil particles and dust is an issue that is faced by site workers on a daily basis. This contamination problem is even more of a concern when one takes into account the semi-arid characteristics of the region where the site is located. To mitigate this problem, workers at the site use a variety of engineered methods to minimize the dispersion of contaminated soil and dust (i.e. use of water and/or suppression agents that stabilizes the soil prior to soil excavation, segregation, and removal activities). A primary contributor to the dispersion of contaminated soil and dust is wind soil erosion. The erosion process occurs when the wind speed exceeds a certain threshold value which depends on a number of factors including wind force loading, particle size, surface soil moisture, and the geometry of the soil. Thus under these circumstances, the mobility of contaminated soil and generation and dispersion of particulate matter are significantly influenced by these parameters. This dependence of soil and dust movement on threshold shear velocity, fixative dilution and/or application rates, soil moisture content, and soil geometry were studied for Hanford's sandy soil through a series of wind tunnel experiments, laboratory experiments and theoretical analysis. In addition, the behavior of plutonium (Pu) powder contamination in the soil was studied by introducing a Pu simulant (cerium oxide). The results showed that soil dispersion and PM10 concentrations decreased with increasing soil moisture. Also, it was shown that the mobility of the soil was affected by increasing wind velocity. It was demonstrated that the use of fixative products greatly decreased the amount of soil and PM10 concentrations when exposed to varying wind conditions. In addition, it was shown that geometry of the soil sample affected the velocity profile and calculation of roughness surface coefficient when comparing round and flat soil samples. Finally, threshold shear velocities were calculated for soil with flat surface and their dependency on surface soil moisture was demonstrated. A theoretical framework was developed to explain these dependencies.

Estimation and prediction of average vehicle occupancies using traffic accident records

As congestion management strategies begin to put more emphasis on person trips than vehicle trips, the need for vehicle occupancy data has become more critical. The traditional methods of collecting these data include the roadside windshield method and the carousel method. These methods are labor-intensive and expensive. An alternative to these traditional methods is to make use of the vehicle occupancy information in traffic accident records. This method is cost effective and may provide better spatial and temporal coverage than the traditional methods. However, this method is subject to potential biases resulting from under- and over-involvement of certain population sectors and certain types of accidents in traffic accident records. In this dissertation, three such potential biases, i.e., accident severity, driver’s age, and driver’s gender, were investigated and the corresponding bias factors were developed as needed. The results show that although multi-occupant vehicles are involved in higher percentages of severe accidents than are single-occupant vehicles, multi-occupant vehicles in the whole accident vehicle population were not overrepresented in the accident database. On the other hand, a significant difference was found between the distributions of the ages and genders of drivers involved in accidents and those of the general driving population. An information system that incorporates adjustments for the potential biases was developed to estimate the average vehicle occupancies (AVOs) for different types of roadways on the Florida state roadway system. A reasonableness check of the results from the system shows AVO estimates that are highly consistent with expectations. In addition, comparisons of AVOs from accident data with the field estimates show that the two data sources produce relatively consistent results. While accident records can be used to obtain the historical AVO trends and field data can be used to estimate the current AVOs, no known methods have been developed to project future AVOs. Four regression models for the purpose of predicting weekday AVOs on different levels of geographic areas and roadway types were developed as part of this dissertation. The models show that such socioeconomic factors as income, vehicle ownership, and employment have a significant impact on AVOs.

A static traffic assignment model combined with an artificial neural network delay model

As traffic congestion continues to worsen in large urban areas, solutions are urgently sought. However, transportation planning models, which estimate traffic volumes on transportation network links, are often unable to realistically consider travel time delays at intersections. Introducing signal controls in models often result in significant and unstable changes in network attributes, which, in turn, leads to instability of models. Ignoring the effect of delays at intersections makes the model output inaccurate and unable to predict travel time. To represent traffic conditions in a network more accurately, planning models should be capable of arriving at a network solution based on travel costs that are consistent with the intersection delays due to signal controls. This research attempts to achieve this goal by optimizing signal controls and estimating intersection delays accordingly, which are then used in traffic assignment. Simultaneous optimization of traffic routing and signal controls has not been accomplished in real-world applications of traffic assignment. To this end, a delay model dealing with five major types of intersections has been developed using artificial neural networks (ANNs). An ANN architecture consists of interconnecting artificial neurons. The architecture may either be used to gain an understanding of biological neural networks, or for solving artificial intelligence problems without necessarily creating a model of a real biological system. The ANN delay model has been trained using extensive simulations based on TRANSYT-7F signal optimizations. The delay estimates by the ANN delay model have percentage root-mean-squared errors (%RMSE) that are less than 25.6%, which is satisfactory for planning purposes. Larger prediction errors are typically associated with severely oversaturated conditions. A combined system has also been developed that includes the artificial neural network (ANN) delay estimating model and a user-equilibrium (UE) traffic assignment model. The combined system employs the Frank-Wolfe method to achieve a convergent solution. Because the ANN delay model provides no derivatives of the delay function, a Mesh Adaptive Direct Search (MADS) method is applied to assist in and expedite the iterative process of the Frank-Wolfe method. The performance of the combined system confirms that the convergence of the solution is achieved, although the global optimum may not be guaranteed.

Development of surface flaw thresholds for pre-cured fiber reinforced polymer and groove size tolerance for near surface mounted fiber reinforced polymer retrofit systems

Since the introduction of fiber reinforced polymers (FRP) for the repair and retrofit of concrete structures in the 1980’s, considerable research has been devoted to the feasibility of their application and predictive modeling of their performance. However, the effects of flaws present in the constitutive components and the practices in substrate preparation and treatment have not yet been thoroughly studied. This research aims at investigating the effect of surface preparation and treatment for the pre-cured FRP systems and the groove size tolerance for near surface mounted (NSM) FRP systems; and to set thresholds for guaranteed system performance. This study was conducted as part of the National Cooperative Highway Research Program (NCHRP) Project 10-59B to develop construction specifications and process control manual for repair and retrofit of concrete structures using bonded FRP systems. The research included both analytical and experimental components. The experimental program for the pre-cured FRP systems consisted of a total of twenty-four (24) reinforced concrete (RC) T-beams with various surface preparation parameters and surface flaws, including roughness, flatness, voids and cracks (cuts). For the NSM FRP systems, a total of twelve (12) additional RC T-beams were tested with different grooves sizes for FRP bars and strips. The analytical program included developing an elaborate nonlinear finite element model using the general purpose software ANSYS. The bond interface between FRP and concrete was modeled by a series of nonlinear springs. The model was validated against test data from the present study as well as those available from the literature. The model was subsequently used to extend the experimental range of parameters for surface flatness in pre-cured FRP systems and for groove size study in the NSM FRP systems. Test results, confirmed by further analyses, indicated that contrary to the general belief in the industry, the impact of surface roughness on the global performance of pre-cured FRP systems was negligible. The study also verified that threshold limits set for wet lay-up FRP systems can be extended to pre-cured systems. The study showed that larger surface voids and cracks (cuts) can adversely impact both the strength and ductility of pre-cured FRP systems. On the other hand, frequency (or spacing) of surface cracks (cuts) may only affect system ductility rather than its strength. Finally, within the range studied, groove size tolerance of ±1/8 in. does not appear to have an adverse effect on the performance of NSM FRP systems.

From stability to insurgency: The root and proximate causes of the September 2002 civil war in Côte d'Ivoire

This dissertation was an analysis of the root and proximate causes of the September 2002 civil war in Côte d’Ivoire. The central question of this study was: Why did Côte d’Ivoire, which was relatively stable under President Houphouët-Boigny, suddenly begin to experience political violence in the 1990s and an explosion in 2002? Côte d’Ivoire was an interesting case because it was stable for a long period of time, apparently making it an infertile ground for conflict. It was also interesting for comparative purposes because of the fact that several states in West Africa (for instance, Benin, Togo, and Ghana) have experienced military coups but not have civil wars. Finally, this case was an opportunity to revisit the debate on the causes of civil wars in the African context. Chapter one has outlined the entire dissertation project and contextualized the analysis that follows in the subsequent chapters. Chapter two has reviewed the literature on civil wars in general, identified the different types of civil wars, and the type the Ivoiran war is. Chapter three has examined the domestic and international political economy as a source of the civil violence in Côte d’Ivoire. Chapter four has examined the role of ethnicity and region as identities of the war, while chapter five has analyzed the role of the foreign relations in the civil war, as well as the regional political context. Chapter six has distinguished between the root and proximate causes of the Ivoirian civil war, made judgments about the relative weight of the various causes, and the extent to which the weight of the causes can be measured. The study found that the “Ivoirité” was the most important trigger of the civil war in Côte d’Ivoire. The overall conclusion of my dissertation was that the September 2002 crisis in that country was a political crisis which occured in the context of a political reform. It first started with succession problems in 1993 followed by the controversial elections in 1995 and 2000. Later, this electoral politics spread beyond electoral issues, namely citizenship matters.

Seismic performance of hybrid fiber reinforced polymer-concrete pier columns

As part of a multi-university research program funded by NSF, a comprehensive experimental and analytical study of seismic behavior of hybrid fiber reinforced polymer (FRP)-concrete column is presented in this dissertation. Experimental investigation includes cyclic tests of six large-scale concrete-filled FRP tube (CFFT) and RC columns followed by monotonic flexural tests, a nondestructive evaluation of damage using ultrasonic pulse velocity in between the two test sets and tension tests of sixty-five FRP coupons. Two analytical models using ANSYS and OpenSees were developed and favorably verified against both cyclic and monotonic flexural tests. The results of the two methods were compared. A parametric study was also carried out to investigate the effect of three main parameters on primary seismic response measures. The responses of typical CFFT columns to three representative earthquake records were also investigated. The study shows that only specimens with carbon FRP cracked, whereas specimens with glass or hybrid FRP did not show any visible cracks throughout cyclic tests. Further monotonic flexural tests showed that carbon specimens both experienced flexural cracks in tension and crumpling in compression. Glass or hybrid specimens, on the other hand, all showed local buckling of FRP tubes. Compared with conventional RC columns, CFFT column possesses higher flexural strength and energy dissipation with an extended plastic hinge region. Among all CFFT columns, the hybrid lay-up demonstrated the highest flexural strength and initial stiffness, mainly because of its high reinforcement index and FRP/concrete stiffness ratio, respectively. Moreover, at the same drift ratio, the hybrid lay-up was also considered as the best in term of energy dissipation. Specimens with glassfiber tubes, on the other hand, exhibited the highest ductility due to better flexibility of glass FRP composites. Furthermore, ductility of CFFTs showed a strong correlation with the rupture strain of FRP. Parametric study further showed that different FRP architecture and rebar types may lead to different failure modes for CFFT columns. Transient analysis of strong ground motions showed that the column with off-axis nonlinear filament-wound glass FRP tube exhibited a superior seismic performance to all other CFFTs. Moreover, higher FRP reinforcement ratios may lead to a brittle system failure, while a well-engineered FRP reinforcement configuration may significantly enhance the seismic performance of CFFT columns.

Estimation of ravine sediment production and sediment dynamics in the lower Le Sueur River watershed, Minnesota

This study focuses on quantifying explicitly the sediment budget of deeply incised ravines in the lower Le Sueur River watershed, in southern Minnesota. High-rate-gully-erosion equations along with the Universal Soil Loss Equation (USLE) were implemented in a numerical modeling approach that is based on a time-integration of the sediment balance equations. The model estimates the rates of ravine width and depth change and the amount of sediment periodically flushing from the ravines. Components of the sediment budget of the ravines were simulated with the model and results suggest that the ravine walls are the major sediment source in the ravines. A sensitivity analysis revealed that the erodibility coefficients of the gully bed and wall, the local slope angle and the Manning’s coefficient are the key parameters controlling the rate of sediment production. Recommendations to guide further monitoring efforts in the watershed and increased detail modeling approaches are highlighted as a result of this modeling effort.

Lattice Boltzmann modeling of fluid flow and solute transport in karst aquifers

A novel modeling approach is applied to karst hydrology. Long-standing problems in karst hydrology and solute transport are addressed using Lattice Boltzmann methods (LBMs). These methods contrast with other modeling approaches that have been applied to karst hydrology. The motivation of this dissertation is to develop new computational models for solving ground water hydraulics and transport problems in karst aquifers, which are widespread around the globe. This research tests the viability of the LBM as a robust alternative numerical technique for solving large-scale hydrological problems. The LB models applied in this research are briefly reviewed and there is a discussion of implementation issues. The dissertation focuses on testing the LB models. The LBM is tested for two different types of inlet boundary conditions for solute transport in finite and effectively semi-infinite domains. The LBM solutions are verified against analytical solutions. Zero-diffusion transport and Taylor dispersion in slits are also simulated and compared against analytical solutions. These results demonstrate the LBM’s flexibility as a solute transport solver. The LBM is applied to simulate solute transport and fluid flow in porous media traversed by larger conduits. A LBM-based macroscopic flow solver (Darcy’s law-based) is linked with an anisotropic dispersion solver. Spatial breakthrough curves in one and two dimensions are fitted against the available analytical solutions. This provides a steady flow model with capabilities routinely found in ground water flow and transport models (e.g., the combination of MODFLOW and MT3D). However the new LBM-based model retains the ability to solve inertial flows that are characteristic of karst aquifer conduits. Transient flows in a confined aquifer are solved using two different LBM approaches. The analogy between Fick’s second law (diffusion equation) and the transient ground water flow equation is used to solve the transient head distribution. An altered-velocity flow solver with source/sink term is applied to simulate a drawdown curve. Hydraulic parameters like transmissivity and storage coefficient are linked with LB parameters. These capabilities complete the LBM’s effective treatment of the types of processes that are simulated by standard ground water models. The LB model is verified against field data for drawdown in a confined aquifer.

An integrated multi-agent framework for optimizing time, cost and environmental impact of construction processes

Environmentally conscious construction has received a significant amount of research attention during the last decades. Even though construction literature is rich in studies that emphasize the importance of environmental impact during the construction phase, most of the previous studies failed to combine environmental analysis with other project performance criteria in construction. This is mainly because most of the studies have overlooked the multi-objective nature of construction projects. In order to achieve environmentally conscious construction, multi-objectives and their relationships need to be successfully analyzed in the complex construction environment. The complex construction system is composed of changing project conditions that have an impact on the relationship between time, cost and environmental impact (TCEI) of construction operations. Yet, this impact is still unknown by construction professionals. Studying this impact is vital to fulfill multiple project objectives and achieve environmentally conscious construction. This research proposes an analytical framework to analyze the impact of changing project conditions on the relationship of TCEI. This study includes green house gas (GHG) emissions as an environmental impact category. The methodology utilizes multi-agent systems, multi-objective optimization, analytical network process, and system dynamics tools to study the relationships of TCEI and support decision-making under the influence of project conditions. Life cycle assessment (LCA) is applied to the evaluation of environmental impact in terms of GHG. The mixed method approach allowed for the collection and analysis of qualitative and quantitative data. Structured interviews of professionals in the highway construction field were conducted to gain their perspectives in decision-making under the influence of certain project conditions, while the quantitative data were collected from the Florida Department of Transportation (FDOT) for highway resurfacing projects. The data collected were used to test the framework. The framework yielded statistically significant results in simulating project conditions and optimizing TCEI. The results showed that the change in project conditions had a significant impact on the TCEI optimal solutions. The correlation between TCEI suggested that they affected each other positively, but in different strengths. The findings of the study will assist contractors to visualize the impact of their decision on the relationship of TCEI.