Case Studies and Information Technology in Civil Engineering Learning

A multimedia-supported case study is presented that deals with a large-scale civil engineering project. This case study is based on the complete analysis, design, and construction files of the developer of the project. The multimedia instructional tool has integrated different disciplines and input from the project manager, senior students, and instructors of different disciplines. This multimedia tool includes hypertext links to modular and stratified information. Information is made available through the user's control in a logical, interactive, deductive, and disciplinary way that follows the flow of a civil engineering project. Text, graphics, and videos are included. The multimedia tool presents a teaching tool that enables senior class civil engineering students to learn about planning, design, and construction phases of a civil engineering project, as well as their integration. The in-class use of the tool and project discussions help the students to relate better their previous academic knowledge to “real-life” problems, enhance their creativity, and increase the level of retention of the new knowledge acquired. Future enhancements and learning possibilities are discussed with the use of additional capabilities of information technology. The multimedia application developed has been used in an academic environment; however, with some modifications, it could be used to improve the “learning curve” of new employees in a company environment.     

Occupancy‐based decision support system for building management: From automation to end‐user persuasion

In this paper, an intelligent occupancy‐based, automated building control system is initially introduced, which has the capability of reducing energy consumption while respecting the occupants' comfort and actions inside building areas. Data stemming from a multisensorial network is combined with implicitly extracted information, since no direct feedback is expected by the users, towards unsupervised monitoring and control of building operation. However, due to significantly higher costs of actuating equipment and the reluctance that some end users show in accepting fully automated solutions, a new hybrid approach is conceptualized and presented; the automated decision support system is supplemented with a persuasion mechanism aimed at increasing energy savings, through raising user awareness. The persuasive methodology employs a continuous feedback mechanism in order to select the optimal incentive strategy by taking into account user success rates, in terms of requested actions, as well as available mechanisms, and daily harassment.     

Applications of Low Field NMR Techniques in the Characterization of Oil Sand Mining,Extraction and Upgrading Processes

A number of techniques have previously been developed that use low field nuclear magnetic resonance (NMR) relaxometry for conventional and heavy oil reservoir characterization. In the current work, the adaptation of these algorithms for use in the oil sands industry is presented. NMR based methods have been developed for identification of water and bitumen content in ore and froth samples. Consistent algorithms have been used to analyze over 500 ore samples and 50 froth samples from the Athabasca oil sands in northern Alberta. Preliminary analyses are shown, with applications for in‐situ fluid determination using NMR logging tools and improved process control in oil sands processing plants.     

LSS linear regulator problem: a partially decentralized approach

This paper presents as its main result a new control approach of regulating linear large-scale systems (LSS). This approach is based on the concept of ‘partial decentralization’. It differs from other LSS control schemes in that, based on direct arguments, it clearly identifies suboptimality due to decomposition of the LSS linear regulator problem into smaller subproblems, it takes advantage of the LSS structure without system model alteration, and it is based only on the decomposition of the objective function. The resulting controller is feedback and non-iterative in nature with the features of utilizing with complete weighting in the objective function the subsystem interconnections, parallel processing for on-line implementation, and structure flexibility in the sense that the addition and/or deletion of a subsystem does not require the design of the control law of the overall LSS from the beginning again. The stability of the resulting closed-loop LSS is also addressed and a numerical example illustrating the applicability of this new controller is presented.     

Human resource optimisation through semantically enriched data

The industrial domain is experiencing a so-called fourth industrial revolution in which the evergrowing complexity of manufacturing information, the increasing amount of knowledge and the use of web-oriented techniques, represent three crucial factors that are accelerating the growth of complexity of industrial systems. On the other hand, continuous-evolving requirements in industrial environments, due to technology outbreaks and a new global marketplace, have led to an on-going evolution of human resource management through the creation and adoption of alternative business models. In the past decade, semantic models such as ontologies have been proven to be effective for many knowledge-intensive applications, since they provide formal models of domain knowledge that can be exploited in different ways. For all these reasons, an innovative human resource optimisation (HRO) engine is introduced, which employs semantically enhanced information and conditional random field (CRFs) probabilistic models with knowledge derived from industrial shop floor level, and proposes the right person for the right job in real-time shop floor operations towards optimising decisions on how to implement and schedule either repeatedly or non-occurring tasks. Industrial information data flow and semantic enrichment were ensured through the combined use of a common interface data exchange model (CIDEM) and ontologies, after which a feasibility study at a chemical plant presented interesting preliminary results.     

Measurement of hydrodynamic data of gas-phase polymerization reactors using non-intrusive methods

The hydrodynamic characteristics of polyethylene resins are studied in detail through a combination of different techniques in our laboratory. Computer Assisted Tomography is used to determine voidage distribution under different operating conditions. Radioactive particle tracking is used to determine the solid particle trajectories, the horizontal and vertical velocities of the solids and the residence time distribution of the solids. X-ray fluoroscopy is used to determine bubble frequency and velocity. All these techniques are then combined with the information obtained through monitoring pressure fluctuations in the fluidized bed columns. All experiments are performed in Plexiglas columns of diameters that vary between 10 and 30 cm in diameter. The materials used are polyethylene and air, respectively. The combination of these techniques provides the unique opportunity to study the fluidized bed systems in great detail. Unfortunately, all techniques cannot be implemented in a single experiment. As a result, the same experiment is repeated as many times as necessary to collect the required data. The column is moved from one imaging system to the next and the experiment is repeated under the same operating conditions. It is believed that the data collected can be used as if all the data were collected during the same test. This paper presents preliminary experimental results for each set of experiments along with the nature and limitations of each set of experimental data. The results from each different system are combined in an effort to describe the complex hydrodynamics of the bed. The incremental information obtained in each set of experiments compared to the macroscopic measurements (flow rate and pressure drop) is demonstrated.     

pH-responsive polymeric nanoassemblies encapsulated into alginate beads: morphological characterization and swelling studies

The aim of this study is to design and develop novel hybrid pH-responsive hydrogels. For this purpose, new copolymers with different molecular weights and different content of the hydrophobic part are synthesized. The self-assembly behavior of PSMA-co-PDMAEMA copolymerswasstudiedin two different dispersion media (simulated gastric fluid-SGF, pH?=?1.2 and simulated intestinal fluid-SIF, pH?=?6.8) and in different concentrations. The physicochemical characteristics of the nano-assemblies were found to be dependent on the composition of the copolymer and the aqueous environment. Having a complete knowledge of the self-assembly behavior of the copolymers in aqueous media, the encapsulation of the PSMA-co-PDMAEMA 1/2 nano-assemblies into Alginate beads was achieved by following the protocol of the preparation of hydrogels. The Calcium:Alginate hydrogels were used as reference systems for comparison reasons. The size and the morphology of pure and mixed beads were found to be dependent on the composition of the block copolymer, as revealed from SEM images. The behavior of the mixed hydrogels was the same during the swelling studies, but the rate of the swelling and the amount of weight change were found to be additionally dependent on the composition of the polymeric guest. The hydration state of the polymeric chains plays a key role inthe swelling behavior of the mixed hydrogels. In conclusion, pH-responsive hybrid hydrogels were developed and their behavior and morphology are strongly dependent on the molecular characteristics of the polymeric guest.     

KLE-(V)AR: A new identification technique for reduced order disturbance models with application to sheet forming processes

A new identification technique that combines the Karhunen–Loève expansion (KLE) with the use of Vector AutoRegressive processes (VAR) is presented in this paper. Given measurements, collected over a period of time, of a set of correlated random variables the method generates a reduced order state-space dynamic model describing the spatial and temporal relationship among the variables. Some of the advantages of the new method are the fewer number of parameters needed to be estimated compared with traditional subspace methods, and its ability to efficiently track nonstationary random processes. Simulation examples from high dimensional sheet forming processes are included for illustration.