Social Network Model of Construction

Engineering and construction projects are dependent on two fundamental elements: (1) the ability to plan and manage the technical components of the project such as the tasks and resources; and (2) the ability of the project participants to effectively develop into a high performance team. Historically, the industry has focused extensively on optimizing the project management processes associated with the former element. In this focus, organizations have emphasized the ability to develop the optimum plan, allocate resources efficiently, and utilize control functions to ensure that the project stays on schedule and within budget. Although this has been effective, this engineering focus has reached the point of diminishing results. Specifically, the engineering approach to project management has neglected to recognize the importance of the participants to the success of the overall project. Rather, the engineering approach has favored the development of an optimum plan as the path to effective project management. In this paper, the engineering-based approach to project success is reconfigured to reemphasize the need to develop high performing teams by recognizing the importance of the project network. This recognition is formalized in the social network model of construction that integrates classic project management concepts with social science variables to enhance the focus on knowledge sharing as the foundation for achieving high performance teams and project results.     

A functional polymeric material based on hybrid electrochemically controlled junctions

A thin film polymeric junction was fabricated which yields a molecular electronic device functionally able to learn, i.e. to respond coherently to an external training signal. The fabricated structure is based upon electrochemical control of electronic current in a conducting polymer in contact with a solid electrolyte polymer. This functional behavior bears some resemblance to simple cases of biological learning processes. We report a comprehensive electronic characterization of the device function. Additional study was performed in order to estimate the possibility of the integration of such kinds of devices in statistical adaptive networks.     

A Theoretical Study of Substitution Effects in Unimolecular Rectifiers

The concept of molecular rectifiers introduced by Aviram and Ratner in 1974 has been the starting point of the field of molecular electronics and the possibility of unimolecular rectification has been widely debated ever since. Despite the large amount of publications on this topic over the years, the physical mechanisms leading to this phenomenon have not yet been clarified to the point where a systematic route for enhancing the rectification ratio (RR) of molecules could be suggested. We present here a theoretical study of RR for a range of molecules with a carboxylic group as a bridge between π‐conjugated chains substituted by nitro and amino groups to improve the rectification. We estimate the RR in two distinct ways, namely: i) as the ratio of the threshold electric fields required to transfer one electron between the donor and acceptor units of the molecule and vice versa, using quantum‐chemical calculations based on the semi‐empirical Hartree–Fock Austin Model 1 (AM1) method, ii) as the ratio of the currents in forward versus reverse bias, as obtained with a non‐equilibrium Green's function (NEGF) approach for charge transport through gold/molecule/gold junctions within the framework of density functional theory (DFT). The trends in RR as a function of the molecular structure agree very well when these two methods are compared and can be explained in terms of the relative position of the nitro group within the generated electrostatic potential. These findings allow us to derive some general conclusions about the physical mechanisms behind unimolecular rectification.     

PTCR barium titanate ceramics obtained from oxalate-derived powders with varying crystallinity

Barium titanate powders with average crystallite sizes of 68–2000 nm have been prepared by the calcination of barium titanyl oxalate (BTO) at temperatures of 700–1150 °C. The morphology and recrystallization kinetics of the powders have been studied using the SEM and X-ray methods. Samples of PTCR (BaCaPb)TiO₃ ceramics have been made from these powders and their microstructure and electrical properties have been investigated. It has been found that the increase of the crystallinity of the starting powders suppresses recrystallization of the ceramics, leading to growth in resistivity and significantly influencing on the resistance jump and breakdown strength of the ceramics. An optimal temperature range for the calcination of BTO has been found to ensure maximum breakdown strength of the PTC thermistors with the resistance of 31 Ω. At this temperature range the barium titanate powders had crystallite sizes of ~200 nm.     

Development and Comparison of Two Fast Surrogate Models for Urban Pluvial Flood Simulations

Detailed full hydrodynamic 1D-2D dual drainage models are a well-established approach to simulate urban pluvial floods. However, despite modelling advances and increasing computational power, this approach remains unsuitable for many real time applications. We propose and test two computationally efficient surrogate models. The first approach links a detailed 1D sewer model to a GIS-based overland flood network. For the second approach, we developed a conceptual sewer and flood model using data-driven and physically based structures, and coupled the model to pre-simulated flood maps. The city of Ghent (Belgium) is used as a test case. Both surrogate models can provide comparable results to the original model in terms of peak surface flood volumes and maximum flood extent and depth maps, with a significant reduction in computing time.     

Monthly Streamflow Modeling Based on Self-Organizing Maps and Satellite-Estimated Rainfall Data

Hydrological data provide valuable information for the decision-making process in water resources management, where long and complete time series are always desired. However, it is common to deal with missing data when working on streamflow time series. Rainfall-streamflow modeling is an alternative to overcome such a difficulty. In this paper, self-organizing maps (SOM) were developed to simulate monthly inflows to a reservoir based on satellite-estimated gridded precipitation time series. Three different calibration datasets from Três Marias Reservoir, composed of inflows (targets) and 91 TRMM-estimated rainfall data (inputs), from 1998 to 2019, were used. The results showed that the inflow data homogeneity pattern influenced the rainfall-streamflow modeling. The models generally showed superior performance during the calibration phase, whereas the outcomes varied depending on the data homogeneity pattern and the chosen SOM structure in the testing phase. Regardless of the input data homogeneity, the SOM networks showed excellent results for the rainfall-runoff modeling, presenting Nash–Sutcliffe coefficients greater than 0.90.

Graphical Abstract