Construction Surety Bonding

The qualification process in the construction bond business is very complicated, labor-intensive, and time-consuming. The construction bond underwriting processes contain subjective judgments that require human involvement to reach decisions. Thus, underwriting evaluations are bound to be very difficult, ambiguous, and have potentially great losses. This paper identifies and classifies quantitative and qualitative risk factors impacting construction bond underwriting, to improve the quality of the evaluation analysis and to reduce the highly unstructured environment and the subjectivity of the bond evaluation in underwriting. The methodology provides a systematic information analysis for the heuristic knowledge of the construction surety bonds underwriting process, provides better control over the risk assessment process by providing independent judgments for the major decision factors and an overall judgment for the final contractor's risk assessment decision, and reduces the time and effort required of the current evaluation process to reach a certain decision and to simplify the complicated nature of this process.     

Characterization and catalytic performance of poly(4-vinylpyridine) supported on mesoporous carbon: comparison with poly(4-vinylpyridine) supported on mesoporous silica

In this study, the synthesis of poly(4-vinylpyridine) (P4VP) supported on mesoporous carbon (CMK-3) by in situ polymerization of 4-vinylpyridine in the presence of CMK-3 has been investigated. The structural properties of the P4VP/CMK-3 were investigated by FT-IR, XRD, BET, TGA, SEM and TEM techniques. The catalytic activity of this new heterogeneous basic catalyst was tested for Knoevenagel reaction. Excellent yields at room temperature in aqueous media and solvent-free conditions were obtained. The catalytic activity of this purely organic hybrid catalyst was compared with P4VP/SBA-15 to clarify the advantages of mesoporous carbon on mesoporous silica as support. The results showed that the stability of P4VP/CMK-3 was excellent and could be reused 10 times without much loss of activity in Knoevenagel reaction. Surprisingly, the composite prepared by mesoporous carbon showed much higher activity than that of P4VP/SBA-15. This unique result opens new perspectives for application of mesoporous carbons as structurally defined hydrophobic catalyst support in catalytic reactions.     

Classifier-ensemble incremental-learning procedure for nuclear transient identification at different operational conditions

An important requirement for the practical implementation of empirical diagnostic systems is the capability of classifying transients in all plant operational conditions. The present paper proposes an approach based on an ensemble of classifiers for incrementally learning transients under different operational conditions. New classifiers are added to the ensemble where transients occurring in new operational conditions are not satisfactorily classified. The construction of the ensemble is made by bagging; the base classifier is a supervised Fuzzy C Means (FCM) classifier whose outcomes are combined by majority voting. The incremental learning procedure is applied to the identification of simulated transients in the feedwater system of a Boiling Water Reactor (BWR) under different reactor power levels.     

Synthesis and characterization of Ni nanoparticles-polyvinylamine/SBA-15 catalyst for simple reduction of aromatic nitro compounds

This work concerns the preparation and characterization of Nickel nanoparticle-PVAm/SBA-15, a polymer-inorganic hybrid composite, which was effectively employed as a novel heterogeneous catalyst for reduction of aromatic nitro compounds in the presence of NaBH₄ as a reducing agent. The reaction was carried out in room temperature and an aqueous medium. The catalyst showed good activity for the reduction of a number of aromatic nitro compounds yielding the respective amine compounds in excellent yield (~ 98%) at room temperature along with good reusability.     

Development of smoothed particle hydrodynamics method for modeling active nematics

This article proposes a novel graphics processing unit-based active nematic flow solver based on the smoothed particle hydrodynamics (SPH) method. Nematohydrodynamics equations are discretized using the SPH algorithm. Flow behavior, nematic ordering, topological defects, and vorticity correlation are calculated and discussed in detail. The spectrum of the kinetic energy with respect to the wavenumber is calculated at high particle resolution, and its slope at the different length scales is discussed. To exploit the SPH capabilities, pathlines of nematic particles are evaluated during the simulation. Finally, the mixing behavior of the active nematics is calculated as well and described qualitatively. The effects of two important parameters, namely, activity and elastic constant are investigated. It is shown that the activity intensifies the chaotic mixing nature of the active nematics, while the elastic constant behaves oppositely.     

Modeling and numerical simulation of solar chimney power plants

The solar chimney power plant is a simple solar thermal power plant that is capable of converting solar energy into thermal energy in the solar collector. In the second stage, the generated thermal energy is converted into kinetic energy in the chimney and ultimately into electric energy using a combination of a wind turbine and a generator. The purpose of this study is to conduct a more detailed numerical analysis of a solar chimney power plant. A mathematical model based on the Navier-Stokes, continuity and energy equations was developed to describe the solar chimney power plant mechanism in detail. Two different numerical simulations were performed for the geometry of the prototype in Manzanares, Spain. First, the governing equations were solved numerically using an iterative technique. Then, the numerical simulation was performed using the CFD software FLUENT that can simulate a two-dimensional axisymmetric model of a solar chimney power plant with the standard k-epsilon turbulence model. Both the predictions were compared with the available experimental data to assess the validity of the model. The temperature, velocity and pressure distributions in the solar collector are illustrated for three different solar radiations. Reasonably good quantitative agreement was obtained between the experimental data of the Manzanares prototype and both the numerical results.     

Response Analysis of Field-Scale Fully Grouted Standard Cable Bolts Using a Coupled ANN–FDM Approach

This paper presents a coupled approach using an artificial neural network (ANN) and the finite difference method (FDM) that has been developed to predict the distribution of axial load along fully grouted standard cable bolts in the field using laboratory pullout test data. A back-propagation training algorithm was used in ANN to determine axial loads in the cables tested in the laboratory. The ANN component of the computational model was trained using two different types of data sets. At first, the ANN was trained to predict the axial loads in a series of short cables grouted with Portland cement at a specific water-to-cement ratio and subjected to different radial confining stiffness values. Next, the ANN model was trained for an expanded case to include the influence of lateral confining stress on the distribution of axial load in the cable reinforcement. Finally, the ANN model was implemented into a widely used, FDM-based geotechnical software (FLAC). The accuracy of the ANN–FDM model is demonstrated in this paper against measured data from laboratory and field tests. The analysis approach introduced in this study is a valuable computational tool that can be used to determine the axial load distribution in long standard cable bolts, which are commonly installed to stabilize rock masses in various geotechnical, transportation, and mining applications.     

Waterproof AlInGaP optoelectronics on stretchable substrates with applications in biomedicine and robotics

Inorganic light-emitting diodes and photodetectors represent important, established technologies for solid-state lighting, digital imaging and many other applications. Eliminating mechanical and geometrical design constraints imposed by the supporting semiconductor wafers can enable alternative uses in areas such as biomedicine and robotics. Here we describe systems that consist of arrays of interconnected, ultrathin inorganic light-emitting diodes and photodetectors configured in mechanically optimized layouts on unusual substrates. Light-emitting sutures, implantable sheets and illuminated plasmonic crystals that are compatible with complete immersion in biofluids illustrate the suitability of these technologies for use in biomedicine. Waterproof optical-proximity-sensor tapes capable of conformal integration on curved surfaces of gloves and thin, refractive-index monitors wrapped on tubing for intravenous delivery systems demonstrate possibilities in robotics and clinical medicine. These and related systems may create important, unconventional opportunities for optoelectronic devices.