Influence of tef flour and its association with other flours on the nutritional,technological, and sensory quality of bakery products

The objective of this study was to investigate chemical, technological, and sensory quality of tef in products made exclusively with tef flour and tef flour associated with other flours. The selection of the studies and the extraction of information were carried out through research in several databases. Tef flour was used in cakes, cookies, breads, cupcakes, muffins, and extruded snacks. Bread was the most evaluated product with tef flour associated with other flours or exclusively. Most of the outcomes were with tef (5–50%) associated with other flours. Increased levels of fibers, minerals, antioxidant capacity, and flavonoids were noted according to the percentage of tef. Technological characteristics demonstrated that these products showed intermediate final quality, due to the characteristics of volume, specific volume, firmness, and luminosity. Regarding sensory quality, studies that used (5–35%) tef flour associated with other flours were well-accepted.     

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

     

Kinetics of Soybean Oil Hydrolysis on Niobium Catalysts

The catalytic hydrolysis of soybean oil was used as an alternative for the production of monoglycerides (MG) and diglycerides (DG). The reactions were conducted in a stainless-steel tubular reactor in the temperature range of 240–290 °C, on niobium phosphate (NBP) and niobium oxide (NBO) as catalysts. In the hydrolysis reactions at 270 °C, the maximum selectivities of the products of interest were obtained at 22 % MG and 48 % DG for the reaction with NBP, and 7 % MG and 33 % DG with NBO, for 59 % and 36 % of triglyceride conversion in 10 min, respectively. The proposed kinetic model presented a good fit of the theoretical model with the experimental data, showing that the previous hypotheses considered for the mechanism development are suitable for describing the kinetics of soybean oil hydrolysis.     

Evaluation of Transport Phenomena for Removing Vanadium from Petrochemical Industry Solid Waste

Transport phenomena are investigated which are involved in the electrokinetic remediation process used for removing vanadium from deactivated catalysts from oil catalytic cracking that are currently allotted to cement plants and class-I landfills. Variables such as the concentration of electrolyte, electric potential, and applied electric current were evaluated in order to determine the effects produced by electroosmosis, diffusion, hydraulic gradient, and electromigration on the removal of vanadium from the catalyst. It was observed that migration is the most relevant phenomenon in the remediation tests, and for the best remediation condition, the migratory flow accounted for about 87 % of the vanadium removal.     

An unsupervised approach for fault diagnosis of power transformers

Electrical utilities apply condition monitoring on power transformers (PTs) to prevent unplanned outages and detect incipient faults. This monitoring is often done using dissolved gas analysis (DGA) coupled with engineering methods to interpret the data, however the obtained results lack accuracy and reproducibility. In order to improve accuracy, various advanced analytical methods have been proposed in the literature. Nonetheless, these methods are often hard to interpret by the decision-maker and require a substantial amount of failure records to be trained. In the context of the PTs, failure data quality is recurrently questionable, and failure records are scarce when compared to nonfailure records. This work tackles these challenges by proposing a novel unsupervised methodology for diagnosing PT condition. Differently from the supervised approaches in the literature, our method does not require the labeling of DGA records and incorporates a visual representation of the results in a 2D scatter plot to assist in interpretation. A modified clustering technique is used to classify the condition of different PTs using historical DGA data. Finally, well-known engineering methods are applied to interpret each of the obtained clusters. The approach was validated using data from two different real-world data sets provided by a generation company and a distribution system operator. The results highlight the advantages of the proposed approach and outperformed engineering methods (from IEC and IEEE standards) and companies legacy method. The approach was also validated on the public IEC TC10 database, showing the capability to achieve comparable accuracy with supervised learning methods from the literature. As a result of the methodology performance, both companies are currently using it in their daily DGA diagnosis.     

The influence of the processing route on the fragmentation of (Nb,Ti)C stringers and its role on mechanical properties and hydrogen embrittlement of nickel based alloy 718

The nickel-base superalloy 718 is a precipitation hardened alloy widely used in the nuclear fuel assembly of pressurized water reactors (PWR). However, the alloy can experience failure due to hydrogen embrittlement (HE). The processing route can influence the microstructure of the material and, therefore, the HE degree. In particular, the size and distribution of the (Nb,Ti)C particles can be affected by the processing. In this regard, the objective of this work was to analyze the influence of cold and hot deformation processing routes on the development of the microstructure, and the consequences on mechanical properties and hydrogen embrittlement. Tensile samples were hydrogenated through gaseous charging and compared to non-hydrogenated samples. Characterization was performed via scanning and transmission electron microscopies, as well as electron backscattered diffraction. The processing was effective to promote significant variations in average grain size and length fraction of special Σ3ⁿ boundaries, as well as reduction of average (Nb,Ti)C particle size, being these changes more intense for the cold-rolled route. For the mechanical properties, on one side, the cold-rolled route presented the highest increase in ductility for non-hydrogenated samples, while, on the other side, had the highest degree of embrittlement under hydrogen. This dual behavior was attributed to the interaction of hydrogen with the (Nb,Ti)C particles and stringers and its ensuing influence on the fracture processes.     

Surface treatment of glass fiber and carbon fiber posts: SEM characterization

Morphology, etching patterns, surface modification, and characterization of 2 different fiber posts: Gfp, Glass fiber post; and Cfp, carbon fiber were investigated by SEM analysis, after different surface treatments. Thirty fiber posts, being 15 Gfp and 15 Cfp were divided into a 5 surface treatments (n = 3): C-alcohol 70% (control); HF 4%-immersion in 4% hydrofluoric acid for 1min; H(3) PO(4) 37%-immersion in 37% phosphoric acid for 30s; H(2) O(2) 10%-immersion in 10% hydrogen peroxide for 20 min; H(2) O(2) 24%-immersion in 24% hydrogen peroxide for 10 min. Morphology, etching patterns, surface modification and surface characterization were acessed by SEM analysis. SEM evaluation revealed that the post surface morphology was modified following all treatment when compared with a control group, for both type of reinforced posts. HF seems to penetrate around the fibers of Gfp and promoted surface alterations. The Cfp surface seems to be inert to treatment with HF 4%. Dissolution of epoxy resin and exposure of the superficial fiber was observed in both post groups, regardless the type of reinforcing fiber, H(2) O(2) in both concentrations. Relative smooth surface area was produced by H(3) PO(4) 37% treatment, but with similar features to untreated group. Surface treatment of fiber post is a determinant factor on micromechanical entanglement to resin composite core. Post treatment with hydrogen peroxide resulted strength of carbon and glass/epoxy resin fiber posts to resin composite core.     

A comparison of the emissions of gasoline–ethanol fuel and compressed natural gas fuel used in vehicles with spark ignition engine in Rio de Janeiro: Brazil

Clean Technologies and Environmental Policy - A comparison of the emissions of gasoline–ethanol fuel and compressed natural gas (CNG) fuel used in vehicles with spark ignition engine was...     

A multi-objective approach for multi-material topology and shape optimization

An automated multi-material approach that integrates multi-objective Topology Optimization (TO) and multi-objective shape optimization is presented. A new ant colony optimization algorithm is presented and applied to solving the TO problem, estimating a trade-off set of initial topologies or distributions of material. The solutions found usually present irregular boundaries, which are not desirable in applications. Thus, shape parameterization of the internal boundaries of the design region, and subsequent shape optimization, is performed to improve the quality of the estimated Pareto-optimal solutions. The selection of solutions for shape optimization is done by using the PROMETHEE II decision-making method. The parameterization process involves identifying the boundaries of different materials and describing these boundaries by non-uniform rational B-spline curves. The proposed approach is applied to the optimization of a C-core magnetic actuator, with two objectives: the maximization of the attractive force on the armature and the minimization of the volume of permanent magnet material.