Application of quenching–partitioning–tempering process and modification to a newly designed ultrahigh carbon steel

The applicability of quenching–partitioning–tempering (Q–P–T) process to an ultrahigh carbon steel (UHCS) has been investigated by means of optical microscopy (OM), scanning electronic microscopy (SEM) combined with energy-dispersive spectrometry (EDS), X-ray diffraction (XRD) and mechanical property tests. The molten steel was modified with a multi-component modifier-rare earth and a low melting point alloy (Al–Bi–Sb) before casting into iron molds. Observations showed that the carbide exists as partly isolated and fine blocky structure in as-cast microstructure, indicating good effect of modification. After the Q–P–T treatment, carbon was partitioned into austenite from martensite, creating a mixture of carbon-depleted martensite, carbon-enriched retained austenite and fine carbides. This kind of microstructure leads to a much higher impact toughness, 32 J/cm², in comparison with the value, i.e., no more than 20 J/cm², of the conventional quenching and tempering (Q–T) treatment at the same hardness level. Furthermore, wear-resisting property of the steel has also been investigated. It showed that the Q–P–T treated steel has better abrasive wear resistance, about 18% increased, compared with the Q–T treated alloy under high load conditions.     

Existence and construction of Hamiltonian paths and cycles on conforming tetrahedral meshes

This paper addresses the existence and construction of Hamiltonian paths and Hamiltonian cycles on conforming tetrahedral meshes. The paths and cycles are constrained to pass from one tetrahedron to the next one through a vertex. For conforming tetrahedral meshes, under certain conditions which are normally satisfied in finite-element computations, we show that there exists a through-vertex Hamiltonian path between any two tetrahedra. The proof is constructive from which an efficient algorithm for computing Hamiltonian paths and cycles can be directly derived.     

Partitioning road networks using density peak graphs: Efficiency vs. accuracy

Road traffic networks are rapidly growing in size with increasing complexities. To simplify their analysis in order to maintain smooth traffic, a large urban road network can be considered as a set of small sub-networks, which exhibit distinctive traffic flow patterns. In this paper, we propose a robust framework for spatial partitioning of large urban road networks based on traffic measures. For a given urban road network, we aim to identify the different sub-networks or partitions that exhibit homogeneous traffic patterns internally, but heterogeneous patterns to others externally. To this end, we develop a two-stage algorithm (referred as FaDSPa) within our framework. It first transforms the large road graph into a well-structured and condensed density peak graph (DPG) via density based clustering and link aggregation using traffic density and adjacency connectivity, respectively. Thereafter we apply our spectral theory based graph cut (referred as α-Cut) to partition the DPG and obtain the different sub-networks. Thus the framework applies the locally distributed computations of density based clustering to improve efficiency and the centralized global computations of spectral clustering to improve accuracy. We perform extensive experiments on real as well as synthetic datasets, and compare its performance with that of an existing road network partitioning method. Our results show that the proposed method outperforms the existing normalized cut based method for small road networks and provides impressive results for much larger networks, where other methods may face serious problems of time and space complexities.     

Analysis of indoor particles and gases and their evolution with natural ventilation

The air composition and reactivity from outdoor and indoor mixing field campaign was conducted to investigate the impacts of natural ventilation (ie, window opening and closing) on indoor air quality. In this study, a thermal desorption aerosol gas chromatograph (TAG) obtained measurements of indoor particle‐ and gas‐phase semi‐ and intermediately volatile organic compounds both inside and outside a single‐family test home. Together with measurements from a suite of instruments, we use TAG data to evaluate changes in indoor particles and gases at three natural ventilation periods. Positive matrix factorization was performed on TAG and adsorbent tube data to explore five distinct chemical and physical processes occurring in the indoor environment. Outdoor‐to‐indoor transport is observed for sulfate, isoprene epoxydiols, polycyclic aromatic hydrocarbons, and heavy alkanes. Dilution of indoor species is observed for volatile, non‐reactive species including methylcyclohexane and decamethylcyclopentasiloxane. Window opening drives enhanced emissions of semi‐ and intermediately volatile species including TXIB, DEET, diethyl phthalate, and carvone from indoor surfaces. Formation via enhanced oxidation was observed for nonanal and 2‐decanone when outdoor oxidants entered the home. Finally, oxidative depletion of gas‐phase terpenes (eg, limonene and α‐pinene) was anticipated but not observed due to limited measurement resolution and dynamically changing conditions.     

Factors affecting forestland owners' allocation of non-forested land to pine plantation for bioenergy in Virginia

Studies have shown that woody bioenergy can have potential economic, social, and environmental benefits. One of the ways to meet the growing biomass demand for woody bioenergy is by allocating currently non-forested land for growing feedstocks such as pine. Towards this end, we conducted a survey on 900 randomly selected private forestland owners in Virginia and asked what proportion of their non-forested land they would allocate for loblolly pine at given bid prices. We then used recursive partitioning based Tobit regression to analyze data. Our results suggest that the experience of having supplied wood for chip-n-saw mills in the past five years, large land holding, prior experience with state/federal financial/technical support programs, among other factors, lead to smaller proportion of non-forested land being allocated for pine. However, a higher price offer, stronger preference for producing non-timber forest products such as evergreen boughs and grapevine, and lesser dependence on working the land for annual income lead to larger proportion of non-forested land being allocate for pine. Our results could assist policy makers in developing and improving land use and energy policies, certification programs, and extension and outreach services. Our contribution also includes the use of threshold analyses to delineate tipping points in variables associated with different response rates and showing the different effect of variables in terms of how they affect the supply of biomass and the supply of land for bioenergy purposes.     

Determination of thiamethoxam,triadimenol and deltamethrin in pineapple using SLE-LTP extraction and gas chromatography

In this work, a simple and low cost method based on solid–liquid extraction with low temperature partitioning (SLE–LTP) was optimized and validated for the residue analyses of the pesticides thiamethoxam, triadimenol and deltamethrin in pineapple samples using gas chromatography with electron capture detector (GC-ECD). The SLE-LTP technique was proven satisfactory with recoveries up to 90% and linear chromatographic response for the analytes, ranging from 0.04 to 1.30 μg g⁻¹ with correlation coefficients above 0.99. The limits of quantification for the pesticides were lower than the allowed maximum limits of residues established for these pesticides in pineapple by the European Union.     

Automatic network clustering via density-constrained optimization with grouping operator

Automatic network clustering is an important technique for mining the meaningful communities (or clusters) of a network. Communities in a network are clusters of nodes where the intra-cluster connection density is high and the inter-cluster connection density is low. The most popular scheme of automatic network clustering aims at maximizing a criterion function known as modularity in partitioning all the nodes into clusters. But it is found that the modularity suffers from the resolution limit problem, which remains an open challenge. In this paper, the automatic network clustering is formulated as a constrained optimization problem: maximizing a criterion function with a density constraint. With this scheme, the established algorithm can be free from the resolution limit problem. Furthermore, it is found that the density constraint can improve the detection accuracy of the modularity optimization. The efficiency of the proposed scheme is verified by comparative experiments on large scale benchmark networks.     

The Effect of Size and Shape of Austenite Grains on the Mechanical Properties of a Low‐Alloyed TRIP Steel

The effects of size and shape of austenite grains on the extraordinary hardening of steels with transformation induced plasticity (TRIP) have been studied. The deformation and transformation of austenite was followed by interrupted ex situ bending tests using electron backscatter diffraction (EBSD) in a scanning electron microscope (SEM). A finite element model (FEM) was used to relate the EBSD based results obtained in the bending experiments to the hardening behavior obtained from tensile experiments. The results are interpreted using a simple rule of mixture for stress partitioning and a short fiber reinforced composite model. It is found that both, the martensite transformation rate and the flow stress difference between austenite and martensite significantly influence the hardening rate. At the initial stage of deformation mainly larger grains deform, however, they do not reach the same strain level as the smaller grains because they transform into martensite at an early stage of deformation. A composite model was used to investigate the effect of grain shape on load partitioning. The results of the composite model show that higher stresses develop in more elongated grains. These grains tend to transform earlier as it is confirmed by the EBSD observations.