Storage and feeding of coal

Reliable feeding of coal from storage bins to process requires the knowledge of the behavior of coal during flow. The study of the flow of bulk solids was undertaken in the 1950's and led to the development of flow ability testing equipment and of the Mass Flow concept of design for reliable flow. The theory has since been expanded to two-phase, solids-gas system, and has found world wide application in the design of storage and feeding systems

Human oral processing and texture profile analysis parameters: bridging the gap between the sensory evaluation and the instrumental measurements

Studies in food oral processing are becoming increasingly important with the advent of the aged society. The food oral processing model of Hutchings and Lillford (Journal of Texture Studies, 19, 1988, 103–115) describes the structural breakdown and lubrication of ingested food before the swallowing stage, and has been revisited in the present article. The instrumental technique texture profile analysis (TPA) purports to mimic the first two bites of mastication and its ease of use has lured some researchers to use it without a critical eye. In this article, we consider inconsistencies in the Hutchings and Lillford model with the hope that it might be further refined. With regard to TPA we question the validity of the data generated and urge authors caution before they publish results from the test protocol. If results are published then the x‐axis should be viewed as deformation or strain, and not time. Hardness should be represented by the breaking stress. Adhesiveness should be measured at a medium strain taking into account the surface properties of the plunger. The ratio of the energy estimated by the area under the curve obtained from the second and the first bites (A2/A1) should be called recoverability and not cohesiveness

A stochastic flow rule for granular materials

There have been many attempts to derive continuum models for dense granular flow, but a general theory is still lacking. Here, we start with Mohr-Coulomb plasticity for quasi-2D granular materials to calculate (average) stresses and slip planes, but we propose a "stochastic flow rule" (SFR) to replace the principle of coaxiality in classical plasticity. The SFR takes into account two crucial features of granular materials - discreteness and randomness - via diffusing "spots" of local fluidization, which act as carriers of plasticity. We postulate that spots perform random walks biased along slip-lines with a drift direction determined by the stress imbalance upon a local switch from static to dynamic friction. In the continuum limit (based on a Fokker-Planck equation for the spot concentration), this simple model is able to predict a variety of granular flow profiles in flat-bottom silos, annular Couette cells, flowing heaps, and plate-dragging experiments -- with essentially no fitting parameters -- although it is only expected to function where material is at incipient failure and slip-lines are inadmissible. For special cases of admissible slip-lines, such as plate dragging under a heavy load or flow down an inclined plane, we postulate a transition to rate-dependent Bagnold rheology, where flow occurs by sliding shear planes. With different yield criteria, the SFR provides a general framework for multiscale modeling of plasticity in amorphous materials, cycling between continuum limit-state stress calculations, meso-scale spot random walks, and microscopic particle relaxation

Modeling Distillers Dried Grains with Solubles (DDGS) Mass Flow Rate as Affected by Drying and Storage Conditions

Ethanol production in 2015 was over 15 million gallons in the United States, and it is projected to increase in the next few years to meet market demands. With the continued growth in the ethanol industry, there has been enormous expansion in distillers grains production. Because the local market for distillers dried grains with solubles (DDGS) is often saturated, it is essential to transport DDGS long distances, across the United States and to international markets. Caking and agglomeration of DDGS particles in hoppers and other storage structures are typical during transportation. The current study deals with DDGS prepared by combining condensed distillers solubles (CDS) with distillers wet grains and then drying at varying temperatures. DDGS was stored in conical hoppers under varying ambient temperature, consolidation pressure, and time conditions. We investigated the effects of CDS (10, 15, and 20% wb), drying temperature (100, 200, and 300°C), drying time (20, 40, and 60 min), cooling temperature (0, 25, and 50°C), consolidation pressure (0, 1.72, and 3.43 kPa), and consolidation time (0, 3, and 6 days) levels on various flow parameters. To examine these factors, Taguchi’s experimental design with an L18 orthogonal array was implemented. Response surface modeling yielded mass flow rate = f(Hausner ratio, angle of repose) with R2 = 0.99, and it predicted moisture content for good, fair, and poor flow. Results showed that drying temperature, drying time, and cooling type were the main factors in predicting mass flow rate. The Johansson model for predicted mass flow rate was calibrated with experimental data, and a new parameter, compressibility factor, with a value of 0.96 g2/(min cm3), was determined to quantify the divergence of compressible and cohesive materials (such as DDGS) for free-flowing bulk solids. Thus, the predicted models may be beneficial for quantitative understanding of DDGS flow

Symptom Dimensions in OCD: Item-Level Factor Analysis and Heritability Estimates

To reduce the phenotypic heterogeneity of obsessive-compulsive disorder (OCD) for genetic, clinical and translational studies, numerous factor analyses of the Yale-Brown Obsessive Compulsive Scale checklist (YBOCS-CL) have been conducted. Results of these analyses have been inconsistent, likely as a consequence of small sample sizes and variable methodologies. Furthermore, data concerning the heritability of the factors are limited. Item and category-level factor analyses of YBOCS-CL items from 1224 OCD subjects were followed by heritability analyses in 52 OCD-affected multigenerational families. Item-level analyses indicated that a five factor model: (1) taboo, (2) contamination/cleaning, (3) doubts, (4) superstitions/rituals, and (5) symmetry/hoarding provided the best fit, followed by a one-factor solution. All 5 factors as well as the one-factor solution were found to be heritable. Bivariate analyses indicated that the taboo and doubts factor, and the contamination and symmetry/hoarding factor share genetic influences. Contamination and symmetry/hoarding show shared genetic variance with symptom severity. Nearly all factors showed shared environmental variance with each other and with symptom severity. These results support the utility of both OCD diagnosis and symptom dimensions in genetic research and clinical contexts. Both shared and unique genetic influences underlie susceptibility to OCD and its symptom dimensions.Obsessive Compulsive FoundationTourette Syndrome AssociationAnxiety Disorders Association of AmericaAmerican Academy of Child and Adolescent Psychiatr

Analysis of shared heritability in common disorders of the brain

ience, this issue p. eaap8757 Structured Abstract INTRODUCTION Brain disorders may exhibit shared symptoms and substantial epidemiological comorbidity, inciting debate about their etiologic overlap. However, detailed study of phenotypes with different ages of onset, severity, and presentation poses a considerable challenge. Recently developed heritability methods allow us to accurately measure correlation of genome-wide common variant risk between two phenotypes from pools of different individuals and assess how connected they, or at least their genetic risks, are on the genomic level. We used genome-wide association data for 265,218 patients and 784,643 control participants, as well as 17 phenotypes from a total of 1,191,588 individuals, to quantify the degree of overlap for genetic risk factors of 25 common brain disorders. RATIONALE Over the past century, the classification of brain disorders has evolved to reflect the medical and scientific communities' assessments of the presumed root causes of clinical phenomena such as behavioral change, loss of motor function, or alterations of consciousness. Directly observable phenomena (such as the presence of emboli, protein tangles, or unusual electrical activity patterns) generally define and separate neurological disorders from psychiatric disorders. Understanding the genetic underpinnings and categorical distinctions for brain disorders and related phenotypes may inform the search for their biological mechanisms. RESULTS Common variant risk for psychiatric disorders was shown to correlate significantly, especially among attention deficit hyperactivity disorder (ADHD), bipolar disorder, major depressive disorder (MDD), and schizophrenia. By contrast, neurological disorders appear more distinct from one another and from the psychiatric disorders, except for migraine, which was significantly correlated to ADHD, MDD, and Tourette syndrome. We demonstrate that, in the general population, the personality trait neuroticism is significantly correlated with almost every psychiatric disorder and migraine. We also identify significant genetic sharing between disorders and early life cognitive measures (e.g., years of education and college attainment) in the general population, demonstrating positive correlation with several psychiatric disorders (e.g., anorexia nervosa and bipolar disorder) and negative correlation with several neurological phenotypes (e.g., Alzheimer's disease and ischemic stroke), even though the latter are considered to result from specific processes that occur later in life. Extensive simulations were also performed to inform how statistical power, diagnostic misclassification, and phenotypic heterogeneity influence genetic correlations. CONCLUSION The high degree of genetic correlation among many of the psychiatric disorders adds further evidence that their current clinical boundaries do not reflect distinct underlying pathogenic processes, at least on the genetic level. This suggests a deeply interconnected nature for psychiatric disorders, in contrast to neurological disorders, and underscores the need to refine psychiatric diagnostics. Genetically informed analyses may provide important "scaffolding" to support such restructuring of psychiatric nosology, which likely requires incorporating many levels of information. By contrast, we find limited evidence for widespread common genetic risk sharing among neurological disorders or across neurological and psychiatric disorders. We show that both psychiatric and neurological disorders have robust correlations with cognitive and personality measures. Further study is needed to evaluate whether overlapping genetic contributions to psychiatric pathology may influence treatment choices. Ultimately, such developments may pave the way toward reduced heterogeneity and improved diagnosis and treatment of psychiatric disorders