Small scale heater tests in argillite of the Eleana Formation at the Nevada Test Site

Near-surface heater tests were run in the Eleana Formation at the Nevada Test Site, in an effort to evaluate argillaceous rock for nuclear waste storage. The main test, which employed a full-scale heater with a thermal output approximating commercial borosilicate waste, was designed to operate for several months. Two smaller, scaled tests were run prior to the full-scale test. This report develops the thermal scaling laws, describes the pretest thermal and thermomechanical analysis conducted for these two tests, and discusses the material properties data used in the analyses. In the first test, scaled to a large heater of 3.5 kW power, computed heater temperatures were within 7% of measured values for the entire 96-hour test run. The second test, scaled to a large heater having 5.0 kW power, experienced periodic water in-flow onto the heater, which tended to damp the temperature. For the second test, the computed temperatures were within 7% of measured for the first 20 hours. After this time, the water effect became significant and the measured temperatures were 15 to 20% below those predicted. On the second test, rock surface spallation was noted in the bore hole above the heater, as predicted. The scaled tests indicated that in-situ argillite would not undergo major thermostructural failure during the follow-on, 3.5 kW, full-scale test. 24 figures, 6 tables

Thermal conductivity of silicic tuffs: predictive formalism and comparison with preliminary experimental results

Performance of both near- and far-field thermomechanical calculations to assess the feasibility of waste disposal in silicic tuffs requires a formalism for predicting thermal conductivity of a broad range of tuffs. This report summarizes the available thermal conductivity data for silicate phases that occur in tuffs and describes several grain-density and conductivity trends which may be expected to result from post-emplacement alteration. A bounding curve is drawn that predicts the minimum theoretical matrix (zero-porosity) conductivity for most tuffs as a function of grain density. Comparison of experimental results with this curve shows that experimental conductivities are consistently lower at any given grain density. Use of the lowered bounding curve and an effective gas conductivity of 0.12 W/m{sup 0}C allows conservative prediction of conductivity for a broad range of tuff types. For the samples measured here, use of the predictive curve allows estimation of conductivity to within 15% or better, with one exception. Application and possible improvement of the formalism are also discussed

Fighting with the Sparsity of Synonymy Dictionaries

Graph-based synset induction methods, such as MaxMax and Watset, induce synsets by performing a global clustering of a synonymy graph. However, such methods are sensitive to the structure of the input synonymy graph: sparseness of the input dictionary can substantially reduce the quality of the extracted synsets. In this paper, we propose two different approaches designed to alleviate the incompleteness of the input dictionaries. The first one performs a pre-processing of the graph by adding missing edges, while the second one performs a post-processing by merging similar synset clusters. We evaluate these approaches on two datasets for the Russian language and discuss their impact on the performance of synset induction methods. Finally, we perform an extensive error analysis of each approach and discuss prominent alternative methods for coping with the problem of the sparsity of the synonymy dictionaries.Comment: In Proceedings of the 6th Conference on Analysis of Images, Social Networks, and Texts (AIST'2017): Springer Lecture Notes in Computer Science (LNCS

Bayesian Inference Semantics: A Modelling System and A Test Suite

We present BIS, a Bayesian Inference Seman- tics, for probabilistic reasoning in natural lan- guage. The current system is based on the framework of Bernardy et al. (2018), but de- parts from it in important respects. BIS makes use of Bayesian learning for inferring a hy- pothesis from premises. This involves estimat- ing the probability of the hypothesis, given the data supplied by the premises of an argument. It uses a syntactic parser to generate typed syn- tactic structures that serve as input to a model generation system. Sentences are interpreted compositionally to probabilistic programs, and the corresponding truth values are estimated using sampling methods. BIS successfully deals with various probabilistic semantic phe- nomena, including frequency adverbs, gener- alised quantifiers, generics, and vague predi- cates. It performs well on a number of interest- ing probabilistic reasoning tasks. It also sus- tains most classically valid inferences (instan- tiation, de Morgan’s laws, etc.). To test BIS we have built an experimental test suite with examples of a range of probabilistic and clas- sical inference patterns

Prevalence and correlates of food insecurity in community-based individuals with severe mental illness receiving long-acting injectable antipsychotic treatment

People with severe mental illness (SMI) have numerous risk factors that may predispose them to food insecurity (FI); however, the prevalence of FI and its effects on health are under-researched in this population. The present study aimed to describe the prevalence of FI and its relationship to lifestyle factors in people with SMI. This cross-sectional study recruited people with SMI receiving long-acting injectable (LAI) antipsychotic medication from community services at three sites in Sydney, Australia. Assessments were completed on physical health and lifestyle factors. χ2 Tests, independent-samples t tests and binary logistic regression analyses were calculated to examine relationships between lifestyle factors and FI. In total, 233 people completed the assessments: 154 were males (66 %), mean age 44·8 (sd 12·7) years, and the majority (70 %) had a diagnosis of schizophrenia. FI was present in 104 participants (45 %). People with FI were less likely to consume fruits (OR 0·42, 95 % CI 0·24, 0·74, P = 0·003), vegetables (OR 0·39, 95 % CI 0·22, 0·69, P = 0·001) and protein-based foods (OR 0·45, 95 % CI 0·25, 0·83, P = 0·011) at least once daily, engaged in less moderate to vigorous physical activity (min) (OR 0·997, 95 % CI 0·993, 1·000, P = 0·044), and were more likely to smoke (OR 1·89, 95 % CI 1·08, 3·32, P = 0·026). FI is highly prevalent among people with SMI receiving LAI antipsychotic medications. Food-insecure people with SMI engage in less healthy lifestyle behaviours, increasing the risk of future non-communicable disease

Eleana near-surface heater experiment final report

This report summarizes the results of a near-surface heater experiment operated at a depth of 23 m in argillite within the Eleana Formation on the Nevada Test Site (NTS). The test geometrically simulated emplacement of a single canister of High-Level Waste (HLW) and was operated at a power level of 2.5 kW for 21 days, followed by 3.8 kW to 250 days, when the power was turned off. Below 85 to 100{sup 0}C, there was good agreement between modeled and measured thermal results in the rock and in the emplacement hole, except for transient transport of water in the heater hole. Above 100{sup 0}C, modeled and measured thermal results increasingly diverged, indicating that the in-situ rock-mass thermal conductivity decreased as a result of dehydration more than expected on the basis of matrix properties. Correlation of thermomechanical modeling and field results suggests that this decrease was caused by strong coupling of thermal and mechanical behavior of the argillite at elevated temperatures. No hole-wall decrepitation was observed in the experiment; this fact and the codrrelation of modeled and measured results at lower temperatures indicate that there is no a priori reason to eliminate argillaceous rocks from further consideration as a host rock for nuclear wastes

Small scale heater tests in argillite of the Eleana Formation at the Nevada Test Site

Near-surface heater tests were run in the Eleana Formation at the Nevada Test Site, in an effort to evaluate argillaceous rock for nuclear waste storage. The main test, which employed a full-scale heater with a thermal output approximating commercial borosilicate waste, was designed to operate for several months. Two smaller, scaled tests were run prior to the full-scale test. This report develops the thermal scaling laws, describes the pretest thermal and thermomechanical analysis conducted for these two tests, and discusses the material properties data used in the analyses. In the first test, scaled to a large heater of 3.5 kW power, computed heater temperatures were within 7% of measured values for the entire 96-hour test run. The second test, scaled to a large heater having 5.0 kW power, experienced periodic water in-flow onto the heater, which tended to damp the temperature. For the second test, the computed temperatures were within 7% of measured for the first 20 hours. After this time, the water effect became significant and the measured temperatures were 15 to 20% below those predicted. On the second test, rock surface spallation was noted in the bore hole above the heater, as predicted. The scaled tests indicated that in-situ argillite would not undergo major thermostructural failure during the follow-on, 3.5 kW, full-scale test. 24 figures, 6 tables