TAMM: Tensor algebra for many-body methods.

Tensor algebra operations such as contractions in computational chemistry consume a significant fraction of the computing time on large-scale computing platforms. The widespread use of tensor contractions between large multi-dimensional tensors in describing electronic structure theory has motivated the development of multiple tensor algebra frameworks targeting heterogeneous computing platforms. In this paper, we present Tensor Algebra for Many-body Methods (TAMM), a framework for productive and performance-portable development of scalable computational chemistry methods. TAMM decouples the specification of the computation from the execution of these operations on available high-performance computing systems. With this design choice, the scientific application developers (domain scientists) can focus on the algorithmic requirements using the tensor algebra interface provided by TAMM, whereas high-performance computing developers can direct their attention to various optimizations on the underlying constructs, such as efficient data distribution, optimized scheduling algorithms, and efficient use of intra-node resources (e.g., graphics processing units). The modular structure of TAMM allows it to support different hardware architectures and incorporate new algorithmic advances. We describe the TAMM framework and our approach to the sustainable development of scalable ground- and excited-state electronic structure methods. We present case studies highlighting the ease of use, including the performance and productivity gains compared to other frameworks.

Physicochemical heterogeneity controls on uranium bioreduction rates at the field scale.

It has been demonstrated in laboratory systems that U(VI) can be reduced to immobile U(IV) by bacteria in natural environments. The ultimate efficacy of bioreduction at the field scale, however, is often challenging to quantify and depends on site characteristics. In this work, uranium bioreduction rates at the field scale are quantified, for the first time, using an integrated approach. The approach combines field data, inverse and forward hydrological and reactive transport modeling, and quantification of reduction rates at different spatial scales. The approach is used to explore the impact of local scale (tens of centimeters) parameters and processes on field scale (tens of meters) system responses to biostimulation treatments and the controls of physicochemical heterogeneity on bioreduction rates. Using the biostimulation experiments at the Department of Energy Old Rifle site, our results show that the spatial distribution of hydraulic conductivity and solid phase mineral (Fe(III)) play a critical role in determining the field-scale bioreduction rates. Due to the dependence on Fe-reducing bacteria, field-scale U(VI) bioreduction rates were found to be largely controlled by the abundance of Fe(III) minerals at the vicinity of the injection wells and by the presence of preferential flow paths connecting injection wells to down gradient Fe(III) abundant areas.

Modeling microbiological and chemical processes in municipal solid waste bioreactor, Part II: Application of numerical model BIOKEMOD-3P.

Biodegradation process modeling of municipal solid waste (MSW) bioreactor landfills requires the knowledge of various process reactions and corresponding kinetic parameters. Mechanistic models available to date are able to simulate biodegradation processes with the help of pre-defined species and reactions. Some of these models consider the effect of critical parameters such as moisture content, pH, and temperature. Biomass concentration is a vital parameter for any biomass growth model and often not compared with field and laboratory results. A more complex biodegradation model includes a large number of chemical and microbiological species. Increasing the number of species and user defined process reactions in the simulation requires a robust numerical tool. A generalized microbiological and chemical model, BIOKEMOD-3P, was developed to simulate biodegradation processes in three-phases (Gawande et al. 2009). This paper presents the application of this model to simulate laboratory-scale MSW bioreactors under anaerobic conditions. BIOKEMOD-3P was able to closely simulate the experimental data. The results from this study may help in application of this model to full-scale landfill operation.

Modeling microbiological and chemical processes in municipal solid waste bioreactor, Part I: Development of a three-phase numerical model BIOKEMOD-3P.

The numerical computer models that simulate municipal solid waste (MSW) bioreactor landfills have mainly two components--a biodegradation process module and a multi-phase flow module. The biodegradation model describes the chemical and microbiological processes. The models available to date include predefined solid waste biodegradation reactions and participating species. Some of these models allow changing the basic composition of solid waste. In a bioreactor landfill several processes like anaerobic and aerobic solids biodegradation, nitrogen and sulfate related processes, precipitation and dissolution of metals, and adsorption and gasification of various anthropogenic organic compounds occur simultaneously. These processes may involve reactions of several species and the available biochemical models for solid waste biodegradation do not provide users with the flexibility to simulate these processes by choice. This paper presents the development of a generalized biochemical process model BIOKEMOD-3P which can accommodate a large number of species and process reactions. This model is able to simulate bioreactor landfill operation in a completely mixed condition, when coupled with a multi-phase model it will be able to simulate a full-scale bioreactor landfill. This generalized biochemical model can simulate laboratory and pilot-scale operations in order to determine biochemical parameters important for simulation of full-scale operations.

Field evaluation of resistivity sensors for in situ moisture measurement in a bioreactor landfill.

The ability of resistance-based sensors to measure in situ waste moisture content in a landfill was examined. One hundred and thirty-five resistance-based sensors were installed in a leachate recirculation well field at a bioreactor landfill in Florida, US. The performance of these sensors was studied for a period of over 6 years. The sensors were found to respond to an increase in moisture resulting from leachate recirculation. It was observed that 78% of sensors worked successfully in the field during the study period. The initial spatial average moisture content determined by the sensor readings (using a laboratory-derived calibration) was 42.8% compared to 23% from gravimetric readings. Eighteen sensors (13%) showed that they were saturated before liquid addition, and no change in moisture content was observed in these sensors during the study period. Laboratory-derived calibration methods resulted in an over-estimation of moisture content. An alternate field-calibration method, where wetted sensor output was assumed equal to the average of gravimetric measurements for wet samples, was evaluated. The final spatial average moisture contents were 64.2% and 44.4% for the laboratory-derived and field-derived calibration methodologies, respectively, compared to 45% measured gravimetrically from excavated waste samples. When moisture content was determined using a mass balance approach, the result was 34.6%. The results suggest that when appropriately calibrated, resistivity-based sensors can be used to obtain a reasonably accurate estimate of local moisture content. However, caution should be taken to extend the moisture content values that are representative of waste surrounding the sensors to estimate the overall moisture content on the landfill-wide scale.

Review of state of the art methods for measuring water in landfills.

In recent years several types of sensors and measurement techniques have been developed for measuring the moisture content, water saturation, or the volumetric water content of landfilled wastes. In this work, we review several of the most promising techniques. The basic principles behind each technique are discussed and field applications of the techniques are presented, including cost estimates. For several sensors, previously unpublished data are given. Neutron probes, electrical resistivity (impedance) sensors, time domain reflectometry (TDR) sensors, and the partitioning gas tracer technique (PGTT) were field tested with results compared to gravimetric measurements or estimates of the volumetric water content or moisture content. Neutron probes were not able to accurately measure the volumetric water content, but could track changes in moisture conditions. Electrical resistivity and TDR sensors tended to provide biased estimates, with instrument-determined moisture contents larger than independent estimates. While the PGTT resulted in relatively accurate measurements, electrical resistivity and TDR sensors provide more rapid results and are better suited for tracking infiltration fronts. Fiber optic sensors and electrical resistivity tomography hold promise for measuring water distributions in situ, particularly during infiltration events, but have not been tested with independent measurements to quantify their accuracy. Additional work is recommended to advance the development of some of these instruments and to acquire an improved understanding of liquid movement in landfills by application of the most promising techniques in the field.

Municipal solid waste in situ moisture content measurement using an electrical resistance sensor.

Moisture content (MC) is a crucial parameter for degradation of solid waste in landfills. Present MC measurement techniques suffer from several drawbacks. A moisture sensor for measurement of in situ moisture content of solid waste in landfills was developed. The sensor measures the electrical resistance across the granular matrix of the sensor, which in turn can be correlated to moisture content. The sensor was also equipped with a thermocouple and tubing that permits simultaneous measurement of temperature and gas sampling. The electrical conductivity of the surrounding moisture and the temperature in the matrix both affect the resistance measurements. This paper describes the results of laboratory experiments designed to select the appropriate granular media particle size, measure the influence of moisture electrical conductivity and temperature, and develop calibration relationships between measured resistance and gravimetrically determined moisture content. With a few limitations, the sensor is able to detect MC of solid waste under conditions allowing moisture movement into the sensor. The application of this technique shows promise for use in bioreactor landfills where high moisture contents are expected and desired.