Structure and flame speed of dilute and dense layered coal-dust explosions

Multidimensional time-dependent simulations were performed to study the interaction of a stoichiometric methane–air detonation with layers of coal dust. The simulations solved equations representing a Eulerian kinetic-theory-based granular multiphase model applicable to dense and dilute particle volume fractions. These equations were solved using a high-order Godunov-based method for compressible fluid dynamics. Two dust layer concentrations were considered: loose with an initial volume fraction of 1%, and dense with an initial volume fraction of 47%. Each layer was simulated with two types of dust: reactive coal and inert ash. Burning of the coal particles results in a coupled complex consisting of an accelerating shock leading a coal-dust flame. The overall structure of the shock–flame complex resembles that of a premixed fast flame with length scales on the order of several meters. The large length scales are direct results of time needed to lift, mix, heat, and autoignite the particle. The flame speeds are large and much larger than the gas-phase velocity. Large spikes of flame speed are characteristic of the 47% case. These spikes and high flame speed are caused by pockets of coal dust autoigniting ahead of the flame. The flame is choked in the 1% case due to the gas-phase products exceeding the sonic velocity with respect to the flame. The 47% case is choked due to attenuation of pressure waves as they propagate through particles. Inert layers of dust substantially reduce the overpressure, impulse, and speed produced by propagating blast wave. The results also show that loose layers of dust are far more dangerous than dense layers. The shock and flame are more strongly coupled for loose layers, propagate at higher velocity, and produce large overpressures and impulses.     

木质类人造板材炭化痕迹实验及数值重构研究

利用锥形量热仪测定不同辐射热通量和不同燃烧时间下木质类人造板材的炭化深度,建立木质类人造板材炭化痕迹的数学模型,并嵌入到FDS(Fire Dynamics Simulator)源程序中,与自身功能相结合,实现重构木质类人造板材炭化痕迹的功能。同时实验研究了不同油盘尺寸、不同燃烧时间、不同火源位置和不同材料种类对炭化痕迹的影响,并利用新编译的FDS程序对实验进行重构,对比重构结果和实验结果,证明该程序可以用于重现木质类人造板材的炭化痕迹。     

Development of numerical model for predicting heat generation and temperatures in MSW landfills

A numerical modeling approach has been developed for predicting temperatures in municipal solid waste landfills. Model formulation and details of boundary conditions are described. Model performance was evaluated using field data from a landfill in Michigan, USA. The numerical approach was based on finite element analysis incorporating transient conductive heat transfer. Heat generation functions representing decomposition of wastes were empirically developed and incorporated to the formulation. Thermal properties of materials were determined using experimental testing, field observations, and data reported in literature. The boundary conditions consisted of seasonal temperature cycles at the ground surface and constant temperatures at the far-field boundary. Heat generation functions were developed sequentially using varying degrees of conceptual complexity in modeling. First a step-function was developed to represent initial (aerobic) and residual (anaerobic) conditions. Second, an exponential growth-decay function was established. Third, the function was scaled for temperature dependency. Finally, an energy-expended function was developed to simulate heat generation with waste age as a function of temperature. Results are presented and compared to field data for the temperature-dependent growth-decay functions. The formulations developed can be used for prediction of temperatures within various components of landfill systems (liner, waste mass, cover, and surrounding subgrade), determination of frost depths, and determination of heat gain due to decomposition of wastes.     

Application of continuous time random walk theory to nonequilibrium transport in soil

Continuous time random walk (CTRW) formulations have been demonstrated to provide a general and effective approach that quantifies the behavior of solute transport in heterogeneous media in field, laboratory, and numerical experiments. In this paper we first apply the CTRW approach to describe the sorbing solute transport in soils under chemical (or) and physical nonequilibrium conditions by curve-fitting. Results show that the theoretical solutions are in a good agreement with the experimental measurements. In case that CTRW parameters cannot be determined directly or easily, an alternative method is then proposed for estimating such parameters independently of the breakthrough curve data to be simulated. We conduct numerical experiments with artificial data sets generated by the HYDRUS-1D model for a wide range of pore water velocities (υ) and retardation factors (R) to investigate the relationship between CTRW parameters for a sorbing solute and these two quantities (υ, R) that can be directly measured in independent experiments. A series of best-fitting regression equations are then developed from the artificial data sets, which can be easily used as an estimation or prediction model to assess the transport of sorbing solutes under steady flow conditions through soil. Several literature data sets of pesticides are used to validate these relationships. The results show reasonable performance in most cases, thus indicating that our method could provide an alternative way to effectively predict sorbing solute transport in soils. While the regression relationships presented are obtained under certain flow and sorption conditions, the methodology of our study is general and may be extended to predict solute transport in soils under different flow and sorption conditions.     

A comparison of numerical solutions of partial differential equations with probabilistic and possibilistic parameters for the quantification of uncertainty in subsurface solute transport

Traditionally, uncertainty in parameters are represented as probabilistic distributions and incorporated into groundwater flow and contaminant transport models. With the advent of newer uncertainty theories, it is now understood that stochastic methods cannot properly represent non random uncertainties. In the groundwater flow and contaminant transport equations, uncertainty in some parameters may be random, whereas those of others may be non random. The objective of this paper is to develop a fuzzy-stochastic partial differential equation (FSPDE) model to simulate conditions where both random and non random uncertainties are involved in groundwater flow and solute transport. Three potential solution techniques namely, (a) transforming a probability distribution to a possibility distribution (Method I) then a FSPDE becomes a fuzzy partial differential equation (FPDE), (b) transforming a possibility distribution to a probability distribution (Method II) and then a FSPDE becomes a stochastic partial differential equation (SPDE), and (c) the combination of Monte Carlo methods and FPDE solution techniques (Method III) are proposed and compared. The effects of these three methods on the predictive results are investigated by using two case studies. The results show that the predictions obtained from Method II is a specific case of that got from Method I. When an exact probabilistic result is needed, Method II is suggested. As the loss or gain of information during a probability–possibility (or vice versa) transformation cannot be quantified, their influences on the predictive results is not known. Thus, Method III should probably be preferred for risk assessments.     

Two case studies of sulfate scavenging processes in the Amazon region (Rondônia)

The scavenging processes of chemical species have been previously studied with numerical modeling, in order to understand the gas and particulate matter intra-reservoir transferences. In this study, the atmospheric (RAMS) and scavenging (B.V.2) models were used, in order to simulate sulfate concentrations in rainwater using scavenging processes as well as the local atmospheric conditions obtained within the LBA Project in the State of Rondonia, during a dry-to-wet transition season. Two case studies were conducted. The RAMS atmospheric simulation of these events presented satisfactory results, showing the detailed microphysical processes of clouds in the Amazonian region. On the other hand, with cloud entrainments, observed values have been overestimated. Modeled sulfate rainwater concentration, using exponential decay and cloud heights of 16 km and no entrainments, presented the best results, reaching 97% of the observed value. The results, using shape parameter 5, are the best, improving the overall result.     

The distribution characteristics of pollutants released at different cross-sectional positions of a river

The distribution characteristics of heavier or lighter pollutants released at different cross-sectional positions of a wide river is investigated with a well-tested three-dimensional numerical model of gravity flows based on Reynolds-Averaged Navier-Stokes equations and turbulence k-? model. By focusing on investigating the influences of flow and buoyancy on pollutants, it is found that while carrying by the river flow downstream: i) a heavier pollutant released from the cross-sectional side position, forms transverse oscillation between two banks with decreased amplitude, i.e. forms kind of helical flow pattern along the straight part of channel bed; ii) a heavier pollutant released from the cross-sectional middle position, forms collapse oscillation in the middle of the straight channel part with reduced amplitude; iii) in the downstream sinuous channel, heavier pollutant is of higher concentration on the outer side of channel bends; iv) a light pollutant released from the cross-sectional side position, slips partly to the other side of the river, resulting in higher concentrations on two sides of the channel top; v) a light pollutant released from the cross-sectional middle position, splits into two parts symmetrically along two sides of the channel top; vi) in the downstream sinuous channel, light pollutant presents higher concentration on the inner side of channel bends. These findings may assist in cost-effective scientific countermeasures to be taken for accidental or planned pollutant releases into a river.     

Evaluation of groundwater flow patterns around a dual-screened groundwater circulation well

Dual-screened groundwater circulation wells (GCWs) can be used to remove contaminant mass and to mix reagents in situ. GCWs are so named because they force water in a circular pattern between injection and extraction screens. The radial extent, flux and direction of the effective flow of this circulation cell are difficult to measure or predict. The objective of this study is to develop a robust protocol for assessing GCW performance. To accomplish this, groundwater flow patterns surrounding a GCW are assessed using a suite of tools and data, including: hydraulic head, in situ flow velocity, measured hydraulic conductivity data from core samples, chemical tracer tests, contaminant distribution data, and numerical flow and transport models. The hydraulic head data show patterns that are consistent with pumping on a dual-screened well, however, many of the observed changes are smaller than expected. In situ thermal perturbation flow sensors successfully measured horizontal flow, but vertical flow could not be determined with sufficient accuracy to be useful in mapping flow patterns. Two types of chemical tracer tests were utilized at the site and showed that much of the flow occurs within a few meters of the GCW. Flow patterns were also assessed based on changes in contaminant (trichloroethylene, TCE) concentrations over time. The TCE data clearly showed treated water moving away from the GCW at shallow and intermediate depths, but the circulation of that water back to the well, except very close to the well, was less clear. Detailed vertical and horizontal hydraulic conductivities were measured on 0.3 m-long sections from a continuous core from the GCW installation borehole. The measured vertical and horizontal hydraulic conductivity data were used to construct numerical flow and transport models, the results of which were compared to the head, velocity and concentration data. Taken together, the field data and modeling present a fairly consistent picture of flow and transport around the GCW. However, the time and expense associated with conducting all of those tests would be prohibitive for most sites. As a consequence, a sequential protocol for GCW characterization is presented here in which the number of tools used can be adjusted to meet the needs of individual sites. While not perfect, we believe that this approach represents the most efficient means for evaluating GCW performance.     

A Numerical Model Simulating the Remediation of Hydrocarbon-Impacted Soils Using Low-Temperature Oxidation

A 2-D mathematical model to simulate the temperature distribution, coke formation, and change in residual extractable oil during remediation by low-temperature oxidation (LTO) process was developed. Simulation results indicate that the spacing between wells, pressure difference, and air-injection temperature and different well patterns influence the temperature distribution and consequently the level of remediation in the soil. The model results for coke formation and residual extractable oil distribution compared well with experimental results. The operating conditions—air-injection temperature of about 200°C, air-injection pressure of 6 to 10 kPa, air-extraction pressure of −110 Pa, and wells spaced 1 m apart installed in a nine-spot pattern—provide good remediation of hydrocarbons in soil by LTO process.

Impact of Climate Change on Ecological Quality Indicators and Biogeochemical Fluxes in the Baltic Sea: A Multi-Model Ensemble Study

Multi-model ensemble simulations using three coupled physical-biogeochemical models were performed to calculate the combined impact of projected future climate change and plausible nutrient load changes on biogeochemical cycles in the Baltic Sea. Climate projections for 1961-2099 were combined with four nutrient load scenarios ranging from a pessimistic business-as-usual to a more optimistic case following the Helsinki Commission's (HELCOM) Baltic Sea Action Plan (BSAP). The model results suggest that in a future climate, water quality, characterized by ecological quality indicators like winter nutrient, summer bottom oxygen, and annual mean phytoplankton concentrations as well as annual mean Secchi depth (water transparency), will be deteriorated compared to present conditions. In case of nutrient load reductions required by the BSAP, water quality is only slightly improved. Based on the analysis of biogeochemical fluxes, we find that in warmer and more anoxic waters, internal feedbacks could be reinforced. Increased phosphorus fluxes out of the sediments, reduced denitrification efficiency and increased nitrogen fixation may partly counteract nutrient load abatement strategies.