Prediction Of Release Rate Research Articles

A numerical investigation on combustion and emission characteristics of a dual fuel engine at part load condition

Dual fuel engines are more attractive due to lower emission levels in comparison with conventional diesel engines particularly at full loads. But it is required to study dual fuel combustion process with more details at part loads due to the poor performance and high CO and UHC emissions at these conditions. In the present study, numerical modeling of OM-355 dual fuel (injection of diesel pilot fuel to premixed mixture of air and methane) engine has been performed by using KIVA-3V code at part and full loads. Sub-models of the code were modified to simulate the fuel spray atomization, combustion and pollutants emissions processes, accurately. Results indicate that in-cylinder pressure, heat release rate and exhaust emissions predictions are in good agreement with experiments at all loads. Results show that a lean premixed natural gas mixture is ignited slowly. The slow progress of combustion process at part load, leads the heat release to be drawn more toward the expansion stroke which causes incomplete combustion, and consequently high amounts of UHC and CO will be emitted. It is found that at part loads, areas that are influenced by diesel diffusion flames are ignited and premixed natural gas flame could not be propagated properly. Hence development of diesel diffusion flame is required to burn lean natural gas mixture. But at full load, in addition to the diesel diffusion flames, premixed natural gas flame could be propagated suitably. Also, at part load because of low gas temperature in the environment of diesel spray and low diesel fuel temperature, diesel liquid droplets evaporate lately which are far from injector nozzles. Hence, it causes diesel diffusion flame from spray of each injector nozzles to be developed distinctly. It can be deduced that the flame structure is affected by operating conditions. Finally the effect of increasing the diesel fuel quantity on improving methane combustion is studied. The studied strategy could help to improving natural gas combustion due to enlarge the size of diesel combustion region.

Numerical modeling on a diesel engine fueled by biodiesel–methanol blends

A modeling study was conducted to investigate the impact of methanol addition on the performance, combustion and emission characteristics of a diesel engine fueled by biodiesel. 3-D CFD simulations were conducted using the KIVA4 code coupled with CHEMKIN II for neat biodiesel and its blend fuels with 5%, 10% and 15% (in vol.) of methanol under 10%, 50% and 100% loads and a fixed engine speed of 2400rpm conditions. A skeletal reaction mechanism was developed to mimic the significant species and reaction pathways of biodiesel and methanol fuels, and it was validated by performing the ignition delay calculations for biodiesel and methanol, as well as 3D numerical simulations against the experimental results for biodiesel. Good agreements in terms of ignition delay, cylinder pressure and heat release rate predictions were obtained. The simulation results revealed that with partial replacement of biodiesel by methanol, tangible improvement on the cylinder pressure was observed under 10% load condition especially for the case with 5% methanol blend ratio. Whereas, under 50% and 100% engine load conditions, only comparable cylinder pressure curves were seen. In terms of performance characteristics, almost linearly increased indicated thermal efficiency with respect to methanol blend ratio were observed under all the engine load conditions. Overall, the indicated CO and soot emissions decreased.

Computational fluid dynamics modeling of combustion in heavy-duty diesel engines

The design and optimization stages of combustion systems for modern heavy-duty diesel engines must be supported by reliable computational fluid dynamics tools for the definition of the chamber geometry and injection strategy. To be fully predictive in terms of in-cylinder thermodynamics and flame structure, the employed combustion models must account for complex chemistry and turbulence–kinetics interactions. Within this context, the authors have implemented into an open-source code a model based on the multiple representative interactive flamelets approach and applied it to diesel combustion simulations. New numerical techniques were integrated in the proposed multiple representative interactive flamelets model in order to speed up the central processing unit time in integrating chemistry and the β-probability density function of the chemical species to compute composition in the computational fluid dynamics domain. A parallel validation was performed both with constant-volume and heavy-duty diesel engine experiments, selecting similar operating conditions. In such way, both flame structure and heat release rate predictions are analyzed and the model capabilities with respect to its setup and mesh structure are assessed.

Affinity-based drug delivery systems for tissue repair and regeneration.

Affinity-based release systems use transient interactions to sustain and control the release of a therapeutic from a polymeric matrix. The most common affinity-based systems use heparin-based scaffolds to sustain the release of heparin-binding proteins, such as fibroblast growth factor-2 (FGF2) and vascular endothelial growth factor (VEGF). However, novel affinity-based systems based on, for example, protein-protein or DNA-protein interactions, are emerging to control the release of an expanding repertoire of therapeutics. Mathematical models of affinity-based systems have provided a thorough understanding of which parameters affect release rate from these systems, and how these release rates can be tuned. In this review, recent affinity-based release systems will be described, including an overview of the various types of affinity interactions used to modulate release, the mechanisms by which release from these systems is tuned, and the time scales of sustained release. This advanced drug delivery paradigm provides tunable and predictable release rates and has expanded the scope of deliverable therapeutics for tissue repair and regeneration.

Enhanced heat release analysis for advanced multi-mode combustion engine experiments

Advanced combustion strategies, such as Homogeneous-Charge Compression-Ignition (HCCI) and Spark-Assisted HCCI or Spark-Assisted Compression-Ignition (SACI) hold considerable promise for improving engine efficiencies while maintaining low pollutant emissions, yet few models exist that accurately include the important chemical and physical mechanisms of these advanced combustion strategies. Further, experimental data from advanced combustion engine experiments are not well represented using conventional spark ignited analytical tools. This paper presents new methods for advanced combustion analysis that integrate previous analytical methods with new algorithms to capture the unique features of advanced combustion strategies like SACI.The new analytical capabilities were incorporated into a program which was designated the Advanced Combustion Engine Heat Release Analysis (ACE-HRA) tool. The models developed and applied in ACE-HRA were assessed by comparison with high fidelity engine simulations of HCCI and SACI. The high fidelity simulations provided data sets with detailed predictions of heat release rates, temperatures, auto-ignition timing, flame speeds and other key parameters not resolved or measured in engine experiments. The sensitivity of ACE-HRA estimates to model input data was quantified for important engine performance parameters. The sensitivity analysis showed that estimates for in-cylinder masses have the largest overall impact on the ACE-HRA results (e.g. ±10% variation led to changes on the order of ±5–10% in peak rate of heat release, burn duration and peak temperature). Noticeable differences in peak heat release rate and ringing intensity were also observed when comparing cycle-by-cycle analysis against ensemble-average analysis, which has implications on how the results are interpreted and applied in modeling work.After validating ACE-HRA with the high-fidelity simulations, ACE-HRA was applied to interpret the data from a recent experimental study of SACI combustion. The ACE-HRA methods were used to infer the effects of flame propagation on in-cylinder gradients and cycle-to-cycle variability, and to provide quantitative estimates for the associated changes in the end-gas burn rate. The trends observed, such as the decrease in burn rate for later auto-ignition and higher burn fraction by flame, provide more in-depth understanding of SACI combustion and demonstrate the insight that can be revealed by the new ACE-HRA tool.

Soot and NOx Modeling

This paper presents an advanced version of the original software developed by the author in order to simulate the combustion in the Diesel engines, focusing on simulate soot and NOx formation. Complex kinetic mechanisms are need for realistic modeling. A model derived by systematic reduction of multi-step chemistry is used. This reduction is based on the partial equilibrium assumption of the considered elementary reactions using the skeletal chemistry for n-decan for ignition, combustion and emissions. Subsequently, predictions of heat release rate, as well as NO and soot emissions are compared with experimental data. However, additional effort is required to enhance the fidelity of NO and soot predictions across a wide range

Effects of variations in incident heat flux when using cone calorimeter test data for prediction of full‐scale heat release rates of polyurethane foam

SummaryThe development of methods to predict full‐scale fire behaviour using small‐scale test data is of great interest to the fire community. This study evaluated the ability of one model, originally developed during the European Combustion Behaviour of Upholstered Furniture (CBUF) project, to predict heat release rates. Polyurethane foam specimens were tested in the furniture calorimeter using both centre and edge ignition locations. Input data were obtained using cone calorimeter tests and infrared video‐based flame area measurements. Two particular issues were investigated: how variations in incident heat flux in cone calorimeter tests impact heat release rate predictions, and the ability of the model to predict results for different foam thicknesses. Heat release rate predictions showed good agreement with experimental results, particularly during the growth phase of the fire. The model was more successful in predicting results for edge ignition tests than for centre ignition tests and in predicting results for thinner foams. Results indicated that because of sensitivity of the burning behaviour to foam specimen geometry and ignition location, a single incident heat flux could not be specified for generating input for the CBUF model. Potential methods to determine appropriate cone calorimeter input for various geometries and ignition locations are discussed. Copyright © 2014 John Wiley & Sons, Ltd.

Nanostructured biocompatible thermal/electrical stimuli-responsive biopolymer-doped polypyrrole for controlled release of chlorpromazine: Kinetics studies

Biocompatible nanostructured conductive heparin-doped polypyrrole film was fabricated and employed as a high-capacity cation exchanger for programmable release of neuroleptic drug, chlorpromazine (CPZ) with thermally and electrical dual-stimulation. Releasing behavior were studied at different applied potentials and temperatures by in-situ monitoring of UV absorbance measurements. Three mathematical models (Higuchi, Power, and Avrami equation) were employed to investigate kinetics of the release. Based on the obtained results, the Avrami model found to be more comprehensive than two other ones for mathematical description of electro-stimulated release of CPZ. A quantitative relationship between activation energy parameters (Ea, ΔG≠, ΔH≠, and ΔS≠) and release conditions (applied potential and temperature) has been developed and established to predict release rate constants at various applied conditions.

Numerical investigation on the combustion and emission characteristics of a hydrogen assisted biodiesel combustion in a diesel engine

The present study aims to bridge the gap on hydrogen assisted biodiesel combustion, and to investigate its impacts on the engine performance, combustion and emission characteristics. Simulations were conducted on a diesel engine fueled by biodiesel with supplementary hydrogen inductions of 0.5%, 1%, 2% and 3% vol of H2 in air. A skeletal reaction mechanism was developed to include the reaction kinetics of biodiesel and hydrogen, with the CO, NOx and soot formation mechanisms embedded. The developed reaction mechanism was validated by performing the ignition delay calculations against the detailed biodiesel reaction mechanism, as well as the 3D numerical simulations against the experimental results. Good agreements in terms of ignition delay, cylinder pressure and heat release rate predictions were obtained. Key simulation results review that with the increase of hydrogen induction, a substantial increase in the peak cylinder pressure and heat release rate can be obtained under 50% and 100% load conditions, indicating an improved performance. But a reduced performance is observed at light load (10% loads) conditions due to the poor ignition and combustion processes. In terms of emissions, a general decreased trend is observed for both CO and soot emissions at all the engine speeds and loads, and a more remarkable reduction is found at 100% engine load conditions. Furthermore, due to the enhanced combustion, NOx emissions are increased slightly at 50% and 100% engine loads.

What controls the variability of wood-decay rates?

Decaying wood provides essential habitats for forest biota, and its CO2 return to the atmosphere is comparable to that from fossil-fuel combustion. Decomposition rates for wood debris (WD) from three tree species were measured by CO2 release in a subtropical forest over two years. Wood temperature and moisture were measured along with CO2, and each WD piece (n=320) was characterized by its initial weight, density, volume, surface area, and decay class. For individual pieces of WD in each wood-species and decay-class group, predictions of release rates based on temperature and moisture together had R2 values ranging from 0.25 to 0.57, predictions based on moisture alone had R2 values ranging from 0.16 to 0.35, and R2 values from 0.07 to 0.35 were seen in temperature-only predictions. Wood density and surface area were negatively related to CO2 release rates (R2=0.10 and 0.04 respectively, over all groups). We also used daily meteorological measurements to predict WD temperature and moisture. Average air temperatures predicted WD temperatures with R2 values above 0.7 over 35days, but total rainfall was a very weak predictor of WD moisture over any interval. We used temperature – decay relationships to estimate annual total CO2 release from WD groups, and found that their average exponential decomposition rate (K) was 0.09year−1. Based on density loss, most WD in the studied forest would be in the late stage of decay, in contrast to some previous studies. Our results support previous studies on the importance of environmental factors in determining WD decomposition, but with only half of the variation explained, we are challenged to explain the rest. Aggressive interactions are common among WD decomposers, and previous work with simplified microbial communities suggests that high diversity leads to slower decomposition. Uncertain predictions for WD decomposition rates, and their global C- cycle implications, will persist until interactions of WD microbial communities are better understood.

An accelerated multi-zone model for engine cycle simulation of homogeneous charge compression ignition combustion

We have developed an accelerated multi-zone model for engine cycle simulation (AMECS) of homogeneous charge compression ignition (HCCI) combustion. This model incorporates chemical kinetics and is intended for use in system-level simulation software. A novel methodology to capture thermal stratification in the multi-zone model is proposed. The methodology calculates thermal stratification inside the cylinder based on a single computational fluid dynamics (CFD) calculation for motored conditions. CFD results are used for tuning zone heat loss multipliers that characterize wall heat loss from each individual engine zone based on the assumption that these heat loss multipliers can then be used at operating conditions different from those used in the single CFD run because the functional form of thermal stratification is more dependent on engine geometry than on operating conditions. The model is benchmarked against detailed CFD calculations and fully coupled HCCI CFD chemical kinetics calculations. The results indicate that the heat loss multiplier approach accurately predicts thermal stratification during the compression stroke and (therefore) HCCI combustion. The AMECS model with the thermal stratification methodology and reduced gasoline chemical kinetics shows good agreement with boosted gasoline HCCI experiments over a range of operating conditions, in terms of in-cylinder pressure and heat release rate predictions. The computational advantage of this method derives from the need for only a single motoring CFD run for a given engine, which makes the method very well suited for rapid HCCI calculations in system-level codes such as GT-Power, where it is often desirable to evaluate consecutive engine cycles.

Influence of thermophysical properties on burning behavior of intumescent fire-retardant materials

Thermophysical properties of intumescent fire-retardant (IFR) materials are important parameters as input data in modeling the combustion process of IFR materials in a fire. In this paper, the influences of several thermophysical properties on burning behavior of IFR materials are simulated based on a combustion model of IFR materials. Thermophysical properties selected here are thermal conductivity of virgin material and char layer, specific heat capacity of virgin material, density of virgin material, surface emissivity of virgin material and char layer, heat of decomposition, heat of combustion, and intumescent temperature. Predicted heat release rates curves for the IFR material at an incident heat flux of 50 kW m−2 are shown for the varied thermophysical parameters’ values. The results show that these varied parameter values can affect the burning behavior of materials remarkably. A comparison with experimental results demonstrates that the predictions of heat release rates are in reasonably good agreement with the experiment.

Effect of different polymers and their combinations on the release of metoclopramide HCl from sustained-release hydrophilic matrix tablets

Metoclopramide HCl (MTC) is commonly used for the management of gastrointestinal disorders. It has a short biological half-life and is usually administered four times daily to maintain effective concentrations throughout the day. The aim of this study is to develop sustained-release hydrophilic matrix tablet formulations of drug to achieve reproducible and predictable release rates, extended duration of activity, decreased toxicity, reduction of required dose, optimized therapy, and improved patient compliance. Hydroxypropylmethyl cellulose (HPMC), carboxymethylcellulose sodium (NaCMC), chitosan and Carbopol 981 were incorporated in the matrix system separately or in combinations as release controlling factor by direct compression technique. Compatibility among the formulation components was assessed by DSC and FTIR analysis. MTC release from matrix was evaluated by using the US Pharmacopeia dissolution apparatus II. All formulations met the criteria of pharmacopeial requirements. Dissolution studies show that polymer type and concentration are important parameters on drug release. Chitosan, carbopol and NaCMC formulations exhibited pH-dependent drug release profile whereas HPMC did not. All the formulations containing 1:1 ratio of HPMC and chitosan exhibited desired drug release showing that all active substance releases progressively in a period of whole dissolution time and therefore it can be regarded as worthy of consideration for the manufacture of sustained-release MTC product.

Methodology for selecting hole sizes for consequence studies

Predicting release rates is the first step, and a crucial step, in consequence analysis. When the release is from an isolated volume of vessel and/or piping, the release rate decreases with time. There is often debate about what equivalent hole sizes should be used for a consequence study, and usually a range of hole sizes (3–4 values) is examined.This paper shows the effect of hole size on the ultimate impact of hydrocarbon releases for several scenarios and the methodology to select them. The impact depends on the intensity and exposure time. The intensity for a fire is the thermal radiation level, and that for an unignited release is the gas concentration. As the release rate decreases with time, so does the intensity. Probit functions describe the probability of a given impact based on the time-varying intensity. For a number of example scenarios, the predictions show that the worst-case hole size is an intermediate hole size, i.e., the impact goes through a maximum with increasing hole size. For smaller holes, the event is small enough that its impact is low even though the duration is long. For larger holes, the initial event is large but decreases so rapidly that the impact is low. For the intermediate hole, the event is large enough, and the duration long enough, to cause the greatest impact.This consequence study was made evaluating hole sizes with diameters between 5 and 400 mm in a fixed volume upstream process vessel. Worst case scenario consequence predictions for fire damages, effects on people and toxic releases were determined to be somewhat different for different hole sizes. However, hole sizes in the 30 mm–90 mm range seems to have the highest impact in dry gas service.

An improved two-layer zone model applicable to both pre- and post-flashover fires

The present paper proposes a sub-model for two-layer zone models to describe heat and mass transfer across the interface between the upper and lower layers as a result of the temperature difference between the two layers. The sub-model is integrated into a two-layer zone fire growth and smoke movement model, which now can predict both pre- and post-flashover fires. The comparison of the numerical predictions of the improved model and experimental data shows that the improved model produces better temperature and heat release rate predictions for both pre- and post-flashover fires than the previous model. Compared with hybrid models consisting of a two-layer zone model and a single-layer zone model, the improved model has no transitional difficulties in switching from the pre- to the post-flashover state and it produces more reasonable temperature gradients for post-flashover fires.

Evaluating Models for Predicting Full-Scale Fire Behaviour of Polyurethane Foam Using Cone Calorimeter Data

Two models that can be used to predict full-scale heat release rates of polyurethane foam slabs were evaluated in this study. Predictions were compared with results of furniture calorimeter tests of 10 cm thick polyurethane foam specimens which were ignited in the centre or on the edge. Furniture calorimeter results indicated that peak heat release rates and fire growth rates were higher during centre ignition tests than edge ignition tests. For both situations, the growth phase of the heat release rate curves measured in the full-scale tests was successfully predicted using t2 design fires; the choice of a specific t2 fire depended on the surface area of the specimen and ignition location. A model originally developed during the European Combustion Behaviour of Upholstered Furniture (CBUF) project was also evaluated using heat release rate data from cone calorimeter tests and flame area burning rates measured using infrared video records of the furniture calorimeter tests. This model was able to successfully predict the initial growth phase of the fires and predictions of peak heat release rates were within 17% of measured values. The model had less success in predicting heat release rates later in the growth phase and during the decay phase of the fires, and did not appear to capture all of the physics of the full-scale tests, in particular foam melting and subsequent liquid pool burning. As the model did show promise, future work is planned to address these shortcomings and to develop improved flame spread models for polyurethane foam.

A Mathematical Model for Predicting Release Rate from Multiple Emulsions and Micro/Nanospheres

AbstractThis paper presents mass transfer models of the release process from hierarchical dispersed systems such as multiple emulsions and micro/nanospheres. The models were validated by experimental data of an active component released from multiple emulsions and microspheres obtained via multiple emulsion thermal cross‐linking. The simulations of release profiles confirmed the importance of the internal structure of multiple emulsions/microspheres, as well as the intensity of external mixing in the modeling of the controlled release process. The models presented allowed the mass released to be determined within satisfactory agreement with experimental data after optimization of parameters that describe internal emulsion/microsphere structure. The model proposed for describing the release process from microspheres can simulate release profiles that exhibit phasic behavior (primary/lag and continuous release). The model simulations were extended to nanoscale particles with satisfactory results.

Comparison of FDS predictions by different combustion models with measured data for enclosure fires

The performance of mixture fraction models FDS4 and FDS5 is investigated under different global equivalence ratios (GER). Predictions of heat release rate (HRR), upper-layer temperature, and CO yield are compared with measurements considering their sensitivities to the lower limit of fuel, mixing time scale, and turbulence model constants. When using FDS4, the inclusion of an extinction model can result in significant variations in both total and volumetric HRR prediction. When using FDS5, the mixing model constant has significant effects on volumetric HRR prediction. At low GER (<0.23), the prediction of upper-layer temperature shows dependency on both the lower fuel limit and the mixing model constant, but the predicted temperature is always lower than measured temperature, with deviations in excess of 30%. At higher GER (0.53<GER<0.81), the upper-layer temperature prediction shows significant dependency on the mixing model constant but can be over-predicted, with deviations up to 24%. The variations of CO yield prediction with lower fuel limit or with the mixing model constant show an opposite trend to that of upper-layer temperature. Furthermore, the prediction of CO yield shows a much greater dependency on the Smagorinsky constant and on the turbulent Schmidt number than do those of HRR and upper-layer temperature.

Application of Dynamic Neural Networks and Fuzzy Algorithms in the Modeling of Drug Release

The aim of the presented study is to propose the utilization of dynamic neural networks and fuzzy algorithms as in silico tools for prediction of drug release rate from hydrophilic and lipid matrix tablets.

Modeling Approach To Assess Clustering Impact on Release Rates of Pesticides from Microencapsulated Products

The pesticide release rate from polymer-encapsulated microcapsules is controlled by diffusion across the polymer membrane, membrane thickness, and pesticide loading. However, conditions for microcapsule clustering following conventional application practices and the impact of clustering on the overall release rate are often ignored. Microcapsules are delivered to target surfaces using water droplets as a carrier, and capillary-driven velocities arise within the deposited sessile drop as the water evaporates. This work describes experimental observations and a quasi-static mathematical approach used to elucidate microcapsule clusters that remain following the drop-drying process, along with the anticipated patterns for pesticide release as a function of cluster geometries. The dynamic behavior of a drying sessile drop was modeled as a trajectory of constrained quasi-static equilibrium shapes having a fixed contact line. Observed monolayer clustering of microcapsules was a function of the initial contact angle and size of the sessile drop, evaporation rate, and the microcapsule number density within the drop. The net pesticide release rate from microcapsule clusters was calculated from superposition of smaller decomposed cluster geometries for which release rates were determined by numerical solution to the mass balance governing equation, thereby coupling the self-assembly of microcapsule and microcapsule clustering with environmental release rate predictions.