Formulation of a non-linear framework for population balance modeling of batch grinding: Beyond first-order kinetics

Population balance models (PBMs) for batch grinding are based on the concepts of specific breakage rate and breakage distribution. In the traditional PBMs, the breakage rate is assumed first-order, thus neglecting the effects of the temporally evolving material properties and multi-particle interactions. As an attempt to explain some of the above effects, a time-dependent specific breakage rate was introduced in the literature. The time-variant PBMs are inadequate to explain the multi-particle interactions explicitly and thoroughly. In this paper, we formulate a non-linear population balance framework to explain the non-first-order breakage rates that originate from multi-particle interactions. Based on this framework, four size-discrete non-linear models with varying complexity have been derived. A simple non-linear model with non-uniform kinetics assumption, Model B, was used to simulate the slowing-down phenomenon commonly observed in dry grinding processes. Not only does the model explain the effects of the fines accumulation on the specific breakage rate of the coarse, but also it is capable of predicting the significant influence of the initial population density. Identification of the proposed models, i.e., the solution of the inverse problem is also discussed.     

Population balance modeling of non-linear effects in milling processes

Specific breakage rate (selection) and breakage distribution functions are used to describe the birth and death terms in population balance models (PBMs) for milling processes. Traditional PBMs for milling processes are inherently linear because the breakage rate is assumed first-order. The specific breakage rate is independent of the population density while it depends on particle size and possibly on time. Even though the linear theory has been applied with some success to the modeling, optimization, and design of various mills in the last 50 years, many researchers have indicated its restrictions and subjected it to serious criticism. In this paper, we first categorize the experimentally observed deviations from the linear theory and suggest the multi-particle interactions as the origin of these deviations. To account for the peculiar non-linear effects, a phenomenological theory has been proposed via multiplicative decomposition of the specific breakage into a size-dependent apparent breakage rate and a population density dependent functional. The proposed theory recovers the first-order breakage kinetics in the limit, yet it is sufficiently general to explain all experimentally observed deviations. Numerical simulations of a batch milling process have demonstrated the potential of the non-linear theory.     

A combined tracer and back-calculation method for determining particulate breakage functions in ball milling.: Part III. Simulation of an open-circuit continuous milling system

The combined tracer and backcalculation method for determining particulate breakage parameters described in Part I of this paper and applied to batch ball milling in Part II is extended here to the open-circuit continuous ball milling of martite iron ore. Breakage parameters are determined by this method in the continuous ball mill in the batch mode of operation. Residence time distributions are obtained in the continuous mode of operation with radioactive tracers. Segregated flow, models based on the dispersion model and the tanks-in-series model are given for use with the breakage parameter and residence time distribution data to predict product weight—size distributions. A particular model based on three perfectly mixed tanks in series is used to describe a mill with entrance and exit trunnions and is compared to both transient and steady-state experimental results. The comparison indicates that this method of simulation will be useful.     

Use of cumulative size distribution to back-calculate the breakage parameters in batch grinding

A new ‘back-calculation’ method of predicting the breakage and selection parameters has been developed using the solution of the cumulative batch grinding equation. As opposed to using the differential mass-size balance, the cumulative form inherently absorbs the noise present in individual mass fraction data. The estimation procedure renders a definite advantage due to the minimum occurrence of accumulation of the round-off error.     

Analysis of nonlinear batch grinding in stirred media mills using self-similarity solution

Generally, particle breakage rate is considered to be independent of the grinding environment, and hence, the system is referred to as a linear time-invariant grinding system with first-order grinding kinetics. However, time-dependent breakage rate exists and perhaps, is more critical for fine grinding of particles. The time-dependent breakage rate also introduces nonlinearity in the grinding phenomena. In the present work, a self-similarity based approach is described to model the evolution of fine particle size distributions in a batch stirred media milling with an emphasis on the nonlinear breakage rate function by considering the breakage rate to be a function of the grind time. The present approach yields analytical expressions for cumulative weight percent finer distributions for the continuous-size continuous-time population balance equation. The breakage parameters in the analytical solution can be estimated for a given system from any three measured size distributions that show self-similarity and these parameters can be used to predict distributions evolving at higher grind times. Several sets of published data of stirred media milling are employed to validate the model.     

Emergence of falsified kinetics as a consequence of multi-particle interactions in dense-phase comminution processes

Particle breakage during dense-phase comminution processes is significantly affected by mechanical multi-particle interactions, which are neglected in traditional discrete linear population model (DL-PBM). A discrete non-linear PBM (DNL-PBM) has been recently proposed to account for multi-particle interactions; however, the inverse problem, i.e., the estimation of the model parameters, has not been addressed. In this paper, a method for the estimation of DNL-PBM parameters is presented with a purpose of determining the consequences of neglecting multi-particle interactions in the traditional DL-PBM. The model parameters were obtained from a constrained, non-linear, least-squares minimization of the residuals between comminution data and discrete PBM prediction. Comminution data exhibiting multi-particle interactions were obtained from a DNL-PBM simulation followed by addition of 0%, 10%, and 20% random error. A comprehensive statistical analysis of the goodness of fit and certainty of the parameters was performed to discriminate the models. Using the estimated parameters, predictive capability of both models was further assessed by comparing their prediction with additional computer-generated data obtained with a different feed particle size distribution. The parameter estimation method was shown to be highly accurate and robust. DNL-PBM can predict the influence of different feed conditions better than DL-PBM when multi-particle interactions are significant. This study has demonstrated that neglecting multi-particle interactions in dense-phase comminution processes via the use of DL-PBM can lead to falsified kinetics with erroneous breakage functions.     

Energy and population balances in comminution process modelling based on the informational entropy

The results of theoretical and experimental studies of a comminution process are presented. There are two random functions: the selection function and the breakage function in the stochastic model based on a population balance. This model enables prediction of particle size distributions of comminution products after determination of both random functions. Maximum entropy method is used in the entropy model for determining the breakage function. Two cases are analysed, based on continuous and discrete particle size distribution functions of the fed material. Apart from mass balance, the energy balance of comminution process is also used. Searched form of breakage function is determined with the application of methodology of calculus of variations. The results of experimental identification of both models are presented. The parameters that occur in the discrete form of the selection and breakage functions were the identification objects. The results of experimental investigations of quartz sand single comminution in a laboratory jet mill provided an identification base. The experimentally identified results of the entropy model confirmed the adequacy of the theoretical analysis and demonstrated the possibility of adequate prediction of particle size distributions resulting from single comminution.     

Nano-milling of pigment agglomerates using a wet stirred media mill: Elucidation of the kinetics and breakage mechanisms

The present study concerns the production of pigment nanoparticles in a wet-batch stirred media mill with polymeric media. The breakage kinetics and mechanisms were investigated using size-discrete population balance models (PBMs). The temporal variation of the particle size distribution was measured via dynamic light scattering. Considering the G-H model, a time-invariant PBM, and a time-variant PBM, the specific breakage rate parameters and breakage distribution parameters were identified. It is found that the breakage rate is not first-order and that a delay time exists for the breakage of nanoparticles. The time-variant PBM captures all these features and suggests a transition from deagglomeration of agglomerates to the breakage of primary particles. The analysis of the breakage distribution parameters suggests splitting as the dominant mechanism as opposed to attrition or massive fracture.     

MSMPR反应结晶器中地塞米松磷酸钠晶体生长模型的研究

The reactive crystallization process of dexamethasone sodium phosphate was investigated in a continuous mixed-suspension, mixed-product-removal(MSMPR) crystallizer. Analyzing experimental data, it was found that the growth of product crystal was size-dependent. The Bransom, CR, ASL, M J2 and M J3 size-dependent growth models were discussed in details. Using experimental steady state population density data of dexamethasone sodium phosphate, parameters of five size-dependent growth models were determined by the method of non-linear least-squares. By comparison of experimental population density and linear growth rate data with those obtained from the five size-dependent growth models, it was found that the MJ3 model predicts the growth more accurately than do the other four models. Based on the theory of population balance, the crystal nucleation and growth rate equations of dexamethasone sodium phosphate were determined by non-linear regression method. The effects of different operation parameters such as supersaturation, magma density and temperature on the quality of product crystal were also discussed, and the optimal operation conditions were derived.     

Numerical Simulation of Open‐Circuit Continuous Mills Using a Non‐Linear Population Balance Framework: Incorporation of Non‐First‐Order Effects

Population balance modeling has been used as a tool for simulating, optimizing, and designing various particulate processes, including milling. A fundamental tenet of the traditional models for milling processes is the first‐order breakage kinetics. Ample data obtained from batch milling studies show that this assumption is not necessarily valid for certain milling systems. In the present theoretical investigation, an attempt has been made to incorporate these experimentally observed non‐first‐order effects into continuous mill models within the context of a novel non‐linear population balance framework. In view of two idealized flow regimes, i.e., perfect mixing and plug‐flow, continuous mills operating in the open‐circuit mode are numerically simulated. The simulations indicate that not only does the product size distribution depend on the degree of mixedness in a continuous mill, but also on the non‐first‐order effects arising from multi‐particle interactions.     

Experimental studies and population balance equation models for breakage prediction of emulsion drop size distributions

A population balance equation (PBE) model for pure drop breakage processes was developed from homogenization experiments and used to investigate model extensibility over a range of emulsion formulation and homogenizer operating variables. Adjustable parameters in the mechanistic breakage functions were estimated from measured drop volume distributions by constrained nonlinear least-squares optimization. Satisfactory prediction of measured bimodal distributions was achieved by the incorporation of two different breakage functions that accounted for large drop breakage due to turbulent shear and for small drop breakage due to collisions between drops and turbulent eddies. Model extensibility to different emulsion compositions and homogenizer pressures was investigated by comparing model predictions generated with the base case parameters to drop volume distributions measured under different conditions. The PBE model satisfactorily accounted for changes in the dispersed phase volume fraction and the interfacial tension with the base case parameters. By contrast, significantly improved predictions for the continuous phase viscosity or multiple formulation variables were obtained through re-estimation of the model parameters using multiple data sets in which the associated variables were systematically varied. The model was not able to satisfactorily predict drop volume distributions resulting from homogenizer pressure changes, perhaps due to the assumption of a constant pressure throughout the homogenizer. We conclude that PBE models of drop breakage can be used to reasonably predict the effects of emulsion formulation variables on drop volume distributions and have the potential for guiding experimental efforts aimed at the design of novel emulsified products.     

A rigorous breakage matrix methodology for characterization of multi-particle interactions in dense-phase particle breakage

Broadbent and Calcott's breakage matrix methodology has been used for more than 50 years to model various comminution processes and to determine breakage functions from experimental data. The methodology assumes first-order law of breakage and neglects mechanical multi-particle interactions that are especially prevalent in dense-phase comminution processes and breakage tests. Although several researchers severely criticized this aspect of the methodology, Baxter et al. (2004, Powder Technol. 143–144:174–178) were the first to modify the methodology toward determining the elements of a feed-dependent breakage matrix. However, no non-linear breakage matrix has ever been constructed from experimental data using the modified approach. In this study, a critical analysis of this modified approach has been performed, and the non-linear breakage matrix was fundamentally derived from a non-linear population balance model. Different approaches were proposed to identify the breakage functions based on the nature of available breakage tests on multiple mono-dispersed feed samples and at least one poly-dispersed sample. Using the derived equations, available experimental data on the breakage of a binary mixture of coarse and fine limestone particles in uniaxial compression test were fitted to quantify the multi-particle interactions. Superior fitting capability of rational approximation to the effectiveness factor was demonstrated.     

Population balance modeling of bubble size distributions in a direct-contact evaporator using a sparger model

The study of bubble size distributions in direct-contact evaporators was addressed both theoretically and experimentally. Recently developed models for calculating bubble coalescence and breakage frequencies in isothermal bubble columns were adapted to the population balance equation using the bubble mass as the internal coordinate which was discretized using an expansion of the number density function by impulse functions. A sparger model was developed based on experimental data for a non-coalescing system and using bubble formation models for isothermal and non-isothermal conditions. Bubble size distributions in a direct-contact evaporator operating in the quasi-steady-state regime for four different gas superficial velocities, including the homogeneous and heterogeneous regimes, together with the sparger model, were used for estimating the three empirical parameters from the population balance model, which were observed to be functions of the gas superficial velocity. In all cases considered, the population balance model fitted the experimental data rather well and the regressed parameters exhibit the physically expected behavior with changes in the gas superficial velocity.     

The back-calculation of specific rates of breakage from continuous mill data

Computer programs for back-calculation of specific rates of breakage S_i from continuous mill data, or batch grinding data, are described. A series of statistical tests to determine the statistically acceptable ranges of values are presented. The most reliable test uses independent estimates of error variance calculated from replicated data. It is shown that the interval-by-interval method of calculating S_i values is especially subject to errors in the top sizes. Back-calculation methods which use only the circuit product in the calculation give different ranges of statistically acceptable values than those which use all the size distributions round the circuit. The statistically acceptable ranges of values from using only the circuit product often do not include the values determined by direct laboratory investigation, and tend to be wider than the ranges given by using all the size distributions; thus, using only circuit product is a non-preferred method. The use of a fully-mixed residence time distribution (RTD) instead of a true RTD leads to radically incorrect values, which cannot be detected by statistical analysis except in the presence of unrealistically low experimental error. It must be realized that a set of breakage parameters which reproduce the data used in their back-calculation with good accuracy are not necessarily real, and statistical analysis is essential to define the statistically acceptable ranges of the parameters.     

Population balance modelling of protein precipitates exhibiting turbulent flow through a circular pipe

The breakage of liquid-liquid, solid-liquid and solid-gas dispersions occurs in many industrial processes during the transport of particulate materials. In this work, breakage of whey protein precipitates passing through a capillary pipe is examined and an experimentally derived breakage frequency is applied to construct a suitable population balance model to characterize the breakage process. It has been shown that the breakage frequency of precipitate particles is highly dependent on their shear history and on the turbulent energy dissipation rate in the pipe. The population balance equation (PBE) uses a volume density based discrete method which is adapted from mass density based discretization. In addition to comparing the model with experimental data, predicted results at different velocities are presented. It was found that the population balance breakage model provides satisfactory results in terms of predicting particle size distributions for such processes.     

Population balance modelling of activated sludge flocculation: Investigating the size dependence of aggregation, breakage and collision efficiency

This paper describes the application of population balance models to activated sludge flocculation. It presents the development and selection of appropriate expressions for aggregation and breakage mechanisms within the population balance framework to describe the evolution of mean size and mass distribution of flocs under shear-induced conditions. To describe the flocculation process, 16 models with different size dependent aggregation and breakage expressions were compared and the kinetic parameters of aggregation rate constant and selection rate constant were extracted by fitting each model to the experimental data. Of the 16 models, the shear-induced aggregation and size-dependent selection model was found to best describe the experimental data, however there were some discrepancies between the model and experimental results at long experimental times. A size dependent collision efficiency was introduced into the aggregation expression and this improved the fitting of the model with the experimental data. However, the relationship between the kinetic parameters and shear rate did not follow expected physical relationships. Further improvements to the model were made by setting the aggregation rate constant proportional to shear rate and the selection rate size independent whilst still including the size-dependent collision efficiency. The aggregation rate constant, selection rate constant and critical size were extracted by fitting the model to the experimental data. This model was able to follow the change in mean size and evolution of mass and was used to predict other experimental data successfully. The modelling results indicated that the population balance model is a useful tool to describe the dynamics of activated sludge flocculation.     

Dynamic modeling of a batch crystallization process: A stochastic approach for agglomeration and attrition process

This paper deals with the dynamic modeling of a batch crystallizer. A complete model taking into account primary and secondary nucleations, crystal growth, agglomeration and attrition mechanisms is established. The proposed model is not restricted to binary agglomeration and breakage phenomena. From markovian considerations, continuous kernel functions are built and the basic balance equations are then presented. The complete model is solved using a finite difference method for the discretization of the size variable. As to distinguish agglomeration and breakage parameters from the others, on line measurement of the Crystal Size Distribution is necessary, a new on line measurement strategy is proposed. Finally, simulations of the crystal size distribution are compared with experimental results at different times. It appears that simulated curves are in good agreement with the experimental data.