solids modelling overview

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Overview of Solids Modeling for Chemical Processes

An Industry White Paper

Jennifer Dyment, Product Marketing, Aspen Technology, Inc.Claus Reimers, Product Management, Aspen Technology, Inc.Ron Beck, Product Marketing, Aspen Technology, Inc.


Solids Overview When Modeling Chemical Processes



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Executive SummaryThis paper describes a new and exciting approach for incorporating granular solids and the corresponding solids

processing steps when modeling chemical processes. Modeling the solids section of a process is important for many

common processes including specialty chemicals, agrochemicals, metals and mining, pharmaceuticals, biofuels, and

more. The main challenges that arise when optimizing or troubleshooting a solids process include inefficient designs due

to separate modeling of fluids and solids sections, overdesign of equipment, high-energy demands, reduced yields, and

quality variability.

Opposed to fluids, which are generally described by concentrated properties like vapor fraction, composition, and

temperature and pressure, granular solids are described by distributed properties such as particle size distribution (PSD).

This adds an extra level of complexity to the description of the material and therefore the solids section of a production

process is often neglected or over simplified. Whether particles are being formed (e.g. crystallization, spray drying),

reduced in size (e.g. crushing/grinding), enlarged (e.g. granulation, agglomeration), participating in reactions (e.g.

fluidized bed reactor, fixed bed reactor) or just being separated from a fluid stream (e.g. cyclones, filters, centrifuges),

ignoring or poorly modeling the solids processing steps may lead to lost opportunities, including costs reductions and

quality improvements. Considering this, some companies use in-house models or spreadsheets to describe the solids

section of a process. The drawback of this custom or one-off approach is that the fluid section of the process is modeled

in one simulation environment (e.g. Aspen Plus) while the solids section is modeled in another (e.g. Excel). In general,

this approach may lead to errors and inefficiencies due to data transfer, different stream structures, or inconsistent

physical properties.

With the introduction of aspenONE version 8 in December 2012, Aspen Plus process simulation software provides the

capability to describe granular solids in detail and provides a comprehensive model library for the equipment associated

with solids processing steps. In V8.4, the model library covers drying, fluidizationincluding chemical reactions,

granulation, crystallization, crushing and grinding, classification, solid/liquid and gas/solid separation, as well as

pneumatic conveying of solids. The Aspen Plus user can consequently model processes that contain both fluids and solids

in one simulation environment using consistent physical properties and avoid errors and inefficiencies that may result

from the transfer of data from one simulation system to the other. The unit models offered in the library can range in

fidelity from conceptual to rigorous. Process engineers who are not solids modeling experts can use conceptual models to

design a sketch of the solids section before handing it off to a solids expert for more rigorous design, if needed. Activated

features in Aspen Plus such as Economics, Energy, and Exchanger Design and Rating are available to further optimize

processes that contain solids sections.

Over 100 organizations have embraced AspenTechs innovative solids modeling since its introduction one year ago with

very positive customer reactions. Evonik Industries AG, a leading specialty chemical manufacturer, has strong potential

business benefits from the new capabilities in terms of improved work flow and more detailed modeling. Furthermore,

Aspen Plus enables the user to optimize the entire process and via features such as Activated Economics and Activated

Energy, achieve operating benefits including reduced capital and energy costs and improved throughput and quality.

According to the head of Computer Aided Process Engineering & Automation at Evonik Industries AG, Dr. Hans-Rolf

Lausch states:

Conceptual models are easy to use and enable Evonik's process engineers to describe solids equipment without being solids

experts, allowing them to model and optimize entire processes. Our engineers in the CAPE & Automation department can work

with the particle technology department to make the model more rigorous, leading to better collaboration and more efficient

projects.


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Introduction In addition to fluids, many industrial processes involve solids processing steps that often have a significant influence on

the overall process performance, product quality, or energy demand. In general, the solids section of an industrial process

has to fulfill one or more of the following tasks: formulate particles (e.g. granulation, crystallization), adjust the moisture

content (e.g. drying), change the composition by chemical reactions (e.g. fluidized bed reactor), adjust the particle size

distribution (crushing/grinding, classifying, compacting) and separate solids from fluids (e.g. cyclone, centrifuge). In

developing a process with a solids section that addresses one or more of the mentioned tasks, four main interconnected

challenges typically arise:

Separate design of fluid and solid sections of a process

The influence of the solids section on the overall process performance is often neglected, as described by use of simple

splitter models or by use of spreadsheet tools or in-house codes. Process engineers model the fluid part of a process in a

simulator, such as Aspen Plus, while particle scientists within the same company model the solids part of the process in a

spreadsheet tool, such as Microsoft Excel. In general, this approach may lead to errors and inefficiencies due to data

transfer, different stream structures or inconsistent physical properties. Furthermore, recycle streams from the solids

section to the upstream part of the processa potentially key energy sinkcould only be considered in a very limited way.

An additional limitation is that the optimization of the overall process is more or less impossible by use of this workflow.

Capital costs due to overdesigned equipment

To reduce the risk of bottlenecks, equipment is often designed in excess leading to exaggerated capital costs. Rigorous

modeling can allow for appropriately sized solids processing equipment and reduced recycle streams to minimize the load

of equipment. Examples of solids processing equipment that is often overdesigned include crushers, compactors, and

dryers.

In most cases, one or several recycles are used to reprocess too coarse or too fine particles. Reducing these recycle

streams is the key to reducing the loadings on certain crushers and compactors, allowing for smaller, less expensive

equipment or the opportunity for increased throughput.

Operating costs due to high-energy demands

For many applications, intermediate or final products need to fulfill very tight specifications regarding their moisture

content to be used for subsequent process steps or to be sold as final products. In some cases, liquid and solid separation

is used for the initial dewatering of solids to remove excess water. After dewatering, the removal of the remaining moisture

is done in most cases by drying. Similarly, particles that are formulated (e.g. by a crystallization step) or by being entrained

from a fluidized bed with the gas stream may need to be separated from the surrounding fluid and be recycled back to the

main solids stream in the process. The separation of solids and gas involve gas cyclones, scrubbers, fabric filters, or

electrostatic precipitators. To ensure that particles are dried to contain adequately low moisture and that the maximum

amount of solids products or intermediates is separated by liquid streams, excess energy may be used. By modeling these

steps both rigorously and in larger processes, substantial energy savings may be unlocked (up to 30% has been reported

in the case of drying).



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Reduced throughput and quality of the product

The design of a profitable process hinges on the throughput and the quality of the final product. While it is important to

produce a large quantity of products to offset operating costs, it is also important to maintain the quality of a product to

appease customers. The selectivity of reactions and the formulation of particles are examples of where both quality and

quantity can be improved. For many important industrial processes, solids can act as educts or a catalyst in the reaction

and therefore will have a major influence on the selectivity and the yield of the reactor. Starting from a solution or slurry,

particles are formulated with the aim to produce a dust-free, free-flowing powder with well-defined properties. This is

done in most cases by crystallization, granulation/agglomeration, or spray drying. The design and operating conditions of

these units can determine the PSD and moisture content of the product.

Similarly, avoiding downtime that may result from unnecessary maintenance, such as clogged solids handling systems,

can improve throughput. Conveying is used to transport solids through pipes and understanding the pressure drops and

velocities needed to avoid clogging while still reducing energy costs is important for increasing uptime and throughput.

In most cases, the solids section is only a part of an overall production process, but may have a significant influence on the

overall process performance and the quality of the final product. The following examples show, in principle, how the fluid

and solids sections of a process may be interconnected in different types of processes:

Specialty chemical processes (including fertilizers, polymers, and pharmaceuticals)

Figure 1 shows a representative process flow diagram for a specialty chemicals process that involves fluid feeds and a solid

product. Typically, chemical reactions with a subsequent separation step occur in the upstream part of the process that is

mostly a pure fluids process. In the downstream part particles are formulated by crystallization, granulation,

agglomeration, or spray drying and depending on the type of the process they are dried in either a convective or a contact

dryer. In some cases, like the synthesis and granulation of urea, the formulation and drying step happens in the same

apparatus. It might also be necessary to adjust the particle size distribution by use of a classification and

grinding/compacting process subsequent to the drying step.

Figure 1: Typical flow diagram of a specialty chemical process with a solid product

Alternatively, as Figure 1 displayed, the reaction step in the upstream part could already involve solids. An example for this

type of process is the synthesis of organosilanes as monomers for silicone polymers. Here, granular silicone reacts in a

fluidized bed in the presence of a solid copper catalyst with chloromethane to dimethyldichlorosilane. Other examples

include the production of rubber, vinyl chloride, polyethylene, and styrene.

Typical challenges for the processes described above is to make sure the product qualitywith regard to composition,

purity, particle size distribution, and moistureminimizes the energy demand of the process.


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Biofuel processes

As shown in Figure 2, in most biofuel processes (e.g. corn stover, switchgrass, sugarcane) the solids feed of the process

are comparably large particles that need to be reduced in size to be further processed. This is done in a grinding and

classification step that produces a material with a well-defined particle size distribution. Subsequently, in the case of

ethanol production, the material enters a section where solid/liquid reactions including hydrolysis and fermentation occur

to produce ethanol and the ethanol must be separated from the remaining biomass and be further purified. Or, in the case

of biodiesel production, oil is extracted from the biomass and then dried to remove excess water before it is processed into

biodiesel1. Alternatively, biomass gasification serves as a way to produce energy using a fluidized bed reactor.

One of the major challenges for this kind of process is the reduction of the total energy demand of the process. Here, size

reduction is an energy-consuming process, especially for second generation biofuels and for a process where an energy

carrier is the productusing less energy is critical for a more economically feasible and sustainable solution2.

Figure 2: Typical flow diagram of a biofuel process with a solid biomass feed

Extractive Processes

Similar to biofuel processes, extractive processes (e.g. oil shale, copper) contain, in most cases, a grinding and

classification step to allow the feed particles to be processed in a subsequent extraction and separation step, as shown in

Figure 3 below. Depending on the specific process, the products could be either fluids (the case of an oil shale process) or

solids (the case of a copper production process) where copper is extracted from the raw ore and then concentrated by use

of flotation.

Figure 3: Typical flow diagram of an extractive process with a solid feed and fluid product

One of the main challenges for this kind of process is to find the optimal combination between the operating conditions for

the upstream grinding and classification part and the downstream extraction and separation part. The finer the material is

grinded in the beginning, the better the extraction and separation may work, but at the same time the energy demand for

the grinding may increase.

The examples above demonstrate that in many industrial production processes, fluids and solids sections influence each

other due to recycles from the solids to the fluid section or vice versa. Therefore, modeling both the fluids and the solids

section of a process is important for many applications including most bulk and specialty chemicals, agrochemicals,

mineral extraction and processing, pharmaceuticals, biofuel, energy, and more.



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New Workflow: A Holistic Fluid and Solids Model in OneSimulation EnvironmentIn response to a lack of an industrial simulator to rigorously model the solids section of an industrial process, the stand-

alone solids simulator SolidSim was developed by solids experts and industry participants in Germany in the early 2000s

to 2010 timeframe. SolidSim introduced a generally applicable flowsheet simulation system to rigorously describe granular

solids and the machines and apparatuses of particle technology3. The development of SolidSim was focused mainly on

solids so users of that tool couldnt rigorously model the fluid section of a process.

In February 2012, Aspen Technology acquired SolidSim Engineering GmbH, the company that was developing and

marketing SolidSim in order to unify these two modeling environments. With the release of Aspen Plus V8 in December

2012, the Aspen Plus model library was enhanced with the SolidSim technology incorporating 25 unit operations models,

including models for drying, crystallization, granulation and agglomeration, crushing and grinding, classification, gas/solid,

and solid liquid separation. In addition, an easy-to-use workflow for the definition of particle size distributions was

introduced with an enhanced results representation that allows visualizing particle size distributions (e.g. cumulative,

density, or RRSB) and apparatus-specific results (e.g. separation efficiency curve of a screen or a gas cyclone) with the

click of a button. Also, characteristic diameters such as d25, d50, or the Sauter Mean Diameter (SMD) are now shown in

Aspen Plus in the stream results.

This enhancement enables the user of Aspen Plus, without any additional software use costs, to model processes that

contain both fluids and solids in one simulation environment using consistent physical properties and avoiding errors and

inefficiencies that may result from the transfer of data from one simulation system to the other. Considering the entire

process, rather than only smaller subsections, allows the user to avoid sub-optimal design due to localized optimization.

By overcoming this challenge, as well as introducing detailed solids modeling, users can address capital costs due to

overdesign, energy and other operating costs, and reduce product quality or throughput. Furthermore, Aspen Plus V8

enables the user to optimize the entire process and use integrated features such as Activated Economics and Activated

Energy.

One example of this more holistic workflow is shown in Figure 4 and displays the process model of the entire urea

production process containing both the synthesis and the granulation part in Aspen Plus V8.

Figure 4: New workflow: Holistic process model of the urea synthesis and granulation in Aspen Plus V8


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Since this model describes the upstream urea synthesis (fluid part) and the downstream urea granulation section (solids

part), the influence of each part is considered in a rigorous way. If, for example, the air flow rate to the fluidized bed

coolers in the granulation section of the urea process needs to be increased, this will lead to a higher entrainment of fines

from the coolers. The entrained particles will be removed from the gas stream by the venturi scrubber, dissolved in the

wash liquid, and then recycled back to the synthesis section. Therefore, the change of the air flow rate to the cooler will

have an influence on the upstream urea synthesis which will then have an impact on the downstream solids part. Figure 5

below shows an example of the process of the predicted process behavior when varying the air flow rate to the fluidized

bed cooler4. By performing sensitivity studies in that way, an optimal operating point for the overall process plant can be

found to match operating constraints.

Figure 5: Case study: urea spray rate, exhaust gas solids load, and product temperature as function of cooling air flow rate

Aspen Technology continues to advance the solids modeling capability in Aspen Plus. Table 1 summarizes the solids

modeling features introduced with each Aspen Plus release since V8.0.

Table 1: Solids-related features highlighted for the Aspen V8.0, V8.2, and V8.4 releases

To further streamline the workflow, new conceptual models have been introduced with Aspen Plus V8.4 that allow the

user to model solids processing steps with only a few parameters and without the requirement of having deep knowledge

of the specific apparatus or particle technology. The conceptual models are an enhancement of the existing solids blocks

in Aspen Plus and allow users to model solids processing steps at different levels of fidelity from conceptual to rigorous

without changing the structure of the flowsheet. When painting a scene, an artist doesnt start in one corner and paint in

great detail while moving slowly across the blank canvas to the opposite corner. An artist will sketch the scene, apply

conceptual shapes, and end with layers of detail. Modeling solids is similar to painting a scene, with some finished models

looking less like finely detailed masterpieces than others. Depending on the stage of project or the project depth, how

Version Date of Release Features

Aspen Plus V8.0 December 2012

Addition of 25 SolidSim unit operations PSD characterization Solids-related results representation

Aspen Plus V8.2 May 2013

Economics for solids processing (Activated Economics) Total of 38 SolidSim unit operations Enhanced PSD definition and results representation

Aspen Plus V8.4 November 2013

Conceptual models Spray dryer unit model Reactions in fluidized bed unit model



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rigorous the model is may differ in appropriateness. For instance, when a rough estimate is quickly needed, the

consideration of exact solids processing equipment may not be necessary. With conceptual modeling, particle scientists

and process engineers can model solids processes in various degrees of detail, from rough sketches to the Mona Lisa of

models. Once a user is ready to switch a unit from conceptual to rigorous, it can be done without changing the flowsheet.

With conceptual models, process engineers that are not savvy with solids modeling can be eased into learning how to use

the capabilities.

Another great opportunity that the conceptual models offer is the possibility that process engineers and particle scientists

can collaborate more closely by using the same simulation environment. When setting up the model of a combined fluids

and solids process, the process engineer can use the conceptual models to describe the solids section of the process.

After having the first simulation results, the process engineer can decide what parts of the solids section need to be

modeled more rigorously, and if necessary, ask the particle scientist to help select and parameterize the rigorous model.

Particle Characterization: The Key to Understanding SolidsProcessingIn Aspen Plus, dispersed solids can be characterized in detail as schematically shown in Figure 6. Users can define

multiple particle types with different distributed properties, such as composition and particle size. In addition to this, it is

also possible to define the moisture content of the particles as a loading of one or more fluid components. The defined

moisture content has an influence on the particles heat capacity and on its density and settling velocity. As a result, wet

particles, for example, will be separated differently in a classifier as dry particles with the composition and same particle

size distribution.

Figure 6: Schematic of the solids characterization in Aspen Plus V8

In addition to this, an intuitive and easy-to-use workflow for the definition of particle size distributions has been integrated

into Aspen Plus that consists of the following steps:

Definition of the particle size classes (particle size mesh)

Aspen Plus offers an automated and a manual mode to generate the particle size classes that should be used to describe

the PSD. The user can select a pre-defined mesh type (e.g. equidistant, geometric, or logarithmic) in automated mode or

the user can import measured data from a particle size analysis in manual mode.


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Definition of the mass fraction within the different particle size classes

For the definition of the mass fractions, Aspen Plus offers an automated or manual mode. In the automated mode, the

user can define mass fractions by selecting a distribution function (e.g. GGS, RRSB (Rosin Rammler Sperling Bennet), log-

normal, or normal distribution) he wants to use to define the PSD and enters a value for the shape (e.g. dispersion

parameter) and the position parameter (e.g. characteristic diameter d63 or d50). In the manual mode, the user defines

the mass fractions as tabular data such as from measured data found during a particle size analysis.

By opening the stream results, users can visualize the defined and calculated particle size distributions with a click of a

button in the form of a cumulative mass, density, or RRSB distribution. It is also possible to show the PSD for different

particle types and streams in the same plot and compare inlet and outlet streams of a unit operation to fully understand

how a certain unit operation changes the particle size distribution of its feed material. An example of how a double-deck

screen changes the PSD is shown in Figure 7.

Figure 7: Cumulative particle size distributions for the stream entering (purple) and the three streams leaving (fines: green, midsize: pink, coarse:blue) the screen

In addition to the plot of the particle size distribution of the streams, the user can easily generate plots that are specific to

a unit operation. This could be the solids volume concentration profile of a fluidized bed, or the solids temperature and

moisture profile in a convective dryer. As an example, Figure 8 shows the separation efficiency curve of the double-deck

screen used in the example above.

Figure 8: Separation Curves for the two decks used in the screen in the granulation example



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Solids Modeling Unit LibraryThe new solids modeling library is a combination of the legacy solids modeling blocks or unit operations available in

Aspen Plus V7 and the new models and blocks introduced from SolidSim. Currently, seventeen new or improved solids

blocks are available as shown in Figure 9. The design philosophy used here is that one block can represent many different

types of equipment at different levels of fidelity from conceptual to rigorous. In total, the solids model library contains over

70 different equipment models.

Figure 9: Solids unit operation available in Aspen Plus V8.4

Moving from Conceptual to RigorousOne unit operation can represent many different types of equipment at various levels of fidelity from conceptual to

rigorous. For example, a decanter centrifuge can be described by use of a conceptual model. In this case, the user defines

the split of the solids and liquid and the separation sharpness (slope of the separation curve), as shown in Figure 10. The

model will then calculate a separation curve based on the settling velocity of the particles and the user input, as shown in

Figure 11meaning that with the conceptual model, the governing classification characteristic, (in the present case) the

settling velocity of the particles is considered. If the user decides he needs to describe the centrifuge in more detail, he can

switch to the rigorous decanter model without changing the structure of the flowsheet or reconnecting streams to the

block. In the rigorous model, the user can define the geometry of the centrifuge and select from different options to

describe the classification and the deliquoring that takes place in the centrifuge. The centrifuge model will then calculate


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the separation efficiency curve based on the more rigorous model, therefore at a higher level of fidelity. A comparison of

the calculated separation efficiency curve using the conceptual and the rigorous model is shown in Figure 11. The plot

shows that the conceptual model predicts the classification in the centrifuge with accuracy that already may be sufficient

for different use cases, for example a feasibility study.

Figure 10: The top image shows a decanter centrifuge described with a conceptual model and the bottom image shows the same decanterdescribed with a rigorous equipment model

Figure 11: Comparison of the calculated separation efficiency curve forthe conceptual centrifuge model (red curve) and the rigorous decantermodel (blue curve)



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From Sequential to Simultaneous Conceptual DesignAspen Plus is surrounded by a suite of integrated products called aspenONE engineering. Aspen Plus supports integrated

workflows, such as Activated Economics and Energy Analysis, as well as Exchanger Design and Rating (EDR). By modeling

solids using Aspen Plus with aspenONE engineering, users have access to these features and can optimize the energy

demand of the entire process with Activated Energy and can assess the capital and utility costs of solids modeling

alternatives with Activated Economics. Using Activated EDR, users can appropriately size heat exchangers required in the

fluid part of the process.

Figure 12: Schematic showing tasks available with the integrated features and layered products surrounding and including Aspen Plus and AspenHYSYS

Economics for solids allows users to consider the capital and utility costs for all solids processing blocks. The impact of

design alternatives and their associated configurations and equipment specifications can be instantly seen. An example of

the activated economic interface and a portion of equipment cost list for the urea synthesis and granulation example is

shown in Figure 13.

Figure 13: Economics for solids helps users determine capital and utility costs


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Use in the IndustryAlthough Aspen Plus V8 with solids has only been available to customers since December 2012, usage of solids modeling

in Aspen Plus has grown at a surprisingly fast rate. Over 100 organizations have started using solids modeling in Aspen

Plus, Evonik Industries AG, Dow Chemical5, and Yara Technology Centre6, just to name a few. In May of 2013, Dow

engineers reported at AspenTechs OPTIMIZETM 2013 conference that they significantly improved their understanding of

the solids behavior in a process involving solid reactants. They were also able to better understand the growth mechanism

they were looking at and relate them with batch cycle time constants. This improved understanding helped them to

optimize the entire process.

Examples Designed for Getting Started FasterModeling the solids section of a process using Aspen Plus V8 has many unique benefits, as previously described. Several

self-service examples have been developed by experts at Aspen Technology for the purpose of providing users a start in

building the models using solids processing operations in Aspen Plus V8 and to allow new and experienced users to get

started faster. These examples were generated using real challenges experienced with solids processing. In addition to the

earlier referenced urea synthesis and granulation example, two examples will be briefly discussed, including a belt dryer

example and a potassium chloride production example.

The belt dryer example illustrates how the energy demand of an industrial multi-stage belt dryer, as shown in Figure 13,

can be optimized using Aspen Plus V8. The convective dryer model in Aspen Plus is used to model the different chambers

of the belt dryer. As a simulation result, the temperature and moisture profile along the dryer, as shown in Figure 14, as

well as the overall energy demand are obtained. The example shows how adding a cooling stage to the dryer and using the

optimization capability of Aspen Plus to determine the optimal drying agent flow rate can help to reduce the energy

demand in the present case by over 23%.

Figure 14: View of the belt dryer layout with the proposed design alternative



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Figure 15: Solids temperature and moisture profile along the belt dryer

The potassium chloride production process example (Figure 15) includes three major process steps: particle formulation

by crystallization, dewatering and drying by use of a centrifuge and a convective dryer, and adjustment of the particle size

by use of a compacting press, multiple hammer mills, and screens in the compacting and sizing part of the process. In the

present example, the throughput of the process should be increased at minimal capital and utility costs. A first analysis

shows that the compacting and sizing part of the process is the bottleneck of the overall process, due to capacity

constraints for the compacting press and the hammer mills.

Figure 16: Example of a potassium chloride production process modeled in Aspen Plus

The example shows how the throughput of the process in the existing layout can be increased by using the optimization

capabilities in Aspen Plus to determine the optimal operating conditions for the hammer mills. This results in an increased

throughput of 30%.


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In the second step, an alternative layout of the process is considered where a third hammer mill is added to improve the

crushing capacity and the 1st screen is exchanged against a double-deck screen to remove particles that are already in the

right particle size range. For this new layout, the optimization capabilities are used to determine the optimal operating

conditions for the mills. Both the optimized original process layout and the optimized alternative layout are compared with

regard to their capital and utility costs using Activated Economics. The example shows that the alternative layout allows

for producing 57% more potassium chloride resulting in a 44% increase in revenue, with only slightly increased capital

costs.

Both the belt dryer and the potassium chloride example are available for self-guided demonstration and can be located on

aspenONE Exchange, the Aspen Technology Support Center Webpage, or by using a link in the resources section of this

paper.

SummaryModeling solid processing steps using Aspen Plus V8 and higher allows for improved workflow and collaboration between

process engineers and particle scientists. Ignoring or poorly modeling the solids section of a process may lead to

suboptimal designs and lost opportunities, such as reduced capital and operating costs and improved throughput and

quality. Modeling fluids and solids in one environment enables the optimization of the entire process at hand. New

conceptual models in Aspen Plus V8.4 further improve workflow for particle scientists and accessibility for process

engineers that arent savvy with solids process modelingallowing users to create models of solids processing steps with

only a few parameters. The integrated workflow associated with using aspenONE engineering stimulates better process

designs and encourages more efficient collaboration.

GlossaryPSD Particle Size Distribution

d50 50% of particles in the distribution are smaller than this diameter

d63 63% of particles in the distribution are smaller than this diameter



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Additional ResourcesDemos: See Whats Possible with 12+ Solids Modeling Examples

http://www.aspentech.com/October_2013_solids_modeling_demo_AT

Jump Start Guide: Solids Process Modeling in Aspen Plus V8

http://www.aspentech.com/solidsjumpstart/

Jump Start Guide: Solids Process Modeling for Experienced Aspen Plus Users, V8

http://www.aspentech.com/SolidsModeling-ExperiencedUsers/

Jump Start Guide: Modeling Granulators in Aspen Plus, V8

http://www.aspentech.com/jumpstartgranulators/

Jump Start Guide: Modeling Convective Dryers in Aspen Plus, V8

http://www.aspentech.com/JumpStartConvectiveDryers/

Jump Start Guide: Modeling Crushers in Aspen Plus, V8

http://www.aspentech.com/jumpstartcrushersmills/

On-demand Webinar: Modeling Solids in a BPA Process

http://www.aspentech.com/November_2013_BPA_ProcessSolids/

References1 J.Y. Zhu, X.J. Pan, Woody biomass pretreatment for cellulosic ethanol production: Technology and energy consumption

evaluation, Bioresource Technology, Volume 101, Issue 13, July 2010, Pages 4992-5002, ISSN 0960-8524,

http://dx.doi.org/10.1016/j.biortech.2009.11.007.

(http://www.sciencedirect.com/science/article/pii/S0960852409015119)

2 J.Y. Zhu, X.J. Pan, Woody biomass pretreatment for cellulosic ethanol production: Technology and energy consumption

evaluation, Bioresource Technology, Volume 101, Issue 13, July 2010, Pages 4992-5002, ISSN 0960-8524,

http://dx.doi.org/10.1016/j.biortech.2009.11.007.

(http://www.sciencedirect.com/science/article/pii/S0960852409015119)

3 Aspen Technology. Aspen Technology acquires SolidSim Engineering GmbH. Press Release. February 29th, 2012.

(http://www.aspentech.com/news/solidsim/press-release/)

4 Werther, J., Poggoda, M., Reimers C., Lakshmanan, A., Beck, R.

Holistic optimization of processes with solids and fluids using flowsheet simulators in: Abstracts and proceedings:.

WCPT6 - World Congress on Particle Technology Nuremburg, Germany, 2013.

(http://reg.mcon-mannheim.de/onlineprogramm-mmv/render.aspx?kongressID=53&t=a&n=26775&speach=ENG)

5 Dow, Vickery, OPTIMIZETM 2013, Boston, MA

6 Yara Techology Centre, Halvor ien, OPTIMIZETM 2013, Boston, MA

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solids overview

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overview of solids modeling

solids sections

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