William M. Barrett

Development of a chemical process modeling environment based on CAPE-OPEN interface standards and the Microsoft .NET framework

Abstract Chemical process simulation has long been used as a design tool in the development of chemical plants, and has long been considered a means to evaluate different design options. The CAPE-OPEN interface standards were developed to allow process modeling components to be used in any compliant process modeling environment. Use of the CAPE-OPEN interfaces and the .NET framework will allow the application described here to develop into a distributed, cross platform simulation and process control environment that can be easily extended to incorporate novel chemical process computing applications. The current effort is the development of a process simulator built to use process modeling components that implement the CAPE-OPEN interfaces. This paper describes the process modeling components and the process modeling environment developed as part of an application intended to evaluate the processes that generate wastes in a metal finishing process. Ultimately, this program will be made available to the general community as an open-source application.

Mining Available Data from the United States Environmental Protection Agency to Support Rapid Life Cycle Inventory Modeling of Chemical Manufacturing

Demands for quick and accurate life cycle assessments create a need for methods to rapidly generate reliable life cycle inventories (LCI). Data mining is a suitable tool for this purpose, especially given the large amount of available governmental data. These data are typically applied to LCIs on a case-by-case basis. As linked open data becomes more prevalent, it may be possible to automate LCI using data mining by establishing a reproducible approach for identifying, extracting, and processing the data. This work proposes a method for standardizing and eventually automating the discovery and use of publicly available data at the United States Environmental Protection Agency for chemical-manufacturing LCI. The method is developed using a case study of acetic acid. The data quality and gap analyses for the generated inventory found that the selected data sources can provide information with equal or better reliability and representativeness on air, water, hazardous waste, on-site energy usage, and production volumes but with key data gaps including material inputs, water usage, purchased electricity, and transportation requirements. A comparison of the generated LCI with existing data revealed that the data mining inventory is in reasonable agreement with existing data and may provide a more-comprehensive inventory of air emissions and water discharges. The case study highlighted challenges for current data management practices that must be overcome to successfully automate the method using semantic technology. Benefits of the method are that the openly available data can be compiled in a standardized and transparent approach that supports potential automation with flexibility to incorporate new data sources as needed.

Implementation of the waste reduction (WAR) algorithm utilizing flowsheet monitoring

Abstract Environmental metric software can be used to evaluate the sustainability of a chemical based upon data from the chemical process used to manufacture it. An obstacle to the development of environmental metric software for use in chemical process modeling software has been the inability to obtain information about the process directly from the model. There have been past attempts to develop environmental metrics that make use of the process models, but there has not been an integrated, standardized approach to obtaining the process information required for calculating metrics. As a result, environmental evaluation packages are largely limited to use in a single simulation package, further limiting the development and adoption of these tools. This paper proposes a standardized mechanism for obtaining process information directly from a process model using a strongly integrated interface set, called flowsheet monitoring. The flowsheet monitoring interface provides read-only access to the unit operation and streams within the process model, and can be used to obtain the material flow data from the process streams. This material flow data can then be used to calculate process-based environmental metrics. The flowsheet monitoring interface has been proposed as an extension of the CAPE-OPEN chemical process simulation interface set. To demonstrate the capability of the flowsheet monitoring interfaces, the US Environmental Protection Agency (USEPA) WAste Reduction (WAR) algorithm is demonstrated in AmsterCHEMs COFE (CAPE-OPEN Flowsheeting Environment). The WAR add-in accesses the material flows and unit operations directly from the process simulator and uses flow data to calculate the potential environmental impact (PEI) score for the process. The WAR algorithm add-in is included in the latest release of COCO Simulation Environment, available from http://www.cocosimulator.org/ .

Coupling Computer-Aided Process Simulation and Estimations of Emissions and Land Use for Rapid Life Cycle Inventory Modeling

A methodology is described for developing a gate-to-gate life cycle inventory (LCI) of a chemical manufacturing process to support the application of life cycle assessment in the design and regulation of sustainable chemicals. The inventories were derived by first applying process design and simulation to develop a process flow diagram describing the energy and basic material flows of the system. Additional techniques developed by the United States Environmental Protection Agency for estimating uncontrolled emissions from chemical processing equipment were then applied to obtain a detailed emission profile for the process. Finally, land use for the process was estimated using a simple sizing model. The methodology was applied to a case study of acetic acid production based on the Cativa process. The results reveal improvements in the qualitative LCI for acetic acid production compared to commonly used databases and top-down methodologies. The modeling techniques improve the quantitative LCI results for inputs and uncontrolled emissions. With provisions for applying appropriate emission controls, the proposed method can provide an estimate of the LCI that can be used for subsequent life cycle assessments.

An overview of the interoperability roadmap for COM/.NET-Based CAPE-OPEN

Abstract The CAPE-OPEN standard interfaces have been designed to permit flexibility and modularization of process simulation environments (PMEs) in order to use process modeling components such as unit operation or thermodynamic property models across a range of tools employed in the lifecycle of chemical process systems engineering. Technical foundations of interoperable software are constantly changing and Microsoft is nowadays declaring .NET and a successor to COM which has been the major platform for numerous CAPE-OPEN components so far. In order to ensure that the CAPE-OPEN idea will be applicable to recent technical changes, the COLaN has gathered experiences in the area of CAPE-OPEN implementations making use of .NET. This paper will demonstrate that CAPE-OPEN can be successfully implemented using .NET development tools and highlight how the CAPE-OPEN development can benefit from these new technologies.

Evaluation of chemical compatibility testing of geomembranes using the Comprehensive Test System and EPA Method 9090

Tests of the compatibility of geomembrane (GM) samples with waste were conducted using U.S. Environmental Protection Agency (EPA) Method 9090 and the Comprehensive Testing System (CTS). The CTS is a multi-axial performance test capable of simultaneous cyclic mechanical loads and chemical exposure. The test chemicals consisted of solvents, transportation-related compounds, and synthesized landfill leachate. Method 9090 testing was unable to distinguish between the effects of individual chemicals to which the GM was subjected, while the CTS was able to provide statistically-significant differences that were also traceable to chemical properties of the solvent and the GM liner. Further, the time required for changes in mechanical properties of the GM was significantly shorter than would be expected based upon diffusion of the solvent into the GM alone. The combination of chemical attack with mechanical load was found to enhance both reduction in mechanical properties and the ability of the solvent to diffuse into the GM. The CTS is a more realistic test than the existing standard test methods because of its ability to provide multi-axial loads and chemical exposure simultaneously.

Determination of the effect of exposure to gasoline components on a high density polyethylene geomembrane using the comprehensive test system

The comprehensive testing system (CTS) for geomembranes was used to test the compatibility of high-density polyethylene (HDPE) geomembrane landfill liner material with chemicals typically found in motor vehicle fuel. The CTS is a testing apparatus specifically designed to test the effects of simultaneously applying mechanical load, fluid head, and chemical exposure on the geomembrane. A combination of these factors is present on the geomembrane material in service, and the CTS provides a laboratory reproduction of actual field conditions. The article provides a description of gasoline based upon the desirable qualities of gasoline and provides background on testing of rubbers used in gasoline-powered engine parts. The tests chemicals were gasoline, motor oil, benzene, ethylbenzene, toluene, xylenes, and iso-octane (2,2,4 trimethyl pentane). This work found that gasoline had an effect on the geomembrane greater than the effect of any of the pure chemicals except ethylbenzene. Benzene, and the other aromatic compounds (ethylbenzene, toluene, and xylenes) are typically the primary regulatory concerns at fuel contaminated sites. The fact that gasoline had a greater effect on the performance of the HDPE geomembrane indicated that chemicals are present in gasoline which can decrease the performance of the containment structures used to hold gasoline, while not having a significant health risk. The clear implication is that risk assessments conducted on facilities must not only include the health risks of chemicals placed in a facility, but must also consider the effect of the chemical on a containment structure. The fact that low-health-risk chemicals may have a great impact on the effectiveness of containment structures leads to a possible synergistic mechanism where the low-health-risk chemicals enable a pathway for greater-health-risk chemicals to enter the environment.

Comparison of the effects of testing conditions and chemical exposure on geomembranes using the comprehensive testing system

Chemical compatibility tests were conducted on high-density polyethylene geomembrane samples using the Comprehensive Testing System (CTS) under low- and high-displacement conditions. CTS development between the two sets of data (low- and high-displacement) was found to significantly reduce the friction within the testing cell. This friction reduction was apparent from the decrease in delta modulus from the larger values obtained during low-displacement testing to the smaller values obtained during high-displacement testing. The results of the high-displacement testing showed statistically significant differences between delta modulus results at the 95% confidence interval (probability = 0.050), which was not possible with the low-displacement test configuration. Further, the high-displacement testing showed that the more soluble the test chemical was in polyethylene, the lower the resulting delta modulus.

A model to predict the breathing zone concentrations of particles emitted from surfaces.

Activity based sampling (ABS) is typically performed to assess inhalation exposure to particulate contaminants known to have low, heterogeneous concentrations on a surface. Activity based sampling determines the contaminant concentration in a persons breathing zone as they perform a scripted activity, such as raking a specified area of soil, while wearing appropriate sample collection instrumentation. As an alternative approach, a probabilistic model based on aerosol physics and fluid dynamics was developed to predict the breathing zone concentration of a particulate contaminant emitted from a surface during activities of variable intensity. The model predicted the particle emission rate, tracked particle transport to the breathing zone, and calculated the breathing zone concentration for two scenarios. One scenario used an Eulerian model based on a Gaussian concentration distribution to quantify aerosol exposure in the trailing wake of a moving object. The second scenario modeled exposure in a quiescent environment. A Lagrangian model tracked the cumulative number of individual particles entering the breathing zone volume at a particular time. A Monte Carlo simulation calculated the breathing zone concentration probability distribution for each scenario. Both models predicted probability distributions of asbestos breathing zone concentrations that bracketed experimentally measured personal exposure concentrations. Modeled breathing zone concentrations were statistically correlated (p-value < 0.001) with independently collected ABS concentrations. The linear regression slope of 0.70 and intercept of 0.03 were influenced by the quantity of ABS data collected and model parameter input distributions at a site broader than those at other sites.

Development of the Releasable Asbestos Field Sampler

Abstract The releasable asbestos field sampler (RAFS) was developed as an alternative to activity-based sampling (ABS; personal breathing zone sampling during a simulated activity). The RAFS utilizes a raking motion to provide the energy that releases particulate material from the soil and aerosolizes the asbestos fibers. A gentle airflow laterally transports the generated aerosol inside of a tunnel to one end where filter sampling cassettes or real-time instruments are used to measure asbestos and particulate release. The RAFS was tested in a series of laboratory experiments to validate its performance and then was deployed for field trials in asbestos-contaminated soil at multiple geographical locations. Laboratory data showed the RAFS generated repeatable and representative aerosol particulate concentrations. Field tests showed the RAFS aerosolized asbestos concentrations were statistically correlated with total particle concentrations. Field tests also showed the RAFS aerosolized asbestos concentrations were statistically correlated with asbestos concentrations measured by multiple ABS tests with different activities, different soil/environmental conditions, and at different geographical locations. RAFS provides a direct measurement of asbestos emission from soil in situ without consideration of meteorology and personal activity on the asbestos transport to the breathing zone.