Operable adaptive sparse identification of systems: Application to chemical processes
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[Challenges and Opportunities in] Process Modeling of Intensified Chemical Processes
Before the benefits of process intensification can be fully realized, a multitude of advances in process modeling will be necessary. Process intensification (PI) has the potential to speed development of chemical engineering innovations. Among its many benefits, PI can increase the driving forces (physical and/or chemical) for transport phenomena, separations, and/or reactions in chemical processes, and inspire novel process configurations with major technical and economic benefits. Examples of PI applications include integrated process units such as heat exchange networks, sorption- or membrane-enhanced reactors, and dividing-wall distillation columns, among others [AIChE(2017)].
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Integrating Cybersecurity Risk Assessment with Process Safety in Chemical Process Industries
This dissertation bridges the gap between industrial cybersecurity and traditional process safety by introducing an integrated Cyber-LOPA framework that combines the Purdue Enterprise Reference Architecture, Cyber Kill Chain, and CVSS v4.0 metrics. Demonstrated on a High-Density Polyethylene slurry process, the work illustrates how cyber threats targeting automation systems can bypass physical protection layers, proving the necessity of unified risk assessments to prevent cyber-induced physical incidents in chemical manufacturing plants.
Cyber-LOPA (CLOPA)↗
Defense Waste Processing Facility Nitric-Glycolic Flowsheet Chemical Process Cell Chemistry: Part 2
The conversions of nitrite to nitrate, the destruction of glycolate, and the conversion of glycolate to formate and oxalate were modeled for the Nitric-Glycolic flowsheet using data from Chemical Process Cell (CPC) simulant runs conducted by Savannah River National Laboratory (SRNL) from 2011 to 2016. The goal of this work was to develop empirical correlation models to predict these values from measurable variables from the chemical process so that these quantities could be predicted a-priori from the sludge or simulant composition and measurable processing variables. The need for these predictions arises from the need to predict the REDuction/OXidation (REDOX) state of the glass from the Defense Waste Processing Facility (DWPF) melter. This report summarizes the work on these correlations based on the aforementioned data. Previous work on these correlations was documented in a technical report covering data from 2011-2015. This current report supersedes this previous report. Further refinement of the models as additional data are collected is recommended. The glass REDOX depends on the concentrations of nitrate and manganese (oxidants), and of glycolate, formate, oxalate, carbon, and antifoam (reductants) in the melter feed. The waste sludge contains nitrite, nitrate, manganese (Mn), and oxalate. Virtually all of the nitrite is converted to nitrate or NO+NO 2 +N 2 O gases in the CPC. The portion of the nitrite converted to nitrate increases the amount of nitrate in the sludge. The amount of glycolate in the final melter feed depends on the amount of the glycolic acid feed that is destroyed. Similarly, the amounts of formate and oxalate formed during the decomposition of glycolic acid are required. The material balance on carbon was found to not close in most cases. Generally, there was less carbon at the end of testing compared to the inputs. The most uncertain product variable was glycolate, so material balances were performed where the glycolate concentration was adjusted, usually upward, to close the balance. Correlation versus the original, as-measured, data was generally poor, but correlation against the material balance adjusted values was greatly improved. It was also shown that the correlation of the measured REDOX versus the predicted REDOX was much better when the material balance adjusted glycolate values were used. Three data series were primarily used during the regressions of the data; these series were 1) Sludge Batch 9 NG flowsheet simulant runs NG51-62 (SB9-NG); 2) Scaled Runs + Bounding Hydrogen Runs (SR+BH); and 3) Runs GN43-50 and 57 (43-50,57). The glycolate destruction was found to correlate with acid stoichiometry (AS), percent reducing acid (PRA), and for some data series, headspace to simulant volume ratio (HSV), mercury (Hg), and nitrate. Although glycolate destruction for pairs of data series (e.g., [SB9-NG] and [SR+BH]) were found to depend on HSV, the combination of all three data series was not found to have significant dependence on this variable. The best model for glycolate destruction depended on AS, nitrate, and Hg. This model predicted the product glycolate compositions of the data to within 92-106%. The conversion of glycolate to formate was high when noble metals and Hg were not present, with values up to 100%. When noble metals and Hg were present, this conversion ranged from zero to 7%, and was dependent on AS. Lower AS gave higher conversions to formate. The conversion to oxalate was found to depend on the AS and the initial concentration of nitrite. An alternative fit versus AS and the form of ruthenium (Ru) used is a possible alternative. This fit was somewhat less statistically significant. This second model predicts that more oxalate is formed when Ru-nitrosyl nitrate is used rather than Ru chloride. The conversion of glycolate to oxalate ranged from zero to 6%. The conversion of nitrite to nitrate depended primarily on AS and PRA, with HSV and Hg being significant when these variables were varied. For multiple series of data, nitrite was also needed to SRNL-STI-2017-00172 5HYLVLRQ viL distinguish between data series, and the effect of HSV became insignificant. The best model for nitrite to nitrate conversion depended on AS, PRA, nitrite, and Hg. The 95% confidence intervals on the predicted values of glycolate destruction, glycolate to oxalate conversion, and nitrite to nitrate conversion were used to determine the uncertainty in the predicted REDOX when starting with only the composition of the sludge, AS, and PRA. Using the 95% confidences on an individual value (that is the confidence in getting a particular value for one single test as opposed to what the mean would be for multiple tests), the uncertainty in the predicted REDOX was calculated. The uncertainty in the actual product composition glycolate, oxalate, formate, and nitrate concentrations translated to an uncertainty in the REDOX value of ±0.1,which is approximately the uncertainty claimed in the REDOX model itself.
12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
Economic risk analysis for the capture of a distributed energy resource using modular chemical process intensification
Recent advances in the chemical process industry have allowed for the intensification of reactors and unit operations, by enhancing heat and mass transfer or combining multiple unit operations. Process intensification can enable chemical plants to be constructed in a more compact, modular fashion, offering improvements over conventional on-site approaches to capital construction, operations and maintenance. This modular chemical process intensification (MCPI) offers several benefits over conventional stick-built (CSB) plant construction in terms of reduced footprint, reduced energy consumption, lower cost, less waste and improved safety and quality control. However, acceptance of MCPI over CSB construction practices within the chemical industry can be impeded by the uncertain risks associated with investing in new technology. Furthermore, the work here documents a case study during the development of a modular chemical plant for capturing distributed energy resources within chemical production. This MCPI approach to plant construction is contrasted with a CSB approach for producing the same chemical product. Data collection tools were developed, based on a literature review, and data was collected from the technology developer to understand the process technology. Sensitivity analysis was then conducted to analyze the business rationale for the application of MCPI over CSB across several market scenarios. It was found that MCPI would be better suited for capacities up to 150 000 metric tons per year, but that improvement in payback period was needed. Additionally, for MCPI approach to achieve acceptable payback periods, efforts are needed to reduce the cost of capital equipment and compress the schedule for ramping up modular production.
42 ENGINEERING↗
Criticality Alarm Systems at the Idaho Chemical Processing Plant
The Idaho Chemical Processing Plant (ICPP) has a number of criticality alarm systems (CAS) in the various facilities. The complexity of the plant creates some unique CAS problems. A detailed review of the CAS has been made to determine the level of compliance with ANSI 8.3-1986. A major CAS upgrade project is currently in the design stage which will expand coverage and bring all CAS monitoring unshielded areas into full compliance with ANSI 8.3-1986. Because DOE Orders do not contain an exclusion that exempts the need for CAS coverage in shielded areas as provided in ANSI 8.3-1986, a future CAS upgrade project is in the planning stage which will also upgrade the CAS coverage in shielded portions of the plant.
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
Analyzing Case Histories of Process Plant Disasters to Understand Chemical Process Cybersecurity
This presentation reviews worst case plant disasters and map a cyberattack scenario that would have a similar outcome.
42 ENGINEERING↗
Specialty chemicals production case study: Economic analysis of modular chemical process intensification versus conventional stick‐built approaches
Abstract The beneficial synergies of chemical process intensification and plant modularization present a unique step‐wise advancement opportunity for many chemical manufacturers, but economic case studies are needed to raise awareness of such opportunities. The primary objective of this case study is to better understand the business case economics of a specialty chemical plant using modular chemical process intensification (MCPI), by comparing it with that of a conventional stick‐built (CSB) plant that produces the same product at the same production capacity. When comparing MCPI against CSB approaches for a plant project strategy decision, analysts should thoroughly understand and model the differences and similarities in scope bases. The MCPI approach for this case study benefitted from dramatic reductions in capital expenditures (CAPEX). A sizeable reduction in plant spatial volume likely explains some of these reductions. Sizeable operational expenditure (OPEX) reductions with the MCPI plant appear to be associated with the reduced operator staffing required from converting a labor‐intensive batch process into an automated, continuous flow process. Traditional project investment economic measures strongly favored the MCPI case for the design, construction, and operation of the specialty chemical plant. The net present value for the MCPI case was nearly twice that for the CSB case over a ten‐year period, and the payback period for the CSB case was nearly five times longer than that of the MCPI case. The opinion‐based perspective of the study participant identified significant contributors to superior MCPI economic performance for this case study. With the two conditions of low MCPI CAPEX and high product profit margin, economic analysis indicates that incorporation of a backup MCPI train, for operational redundancy when downtime occurs, is a very beneficial strategy.
O'Connor, James T.↗
Optimization-based Approaches for Design of Chemical Process Families Using ReLU Surrogates
Presentation delivered at 2023 Foundations of Computer-Aided Process Operations (FOCAPO) and Chemical Process Control (CPC) conference.
Stinchfield, Georgia↗
Chemical Process Safety at TRISO-Based, Metal-Based, and Salt-Based Fuel Fabrication Facilities: Technical Assessment and Guidance Assessment
As part of efforts to prepare for potential and ongoing safety reviews for licensing of advanced non-light-water reactor fuel cycles, the U.S. Nuclear Regulatory Commission (NRC) tasked Pacific Northwest National Laboratory to prepare an assessment on the state of knowledge of potential chemical processes at fuel cycle facilities supporting the front end of these fuel cycles, and to assess the associated regulatory guidance. This report provides a technical assessment of chemical process safety considerations to support NRC licensing reviews of fabrication processes for tri-structural isotropic (TRISO) based, metallic-based, and salt-based fuels. The assessments involved collecting publicly available information on the fuel fabrication processes to (i) identify the operational process steps, characteristics and chemicals involved, (ii) identify the physical safety considerations and health safety considerations during licensing reviews of the various process steps, and (iii) collect information to support assessments of severity of accidents and potential mitigative measures to be implemented. The assessment provides a foundational basis on chemical process safety considerations for advanced fuel fabrication activities, although it is recognized that licensing reviews may necessitate design-specific considerations. The specific conditions under which chemical hazards emerge will require process-specific considerations, highlighting the importance of process-informed interpretation. The assessment also determined that exposure guidelines and limits to assess the consequences of acute exposures are limited for some chemicals, although alternative limits and supplementary information from databases or safety data sheets provide sufficient information to evaluate consequences of acute exposures. In addition, it was identified that metallic and salt fuel fabrication processes may involve beryllium, which is an exposure hazard. The regulatory framework for the licensing of advanced fuel cycle facilities, per 10 CFR Part 70 Domestic Licensing of Special Nuclear Material, is deemed robust and flexible to address the chemical safety considerations in this report. A review was conducted on various regulatory guidance and technical basis documents. This included reviewing NUREG-1520, Revision 2, Standard Review Plan for Fuel Cycle Facilities License Applications – Final Report and the process descriptions in Appendix A of NUREG/CR-6410, Nuclear Fuel Cycle Facility Accident Analysis Handbook, to address advanced fuel types. As new fuels will involve process-specific chemical uses, process-specific considerations are provided in this report. Additionally, it is noted that the U.S. Department of Energy protective action criteria database includes Temporary Emergency Exposure Limits (TEELs) for process-specific chemicals. This report provides technical information to support chemical safety assessments of new advanced fuel cycle facilities and identifies technical and safety information to support licensing reviews. No regulatory barriers were identified for the licensing of advanced fuel cycle facilities.
11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
Phenomena-based graph representations and applications to chemical process simulation
Rapid and robust simulation of chemical processes is critical to conduct process design, optimization, techno-economic analysis, and sustainability analysis. Yet, efficiently solving simulation models remains a challenge due to the highly coupled and nonlinear nature of the underlying algebraic equations that capture the physical phenomena taking place in the process (e.g., material and energy conservation, phase equilibrium, reactions). In this work, we show that graph-theoretic representations of the physical phenomena within unit operations can help navigate and decompose equations to systematically identify alternative approaches for fast and robust numerical solutions. Specifically, we present a graph-theoretic abstraction that captures the connectivity between the model variables/equations and use this abstraction to group variables/equations into fundamental phenomena. We show that phenomena-based decomposition of the underlying equations can help decouple nonlinearities and enforce material/energy conservation at the process level to accelerate convergence. The proposed decomposition approach differs from the more traditional sequential modular simulation approach, in which equations are grouped and decomposed by unit operations. We implemented the phenomena-based decomposition in BioSTEAM—an open-source process simulation platform in Python—and demonstrated that this approach can converge a variety of separation process models. Compared to sequential modular simulation, the phenomena-based approach can converge idealized systems faster, but it can be slower for (or even fail to converge) highly coupled and nonideal process systems.
Convergence↗
Strategies to overcome electron-beam issues in liquid phase TEM: Study of chemical processes
Abstract Liquid phase (or liquid cell) transmission electron microscopy (TEM) has become a powerful platform for in situ investigation of various chemical processes at the nanometer or atomic level. The electron beam for imaging can also induce perturbation to the chemical processes. Thus, it has been a concern that the observed phenomena in a liquid cell could deviate from the real-world processes. Strategies have been developed to overcome the electron-beam-induced issues. This article provides an overview of the electron-beam effects, and discusses various strategies in liquid cell TEM study of nucleation, growth, and self-assembly of nanoscale materials, where an electron beam is often used to initiate the reactions, and highly electron-beam-sensitive electrochemical reactions. Graphical abstract
Zheng, Wenjing↗
Simulation of DWPF Chemical Process Cell Using a Reaction Calorimeter
The Defense Waste Processing Facility (DWPF) converts liquid radioactive waste into glass using a Sludge Receipt Adjustment Tank (SRAT) and Slurry Mix Evaporator (SME) in addition to other processes. The SRAT and SME processes can be simulated on a small-scale using the Mettler-Toledo Reaction Calorimeter (RC1). This equipment is able to automate the execution and monitoring of experiments involving nonradioactive chemical simulants. During the chemical processing of sludge in the SRAT process, foam begins to form and can foam over the reaction vessel. The current antifoam used at DWPF creates a risk of increased flammability and has a limited pH range. Usually, mercury is circulated back into the reaction vessel during the SRAT process, making it difficult to remove. To combat foam over, novel antifoams will be tested during the boil-up process using the RC1. To improve mercury extraction, 3D-printed coalescer columns will be tested within the Mercury Water Wash Tank (MWWT) of the RC1. Testing of Simulant Sludge Batch 6 (SB6) was performed to ensure: the sludge would form a stable foam at boiling during full SRAT/SME runs; the antifoam would reduce the amount of foam within the vessel The sludge and a Precipitate Reactor Feed Tank (PRFT) simulant with monosodium titanate (MST) were mixed separately, combined, and then heated to boiling. As shown below, the antifoam used was able to eliminate the foam within the vessel, as expected. The FormLabs Form2 3D Printer can be used to create roughly 3-inch tall and 1-inch diameter columns from clear and ceramic resins. The columns will utilize chemical and physical forces to draw the mercury out of a condensed offgas stream leaving the RC1 reaction vessel. These columns will be tested during full SRAT/SME runs on the basis of how well they are able to collect elemental mercury. In preparation for full-scale runs, the RC1 equipment was assembled onto a custom table and tested with water runs. The software used to control automation, iControl, has a user-friendly interface that allows the experiment to be altered as needed. An example of the data recorded during an experimental run is represented in Figure 1 below. Water runs were utilized as a way to prove if the RC1 system was functioning in the following areas: Boil-up rates, Chemical additions using pumps, Temperature readings, Balance readings, Probe readings, Offgas system, Agitation. Future Plans: Five novel antifoams will be tested during full SRAT/SME runs. The most effective antifoam will be utilized in DWPF's Chemical Process Cell. The design of the Mercury Extraction Coalescer can be further manipulated to increase the extraction of not only elemental mercury, but other heavy metals in environmental remediation processes as well.
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Electron-beam-driven chemical processes during liquid phase transmission electron microscopy
Liquid phase (or liquid cell) transmission electron microscopy (LP-TEM) has been established as a powerful tool for observing dynamic processes in liquids at nanometer to atomic length scales. However, the simple act of observation using electrons irreversibly alters the nature of the sample. A clear understanding of electron beam-driven processes during LP-TEM is required to interpret in situ observations and utilize the electron beam as a stimulus to drive nanoscale dynamic processes. In this review, we discuss recent advances toward understanding, quantifying, mitigating, and harnessing electron beam-driven chemical processes occurring during LP-TEM. We will highlight progress in several research areas, including modeling electron beam-induced radiolysis near interfaces, electron beam-induced nanocrystal formation, and radiation damage of soft materials and biomolecules.
Woehl, Taylor J.↗
Hyperplane decision trees as piecewise linear surrogate models for chemical process design
Recent trends in chemical engineering research point towards an increasing reliance on data-driven modeling approaches. Neural networks, for instance, have proven to be accurate when data is plentiful and high-dimensional, but in many cases, they require computationally-intensive training procedures. Here, in this work, we describe hyperplane decision trees (HT) as a highly expressive and low-compute machine learning model architecture. These models are locally linear and have linear decision boundaries, resulting in a piecewise linear model of the data. This property allows them to be converted into mixed-integer linear constraints which can be globally optimized. Our open-source PyTorch implementation of this method is a fast, flexible, and accessible way to build accurate piecewise linear models of data.
Decision trees↗
Teaching Manufacturing Process Design as a Means for Competitive Advantage in Chemical Process Industries
Not Available
Summerville, Steven↗
Accessing bands with extended quantum metric in kagome Cs 2 Ni 3 S 4 through soft chemical processing
Flat bands that do not merely arise from weak interactions can produce exotic physical properties, such as superconductivity or correlated many-body effects. The quantum metric can differentiate whether flat bands will result in correlated physics or are merely dangling bonds. A potential avenue for achieving correlated flat bands involves leveraging geometrical constraints within specific lattice structures, such as the kagome lattice; however, materials are often more complex. In these cases, quantum geometry becomes a powerful indicator of the nature of bands with small dispersions. We present a simple, soft-chemical processing route to access a flat band with an extended quantum metric below the Fermi level. By oxidizing Ni-kagome material Cs 2 Ni 3 S 4 to CsNi 3 S 4 , we see a two orders of magnitude drop in the room temperature resistance. However, CsNi 3 S 4 is still insulating, with no evidence of a phase transition. Using experimental data, density functional theory calculations, and symmetry analysis, our results suggest the emergence of a correlated insulating state of unknown origin.
Science & Technology - Other Topics↗