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Chemical Plants (chemical + plant)

Distribution by Scientific Domains

Chemistry	81%

Selected Abstracts

Storage Tanks at a Chemical Plant.

CHEMICAL ENGINEERING & TECHNOLOGY (CET), Issue 7 2008
Courtesy of Corbis Images (Chem. Eng.
No abstract is available for this article. [source]

Chemical plants , inherent safety

PROCESS SAFETY PROGRESS, Issue 4 2006
Dennis Hendershot
No abstract is available for this article. [source]

Real Options: Meeting the Georgetown Challange

JOURNAL OF APPLIED CORPORATE FINANCE, Issue 2 2005
Thomas E. Copeland
In response to the demand for a single, generally accepted real options methodology, this article proposes a four-step process leading to a practical solution to most applications of real option analysis. The first step is familiar: calculate the standard net present value of the project assuming no managerial flexibility, which results in a value estimate (and a "branch" of a decision tree) for each year of the project's life. The second step estimates the volatility of the value of the project and produces a value tree designed to capture the main sources of uncertainty. Note that the authors focus on the uncertainty about overall project value, which is driven by uncertainty in revenue growth, operating margins, operating leverage, input costs, and technology. The key point here is that, in contrast to many real options approaches, none of these variables taken alone is assumed to be a reliable surrogate for the uncertainty of the project itself. For example, in assessing the option value of a proven oil reserve, the relevant measure of volatility is the volatility not of oil prices, but of the value of the operating entity,that is, the project value without leverage. The third step attempts to capture managerial flexibility using a decision "tree" that illustrates the decisions to be made, their possible outcomes, and their corresponding probabilities. The article illustrate various kinds of applications, including a phased investment in a chemical plant (which is treated as a compound option) and an investment in a peak-load power plant (a switching option with changing variance, which precludes the use of constant risk-neutral probabilities as in standard decision tree analysis). The fourth and final step uses a "no-arbitrage" approach to form a replicating portfolio with the same payouts as the real option. For most corporate investment projects, it is impossible to locate a "twin security" that trades in the market. In the absence of such a security, the conventional NPV of a project (again, without flexibility) is the best candidate for a perfectly correlated underlying asset because it represents management's best estimate of value based on the expected cash flows of the project. [source]

Recursive estimation in constrained nonlinear dynamical systems

AICHE JOURNAL, Issue 3 2005
Pramod Vachhani
In any modern chemical plant or refinery, process operation and the quality of product depend on the reliability of data used for process monitoring and control. The task of improving the quality of data to be consistent with material and energy balances is called reconciliation. Because chemical processes often operate dynamically in nonlinear regimes, techniques such as extended-Kalman filter (EKF) and nonlinear dynamic data reconciliation (NDDR) have been developed for reconciliation. There are various issues that arise with the use of either of these techniques. EKF cannot handle inequality or equality constraints, whereas the NDDR has high computational cost. Therefore, a more efficient and robust method is required for reconciling process measurements and estimating parameters involved in nonlinear dynamic processes. Two solution techniques are presented: recursive nonlinear dynamic data reconciliation (RNDDR) and a combined predictor,corrector optimization (CPCO) method for efficient state and parameter estimation in nonlinear systems. The proposed approaches combine the efficiency of EKF and the ability of NDDR to handle algebraic inequality and equality constraints. Moreover, the CPCO technique allows deterministic parameter variation, thus relaxing another restriction of EKF where the parameter changes are modeled through a discrete stochastic equation. The proposed techniques are compared against the EKF and the NDDR formulations through simulation studies on a continuous stirred tank reactor and a polymerization reactor. In general, the RNDDR performs as well as the two traditional approaches, whereas the CPCO formulation provides more accurate results than RNDDR at a marginal increase in computational cost. © 2005 American Institute of Chemical Engineers AIChE J, 51: 946,959, 2005 [source]

Optimizing periodic inspections in chemical plants by corrosion monitoring

MATERIALS AND CORROSION/WERKSTOFFE UND KORROSION, Issue 12 2007
M. Winkelmans
An efficient industrial corrosion monitoring system would give information about the corrosion activity and corrosion damage of critical components within a chemical plant in real time. A research project to develop an industrial tool for the simultaneous monitoring of general and localized corrosion was initiated. General and localized corrosion can be monitored by combining several non-destructive techniques. An industrial probe for corrosion monitoring is an excellent tool for an intelligent material selection, to identify critical process conditions or to optimize the use of corrosion inhibitors. The highest added value of an industrial tool for corrosion monitoring is its capacity to optimize periodic inspections. [source]

Supply chain risk identification using a HAZOP-based approach

AICHE JOURNAL, Issue 6 2009
Arief Adhitya
Abstract Risk management has become imperative for today's complex supply chains. Most approaches reported in the literature have been ad-hoc and specific to certain risks; a general and comprehensive approach is lacking. To address this, we present a structured methodology for risk identification. Supply chain networks are in many ways similar to chemical plants, therefore well-established methods and concepts from chemical process risk management can be adapted to supply chains. Drawing from this analogy, we propose to represent supply chain structure and operations using flow and work-flow diagrams, equivalent to process flow diagrams (PFDs) and operating procedures. Following the HAZard and OPerability (HAZOP) analysis method common in process safety, risk identification can be performed by systematically generating deviations in different supply chain parameters and identifying their possible causes, consequences, safeguards, and mitigating actions. The application and benefits of the proposed approach are demonstrated using a refinery supply chain case study. © 2009 American Institute of Chemical Engineers AIChE J, 2009 [source]

Dynamic operability analysis of nonlinear process networks based on dissipativity

AICHE JOURNAL, Issue 4 2009
Osvaldo J. Rojas
Abstract Most modern chemical plants are complex networks of multiple interconnected nonlinear process units, often with multiple recycle and by-pass streams and energy integration. Interactions between process units often lead to plant-wide operability problems (i.e., difficulties in process control). Plant-wide operability analysis is often difficult due to the complexity and nonlinearity of the processes. This article provides a new framework of dynamic operability analysis for plant-wide processes, based on the dissipativity of each process unit and the topology of the process network. Based on the concept of dissipative systems, this approach can deal with nonlinear processes directly. Developed from a network perspective, the proposed framework is also inherently scalable and thus can be applied to large process networks. © 2009 American Institute of Chemical Engineers AIChE J, 2009 [source]

Development of a new soft sensor method using independent component analysis and partial least squares

AICHE JOURNAL, Issue 1 2009
Hiromasa Kaneko
Abstract Soft sensors are used widely to estimate a process variable which is difficult to measure online. One of the crucial difficulties of soft sensors is that predictive accuracy drops due to changes of state of chemical plants. To cope with this problem, a regression model can be updated. However, if the model is updated with an abnormal sample, the predictive ability can deteriorate. We have applied the independent component analysis (ICA) method to the soft sensor to increase fault detection ability. Then, we have tried to increase the predictive accuracy. By using the ICA-based fault detection and classification model, the objective variable can be predicted, updating the PLS model appropriately. We analyzed real industrial data as the application of the proposed method. The proposed method achieved higher predictive accuracy than the traditional one. Furthermore, the nonsteady state could be detected as abnormal correctly by the ICA model. © 2008 American Institute of Chemical Engineers AIChE J, 2009 [source]

Managing risk through a flexible recipe framework

AICHE JOURNAL, Issue 3 2008
Sergio Ferrer-Nadal
Abstract A novel approach is proposed that exploits the use of a flexible recipe framework as a better way to handle the risk associated with the scheduling under uncertainty of batch chemical plants. The proposed solution strategy relies on a novel two-stage stochastic formulation that explicitly includes the trade-off between risk and profit at the decision-making level. The model uses a continuous-time domain representation and the generalized notion of precedence. Management of risk is explicitly addressed by including a control measure (i.e., the profit in the worst scenario), as an additional objective to be considered, thus, leading to a multiobjective optimization problem. To overcome the numerical difficulties associated with such mathematical formulation, a decomposition strategy based on the sample average approximation (SAA) is introduced. The main advantages of this approach are illustrated through a case study, in which a set of solutions appealing to decision makers with different attitudes toward risk are obtained. The potential benefits of the proposed flexible recipe framework as a way of managing the risk associated with the plant operation under demand uncertainty are highlighted through comparison with the conventional approach that considers nominal operating conditions. Numerical results corroborate the advantages of exploiting the capabilities of the proposed flexible recipe framework for risk management purposes. © 2008 American Institute of Chemical Engineers AIChE J, 2008 [source]

Addressing the scheduling of chemical supply chains under demand uncertainty

AICHE JOURNAL, Issue 11 2006
Gonzalo Guillén
Abstract A multistage stochastic optimization model is presented to address the scheduling of supply chains with embedded multipurpose batch chemical plants under demand uncertainty. In order to overcome the numerical difficulties associated with the resulting large-scale stochastic mixed-integer-linear-programming (MILP) problem, an approximation strategy comprising two steps, and based on the resolution of a set of deterministic and two-stage stochastic models is presented. The performance of the proposed strategy regarding computation time and optimality gap is studied through comparison with other traditional approaches that address optimization under uncertainty. Results indicate that the proposed strategy provides better solutions than stand-alone two-stage stochastic programming and two-stage shrinking-horizon algorithms for similar computational efforts and incurs much lower computation times than the rigorous multistage stochastic model. © 2006 American Institute of Chemical Engineers AIChE J, 2006 [source]

Fault-tolerant control of process systems using communication networks

AICHE JOURNAL, Issue 6 2005
Nael H. El-Farra
Abstract A methodology for the design of fault-tolerant control systems for chemical plants with distributed interconnected processing units is presented. Bringing together tools from Lyapunov-based nonlinear control and hybrid systems theory, the approach is based on a hierarchical architecture that integrates lower-level feedback control of the individual units with upper-level logic-based supervisory control over communication networks. The local control system for each unit consists of a family of control configurations for each of which a stabilizing feedback controller is designed and the stability region is explicitly characterized. The actuators and sensors of each configuration are connected, via a local communication network, to a local supervisor that orchestrates switching between the constituent configurations, on the basis of the stability regions, in the event of failures. The local supervisors communicate, through a plant-wide communication network, with a plant supervisor responsible for monitoring the different units and coordinating their responses in a way that minimizes the propagation of failure effects. The communication logic is designed to ensure efficient transmission of information between units, while also respecting the inherent limitations in network resources by minimizing unnecessary network usage and accounting explicitly for the effects of possible delays due to fault-detection, control computations, network communication and actuator activation. The proposed approach provides explicit guidelines for managing the various interplays between the coupled tasks of feedback control, fault-tolerance and communication. The efficacy of the proposed approach is demonstrated through chemical process examples. © 2005 American Institute of Chemical Engineers AIChE J, 2005 [source]

Optimizing periodic inspections in chemical plants by corrosion monitoring

Analysis of management actions, human behavior, and process reliability in chemical plants.

PROCESS SAFETY PROGRESS, Issue 1 2008
I. impact of management actions
Abstract While management and engineering actions have a significant impact on process reliability, these factors have received too little attention in calculating plant risks. In this work, the focus is on understanding and modeling the influence of human behavior patterns on plant safety in two settings. The first, introduced in Part I, involves a framework to estimate the impacts of management and engineering decisions, process operator performance, and processing equipment operations on the failure state of chemical plants. As examples, the impacts of poor training, maintenance problems, operator inabilities, control system failures, and excessive feed quantities, on failure states are studied. The management and engineering team and the operators are found to have significant impacts on process reliability. While the theoretical framework introduced herein is illustrated using hypothetical plant data, it should provide a basis for more quantitative safety analyses. Attempts to obtain operating data in industrial plants for validation of the framework were unsuccessful because of confidentiality and liability issues associated with industrial data. © 2007 American Institute of Chemical Engineers Process Saf Prog, 2007 [source]

Management system failures identified in incidents investigated by the U.S. Chemical Safety and Hazard Investigation Board,

PROCESS SAFETY PROGRESS, Issue 4 2004
Angela S. Blair PE, Chemical Incident Investigator
A key mission of the US Chemical Safety and Hazard Investigation Board (CSB) is to determine the root causes of incidents, report the findings, and issue recommendations to prevent similar incidents from occurring. CSB investigators respond to a variety of events occurring in a wide range of workplaces, from chemical plants and refineries to food-flavoring factories and steel mills. The details of each investigation are unique and the root causes are pertinent to each specific case. However, a common thread that emerges in CSB investigations is the inadequacy of management systems that might have prevented the incident from occurring. Examples of the systemic issues identified in CSB reports are: Lack of hazard review to predict and prevent incidents Insufficient investigation and follow-up after previous incidents Inadequate training of staff Failure to implement effective mechanical integrity programs These issues are well recognized as elements of a process safety management (PSM) program, although many incidents investigated by the CSB occurred at facilities that are not regulated by OSHA's process safety management rule.1 Indeed, a number of these incidents occurred at facilities that are well outside society's definition of "chemical plants." Please note that the opinions and conclusions expressed in this paper are those of the author, and do not necessarily represent the opinions of the Chemical Safety and Hazard Investigation Board. © 2004 American Institute of Chemical Engineers Process Saf Prog, 2004 [source]

Gedanken zur Zukunft der Feststoffverfahrenstechnik

CHEMIE-INGENIEUR-TECHNIK (CIT), Issue 12 2002
H.J. Feise Dr.
Abstract Die chemische Industrie erlebt derzeit große Veränderungen. Für die Zukunft erwarten die im ,Solids Processing Industrial Network" beteiligten Experten, dass sich zwei verschiedene Arten von chemischen Anlagen entwickeln: einerseits die vielseitige, modularisierte Mehrzweckanlage und andererseits ,World scale"-Großanlagen. Gleichzeitig wird der bereits hohe Anteil von Feststoffen unter den Produkten der chemischen Industrie weiter steigen und neue Anforderungen stellen: Die Kleinmengenprodukte müssen individuell auf die Bedürfnisse des jeweiligen Kunden zugeschnitten werden, wodurch Product Design zu einer den Wettbewerb bestimmenden Technologie wird. Bei Großanlagen müssen neue Technologien entwickelt werden, welche die notwendigen, hohen Durchsätze bereitstellen und außerdem vom Labor- auf World scale-Maßstab hochskaliert werden können. Einen erheblichen Anteil am künftigen Erfolg wird die Automatisierung haben, deren Einsatz zum Großteil von der Verfügbarkeit geeigneter Inline-Messsysteme und der Entwicklung von Modellen zur Simulation des Prozesses und der dazugehörigen Partikeleigenschaften abhängen wird. On the Future of Solid Processing Techniques The chemical industry is experiencing major changes. The experts of the "Solids Processing Industrial Network" expect that in the future two kinds of chemical plants will develop: on the one hand the polyvalent, multipurpose, modular plant and on the other hand the world-scale plants. At the same time the high percentage of solids as products of chemical processes will continue to increase and therefore new challenges have to be met. Small-scale production of solids has to be customized to the individual customer needs, which means that product design will be a technology that defines the competitiveness. For large plants techniques have to be developed that enable large volumes to be produced but that also allow the reliable scale-up from laboratory scale to world-scale production. Automatization will play a crucial role in the success of solids processing, which will depend on the availability of on-line measurement systems and the development of simulation models for the processes and the particle properties involved. [source]