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Process Units (process + unit)

Distribution by Scientific Domains

Chemistry	80%

Selected Abstracts

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]

Incident investigation: Process to identify root causes of mechanical failures,

PROCESS SAFETY PROGRESS, Issue 1 2006
A. M. (Art) Dowell III P.E.
This paper describes an actual incident investigation into unexpected premature failure of sealed diaphragm pressure transmitters in a chemical process. Some nontypical investigation tools from the CCPS Guidelines for Investigating Chemical Process Incidents (2nd edition) were used. A typical failure allowed a release of a corrosive process fluid with potential injury to personnel. The failures also required a shutdown of the process with loss of production. The cause of the problem was elusive; pressure transmitters from the same manufacturer had no problems in a similar process unit, although component designs differed between the two units. The investigation included confirmation of materials of construction, photographic and visual analyses of failed components, simulation of assembly of the pressure transmitter in the process and measurement of torque values, and brainstorming of possible failure mechanisms. Several hypotheses were tested using a fact,hypothesis matrix to determine most likely cause scenarios. Similarly, a matrix was used to illustrate which scenarios could be prevented by which corrective actions. The investigation included a root cause analysis tree to confirm cause scenarios. The paper discusses the incident investigation process, including diversity of skills on the investigation team, and how each of the tools was used. The paper also discusses the communication of the findings to operations. © 2005 American Institute of Chemical Engineers Process Saf Prog, 2006 [source]

Nonlinear parametric predictive control.

ASIA-PACIFIC JOURNAL OF CHEMICAL ENGINEERING, Issue 6 2009
Application to a continuous stirred tank reactor
Abstract This paper presents a nonlinear model-based controller based on the ideas of parametric predictive control applied to a continuous stirred tank reactor (CSTR) process unit. Controller design aims at avoiding the complexity of implementation and long computational times associated with conventional NMPC while maintaining the main advantage of taking into account process nonlinearities that are relevant for control. The design of the parametric predictive controller is based on a rather simplified process model having parameters that are instrumental in determining the required changes to the manipulated variables for error reduction. The nonlinear controller is easy to tune and can operate successfully over a wide range of operating conditions. The use of an estimator of unmeasured disturbances and process-model mismatch further enhances the behavior of the controller. Copyright © 2009 Curtin University of Technology and John Wiley & Sons, Ltd. [source]

Dynamic operability analysis of nonlinear process networks based on dissipativity

Energy optimization for the design of corn-based ethanol plants

AICHE JOURNAL, Issue 6 2008
Ramkumar Karuppiah
Abstract In this work, we address the problem of optimizing corn-based bioethanol plants through the use of heat integration and mathematical programming techniques. The goal is to reduce the operating costs of the plant. Capital cost, energy usage, and yields,all contribute to production cost. Yield and energy usage also influence the viability of corn-based ethanol as a sustainable fuel. We first propose a limited superstructure of alternative designs including the various process units and utility streams involved in ethanol production. Our objective is to determine the connections in the network and the flow in each stream in the network such that we minimize the energy requirement of the overall plant. This is accomplished through the formulation of a mixed-integer nonlinear programming problem involving short-cut models for mass and energy balances for all the units in the system, where the model is solved through two nonlinear programming subproblems. We then perform a heat integration study on the resulting flowsheet; the modified flowsheet includes multieffect distillation columns that further reduces energy consumption. The results indicate that it is possible to reduce the current steam consumption required in the transformation of corn into fuel grade ethanol by more than 40% compared to initial basic design. © 2008 American Institute of Chemical Engineers AIChE J, 2008 [source]

Performance analysis of small size pilot plant and laboratory relief valves

PROCESS SAFETY PROGRESS, Issue 3 2003
Richard P. Palluzi
Spring-loaded relief valves are one of the most common safety devices installed in pilot plants and laboratory bench-top units. They are typically used in sizes much smaller than those in process units, but their performance is assumed to be equivalent. Most organizations provide only limited preventive maintenance and re-inspection for these valves under the assumption that they are very reliable devices and operation is fairly assured. Our experience and detailed test data with small size (1/2-inch and less) spring-loaded relief devices indicates that most will not perform as reliably as expected due to adhesion of the elastomer seal over time. This leads to initial relief pressures well over the 10% overpressure considered routine, with 30% overpressure being fairly common among certain sizes and conditions. Failing to recognize this problem can lead to otherwise preventable accidents, and even injuries. Data on more than 1,000 relief devices in actual research service for several years was analyzed and the performance measured over time. The data clearly indicate the problem is endemic across all manufacturers and not easily solved. Results are presented in summary form to allow evaluation of the risk inherent in the use of these devices. It indicates a lower level of confidence in actual valve performance, as well as a need for more detailed hazard analysis and risk assessment of the potential for significant relief valve overpressure. [source]

Artificial intelligence advancements applied in off-the-shelf controllers

PROCESS SAFETY PROGRESS, Issue 2 2002
Edward M. Marszal P.E.
Since the earliest process units were built, CPI engineers have employed artificial intelligence to prevent losses. The expanding use of computer-based systems for process control has allowed the amount of intelligence applied in these expert systems to drastically increase. Standard methods for performing Expert System tasks are being formalized by numerous researchers in industry and academia. Work products from these groups include designs that present process hazards knowledge in a structured, hierarchical, and modular manner. Advancements in programmable logic controller (PLC) technology have created systems with substantial computing power that are robust and fault tolerant enough to be used in safety critical applications. In addition, IEC 1131-3 standardized the programming languages available in virtually every new controller. The function block language defined in IEC 1131-3 is particularly well suited to performing modular tasks, which makes it an ideal platform for representing knowledge. This paper begins by describing some of the advancements in knowledge-based systems for loss prevention applications. It then explores how standard IEC 1131-3 programming techniques can be used to build function blocks that represent knowledge of the hazards posed by equipment items. The paper goes on to develop a sample function block that represents the hazards of a pressure vessel, using knowledge developed in the API 14-C standard. [source]

Application of agent-based system for bioprocess description and process improvement

BIOTECHNOLOGY PROGRESS, Issue 3 2010
Ying Gao
Abstract Modeling plays an important role in bioprocess development for design and scale-up. Predictive models can also be used in biopharmaceutical manufacturing to assist decision-making either to maintain process consistency or to identify optimal operating conditions. To predict the whole bioprocess performance, the strong interactions present in a processing sequence must be adequately modeled. Traditionally, bioprocess modeling considers process units separately, which makes it difficult to capture the interactions between units. In this work, a systematic framework is developed to analyze the bioprocesses based on a whole process understanding and considering the interactions between process operations. An agent-based approach is adopted to provide a flexible infrastructure for the necessary integration of process models. This enables the prediction of overall process behavior, which can then be applied during process development or once manufacturing has commenced, in both cases leading to the capacity for fast evaluation of process improvement options. The multi-agent system comprises a process knowledge base, process models, and a group of functional agents. In this system, agent components co-operate with each other in performing their tasks. These include the description of the whole process behavior, evaluating process operating conditions, monitoring of the operating processes, predicting critical process performance, and providing guidance to decision-making when coping with process deviations. During process development, the system can be used to evaluate the design space for process operation. During manufacture, the system can be applied to identify abnormal process operation events and then to provide suggestions as to how best to cope with the deviations. In all cases, the function of the system is to ensure an efficient manufacturing process. The implementation of the agent-based approach is illustrated via selected application scenarios, which demonstrate how such a framework may enable the better integration of process operations by providing a plant-wide process description to facilitate process improvement. © 2009 American Institute of Chemical Engineers Biotechnol. Prog., 2010 [source]

Application of modeling and simulation tools for the evaluation of biocatalytic processes: A future perspective

BIOTECHNOLOGY PROGRESS, Issue 6 2009
Gürkan Sin
Abstract Modeling and simulation techniques have for some time been an important feature of biocatalysis research, often applied as a complement to experimental studies. In this short review, we report on the state-of-the-art process and kinetic modeling for biocatalysis with the aim of identifying future research needs. We have particularly focused on four aspects of modeling: (i) the model purpose, (ii) the process model boundary, (iii) the model structure, and (iv) the model identification procedure. First, one finds that most of the existing models describe biocatalyst behavior in terms of enzyme selectivity, mechanism, and reaction kinetics. More recently, work has focused on extending these models to obtain process flowsheet descriptions. Second, biocatalysis models remain at a relatively low level of complexity compared with the trends observed in other engineering disciplines. Hence, there is certainly room for additional development, i.e., detailed mixing and hydrodynamics, more process units (e.g., biorefinery). Third, biocatalysis models have been only partially subjected to formal statistical analysis. In particular, uncertainty analysis is needed to ascertain reliability of the predictions of the process model, which is necessary to make sound engineering decisions (e.g., the optimal process flowsheet, control strategy, etc). In summary, for modeling studies to be more mature and successful, one needs to introduce Good Modeling Practice and that asks for (i) a standardized and systematic guideline for model development, (ii) formal identifiability analysis, and (iii) uncertainty analysis. This will advance the utility of models in biocatalysis for more rigorous application within process design, optimization, and control strategy evaluation. © 2009 American Institute of Chemical Engineers Biotechnol. Prog., 2009 [source]