The propagation of faults in process plants: Hazard identification

Many of the techniques introduced in recent years for the identification and assessment of hazards in process plants have the common feature that they deal with the propagation of faults through the plant. The modelling of fault propagation, its application to fault tree synthesis, a computer-based interactive facility and an illustrative example have been described in previous papers. This paper describes a similar, though not identical, method of modelling fault propagation for the purpose of hazard identification implemented on a computer-based interactive facility. The information produced is similar to that obtained from a hazard and operability study, though less complete. Consideration is also given to expert system enhancement of the method. An illustrative example is described in a further, complementary paper.     

Comparison of Markov model and fault tree approach in determining initiating event frequency for systems with two train configurations

This study explores the use of Markov models in some areas of systems analysis in which time evolution of the system may be a significant factor in influencing the system reliability or availability. Comparisons are made between the Markov models and the time-averaged fault tree models for determining support system failure initiating event frequency in a nuclear power plant, for both power and shutdown conditions. Factors affecting consistency between the fault tree approach and the Markov model approach are studied for systems with common two train configurations. A correlation is developed to estimate the ratio between initiator frequencies through both approaches for a two parallel component system. Insights are developed as to when time averaged and simplified fault tree models support a good approximation to the more rigorous time-dependent Markov models.     

Advanced production scheduling for batch plants in process industries

An Advanced Planning System (APS) offers support at all planning levels along the supply chain while observing limited resources. We consider an APS for process industries (e.g. chemical and pharmaceutical industries) consisting of the modules network design (for long–term decisions), supply network planning (for medium–term decisions), and detailed production scheduling (for short–term decisions). For each module, we outline the decision problem, discuss the specifi cs of process industries, and review state–of–the–art solution approaches. For the module detailed production scheduling, a new solution approach is proposed in the case of batch production, which can solve much larger practical problems than the methods known thus far. The new approach decomposes detailed production scheduling for batch production into batching and batch scheduling. The batching problem converts the primary requirements for products into individual batches, where the work load is to be minimized. We formulate the batching problem as a nonlinear mixed–integer program and transform it into a linear mixed–binary program of moderate size, which can be solved by standard software. The batch scheduling problem allocates the batches to scarce resources such as processing units, workers, and intermediate storage facilities, where some regular objective function like the makespan is to be minimized. The batch scheduling problem is modelled as a resource–constrained project scheduling problem, which can be solved by an efficient truncated branch–and–bound algorithm developed recently. The performance of the new solution procedures for batching and batch scheduling is demonstrated by solving several instances of a case study from process industries.     

Parameter identification and computational simulation of polyurethane foaming process by finite pointset method

Numerical simulation of the polyurethane foaming process is a valuable method to analyze the molding process at an early stage of product development to shorten time-to-market cycles and cut costs by using fewer prototypes. However, this process involves highly coupled thermo-chemo-rheological modeling and needs adequate model parameters’ identification. A theoretical model including chemical reactions and thermo-rheological coupling of conservation equations was developed. Based on the theoretical model, three-dimensional numerical simulation for mold filling of the polyurethane foam was carried out by using Finite Pointset Method (FPM) to predict flow field, flow front advancement, temperature and density distributions during mold filling. A FOAMAT system was used to monitor foam height rise and reaction temperature on a cylindrical test tube and foam viscosity was measured by using a dynamic rotational rheometer with parallel-plate system. The parameters of the model were identified by an inverse analysis method which consists in determining the parameters by comparing the computed quantities to those measured experimentally. The overall modeling was validated by using short shot foams obtained with a panel mold cavity. Mold filling of an automotive underlay carpet cavity was investigated numerically. Flow front results were successfully compared to short shot foams obtained with the industrial mold cavity.     

Task analysis for error identification: Theory,method and validation

This paper presents the underlying theory of Task Analysis for Error Identification. The aim is to illustrate the development of a method that has been proposed for the evaluation of prototypical designs from the perspective of predicting human error. The paper presents the method applied to representative examples. The methodology is considered in terms of the various validation studies that have been conducted, and is discussed in the light of a specific case study.     

TECHNICAL NOTE: Nonparametric estimation and variate generation for a nonhomogeneous Poisson process from event count data

Given a finite time horizon that has been partitioned into subintervals over which event counts have been accumulated for multiple realizations of a population NonHomogeneous Poisson Process (NHPP), this paper develops point and confidence-interval estimators for the cumulative intensity (or mean value) function of the population process evaluated at each subinterval endpoint. As the number of realizations tends to infinity, each point estimator is strongly consistent and the corresponding confidence-interval estimator is asymptotically exact. If the NHPP has a piecewise constant intensity (rate) function, then the proposed point and confidence-interval estimators for the cumulative intensity function are valid over the entire time horizon and not just at the subinterval endpoints; and in this case algorithms are presented for generating event times from the estimated NHPP. Event count data from a call center illustrate the point and interval estimators.     

Ultrasonic based method for damage identification in composite materials

We present an ultrasonic-based Lamb wave propagation method for identifying and measuring the damage location in a material as a basis for structural health monitoring (SHM). Lamb waves can propagate in a structure via mode conversion and reflection from the surfaces of the structure, and can lead to interference patterns as a resulting wave vector propagates along the structure. We determined the experimental and analytical effects of various parameters on the sensitivity of damage detection. A methodology is proposed for estimating and measuring the location of damage in test specimens. An experimental setup is used for generating A_o? Lamb waves by calibrating ultrasonic pulse generation for optimal values of parameters. Materials with different damage levels are tested in their undamaged and damaged conditions, and the effects of the parameters on the generated waves in test specimens are observed experimentally.     

A linear predictive method for on-line track recognition and event analysis for cylindrical magnetic spectrometers

A fast and simple track search algorithm based on a linear predictive method and applicable to cylindrical magnetic spectrometers is described. Resulting track parameters, expressed in terms of linear predictors, can be used to do event analysis on-line. The application of the algorithm to the μ → 3e experiment using the SINDRUM detector is detailed.     

Risk-based inspection and maintenance in process plants and their practices in Taiwan

The content of risk-based assessment and management and risk-based inspection and maintenance (RBI&M) employed in process plants are addressed in this article. Probabilistic analyses including probabilistic risk assessment developed in the engineering field over the past few decades are reviewed first. Following that, RBI and risk-informed management employed in the nuclear industry and risk-based inspection, maintenance, and other risk-based approaches used in chemical plants as well as their developments are reviewed, respectively. While most of the above were developed and practiced in industrialized countries, the current situation in Taiwan is also mentioned. Special attention is paid to the possibility and difficulties of employing RBI&M in Taiwan’s power and process plants. The difficulties in adopting existing risk-based approaches to inspect and manage Kaohsiung’s underground pipelines are pointed out in particular. Comments are made at the end of the article.     

Seismic PSA method for multiple nuclear power plants in a site

The maximum number of nuclear power plants in a site is eight and about 50% of power plants are built in sites with three or more plants in the world. Such nuclear sites have potential risks of simultaneous multiple plant damages especially at external events. Seismic probabilistic safety assessment method (Level-1 PSA) for multi-unit sites with up to 9 units has been developed. The models include Fault-tree linked Monte Carlo computation, taking into consideration multivariate correlations of components and systems from partial to complete, inside and across units. The models were programmed as a computer program CORAL reef. Sample analysis and sensitivity studies were performed to verify the models and algorithms and to understand some of risk insights and risk metrics, such as site core damage frequency (CDF per site-year) for multiple reactor plants. This study will contribute to realistic state of art seismic PSA, taking consideration of multiple reactor power plants, and to enhancement of seismic safety.     

ARAMIS project: a comprehensive methodology for the identification of reference accident scenarios in process industries

In the frame of the Accidental Risk Assessment Methodology for Industries (ARAMIS) project, this paper aims at presenting the work carried out in the part of the project devoted to the definition of accident scenarios. This topic is a key-point in risk assessment and serves as basis for the whole risk quantification.

The first result of the work is the building of a methodology for the identification of major accident hazards (MIMAH), which is carried out with the development of generic fault and event trees based on a typology of equipment and substances. The term “major accidents” must be understood as the worst accidents likely to occur on the equipment, assuming that no safety systems are installed.

A second methodology, called methodology for the identification of reference accident scenarios (MIRAS) takes into account the influence of safety systems on both the frequencies and possible consequences of accidents. This methodology leads to identify more realistic accident scenarios. The reference accident scenarios are chosen with the help of a tool called “risk matrix”, crossing the frequency and the consequences of accidents.

This paper presents both methodologies and an application on an ethylene oxide storage.     

18O labeling method for identification and quantification of succinimide in proteins

We have developed a new method for identification and quantification of succinimide in proteins. The method utilizes 18O water to monitor succinimide hydrolysis. 18O-labeled isoaspartic acid and aspartic acid peptides were produced by hydrolysis of a succinimide-containing protein in 18O water (H218O) followed by tryptic digestion in regular water (H216O). The peptides that had 18O incorporated were 2 Da heavier than their 16O native counterparts. The mass difference was detected and quantified by electrospray time-of-flight mass spectrometry. The amount of 18O incorporation into the isoaspartic acid- and aspartic acid-containing peptides was used to quantify the amount of succinimide present in the native sample. The method was applied to analyze a degraded recombinant monoclonal antibody, which exhibited the accumulation of succinimide after storage in mildly acidic buffers at elevated temperatures for a few weeks. We unambiguously identified amino acid residue 30 located in the antibody light chain as the site of aspartic acid isomerization. At this site, there were 20% isoaspartic acid and 80% aspartic acid detected by peptide mapping in the degraded sample (8 weeks, 45 degrees C, pH 5.0). Hydrolysis in 18O water showed that 80% of the isoaspartic acid and 6% of the aspartic acid had 18O incorporated. The only explanation of 18O incorporation was the presence of succinimide in the sample. Together, a total of 21% (0.8x20% isoaspartic acid+0.06x80% aspartic acid) of aspartic acid residue 30 was found to be present in the form of succinimide in this degraded sample. As a control, the same sample, analyzed using regular 16O water did not show any incorporation of 18O water. By monitoring the amount of 18O-labeled isoaspartic acid and aspartic acid over time under both denaturing and native conditions at pH 8.2, we found that, at denaturing conditions, succinimide at light chain residue 30 hydrolyzed very rapidly (in less than 5 s), but slower (succinimide half-life of approximately 6 h) under native conditions. We also found that, under denaturing conditions, succinimide hydrolyzed at an isoaspartic acid/aspartic acid ratio of 3.5:1, but hydrolyzed almost exclusively to aspartic acid under native conditions. This finding indicates that protein structure plays an important role in the kinetics of succinimide hydrolysis as well as in the generation of the hydrolysis products isoaspartic acid and aspartic acid.     

An improved method for magnetic identification and localization of cracks in conductors

A SQUID magnetometer can be used to measure the magnetic field produced by flaws in a two-dimensional, conducting plate carrying a current. Identification of the flaw-induced magnetic field is difficult because of the large magnetic field associated with the edges of the plate and the current in the leads that connect the plate to the power supply. We have developed a technique by which the wire and edge fields can be cancelled prior to mapping the magnetic field. In this technique, a similar unflawed conducting sheet is placed adjacent to the flawed plate, with a connection between the sheet and the plate at one edge, and with the opposite edges of the sheet and of the plate connected to the two conductors of a coaxial cable. Thus, an applied current will flow along one conductor of the cable, across the cancelling sheet, cross into the flawed plate, return along the plate, and then return to the power supply along the other conductor of the coaxial cable. As a result of this geometry, there is no magnetic field from the lead-in wires because they are coaxial, and the magnetic field due to the edges of the plate is cancelled by the opposing magnetic field of the edges in the adjacent sheet. The extent of cancellation is determined primarily by the separation between the plate and the cancelling sheet, by the thickness of the plate, and by macroscopic inhomogeneities in their electrical conductivities.     

动态载荷识别中的模态确定方法研究

提出了模态选取概念，这一概念比目前所采用的模态截断概念合理；在此基础上提出了反分析中模态选取的准则，并给出了相应的公式。大量算例表明，采用本文提出的准则和公式可以防止因模态选取不当而产生的伪解，避免计算中的数值病态，明显提高了动态载荷识别的成功率和精度。     

The propagation of faults in process plants: 10, fault tree synthesis-2

An interactive, computer-based facility has been developed for the investigation of fault propagation in process plants, including fault tree synthesis, which is embodied in the FAULTFINDER code. The general development and status of the work and the modelling are described in an overview paper and work on dividers and headers, on trip systems and on fault tree synthesis in further companion papers. This paper describes the treatment of control systems in the methodology. Control loops are integral to the whole pattern of operation of the plant. They tend to be a central feature of, and to dictate the form of, manually constructed fault trees. It is desirable that this feature be reflected in automatically synthesised trees also. Further, it is found in practice that it is necessary to treat control loops as a special feature in order to obtain correct trees. Characteristic features of the methodology developed include systematic decomposition of the control system; special features of the modelling of the control loop units; use of control loop templates; and additional rules for handling hierarchial and other complex control systems.     

Diagnostic system for identification of accident scenarios in nuclear power plants using artificial neural networks

This paper presents the work carried out towards developing a diagnostic system for the identification of accident scenarios in 220 MWe Indian PHWRs. The objective of this study is to develop a methodology based on artificial neural networks (ANNs), which assists in identifying a transient quickly and suggests the operator to initiate the corrective actions during abnormal operations of the reactor. An operator support system, known as symptom-based diagnostic system (SBDS), has been developed using ANN that diagnoses the transients based on reactor process parameters, and continuously displays the status of the reactor. As a pilot study, the large break loss of coolant accident (LOCA) with and without the emergency core cooling system (ECCS) in reactor headers has been considered. Several break scenarios of large break LOCA have been analyzed. The time-dependent transient data have been generated using the RELAP5 thermal hydraulic code assuming an equilibrium core, which conforms to a realistic estimation. The diagnostic results obtained from the ANN study are satisfactory. These results have been incorporated in the SBDS software for operator assistance. A few important outputs of the SBDS have been discussed in this paper.     

Hydrodynamic and mass transfer evaluation of post-combustion CO2 capture process for power plants

Clean Technologies and Environmental Policy - The present work is a comparative evaluation on CO2 capture process post-combustion by chemical absorption with alkanolamines, of three Mexican power...     

A new method for guiding process flexibility investment: flexibility fit index

Flexibility enables manufacturing firms to respond efficiently to changes in the environment. Many firms make great efforts to increase their manufacturing flexibility to remain competitive in today's turbulent market. However, it is not true to say that the more flexible the better, because the cost of flexibility investment is high, and the capital for flexibility investment is limited. In this paper, we present a new method to guide process flexibility investment by developing a flexibility fit index. Taking demand changes into account, our method first defines a measure to quantify the requirement level of process flexibility. Then, a flexibility fit index is defined, which specifically identifies where flexibility is insufficient and where flexibility is surplus for a manufacturing system operating in a changing environment. The proposed fit index is objective and dimensionless, and so can be used more universally than previous subjective or non-dimensionless measures proposed in the literature. A set of simulation experiments shows that the proposed method can better guide flexibility investment by indicating the system structure which fits best with a given business situation, and other measures that ignore demand information may lead to over-investment or adding links that bring little benefit.     

Digital Logic and Arithmetic: Background for Interfacing Microcomputers

In order to effectively plan and develop projects involving microcomputers, the industrial engineer requires background information on number systems, binary arithmetic, and binary logic. In this tutorial article, a basic introduction to these topics is provided. Specific topics include: positional number systems, conversion between number systems, addition and subtraction of binary numbers, the two's complement of negative numbers, the ASCII and Gray codes, the basic logic functions (AND, OR, NOT, NAND, NOR, XOR), and some applications of basic logic functions, including a decoder, an adder, and a binary latch. This is the first of an integrated series of articles dealing with concepts and techniques for interfacing microcomputers to industrial devices.