Risk-Based Engineering

579 Pages·2018·14.148 MB·English

by  Prabhakar V. Varde, Michael G. Pecht

Springer Series in Reliability Engineering
Prabhakar V. Varde · Michael G. Pecht
Risk-Based
Engineering
An Integrated Approach to Complex
Systems—Special Reference to Nuclear
Plants
Springer Series in Reliability Engineering
Series editor
Hoang Pham, Piscataway, NJ, USA
More information about this series at http://www.springer.com/series/6917
Prabhakar V. Varde Michael G. Pecht
(cid:129)
Risk-Based Engineering
An Integrated Approach to Complex
—
Systems Special Reference to Nuclear Plants
123
Prabhakar V.Varde Michael G.Pecht
Research Reactor ServicesDivision, Centerfor AdvancedLife Cycle
HomiBhabhaNational Institute Engineering
Bhabha Atomic Research Centre University of Maryland
Mumbai CollegePark, MA
India USA
ISSN 1614-7839 ISSN 2196-999X (electronic)
SpringerSeries inReliability Engineering
ISBN978-981-13-0088-2 ISBN978-981-13-0090-5 (eBook)
https://doi.org/10.1007/978-981-13-0090-5
LibraryofCongressControlNumber:2018938367
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Preface
This book has been written for the students, researchers, and professionals in the
area of reliability and risk modeling who are looking for a single reference that
could help them solve problems related to practical applications with risk as the
bottom line. Worldwide, there is an increasing trend for application of
risk-informed approach that uses available risk insights, in support of design,
operation, and regulation of complex system.
This book proposes an integrated risk-based engineering approach where the
basic premise is that deterministic and probabilistic aspects are integral to any
problem space, and for holistic solution, these two components need to be treated
suitably for effective modeling and analysis of safety cases. For example, tradi-
tionally,thesafetycommunityhasbeendependingonthedeterministicriskinsights
for design, operations, and regulations employing conservative approach that
addresses the lack of knowledge or data. With the advent of risk assessment
techniques ingeneral and probabilistic risk assessment in particular, it has become
possible to quantify the reliability and safety indicators, like failure frequency,
system unavailability, and core damage frequency. Hence, this work proposes an
integrated risk-based engineering (IRBE) approach which employs qualitative
insights from deterministic and quantitative insights from probabilistic risk
assessment to address the safety aspects in design, operation, and maintenance.
The more popular approach in this context is risk-informed approach which is
targeted to a complex issue of decision-making. In risk-informed approach to
decision-making, particularly in support of regulatory decisions, the insight from
PRA forms one input along with other insights, be it design, operation, and regu-
latory stimulation that relate to available margins, provision of defense in depth,
etc., in support of decision-making. Therefore, this book has a separate Chap. 14
on risk-informed decisions.
The chapters in this book deal with individual topics that support the imple-
mentationofintegratedrisk-basedengineeringasasubject.Therearehostoftopics
which are related or support risk-based decisions; however, in this book, a con-
sciousdecisionhasbeentakeninrespectoflevelofdetailsthatneedtobecovered
v
vi Preface
inindividualchapterandaspectsthataremorerelevantandhelpbuiltthesubjectin
an effective manner.
Chapter 1 introduces the integrated risk-based engineering—the subject of this
book. This chapter explains the premise; that is, deterministic and probabilistic
aspects are integral to any engineering issue, and integrated risk-based approach
seeks to apply them toward reducing uncertainty in results of the analysis. The
increasing application of probabilistic approach in many fields, like structural
engineering, thermal hydraulics in general and passive systems in particular,
nuclear physics, damage and degradation modeling, and surveillance and moni-
toring through implementation of prognostics and health management to reduce
uncertaintyinpredictions,aresomeoftheareaswhereextensivedevelopmentwork
is being performed. As such, the literature shows many applications of risk-based
approach in complex systems. It can be argued that this book discusses a new
approach which might at the outset appear like risk informed; however, it looks at
the subject in a different way where deterministic and probabilistic aspects work
hand in hand and not as separate subject.
Chapter 2 provides a brief overview of risk characterization that is directly
relevanttointerpretationofresultsofriskanalysisforengineeringsystems.Therisk
characterizationdealswithtwoaspects:Thefirstoneisthepresentationofresultsof
reliability studies at system level and risk metrics at plant level, e.g., core damage
frequency which is a quantified statement of level of safety of the plant. Risk
metricsisalsousedinsupportofapplicationofprobabilisticriskassessmentwhere
risk prioritization is performed considering likelihood and consequence associated
with the items under considerations. The second aspect is the presentation of
uncertainty, which also forms part of risk characterization, and this chapter just
touches upon this aspect.
Chapter 3 provides the fundamentals on probabilistic/reliability modeling. This
chapter begins with the discussion on bathtub curve, then introduces major relia-
bility indicators, provides insights into and application of probability distributions,
and further provides models and methods for data interpretationandanalysis. This
chapter is a prerequisite to system-level modeling.
Chapter 4 presents the models and methods for system-level reliability or risk
prediction. In this chapter, the current practices in reliability and risk modeling,
reliability block diagram, failure mode andeffect analysis, and fault tree and event
treeanalysesarepresented.However,thesemethodsarestaticinnatureandthereis
an increasing interest in the development and application of dynamic methods. In
thiscontext,thedynamictools,likeMarkovmodeling,Petrinet,anddynamicfault
tree and event tree, have been introduced in this chapter.
Chapter 5 on life testing discusses the requirements and application of
life-testing approach in support of risk modeling. The basic requirements are to
have an approach where data from field experience are not available, particularly
for new components, and this is where the accelerated life-testing approach pro-
vides insights into the competing failure mechanism as also reliability or life pre-
diction. Accelerated life-testing methods and the related models have been
discussed in this chapter. Life prediction is an essential component of physics of
Preface vii
failureandprognosticsandhealthmanagementforcomponentandsystems.Inthis
context,thischapter,apartfromlifeandfailurerateprediction,isaprerequisitefor
Chaps. 12 and 13.
Chapter 6 on probabilistic risk assessment is central to IRBE. The available
literatureshowsthatprobabilisticapproachesareincreasinglybeingusedindesign
of engineering systems. In this chapter, the major objectives are to develop a risk
model of a complex system that enables (a) quantified statement of risk or con-
versely speaking safety, (b) propagation of uncertainty from component to system
further to plant level, and (c) integration of human factor with the plant model.
InIRBEapproach,theroleofPRAistoprovidethequantifiedestimateofriskand
uncertainty associated with results of the analysis. In this chapter, a conscious
decisionistakentodealwithLevel1PRAindetail,whileLevel2andLevel3PRA
are kept to introductory level as major aspects of risk are addressed using
system-level analysis using statement of core damage frequency for the plant.
Chapter 7 provides an overview of risk-based design methodology to complex
engineering systems. Risk-based design at varying levels of details is being
employedtomany engineering systems. Major elements of risk-based design have
been discussed. In the approach proposed, the complete design approach has been
divided into two parts—higher-level modeling, which deals with plant-level mod-
eling employing PRA framework and lower-level modeling, which requires prob-
abilistic structural analysis methods. Supporting tools and methods, applicable
codes and standards, and a case study have been discussed in brief.
Fatigue is one of the major contributors to mechanical failure and requires
modeling and analysis. There are relatively large uncertainties associated with
model and parameters in conventional fracture analysis methods. In this context,
Chap. 8 introduces probabilistic fracture mechanics as part offracture risk assess-
ment. Characterization of uncertainty is central to any advanced safety methodol-
ogy and this is where probabilistic tools and methods can provide a framework to
quantifyuncertainty primary toaddress the issues related to application and use of
factor of safety.
Uncertainty characterization is a vital component of integrated risk-based
engineering. Chapter 9 provides an overview of uncertainty modeling approaches.
This chapter establishes relevance of uncertainty with risk-based approaches, par-
ticularly the aspects related to decision under uncertainty. A brief overview of
codes, guides, etc. has been provided.
Probabilisticriskassessmentmethodsprovideawaytointegratehumanfactorin
risk modeling, and in this context, human factor or human reliability is a critical
aspect of risk evaluation. Chapter 10 provides an overview of the available meth-
ods, research work being done, and a generic methodology for integrating human
factor in probabilistic risk assessment. Most of the available approaches lack
considerations of a robust human model that can link, apart from cognitive aspect,
the consciousness and conscience phenomenon that governs human behavior,
particularly in emergency conditions and security environment. This chapter
introduces a consciousness, cognition, consciousness, and brain (C3B or CQB)-
basedframework.Inthisapproach,directmeasurementofparametersforassessing
viii Preface
physiological and psychological stresses is proposed apart from the traditional
performance shaping factors. A human reliability model has been proposed based
on the research work performed with field data and simulator environment.
The electronic/electrical controls and logic in a complex system require, apart
fromnormalriskmodelingapproaches,treatmentofsubjectconsideringthespecific
characteristicsandtheconstraintsposedbythesesystems.Chapter11dealswiththe
reliability modeling of digital systems. There are challenges in digital system
modeling,likesoftwarereliability,digitalbeingnewtechnology,non-availabilityof
hardwarefailuredata,andnon-availabilityofagenerallyacceptedmethodology.In
thiscontext,thischapterprovidesthestateoftheartinthedigitalsystemmodeling
andpresentsasimplifiedapproachfordigitalsystemmodeling,wheretheavailable
taxonomy along with conservative approach attempts to provide a solution.
Traditional approach to electronic component reliability employs handbook or
statisticalmethodology.Handbookapproachisbeingdiscouragedbytheexpertsas
the modifying factors may not account for the stresses actually experienced by the
componentinfieldenvironment.Thephysics-of-failure-basedapproachisbasedon
thescience-baseddegradationmodelsforlifeandreliabilityprediction.Chapter12
onphysicsoffailureprovidesabriefoverviewofthismethodologyasthisapproach
hasshownpotentialtobeimprovedoveroftraditionalhandbookapproachwhichis
beingdiscouragedbytheexpertsinthefield.Thischapterintroducesvariousfailure
mechanisms and available physics-of-failure software.
Traditionally, the deterministic approach depends on the periodic surveillance
and maintenance programs to ensure availability of the process- and safety-related
components and systems. There is an increasing trend in employing condition
monitoring methods for predicting failure trends. However, these methods lack
instant of failure prediction with acceptable level of uncertainty. Chapter 13 pro-
vides an overview and potential for application of prognostics and health man-
agement (PHM) to electronics and control systems. The PHM approach provides
tools and methods to predict the prognostic distance that facilitates application of
management offailures in a real-time environment.
Decision-making is a complex process where, apart from technical rationales, a
judgment is required to comprehend the uncertainty in respect of decision alter-
natives.Apartfromthis,decisionmakersarerequiredtoevaluatethelong-termand
short-term consequences. Also, the ethical aspects form an important aspect of
decision-making. Chapter 14 provides research work on the application of inte-
grated risk-based engineering to risk-informed decisions. This chapter attempts to
presentthe role ofPRA, its limitation, and the role of humans and deliberations in
decision-making.
Chapter 15 provides the R&D on the application of risk-based/risk-informed
approachtoreal-time challenges, likelifeextension, testinterval optimization,and
risk monitor. The case studies presented deal with the R&D efforts in developing
risk-based/risk-informed decisions. However, the available literature shows that
risk-based in-service inspection, deployment of risk monitor for nuclear power
plants, test interval, and allowable outage time evaluation as part of technical
Preface ix
specification optimization, etc. are some of the major applications of risk-based
applications.
This book, as the author feels, has been able to develop a new subject, i.e.,
integrated risk-based engineering which can be taught in university-level courses,
and at the same time, risk professional can apply it to address the real-time issues.
It goes without saying that for any project support and encouragement forms a
majordrivingforce.WethankDr.S.Basu,Chairman,AtomicEnergyCommission,
India, for providing the necessary support and encouragement for this project.
Mr. K. N. Vyas, Director, BARC, Mumbai, has unconditionally supported this
work and that provided us the needed driving force for this work. We sincerely
appreciate the help provided by Mr. S. Bhattacharya, Associate Director, Reactor
Group, BARC, Mumbai.
We thank Dr. Michael Osterman, Research Scientist, and Mr. Guru Prasad
Pandian, CALCE, University of Maryland, for providing important modification
andchangesinChap.12onphysicsoffailure.Theauthorsofthisbookwouldlike
to thank Dr. Myeongsu Kang, CALCE, University of Maryland, for providing
valuable input and updates on the original work in respect of Chap. 13 on prog-
nostics and health management. We also, in all sincerity, appreciate the editorial
support from Ms. Cheryl Wurzbacher, Staff at CALCE, University of Maryland.
WethankMr.ArihantJain,ScientistatBARC,inprovidingreviewcommentsand
support in document editing and management. Support from N. S. Joshi, Vivek
Mishra, and other colleagues at BARC and CALCE is also appreciated.
Theauthorsareawarethatlikeanyotherworkthisisnotaperfectpieceofwork,
and by this token, the readers will have comments. We sincerely welcome review
comments on this book in general and specific comments on chapters, and we
assure you that these reviews will help us update/enrich the work.
Mumbai, India Prabhakar V. Varde
College Park, USA Michael G. Pecht