ASHRAE 4690-2004 Uncertainty-Based Quantitative Model for Assessing Risks in Existing Buildings《在现有的建筑物中 以评估风险为目的 不确定性为基础的定量模式》.pdf

《ASHRAE 4690-2004 Uncertainty-Based Quantitative Model for Assessing Risks in Existing Buildings《在现有的建筑物中 以评估风险为目的 不确定性为基础的定量模式》.pdf》由会员分享，可在线阅读，更多相关《ASHRAE 4690-2004 Uncertainty-Based Quantitative Model for Assessing Risks in Existing Buildings《在现有的建筑物中 以评估风险为目的 不确定性为基础的定量模式》.pdf（15页珍藏版）》请在麦多课文档分享上搜索。

1、4690 Uncertainty-Based Quantitative Model for Assessing Risks in Existing Buildings T. Agami Reddy, Ph.D., P.E. Member ASHRAE ABSTRACT Risk anabsis involves three interrelated aspects, namely, risk assessment (characterization and estimation of potential adverse efects associated with exposure to ha

2、zards), risk management or mitigation roces of controlling risks or reducing their probability of occurrence by weighing alterna- tives and selecting appropriate action and also by putting in place response and recovery measures should an adverse phenomenon occur), and risk communication to the gene

3、ral public and concerned agencies. The objective of this paper is to propose a conceptual quantitative model for riskassessment in existing buildings that, while being consistent with current financial practice, would allow determination of expected annual monetary cost to recover from various risk.

4、 The meth- odology would thus provide guidance on identifiing the specijc risks that need to be managed most critically. The proposed methodology allows for the perceived importance with which dflerent stakeholders in a building for example, a building owner or the tenants) view the interaction betw

5、een vuinerabie risk targets (occupants, property damage, revenue loss) and building elements (such as civil, direct physical, cybernetic, mechanical and electrical system failure, and operation services) that are affected by different hazard cate- gories. Each risk target is further subdivided into

6、several sub- targets, whileeach hazard category is broken down into hazard events. The anabsis involves (1) assigning conditional fuzzy values (with symmetric triangular membership functions) characterizing the perceived importance of different targets and subtargets to the concerned stakeholdeq (2)

7、 multiplying them with the relevant binary applicability matrix (which is also stakeholder specijc), thus, allowing subtargets to be Jason Fierko Student Member ASHRAE mapped onto hazard categories, (3) multiplying them with historic hazard event probabilities (or absolute annual prob- ability of oc

8、currence of certain hazard events) that depend on such considerations as climate and geographic location of the city, location of building within the city, importance and type of building, and finally, (4) using industry-accepted building specijc financial inputs (such as building replacement cost,

9、net return on investment, number of occupants, insurance- related costs, etc.) to compute expected estimates of monetary risk (along with their uncertainty) to various hazards. We adopt a decision tree diagram approach for greater clarity in visualizing the process as well as the ease that it provid

10、es in performing the sequential calculations. An illustrative solved example pertinent to a large leased ofice building is presented and discussed to better illustrate the entire methodology. Logi- cal improvements and extensions are also pointed out. The methodologyproposed is ofgeneral relevance a

11、nd is not meant exclusively for assessing risk due to extraordinary incidents. RISK ANALYSIS: GENERAL BACKGROUND Risk has different connotations in both everyday and scientific contexts, but all deal with the potential effects of a loss (financial, physical, etc.) caused by an undesired event or haz

12、ard. The analysis of risk can be viewed as a more formal and scientific approach to the well-known Murphys Law (Wang and Roush 2000). Though different sources categorize them a little differently, the formal treatment of risk analysis includes three specific and interlinked aspects (NRC 1983; Haimes

13、 1998; USCG 2001): 1. Risk assessment involves several activities such as identi- sling the sources and nature of the hazards (either natural or T. Agami Reddy is a professor in the Civil, Architectural and Environmental Engineering Department of Drexel University, Philadelphia, Penn. Jason Fierko i

14、s with Ewing Cole, Philadelphia, Penn. 02004 ASHRAE. 21 7 man-made), estimating the likelihood of their occurrence (i.e., quantifying them through subjective or objective prob- abilities), and, finally, evaluating the consequences (mone- tary, human life, etc.) were they to occur. Regardless of the

15、type of potential loss, risk assessment can be one of two types: (i) qualitative, which is based on common sense or tacit knowledge of experienced professionals, and (ii) quantitative, which is based on adopting scientific and statistical approaches. Generally, the former is extensively used either

16、during the early stages of a new threat (such as that associated with recent extraordinary incidents) or when the overall problem is so complex and uncertain in its cause and effects that quantitative methods yield close to mean- ingless results. Quantitative methods, on the other hand, provide grea

17、t accuracy in applications where the hazards are reasonably well-defined in their character, probability of occurrence, and their consequences. Quantitative risk assessment methods are tools based on accepted and standardized mathematical models that rely on real life data as their inputs. This info

18、rmation may come from a random sample, previously available data, or expert opinion. Risk assessment can be used to analyze the risk that is associated with a specific danger or to a whole gamut of hazards. The basis of quantitative risk assessment is that it can be characterized as the product of t

19、he probability of occurrence of an adverse event or hazard multiplied by its consequence. Since both these terms are inherently such that they cannot be quantified exactly, a major issue in quantitative risk assessment is how to simulate, and thereby determine, confidence bands of the uncertainty in

20、 the risk estimates. Very sophisticated probability-based statistical tech- niques have been proposed in the published literature involving traditional probability distributions in conjunction with Monte Carlo and bootstrap techniques (Haas et al. 1999) as well as artificial intelligence meth- ods s

21、uch as fuzzy logic (Hopgood 2001). 2. Riskmanagement is the process of controlling risks, weigh- ing alternatives, and selecting the most appropriate action based on engineering, economic, legal, or political issues. Risk management deals with how best to control or mini- mize the specific identifie

22、d risks through remedial planning and implementation. These include (i) enhanced technical innovations intended to minimize the consequences of a mishap and (ii) increased training to concerned personnel in order to both reduce the likelihood and consequences of a mishap (USCG 2001). Thus, good risk

23、 management and control cannot prevent bad things from happening alto- gether, but they can minimize both the probability of occur- rence as well as the consequences of a hazard. Risk management includes riskresolution, which narrows the set of remedial options (or alternatives) to the most promisin

24、g few by determining their risk leverage factor. This measure of their relative cost-benefit is computed as the difference in 3. risk assessment estimates before and after the implementa- tion of the specific risk action plan or measure divided by its implementation cost (Hall 1998). Risk management

25、 also includes putting in place response and recovery measures. A major natural disas- ter occurs in the U.S. on an average of 10 times/yr with minor disasters being much more frequent (AIA 1999). Once such disasters occur, the community needs to respond immediately and provide relief to those affec

26、ted. Hence, rapid-response relief efforts and longer-term rebuilding assistance processes have to be well thought out and in place beforehand. Such disaster response efforts are typically coordinated by federal agencies, such as the Federal Emergency Management Agency (FEMA), along with national and

27、 local volun- teer organizations. Risk communication can be done both on a long-term or short-term basis and involves informing the concerned people (managers, stakeholders, officials, public, etc.) as to the results of the two previous aspects. For example, at a government agency level, the announc

28、ement of a potential terrorist threat can lead to the implementation of certain immediate mitigation measures such as increased surveil- lance, while on an individual level it can result in people altering their daily habits by, say, becoming more vigilant and/or buying life safety equipment and sto

29、ring food rations. It is clear that all three aspccts are interlinked since measures from one aspect can affect the other two. For example, increased vigilance can deter potential terror- ists and thus lower the probability of occurrence of such an event. As pointed out by Haimes (1998), risk analys

30、is is viewed by some as a separate, independent, and well- defined discipline as a whole. On the other hand, there are others who view this discipline as being a subset of systems engineering that involves (i) improving the decision-making process (involving planning, design, and operation), (ii) im

31、proving the understanding of how the system behaves and interacts with its environment, and (iii) incorporating risk analysis into the decision- making process. Because of the preliminary nature of this study, we shall simply adopt the narrower view of risk analysis, which can, nonetheless, provide

32、useful and relevant tools to a variety ofproblems. Consequently, its widespread appeal has resulted in it becoming a basic operational tool across the physical, engineering, biological, social, environmental, business, and human sciences areas, which in turn has led to an exponential demand for risk

33、 analysts in recent years (Kammen and Hassenzahl 1999). OBJECTIVE AND SCOPE The objective of this study is to propose a conceptual quantitative model for risk assessment in existing buildings that is consistent with current financial practices, which would 218 ASHRAE Transactions: Research provide g

34、uidance on identiing the specific risks that need to be managed most critically in the building under consider- ation. This would involve identifying and quantiing the vari- ous types and categories of hazards in typical buildings and proposing means to deal with their associated uncertainties. The

35、methodology should also explicitly identi the vulnera- bilities or targets of these hazards (such as occupant safety, civil and operating costs, physical damage to a building and its contents, and failure of one or several of the major building systems), as well as consider the subtler fact that dif

36、ferent stakeholders of the building may differ in their perception as to the importance of these vulnerabilities to their businesses. Finally, the consequences of the occurrence of these risks have to be quantified in terms of financial costs consistent with the current business practice of insuring

37、 a building and its occu- pants. The quantitative risk assessment methodology should be simple, but not simplistic. Further, given the lack of previ- ous studies of this sort, it should be flexible enough that it can be refined over time. The emphasis in this study is on devel- oping the conceptual

38、methodology rather than accurate quan- tification of the risks as they pertain to an actual building. This study will be limited to assessing the risks in existing commercial buildings. For a new building in the design phase, there exist numerous additional construction and operation alternatives th

39、at are poorly delineated and understood and whose quantitative effect on the risk values are highly uncer- tain at best at this time. In addition, we shall choose a specific category among existing commercial building stock to focus on during this study. Huang and Franconi (1 999) break up different

40、 commercial building types into twelve major catego- ries: large offices, small offices, large retail stores, small retail stores, schools, hospitals, large hotels, small hotels, fast food restaurants, sit down restaurants, food stores (supermarkets), and warehouses. Of the above choices, this study

41、 focuses on large offices, though the risk analysis methodology suggested can be applied to any building category by suitable modifica- tion of the model inputs. We start with a brief review of traditional areas where risk analysis has been applied, including a review of studies perti- nent to build

42、ings. Subsequently, we describe the methodology, the relevant inputs to the model, how uncertainty has been incorporated, and the calculation procedure. Finally, the meth- odology has been applied to a fictitious building to serve as a case study illustration. RISK ANALYSIS: APPLICATION AREAS Engine

43、ering Recent world events have led leading American engineer- ing societies (such as IEEE, ASCE, ASME, ASHRAE) as well as several federal and state agencies to form expert working groups with the mission to review all aspects of risk analysis as they apply to critical infrastructure systems. For exa

44、mple, in the area of buildings, certain specific aspects, such as IAQ, building systems, and structural integrity, have become the focus of rather extensive risk management efforts by several universities, federal and national agencies, national laborato- ries, and private companies. DeGaspari (2002

45、) describes past and ongoing activities by ASME on managing industrial risk and quotes experts as stating that: 1. risk analysis with financial tools can benefit a companys bottom line and contribute to safety, 2. a full quantitative analysis can cost 10 times as much as a qualitative analysis, and

46、3. fully quantitative risk analysis provides the best bet for opti- mizing plant performance and corporate values for the inspectiodmaintenance investment while addressing safety concerns. Lancaster (2000) investigates the major accidents in the history of engineering and gives reasons why they occu

47、rred. The book gives many statistics for different types of hazards and cost for each type of disaster. Additionally, chapters on human error are also included. Smith (2002) urges that design for terrorists requires a new way of thinking for engineers and the development of new protocols due to the

48、unpredictable and illogical nature of the attack. This is complicated by the lack of scientific data to guide engineers as to how to counter it. There is extensive literature on risk analysis as applied to nuclear power plants, nuclear waste management and trans- portation, as well as more mundane a

49、pplications in mechani- cal engineering. A form of risk analysis that is commonly used in the engineering field is reliability analysis. This particular analytical approach is associated with the probability distri- bution of the time a component or machine will operate before failing (Vose 1996). Reliability has been extensively used in mechanical and power engineering in general and in the field of machine design in particular. It is especially useful in modeling the likelihood of a single component of the machine failing and then deducing the failure risk of several compo- nents p