Uncertainty and Intelligence in Computational Stochastic Mechanics

Classical structural reliability assessment techniques are based on precise and crisp (sharp) definitions of failure and non-failure (survival) of a structure in meeting a set of strength, function and serviceability criteria. These definitions are provided in the form of performance functions and limit state equations. Thus, the criteria provide a dichotomous definition of what real physical situations represent, in the form of abrupt change from structural survival to failure. However, based on observing the failure and survival of real structures according to the serviceability and strength criteria, the transition from a survival state to a failure state and from serviceability criteria to strength criteria are continuous and gradual rather than crisp and abrupt. That is, an entire spectrum of damage or failure levels (grades) is observed during the transition to total collapse. In the process, serviceability criteria are gradually violated with monotonically increasing level of violation, and progressively lead into the strength criteria violation. Classical structural reliability methods correctly and adequately include the ambiguity sources of uncertainty (physical randomness, statistical and modeling uncertainty) by varying amounts. However, they are unable to adequately incorporate the presence of a damage spectrum, and do not consider in their mathematical framework any sources of uncertainty of the vagueness type. Vagueness can be attributed to sources of fuzziness, unclearness, indistinctiveness, sharplessness and grayness; whereas ambiguity can be attributed to nonspecificity, one-to-many relations, variety, generality, diversity and divergence. Using the nomenclature of structural reliability, vagueness and ambiguity can be accounted for in the form of realistic delineation of structural damage based on subjective judgment of engineers. For situations that require decisions under uncertainty with cost/benefit objectives, the risk of failure should depend on the underlying level of damage and the uncertainties associated with its definition. A mathematical model for structural reliability assessment that includes both ambiguity and vagueness types of uncertainty was suggested to result in the likelihood of failure over a damage spectrum. The resulting structural reliability estimates properly represent the continuous transition from serviceability to strength limit states over the ultimate time exposure of the structure. In this section, a structural reliability assessment method based on a fuzzy definition of failure is suggested to meet these practical needs. A failure definition can be developed to indicate the relationship between failure level and structural response. In this fuzzy model, a subjective index is introduced to represent all levels of damage (or failure). This index can be interpreted as either a measure of failure level or a measure of a degree of belief in the occurrence of some performance condition (e.g., failure). The index allows expressing the transition state between complete survival and complete failure for some structural response based on subjective evaluation and judgment

Strategic implementation of infrastructure priority projects: case study in Palestine

A strategy was developed for implementation and management of multisector urban infrastructure projects. The strategy includes risk-based analytical hierarchy process (AHP) for project prioritization that is based on project deliverables and project life-cycle and implementation guidelines. The expert-opinion elicitation process used for this study consists of a variation of the Delphi technique, scenario analysis, civil works, and nuclear industry recommendations. The AHP methodology utilizes a multicriteria decision-making technique that allows the consideration of both objective and subjective factors in obtaining cardinal priority ranking of infrastructure projects. The methodology, which deals with different fields of infrastructure, can incorporate uncertainty in the process and can be implemented using simple spreadsheet format. The methodology was developed for a group of players (methodology implementers

Time-Dependent Reliability of Aging Structures: Overview of Assessment Methods

Reliability assessment of engineered structures is a powerful and useful concept to estimate the structural capacity of withstanding hazardous events during their service lives. Taking into account the time variation of both structural resistance and the external load processes, the structural safety level is dependent on the duration of service period of interest, due to the accumulation of hazards by exposure in time. This paper presents an overview on the nonempirical assessment methods for time-dependent reliability of deteriorating structures. Generally, these methods can be classified into two types, namely simulation-based and analytical methods. The former is usually brute, and is especially suitable for solving high-dimensional reliability problems. Conversely, analytical solutions may improve the calculation efficiency significantly, and offer insights into the reliability problem that otherwise could be difficult to achieve through Monte Carlo simulation. Both the simulation-based and analytical methods will be reviewed in this paper. Furthermore, the application of time-dependent reliability methods in practical engineering is discussed. Recommendations for future research efforts are also presented

From Reliability-Based Design to Resilience-Based Design

Abstract Reliability-based design has been a widely used methodology in the design of engineering structures. For example, the structural design standards in many countries have adopted the load and resistance factor design (LRFD) method. In recent years, the concept of resilience-based design has emerged, which additionally takes into account the posthazard functionality loss and recovery process of a structure. Under this context, the following questions naturally arise: can we establish a linkage between reliability-based design and resilience-based design? Does there exist a simple resilience-based design criterion that takes a similar form of LRFD? This paper addresses these questions, and the answer is “yes”. To this end, a new concept of structural resilience capacity is proposed, which is a generalization of structural load bearing capacity (resistance). The probabilistic characteristics (mean value, variance, probability distribution function) of resilience capacity are derived. Applying the concept of resilience capacity, this paper explicitly shows the relationship between the following four items: time-invariant reliability-, time-invariant resilience-, time-dependent reliability-, and time-dependent resilience-based design methods. Furthermore, an LRFD-like design criterion is proposed for structural resilience-based design, namely, load and resilience capacity factor design (LRCFD), whose applicability is demonstrated through an example. The LRCFD method can also be used, in conjunction with LRFD, to achieve reliability and resilience goals simultaneously of the designed structure.</jats:p

Evaluating knowledge to support climate action: A framework for sustained assessment. report of an independent advisory committee on applied climate assessment.

Author Posting. © American Meteorological Society, 2019. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Weather Climate and Society 11(3), (2019):465-487, doi: 10.1175/WCAS-D-18-0134.1.As states, cities, tribes, and private interests cope with climate damages and seek to increase preparedness and resilience, they will need to navigate myriad choices and options available to them. Making these choices in ways that identify pathways for climate action that support their development objectives will require constructive public dialogue, community participation, and flexible and ongoing access to science- and experience-based knowledge. In 2016, a Federal Advisory Committee (FAC) was convened to recommend how to conduct a sustained National Climate Assessment (NCA) to increase the relevance and usability of assessments for informing action. The FAC was disbanded in 2017, but members and additional experts reconvened to complete the report that is presented here. A key recommendation is establishing a new nonfederal “climate assessment consortium” to increase the role of state/local/tribal government and civil society in assessments. The expanded process would 1) focus on applied problems faced by practitioners, 2) organize sustained partnerships for collaborative learning across similar projects and case studies to identify effective tested practices, and 3) assess and improve knowledge-based methods for project implementation. Specific recommendations include evaluating climate models and data using user-defined metrics; improving benefit–cost assessment and supporting decision-making under uncertainty; and accelerating application of tools and methods such as citizen science, artificial intelligence, indicators, and geospatial analysis. The recommendations are the result of broad consultation and present an ambitious agenda for federal agencies, state/local/tribal jurisdictions, universities and the research sector, professional associations, nongovernmental and community-based organizations, and private-sector firms.This report would not have been possible without the support and participation of numerous organizations and individuals. We thank New York State Governor Andrew M. Cuomo for announcing in his 2018 State of the State agenda that the IAC would be reconvened. The New York State Energy Research and Development Authority (Contract ID 123416), Columbia University’s Earth Institute, and the American Meteorological Society provided essential financial support and much more, including sage advice and moral support from John O’Leary, Shara Mohtadi, Steve Cohen, Alex Halliday, Peter deMenocal, Keith Seitter, Paul Higgins, and Bill Hooke. We thank the attendees of a workshop, generously funded by the Kresge Foundation in November of 2017, that laid a foundation for the idea to establish a civil-society-based assessment consortium. During the course of preparing the report, IAC members consulted with individuals too numerous to list here—state, local, and tribal officials; researchers; experts in nongovernmental and community-based organizations; and professionals in engineering, architecture, public health, adaptation, and other areas. We are so grateful for their time and expertise. We thank the members and staff of the National Academy of Sciences, Engineering, and Medicine’s Committee to Advise the U.S. Global Change Research Program for providing individual comments on preliminary recommendations during several discussions in open sessions of their meetings. The following individuals provided detailed comments on an earlier version of this report, which greatly sharpened our thinking and recommendations: John Balbus, Tom Dietz, Phil Duffy, Baruch Fischhoff, Brenda Hoppe, Melissa Kenney, Linda Mearns, Claudia Nierenberg, Kathleen Segerson, Soroosh Sorooshian, Chris Weaver, and Brian Zuckerman. Mary Black provided insightful copy editing of several versions of the report. We also thank four anonymous reviewers for their effort and care in critiquing and improving the report. It is the dedication, thoughtful feedback, expertise, care, and commitment of all these people and more that not only made this report possible, but allow us all to continue to support smart and insightful actions in a changing climate. We are grateful as authors and as global citizens. Author contributions: RM, SA, KB, MB, AC, JD, PF, KJ, AJ, KK, JK, ML, JM, RP, TR, LS, JS, JW, and DZ were members of the IAC and shared in researching, discussing, drafting, and approving the report. BA, JF, AG, LJ, SJ, PK, RK, AM, RM, JN, WS, JS, PT, GY, and RZ contributed to specific sections of the report.2020-05-2

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries