Academic Appointments


  • Adjunct Professor, Civil and Environmental Engineering

Administrative Appointments


  • Executive Director, ProbabilityManagement.org (2006 - Present)
  • Fellow, Cambridge University, Judge Business School (2006 - Present)

2020-21 Courses


All Publications


  • Characterization of Historical Methane Occurrence Frequencies from U.S. Underground Natural Gas Storage Facilities with Implications for Risk Management, Operations, and Regulatory Policy. Risk analysis : an official publication of the Society for Risk Analysis Schultz, R. A., Hubbard, D. W., Evans, D. J., Savage, S. L. 2019

    Abstract

    Defining a baseline for the frequency of occurrences at underground natural gas storage facilities is critical to maintaining safe operation and to the development of appropriate risk management plans and regulatory approaches. Currently used frequency-estimation methods are reviewed and broadened in this article to include critical factors of cause, severity, and uncertainty that contribute to risk. A Bayesian probabilistic analysis characterizes the aleatoric historical occurrence frequencies given imperfect sampling. Frequencies for the three main storage facility types in the United States (depleted oil-and-gas field storage, aquifer storage, solution-mined salt cavern storage) are generally on the order of 3 to 9 * 10-2 occurrences, of all causes (surface, well integrity, subsurface integrity) and severities (nuisance, serious, catastrophic), per facility-year. Loss of well integrity is associated with many, but not all, occurrences either within the subsurface or from there up to the surface. The probability of one serious or catastrophic leakage occurrence to the ground surface within the next 10 years, assuming constant number of facilities, is approximately 0.1-0.3% for any facility type. Storage operators and industry regulators can use occurrence frequencies, their associated probabilities and uncertainties, and forecasts of severity magnitudes to better prioritize resources, establish a baseline against which progress toward achieving a reduction target could be measured, and develop more effective mitigation/monitoring/reduction programs in a risk management plan.

    View details for DOI 10.1111/risa.13417

    View details for PubMedID 31691334

  • PROBABILISTIC DESIGN OF SUSTAINABLE REINFORCED CONCRETE INFRASTRUCTURE REPAIRS USING SIPMATH Zirps, M., Lepech, M., Savage, S., IEEE IEEE. 2019: 3104–15
  • Probability Management 2.0 OR/MS Today Savage, S. L., Kirmse, M., et al 2014; 41 (5)
  • Probability Management in Financial Planning Government Finance Review. Savage, S. L., Kavanagh, S., et al 2014
  • Teaching Modern Portfolio Theory to 10-year-olds OR/MS Today Savage, S. L. 2014; 41 (5)
  • Cost vs. Risk in Defense Portfolios Bulletin of Military Operations Research Savage, S. L., Fahringer, P., et al 2012
  • Distribution Processing and the Arithmetic of Uncertainty Analytics Magazine Savage, S. L. 2012
  • The Flaw of Averages in Project Management Project Management Institute Savage, S. L., Hinton, J., Thibault, M., Farhinger, P., et al 2011
  • Toward a Consolidated Risk Statement Risk Professional magazine Savage, S. L., Brown, A., et al 2009
  • Until Proven Guilty: False Positives and the War on Terror Chance magazine Savage, S. L., Wainer, H., et al 2008; 21 (1)
  • Interactive simulation 2006 Winter Simulation Conference Savage, S. IEEE. 2006: 2293–2293
  • Probability Management OR/MS Today Savage, S. L., Scholtes, S., Zweidler, D., et al 2006; Volume 33 (1)
  • Some Gratuitous Inflammatory Remarks on the Accounting Industry Journal of Forensic Accounting Savage, S. L. 2003; IV
  • The flaw of averages HARVARD BUSINESS REVIEW Savage, S. 2002; 80 (11): 20-?
  • Accounting for uncertainty - When the only thing certain is the date. JOURNAL OF PORTFOLIO MANAGEMENT Savage, S., Van Allen, M. 2002; 29 (1): 31-39
  • The Flaw of Averages, Soapbox column , San Jose Mercury News, October 8, 2000. Reprinted in The Stanford Report, November 8, 2000 Savage, S. L. 2000
  • Holistic vs. hole-istic E&P strategies JOURNAL OF PETROLEUM TECHNOLOGY Ball, B. C., Savage, S. L. 1999; 51 (9): 74-?
  • Equivalence of linear deviation about the mean and mean absolute deviation about the mean objective functions OPERATIONS RESEARCH LETTERS Kenyon, C. M., Savage, S., Ball, B. 1999; 24 (4): 181-185
  • Some Theoretical Implications of Local Optimization Mathematical Programming Savage, S. L. 1976; 10 (pp. 354-366)
  • Neighborhood Search Algorithms for Finding Optimal Travelling Salesmen Tours Must be Inefficient Journal of Computer and System Sciences Savage, S. L., Bahchi, A., Weiner, P. 1976; 12 (1)