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(in reverse chronological order)
 ESD-WP-2013-08 Making Infrastructure Procurement Processes more Flexible under Uncertainty
Vivek Sakhrani
Engineering Systems Division
Massachusetts Institute of Technology
Corresponding author, sakhrani@mit.edu
Luke Jordan
Competitive Industries Practice
The World Bank Group
Richard de Neufville
Engineering Systems Division
Massachusetts Institute of Technology
A third to a half of development projects undergo restructuring due to changes in project objectives, scope or other unanticipated changes, therefore requiring schedule extensions, budget additions and rework. Current procurement processes discourage managers from responding strategically by anticipating and preparing for such changes in advance through better information search and design concept evaluation. This paper suggests three principles for making the front-end phases of procurement more flexible - understanding uncertainty, studying system-wide impacts, and phasing designs. A case study analysis of urban water system design in Kabul demonstrates the conceptual and analytical application of these principles.
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ESD-WP-2013-07 The Coming Hangover: Magnified Effects of Sequestration on Research Enterprises
Navid Ghaffarzadegan
Engineering Systems Division
Massachusetts Institute of Technology
John Glenn School of Public Affairs
Ohio State University
Richard C. Larson
Engineering Systems Division
Massachusetts Institute of Technology
Joshua Hawley
John Glenn School of Public Affairs
Ohio State University
As of March 1, 2013 the US government is taking an $85 billion budget cut. Also referred as the “sequestration”, this automatic spending cut policy might continue for several upcoming years and potentially affect many industries, including the research enterprise. The cut is expected to reflect in the budget of federal agencies that support research activities, such as the National Institutes of Health (NIH) and the National Science Foundation (NSF). For a wide range of structural reasons, discussed in this commentary, the impacts of the budget cut on research enterprises can be magnified.
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ESD-WP-2013-06 Too Many Ph.D. Graduates or Too Few Academic Job Openings: The Basic Reproductive Number R0 in Academia
Richard C. Larson
Engineering Systems Division
Massachusetts Institute of Technology
Navid Ghaffarzadegan
Engineering Systems Division
Massachusetts Institute of Technology
Yi Xue
Engineering Systems Division
Massachusetts Institute of Technology
The academic job market has become increasingly competitive for Ph.D. graduates. In this Note we ask the basic question of “Are we producing more Ph.D.’s than needed?” We take a systems approach and offer a “birth rate” perspective: professors graduate Ph.D.’s who later become professors themselves, an analog to how a population grows. We show that the reproduction rate in academia is very high. For example, in engineering, a professor in the U.S. graduates 7.8 new Ph.D.’s during his/her whole career on average, and only one of these graduates can replace the professor’s position. This implies that in a steady state, only 12.8% of Ph.D. graduates can attain academic positions in the U.S. The key insight is that the system in many places is saturated, far beyond capacity to absorb new Ph.D.’s in academia at the rates that they are being produced. Based on the analysis, we discuss policy implications.
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ESD-WP-2013-05 Carbon Efficient Logistics: A Case study in Modal Shift
Peter Oberhofer
PhD Student
Institute for Transport and Logistics Management
WU Vienna
E-mail: Peter.Oberhofer@wu.ac.at
Edgar E Blanco
Research Director
Center for Transportation & Logistics
Massachusetts Institute of Technology
77 Massachusetts Ave, E40-276
Cambridge, MA, 02139, USA
E-mail: eblanco@mit.edu
Corporate sustainability is becoming increasingly important in the development of business strategies. Consequently, transport and logistics operations come under particular scrutiny due to their substantial impact on the environment. The aim of this paper is to illustrate two successful examples where logistics performance is optimized in tandem with a reduction in carbon emission. The selected case study provides documented examples, detailing how GHG reductions can be achieved while improving business efficiency. The following two initiatives of an US company of the paper and packaging producing sector will be presented:
Initiative I:
- The company works closely with their customers to promote rail transport.
- Goods are directly sent from production plants which operate their own railway connection to the customer that is also located along the railway.
- In 2011, the promotion of rail transport on 4 US routes saved 62–72% CO2 emission (1,500-2,300 tons of CO2) compared to trucking. These savings are equivalent to taking 300-450 cars off the road every year.
Initiative II:
- The company uses space-efficient pallets in selected railcars and thereby increases the number of shipped goods.
- Besides optimizing the spatial utilization of the cars, CO2 can be saved by transporting more goods on the same railcar.
- 190 tons of CO2 were saved by using space-efficient pallets in 930 railcars in 2011. This equals the CO2 emission caused by 21,637 gallons of gasoline consumed by road vehicles.
The case study calculations illustrate, step-by-step, how the reductions were estimated, and provide a detailed “road map” for future participants to implement and properly estimate the GHG reductions. Additionally, we also aim to present ‘Carbon Footprinting’ as a useful method of environmental monitoring and reporting and discuss different methodological approaches.
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ESD-WP-2013-04 Heterogeneous Unit Clustering for Efficient Operational Flexibility Modeling for Strategic Models
Bryan S. Palmintier
Engineering Systems Division
Massachusetts Institute of Technology
Cambridge, MA 02139 USA
E-mail: b_p@mit.edu
Mort D. Webster
Engineering Systems Division
Massachusetts Institute of Technology
Cambridge, MA 02139 USA
Phone: 617-253-3901
E-mail: mort@mit.edu
The increasing penetration of wind generation has led to significant improvements in unit commitment models. However, long-term capacity planning methods have not been similarly modified to address the challenges of a system with a large fraction of generation from variable sources. Designing future capacity mixes with adequate flexibility requires an embedded approximation of the unit commitment problem to capture operating constraints. Here we propose a method, based on clustering units, for a simplified unit commitment model with dramatic improvements in solution time that enable its use as a submodel within a capacity expansion framework. Heterogeneous clustering speeds computation by aggregating similar but non-identical units thereby replacing large numbers of binary commitment variables with fewer integers that still capture individual unit decisions and constraints. We demonstrate the trade-off between accuracy and run-time for different levels of aggregation. A numeric example using an ERCOT-based 205-unit system illustrates that careful aggregation introduces errors of 0.05-0.9% across several metrics while providing several orders of magnitude faster solution times (400x) compared to traditional binary formulations and further aggregation increases errors slightly (~2x) with further speedup (2000x). We also compare other simplifications that can provide an additional order of magnitude speed-up for some problems.
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ESD-WP-2013-03 Optimal Selection of Sample Weeks for Approximating the Net Load in Generation Planning Problems
Fernando J. de Sisternes
Engineering Systems Division
Massachusetts Institute of Technology
Cambridge, MA 02139 USA
E-mail: ferds@mit.edu
Mort D. Webster
Engineering Systems Division
Massachusetts Institute of Technology
Cambridge, MA 02139 USA
Phone: 617-253-3901
E-mail: mort@mit.edu
The increasing presence of variable energy resources (VER) in power systems –most notably wind and solar power– demands tools capable of evaluating the flexibility needs to compensate for the resulting variability in the system. Capacity expansion models are needed that embed unit commitment decisions and constraints to account for the interaction between hourly variability and realistic operating constraints. However, the dimensionality of this problem grows proportionally with the time horizon of the load profile used to characterize the system, requiring massive amounts of computing resources. One possible solution to overcome this computational problem is to select a small number of representative weeks, but there is no consistent criterion to select these weeks, or to assess the validity of the approximation. This paper proposes a methodology to optimally select a given number of representative weeks that jointly characterize demand and VER output for capacity planning models aimed at evaluating flexibility needs. It also presents different measures to assess the error between the approximation and the complete time series. Finally, it demonstrates that the proposed methodology yields a valid approximation for unit commitment constraints embedded in long-term planning models.
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ESD-WP-2013-02 Living Close To Highways: Residential Satisfaction and The Influence of (Perceived Changes In) Accessibility and Negative Externalities
Marije Hamersma
Faculty of Spatial Sciences
University of Groningen
PO Box 800
9700 AV Groningen
The Netherlands
Phone: +31-50-363-3875
Fax: +31-50-363-3901
E-mail: m.hamersma@rug.nl
Taede Tillema
Faculty of Spatial Sciences
University of Groningen
PO Box 800
9700 AV Groningen
The Netherlands
Phone: +31-50-363-3875
Fax: +31-50-363-3901
E-mail: t.tillema@rug.nl
Joseph Sussman
Department of Civil and Environmental Engineering
Massachusetts Institute of Technology
77 Massachusetts Avenue
Cambridge, MA 02139
Phone: +1-617-253-4430
Fax: +1-617-258-5942
E-mail: sussman@mit.edu
Residential satisfaction is an important proxy for people´s wellbeing and for relocation behavior. In 2 this paper we focus on gaining insight into the residential satisfaction of households near highways, 3 based on survey data collected among 1,230 respondents in the Netherlands. Using ordinal regression 4 analysis, we studied the effect of accessibility and negative externalities, alongside other contextual 5 factors, on residential satisfaction. Moreover, the objective was to gain first insights into the extent to 6 which plans for road infrastructure adjustments influence residential satisfaction. On average, 90 7 percent of respondents reported to be satisfied with living near the highway. Regarding explanatory 8 characteristics, negative externalities slightly outweigh accessibility aspects. Moreover, subjective 9 evaluations of hindrance appear to have stronger explanatory power than calculated air and noise 10 exposure. Regarding road adjustments, we found that respondents living near locations where a road 11 adjustment has been announced are marginally more satisfied compared to other locations. A reason 12 could be that respondents expect the current situation to improve once the adjustments are finished, 13 for instance by increased accessibility. The overall positive residential satisfaction evaluations near 14 highways may imply that, generally speaking, problems regarding living near highways may be 15 somewhat overstated. Moreover, the notion that the explanatory power of subjective hindrance 16 outperforms calculated exposure levels may give reason to be cautious when making transportation 17 planning decisions based solely on calculations.
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ESD-WP-2013-01 A Systems Thinking Approach to Leading Indicators in the Petrochemical Industry
Nancy Leveson
Professor of Aeronautics and Astronautics and Engineering Systems
Massachusetts Institute of Technology
There are always warning signs before a major accident, but these signs may only be noticeable or interpretable as a leading indicator in hindsight. Before an accident, such “weak signals” are often perceived only as noise. To ask people to “be mindful of weak signals” is asking them to do something that is impossible. There is always a lot of noise and always a lot of signals that do not presage an accident. The problem then becomes how to distinguish the important signals from all the noise. Defining effective leading indicators is a way to accomplish this goal by providing specific clues that people need to look for. Asking people to “look for anything that might be an important sign” is usually asking them to do the impossible.
Almost all of the past effort to identify leading indicators has involved finding a set of generally applicable metrics or signals that presage an accident. Examples of such identified leading indicators are quality and backlog of maintenance, inspection, and corrective action; minor incidents such as leaks or spills, equipment failure rates, and so on. There is commonly a belief—or perhaps, hope—that a small number of such “leading indicators” can identify an increase in risk of an accident. While some general indicators may be useful, large amounts of effort over decades has not provided much progress. The lack of progress may be a sign that such general, industry-wide indicators do not exist or will not be particularly effective in identifying increasing risk. An alternative is to identify leading indicators that are specific to the system being monitored.
This paper proposes an approach to identifying and monitoring system-specific leading indicators and provides some guidance in designing a risk management structure to use such indicators effectively. The approach is based on the STAMP model of accident causation and tools that have been designed to build on that model. STAMP extends current accident causality to include more complex causes than simply component failures and chains of failure events. It incorporates basic principles of systems thinking and is based on systems theory rather than traditional reliability theory. The next section briefly describes STAMP and STPA, the latter being a new hazard analysis technique based on STAMP. Then the proposal for a new approach to generating and managing leading indicators is outlined.
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