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Potential impacts of climate warming and increased summer heat stress on the electric grid: a case study for a large power transformer (LPT) in the Northeast United States

Published in:
Climatic Change, 20 November 2017, https://doi.org/10.1007/s10584-017-2114-x
R&D group:

Summary

Large power transformers (LPTs) are critical yet vulnerable components of the power grid. More frequent and intense heat waves or high temperatures can degrade their operational lifetime and increase the risk of premature failure. Without adequate preparedness, a widespread situation could ultimately lead to prolonged grid disruption and incur excessive economic costs. Here, we investigate the potential impact of climate warming and corresponding shifts in summertime "hot days" on a selected LPT located in the Northeast United States. We apply an analogue method, which detects the occurrence of hot days based on the salient, associated large-scale atmospheric conditions, to assess the risk of future change in their occurrence. Compared with the more conventional approach that relies on climate model simulated daily maximum temperature, the analogue method produces model medians of late twentieth century hot day frequency that are more consistent with observation and have stronger inter-model consensus. Under the climate warming scenarios, multi-model medians of both model daily maximum temperature and the analogue method indicate strong decadal increases in hot day frequency by the late twenty-first century, but the analogue method improves model consensus considerably. The decrease of transformer lifetime with temperature increase is further assessed. The improved inter-model consensus of the analogue method is viewed as a promising step toward providing actionable information for a more stable, reliable, and environmentally responsible national grid.
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Summary

Large power transformers (LPTs) are critical yet vulnerable components of the power grid. More frequent and intense heat waves or high temperatures can degrade their operational lifetime and increase the risk of premature failure. Without adequate preparedness, a widespread situation could ultimately lead to prolonged grid disruption and incur excessive...

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Detecting pathogen exposure during the non-symptomatic incubation period using physiological data

Summary

Early pathogen exposure detection allows better patient care and faster implementation of public health measures (patient isolation, contact tracing). Existing exposure detection most frequently relies on overt clinical symptoms, namely fever, during the infectious prodromal period. We have developed a robust machine learning based method to better detect asymptomatic states during the incubation period using subtle, sub-clinical physiological markers. Starting with highresolution physiological waveform data from non-human primate studies of viral (Ebola, Marburg, Lassa, and Nipah viruses) and bacterial (Y. pestis) exposure, we processed the data to reduce short-term variability and normalize diurnal variations, then provided these to a supervised random forest classification algorithm and post-classifier declaration logic step to reduce false alarms. In most subjects detection is achieved well before the onset of fever; subject cross-validation across exposure studies (varying viruses, exposure routes, animal species, and target dose) lead to 51h mean early detection (at 0.93 area under the receiver-operating characteristic curve [AUCROC]). Evaluating the algorithm against entirely independent datasets for Lassa, Nipah, and Y. pestis exposures un-used in algorithm training and development yields a mean 51h early warning time (at AUCROC=0.95). We discuss which physiological indicators are most informative for early detection and options for extending this capability to limited datasets such as those available from wearable, non-invasive, ECG-based sensors.
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Summary

Early pathogen exposure detection allows better patient care and faster implementation of public health measures (patient isolation, contact tracing). Existing exposure detection most frequently relies on overt clinical symptoms, namely fever, during the infectious prodromal period. We have developed a robust machine learning based method to better detect asymptomatic states...

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Peregrine: 3-D network localization and navigation

Published in:
IEEE 9th Latin-American Conf. on Communications, LATINCOM, 8-10 November 2017.

Summary

Location-aware devices will create new services and applications in emerging fields such as autonomous driving, smart cities, and the Internet of Things. Many existing localization systems rely on anchors such as satellites at known positions which broadcast radio signals. However, such signals may be blocked by obstacles, corrupted by multipath propagation, or provide insufficient localization accuracy. Therefore, ubiquitous localization remains an extremely challenging problem. This paper introduces Peregrine, a 3-D cooperative network localization and navigation (NLN) system. Peregrine nodes are low-cost business-card-sized devices, consisting of a microprocessor, a commercially available ultra-wideband (UWB) radio module, and a small battery. Recently developed distributed algorithms are used in Peregrine to solve the highly interrelated problems of node inference and node activation in real-time, enabling resource efficiency, scalability, and accuracy for NLN. Node inference – based on the recently introduced sigma point belief propagation (SPBP) algorithm – enables spatiotemporal cooperation in realtime and estimates the nodes' positions accurately from UWB distance measurements. A distributed node activation algorithm controls channel access to improve the efficiency and reduce the localization error of the network. Contributions of each algorithmic component to overall system performance are validated through indoor localization experiments. Our results show that Peregrine achieves decimeter-level 3-D position accuracy in a challenging propagation environment.
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Summary

Location-aware devices will create new services and applications in emerging fields such as autonomous driving, smart cities, and the Internet of Things. Many existing localization systems rely on anchors such as satellites at known positions which broadcast radio signals. However, such signals may be blocked by obstacles, corrupted by multipath...

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Preliminary UAS Weather Research Roadmap(1.51 MB)

Published in:
Project Report ATC-438, MIT Lincoln Laboratory

Summary

A companion Lincoln Laboratory report (ATC-437, “Preliminary Weather Information Gaps for UAS Operations”) identified initial gaps in the ability of current weather products to meet the needs of UAS operations. Building off of that work, this report summarizes the development of a proposed initial roadmap for research to fill the gaps that were identified.
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Summary

A companion Lincoln Laboratory report (ATC-437, “Preliminary Weather Information Gaps for UAS Operations”) identified initial gaps in the ability of current weather products to meet the needs of UAS operations. Building off of that work, this report summarizes the development of a proposed initial roadmap for research to fill the...

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Preliminary Weather Information Gap Analysis for UAS Operations(4.88 MB)

Published in:
Project Report ATC-437, MIT Lincoln Laboratory

Summary

Unmanned Aircraft System (UAS) operations in the National Airspace System (NAS) are rapidly increasing. For example, 2017 has seen dramatically increased low altitude UAS usage for disaster relief and by first responders. The ability to carry out these operations, however, can be strongly impacted by adverse weather conditions. This report documents a preliminary quick-look identification and assessment of gaps in current weather decision support for UAS operations.
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Summary

Unmanned Aircraft System (UAS) operations in the National Airspace System (NAS) are rapidly increasing. For example, 2017 has seen dramatically increased low altitude UAS usage for disaster relief and by first responders. The ability to carry out these operations, however, can be strongly impacted by adverse weather conditions. This report...

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Preliminary weather information gap analysis for UAS operations, revision 1

Published in:
MIT Lincoln Laboratory Report ATC-437-REV-1

Summary

Unmanned Aircraft System (UAS) operations in the National Airspace System (NAS) are rapidly increasing. For example, 2017 has seen dramatically increased low altitude UAS usage for disaster relief and by first responders. The ability to carry out these operations, however, can be strongly impacted by adverse weather conditions. This report documents a preliminary quick-look identification and assessment of gaps in current weather decision support for UAS operations. An initial set of surveys and interviews with UAS operators identified 12 major gaps. These gaps were then prioritized based on the importance of the weather phenomena to UAS operations and the current availability of adequate weather information to UAS operators. Low altitude UAS operations are of particular concern. The lack of observations of ceiling, visibility, and winds near most low altitude UAS operational locations causes the validation of numerical weather forecasts of weather conditions for those locations to be the highest priority. Hazardous weather alerting for convective activity and strong surface winds are a major concern for UAS operations that could be addressed in part by access to existing FAA real time conventional aircraft weather products.
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Summary

Unmanned Aircraft System (UAS) operations in the National Airspace System (NAS) are rapidly increasing. For example, 2017 has seen dramatically increased low altitude UAS usage for disaster relief and by first responders. The ability to carry out these operations, however, can be strongly impacted by adverse weather conditions. This report...

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MOVPE growth of LWIR AlInAs/GaInAs/InP quantum cascade lasers: impact of growth and material quality on laser performance

Summary

The quality of epitaxial layers in quantum cascade lasers (QCLs) has a primary impact on QCL performance, and establishing correlations between epitaxial growth and materials properties is of critical importance for continuing improvements. We present an overview of the growth challenges of these complex QCL structures; describe the metalorganic vapor phase epitaxy growth of AlInAs/GaInAs/InP QCL materials; discuss materials properties that impact QCL performance; and investigate various QCL structure modifications and their effects on QCL performance. We demonstrate uncoated buried-heterostructure 9.3-um QCLs with 1.32-W continuous-wave output power and maximum wall plug efficiency (WPE) of 6.8%. This WPE is more than 50% greater than previously reported WPEs for unstrained QCLs emitting at 8.9 um and only 30% below strained QCLs emitting around 9.2 um.
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Summary

The quality of epitaxial layers in quantum cascade lasers (QCLs) has a primary impact on QCL performance, and establishing correlations between epitaxial growth and materials properties is of critical importance for continuing improvements. We present an overview of the growth challenges of these complex QCL structures; describe the metalorganic vapor...

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Photonic lantern kW-class fiber amplifier

Published in:
Opt. Express, Vol. 25, No. 22, 30 October 2017, pp. 27543-27550.

Summary

Pump-limited kW-class operation in a multimode fiber amplifier using adaptive mode control and a photonic lantern front end was achieved. An array of three single-mode fiber inputs was used to adaptively inject the appropriate superposition of input modes in a three-mode gain fiber to achieve the desired mode at the output. Mode fluctuations at high power were compensated by adjusting the relative phase, amplitude, and polarization of the single-mode fiber inputs. The outlook for further power scaling and adaptive-optic compensation is described.
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Summary

Pump-limited kW-class operation in a multimode fiber amplifier using adaptive mode control and a photonic lantern front end was achieved. An array of three single-mode fiber inputs was used to adaptively inject the appropriate superposition of input modes in a three-mode gain fiber to achieve the desired mode at the...

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Designing agility and resilience into embedded systems

Summary

Cyber-Physical Systems (CPS) such as Unmanned Aerial Systems (UAS) sense and actuate their environment in pursuit of a mission. The attack surface of these remotely located, sensing and communicating devices is both large, and exposed to adversarial actors, making mission assurance a challenging problem. While best-practice security policies should be followed, they are rarely enough to guarantee mission success as not all components in the system may be trusted and the properties of the environment (e.g., the RF environment) may be under the control of the attacker. CPS must thus be built with a high degree of resilience to mitigate threats that security cannot alleviate. In this paper, we describe the Agile and Resilient Embedded Systems (ARES) methodology and metric set. The ARES methodology pursues cyber security and resilience (CSR) as high level system properties to be developed in the context of the mission. An analytic process guides system developers in defining mission objectives, examining principal issues, applying CSR technologies, and understanding their interactions.
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Summary

Cyber-Physical Systems (CPS) such as Unmanned Aerial Systems (UAS) sense and actuate their environment in pursuit of a mission. The attack surface of these remotely located, sensing and communicating devices is both large, and exposed to adversarial actors, making mission assurance a challenging problem. While best-practice security policies should be...

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Cloud computing in tactical environments

Summary

Ground personnel at the tactical edge often lack data and analytics that would increase their effectiveness. To address this problem, this work investigates methods to deploy cloud computing capabilities in tactical environments. Our approach is to identify representative applications and to design a system that spans the software/hardware stack to support such applications while optimizing the use of scarce resources. This paper presents our high-level design and the results of initial experiments that indicate the validity of our approach.
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Summary

Ground personnel at the tactical edge often lack data and analytics that would increase their effectiveness. To address this problem, this work investigates methods to deploy cloud computing capabilities in tactical environments. Our approach is to identify representative applications and to design a system that spans the software/hardware stack to...

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