Publications
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
November 20, 2017
Journal Article
Published in:
Climatic Change, 20 November 2017, https://doi.org/10.1007/s10584-017-2114-x
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.
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
November 13, 2017
Journal Article
Published in:
bioRxiv preprint doi: https://doi.org/10.1101/218818, 13 November 2017.
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.
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
November 8, 2017
Conference Paper
Published in:
IEEE 9th Latin-American Conf. on Communications, LATINCOM, 8-10 November 2017.
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R&D group:
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.
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)
November 3, 2017
Project Report
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.
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)
November 2, 2017
Project Report
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.
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
November 2, 2017
Project Report
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.
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
November 1, 2017
Journal Article
Published in:
IEEE J. Sel. Top. Quantum Electron., Vol. 23, No. 6, November/December 2017, 1200413.
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R&D area:
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.
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
October 30, 2017
Journal Article
Published in:
Opt. Express, Vol. 25, No. 22, 30 October 2017, pp. 27543-27550.
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R&D area:
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.
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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UAS weather research roadmap
October 23, 2017
Project Report
Published in:
MIT Lincoln Laboratory Report ATC-438
Topic:
R&D area:
Summary
Unmanned Aircraft System (UAS) operations in the National Airspace System (NAS) are rapidly increasing, and the trend is expected to continue as regulations are refined to allow broader access to the airspace. The unique characteristics of UAS (e.g., extensive operations in populated areas at altitudes below 500 feet, speed capability, and control systems) may drive the need for new and unique operational strategies, many of which are highly dependent on weather conditions. The objective of this study is to identify information gaps in the ability of current weather products to meet the needs of UAS operations, and provide a roadmap of research required to fill the gaps. There are several trends in the information gaps that surfaced repeatedly. A key item is the availability of weather observations, and forecasts tailored for on-airport operations are not necessarily sufficient for off-airport operations. Surveyed users indicated that airport-specific weather information (e.g., METAR, TAFs, etc.) do not readily translate to conditions at remote launch locations, which may be 10-30 miles from the nearest airport, and are influenced by local terrain, vegetation, and water sources. Moreover, the results show significantly less weather information available to support low-altitude flight than for typical manned-flight profiles. Beyond Visual Line of Sight (BVLOS) operations are found to have higher need for weather forecasts, uncertainty information, and contingency planning than Visual Line of Sight (VLOS) operations. Furthermore, the study identifies specific gaps related to how the airspace should be managed to mitigate safety and efficiency impacts to UAS operations. The research roadmap is composed of research recommendations that are derived from the aforementioned weather information gaps. In total, there are 14 specific recommendations that define the roadmap. The first two recommendations are not explicitly tied to specific gaps; rather they are based on lessons learned through the course of research in this study. The remaining recommendations are ordered such that their priority is based on their overall significance to the operation, the maturity of the operation, and any dependence among other recommendations.
Summary
Unmanned Aircraft System (UAS) operations in the National Airspace System (NAS) are rapidly increasing, and the trend is expected to continue as regulations are refined to allow broader access to the airspace. The unique characteristics of UAS (e.g., extensive operations in populated areas at altitudes below 500 feet, speed capability...
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Towards a universal CDAR device: a high performance adapter-based inline media encryptor
October 23, 2017
Conference Paper
Published in:
MILCOM 2017, 23-25 October 2017.
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R&D area:
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Summary
As the rate at which digital data is generated continues to grow, so does the need to ensure that data can be stored securely. The use of an NSA-certified Inline Media Encryptor (IME) is often required to protect classified data, as its security properties can be fully analyzed and certified with minimal coupling to the environment in which it is embedded. However, these devices are historically purpose-built and must often be redesigned and recertified for each target system. This tedious and costly (but necessary) process limits the ability for an information system architect to leverage advances made in storage technology. Our universal Classified Data At Rest (CDAR) architecture represents a modular approach to reduce this burden and maximize interface flexibility. The core module is designed around NVMe, a high-performance storage interface built directly on PCIe. Interfacing with non-NVMe interfaces such as SATA is achieved with adapters which are outside the certification boundary and therefore can be less costly and leverage rapidly evolving commercial technology. This work includes an analysis for both the functionality and security of this architecture. A prototype was developed with peak throughput of 23.9 Gb/s at a power consumption of 8.5W, making it suitable for a wide range of storage applications.
Summary
As the rate at which digital data is generated continues to grow, so does the need to ensure that data can be stored securely. The use of an NSA-certified Inline Media Encryptor (IME) is often required to protect classified data, as its security properties can be fully analyzed and certified...
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