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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 505 records · Page 28
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Prototyping and validating requirements of radiation and nuclear emergency plan simulator

Organizational incapability in developing unrealistic, impractical, inadequate and ambiguous mechanisms of radiological and nuclear emergency preparedness and response plan (EPR) causing emergency plan disorder and severe disasters. These situations resulting from 65.6% of poor definition and unidentified roles and duties of the disaster coordinator. Those unexpected conditions brought huge aftermath to the first responders, operators, workers, patients and community at large. Hence, in this report, we discuss prototyping and validating of Malaysia radiation and nuclear emergency preparedness and response plan simulation model (EPRM). A prototyping technique was required to formalize the simulation model requirements. Prototyping as systems requirements validation was carried on to endorse the correctness of the model itself against the stakeholder’s intensions in resolving those organizational incapability. We have made assumptions for the proposed emergency preparedness and response model (EPRM) through the simulation software. Those assumptions provided a twofold of expected mechanisms, planning and handling of the respective emergency plan as well as in bringing off the hazard involved. This model called RANEPF (Radiation and Nuclear Emergency Planning Framework) simulator demonstrated the training emergency response perquisites rather than the intervention principles alone. The demonstrations involved the determination of the casualties’ absorbed dose range screening and the coordination of the capacity planning of the expected trauma triage. Through user-centred design and sociotechnical approach, RANEPF simulator was strategized and simplified, though certainly it is equally complex.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Characterizing manufacturing sector disruptions with targeted mitigation strategies

It has become clear in recent decades that manufacturing supply chains are increasingly vulnerable to disruptions of varying geographical scales and intensities. These disruptions—whether intentional, accidental, or resulting from natural disasters—cause failures and capacity reductions to manufacturing infrastructure, with lasting effects that can cascade throughout the manufacturing network. An overall lack of understanding of solutions to mitigate disturbances has rendered the challenge of reducing manufacturing supply chain vulnerability even more difficult. Additionally, the variability of disruptions and their impacts complicates policy maker and stakeholder efforts to plan for specific disruptive scenarios. It is necessary to comprehend different kinds of disturbances and group them based on stakeholder-provided metrics to support planning processes and modeling efforts that promote adaptable, resilient manufacturing supply chains. This paper reviews existing methods for risk management in manufacturing supply chains and the economic and environmental impacts of disruptions. In addition, we develop a framework using agglomerative hierarchical clustering to classify disruptions using U.S. manufacturing network data between 2000 and 2021 and characteristic metrics defined in the literature. Our review identifies five groups of disruptions and discusses both general mitigation methods and strategies targeting each identified group. Further, we highlight gaps in the literature related to estimating and including environmental costs in disaster preparedness and mitigation planning. We also discuss the lack of easily available metrics to quantify environmental impacts of disruptions and how such metrics could be included into our methodology.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2018

Dynamic Distribution Voltage Stability Control Using Distributed Energy Resources for Improved Resiliency

The main goal of this paper is to present the development and simulation of a new dynamic voltage stability control technique, with a focus on effective control and coordination of all available reactive power generation resources in a microgrid setting. Both power electronics and synchronous generator based distributed energy resources (DERs), and grid-supporting functions, are considered to accommodate a high penetration of diverse DERs and energy storage by using an enhanced microgrid voltage stabilizer. A systematic controller parameter synthesizing method is employed, and the overall dynamic voltage stability of the system is studied and evaluated with a time-domain dynamic simulation during emergency, hazard and disaster events. The results with the new approach show significant improvements and enhancements on the dynamic voltage profile of the distribution system, leading towards a more resilient grid system with high penetration of diverse DERs during emergency, hazard and disaster events.

Hatipoglu, Kenan↗
DOE OSTI2024

Conditional Experts for Improved Building Damage Assessment Across Satellite Imagery View Angles

Rapid building damage assessment (BDA) is vital in guiding disaster response missions and estimating population distribution across impacted areas. While commercial satellite imagery providers have enabled near-daily monitoring of the Earth, near-realtime assessment of disaster scenarios frequently requires analysis of off-nadir imagery, as satellites are often far from impacted areas for at-nadir post-event imaging to occur Such scenarios are, however, underrepresented in existing BDA datasets and methodologies. With this motivation, we investigate generalization capabilities of current BDA practices across overhead view-angles and strategies for their improvement. Using a labeled dataset of images capturing conflict-related damages, we first train a baseline BDA architecture using imbalanced and balanced datasets with respect to view-angle. Then, we explore conditional convolutions parameterized on image features, image nadir, and their combination as a mechanism for conditioning on view-angles. Experiments demonstrate the limitations of current practice and the potential of conditional mechanisms to increase model robustness to view-angle variations.

Ambrozio Dias, Philipe↗
DOE OSTI2017

Modernizing Distribution System Restoration to Achieve Grid Resiliency Against Extreme Weather Events: An Integrated Solution

Recent severe power outages caused by extreme weather hazards have highlighted the importance and urgency of improving the resilience of the electric power grid. As the distribution grids still remain vulnerable to natural disasters, the power industry has focused on methods of restoring distribution systems after disasters in an effective and quick manner. The current distribution system restoration practice for utilities is mainly based on predetermined priorities and tends to be inefficient and suboptimal, and the lack of situational awareness after the hazard significantly delays the restoration process. As a result, customers may experience an extended blackout, which causes large economic loss. On the other hand, the emerging advanced devices and technologies enabled through grid modernization efforts have the potential to improve the distribution system restoration strategy. However, utilizing these resources to aid the utilities in better distribution system restoration decision-making in response to extreme weather events is a challenging task. Therefore, this paper proposes an integrated solution: a distribution system restoration decision support tool designed by leveraging resources developed for grid modernization. We first review the current distribution restoration practice and discuss why it is inadequate in response to extreme weather events. Then we describe how the grid modernization efforts could benefit distribution system restoration, and we propose an integrated solution in the form of a decision support tool to achieve the goal. The advantages of the solution include improving situational awareness of the system damage status and facilitating survivability for customers. The paper provides a comprehensive review of how the existing methodologies in the literature could be leveraged to achieve the key advantages. The benefits of the developed system restoration decision support tool include the optimal and efficient allocation of repair crews and resources, the expediting of the restoration process, and the reduction of outage durations for customers, in response to severe blackouts due to extreme weather hazards.

Automated feeder switch↗
DOE OSTI2018

Multiparameter Outstation Agents for Cyber-Physical Electrical Grid Security and Restoration

This paper describes the development and deployment of cyberaware sensors to monitor the electrical grid and aid with disaster relief. These cyberaware sensors, outstation agents, provide information of multiple parameters simultaneously acting like a black box. The sensors embedded in the outstation agents and the communication architectures are described. These outstation agents are deployed around electrical substations in stationary and mobile platforms. The data collected from the outstation agents is sent to the utility control center providing information of the current status of the electrical grid. In the event of a disaster, the outstation agents make available information on the state of the grid, failures, and resources available to create an effective restoration pathway.

Morales Rodriguez, Marissa↗
DOE OSTI2019

DGs for Service Restoration to Critical Loads in a Secondary Network

During a major outage in a secondary network distribution system, distributed generators (DGs) connected to the primary feeders as well as the secondary network can be used to serve critical loads. This paper proposed a resilience-oriented method to determine restoration strategies for secondary network distribution systems after a major disaster. Technical issues associated with the restoration process are analyzed, including the operation of network protectors, inrush currents caused by the energization of network transformers, synchronization of DGs to the network, and circulating currents among DGs. A look-ahead load restoration framework is proposed, incorporating technical issues associated with secondary networks, limits on DG capacity and generation resources, dynamic constraints, and operational limits. The entire outage duration is divided into a sequence of periods. Restoration strategies can be adjusted at the beginning of each period using the latest information. Numerical simulation of the modified IEEE 342-node low voltage networked test system is performed to validate the effectiveness of the proposed method.

Xu, Yin (ORCID:0000000209459024)↗
DOE OSTI2019

Modeling Load Dynamics to Support Resiliency-based Operations in Low-Inertia Microgrids

Microgrids have repeatedly demonstrated the ability to provide uninterrupted service to critical end-use loads during normal outages, severe weather events, and natural disasters. While their ability to provide critical services is well documented, microgrids present a more dynamic operational environment than grid-connected distribution systems. The dynamics of a microgrid are commonly driven by the high inertia of rotating generators, which are common in many microgrids. In such high-inertia systems, the impact of end-use load dynamics are often not examined. However, with the increased penetration of inverter-based generation with little or no inertia, it is necessary to consider the impact that the dynamics of the end-use loads have on the operations of microgrids, particularly for a resiliency-based operation. These operations include, but are not limited to, switching operations, loss of generating units, and the starting of induction motors. This paper examines the importance of including dynamic models of the end-use load when evaluating the operations of low inertia microgrids, and shows that by properly representing their behavior, it is possible to cost effectively size equipment while supporting resilient operations of critical end-use loads.

Tuffner, Francis K.↗
DOE OSTI2013

Fukushima two year processing update

On March 11, 2011, now two years ago, the magnitude 9.0 Great East Japan earth quake, Tohoku, hit off the Fukushima coast of Japan. This was one of the most powerful earthquakes in recorded history and the most powerful one known to have hit Japan. The ensuing tsunami devastated a huge area resulting in some 25,000 persons confirmed dead or missing. The perfect storm was complete when the tsunami then found the four-reactor, Fukushima- Daiichi Nuclear Station directly in its destructive path. Some 2 million people were evacuated from a fifty mile radius of the area and evaluation and cleanup began. A tremendous effort has been made, by many nationalities, since this time to restore this damaged plant and surrounding area and to return a great deal of the residents to their homes and farm lands. While most of the outcome of this unprecedented natural and manmade disaster was negative, both in Japan and worldwide, there have been some extremely valuable lessons learned and new emergency recovery technologies and systems developed to cope with the aftermath of this disaster. This paper describes new technology developed to selectively remove radioactive materials dangerous to workers, local citizens, and the natural environment from seawater used to cool the damaged reactors at Fukushima. As always, the mother of invention is necessity. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Analyzing Infrastructure Interdependencies Using Network-Of-Networks Modeling

Infrastructure networks play a crucial role in our day-to-day lives, and modeling these infrastructure networks can help decisionmakers prepare for and respond to disruptions such as natural disasters or cyberattacks. Because these infrastructure networks depend on each other, it is not sufficient to model a single network in isolation. We build on previous single-network-modeling techniques to develop a methodology for modeling infrastructure interdependencies as a Network-of-Networks. Using distributionlevel data from a real U.S. city on the power grid, road geometry, and hospital locations, we show how to apply this methodology to modeling three of the U.S. Department of Homeland Security's Critical Infrastructure Sectors: Healthcare, Transportation, and Energy. We also analyze three primary metrics before and after a simulated disaster: 1) impact on hospital access; 2) road network impact with the change in betweenness centrality; 3) electric customer outage. We simulate three different disruptions: 1) road flooding from nearby rivers; 2) a malicious actor targeting the road networks; 3) a malicious actor targeting the electric grid. Finally, we discuss how our methodology can be applied to additional infrastructure networks and types of disruption, and how Artificial Intelligence (AI) techniques may be incorporated into this methodology for further research.

Scherrer, Evan [Drake University, Iowa]↗
DOE OSTI2020

PERSIANN Dynamic Infrared–Rain Rate Model (PDIR) for High-Resolution, Real-Time Satellite Precipitation Estimation

Precipitation measurements with high spatiotemporal resolution are a vital input for hydrometeorological and water resources studies; decision-making in disaster management; and weather, climate, and hydrological forecasting. Moreover, real-time precipitation estimation with high precision is pivotal for the monitoring and managing of catastrophic hydroclimate disasters such as flash floods, which frequently transpire after extreme rainfall. While algorithms that exclusively use satellite infrared data as input are attractive owing to their rich spatiotemporal resolution and near-instantaneous availability, their sole reliance on cloud-top brightness temperature (T b ) readings causes underestimates in wet regions and overestimates in dry regions—this is especially evident over the western contiguous United States (CONUS). We introduce an algorithm, the Precipitation Estimations from Remotely Sensed Information Using Artificial Neural Networks (PERSIANN) Dynamic Infrared–Rain rate model (PDIR), which utilizes climatological data to construct a dynamic (i.e., laterally shifting) T b –rain rate relationship that has several notable advantages over other quantitative precipitation-estimation algorithms and noteworthy skill over the western CONUS. Validation of PDIR over the western CONUS shows a promising degree of skill, notably at the annual scale, where it performs well in comparison to other satellite-based products. Analysis of two extreme landfalling atmospheric rivers show that solely IR-based PDIR performs reasonably well compared to other IR- and PMW-based satellite rainfall products, marking its potential to be effective in real-time monitoring of extreme storms. This research suggests that IR-based algorithms that contain the spatiotemporal richness and near-instantaneous availability needed for rapid natural hazards response may soon contain the skill needed for hydrologic and water resource applications.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Automated Operational Forecasting of Monsoon Low Pressure Systems

Monsoon low pressure systems (LPSs) are the dominant rain-bearing weather system of South Asia, often producing extreme precipitation and hydrological disasters in a region inhabited by nearly two billion people. Despite the importance of these storms, no operational system has automatically identified and tracked LPS in real time in numerical weather prediction model output; many commonly used vortex-tracking algorithms are ill suited for monsoon LPS because of the weak winds and cold cores of these systems. Here, we describe a new system that uses optimized algorithms to identify monsoon LPS in short- to medium-range forecasts from the U.S. Global Ensemble Forecast System (GEFS) and a version of the deterministic Global Forecast System (GFS) adapted and used operationally by the Indian Institute of Tropical Meteorology (IITM). We also assess the historical performance of these models in forecasting South Asian monsoon LPS, comparing this with the performance of the Integrated Forecasting System of the ECMWF. We assess the accuracy of model predictions of LPS genesis, position, intensity, and precipitation rates for forecast lead times of 1–5 days, yielding quantitative information on model biases to guide operational forecasters and disaster managers. The system we introduce here could be extended to other low-latitude regions affected by dynamically weak, heavily precipitating atmospheric vortices that are often not included in tropical cyclone inventories.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Evaluating Ensemble Predictions of South Asian Monsoon Low Pressure System Genesis

Abstract Synoptic-scale vortices known as monsoon low pressure systems (LPSs) frequently produce intense precipitation and hydrological disasters in South Asia, so accurately forecasting LPS genesis is crucial for improving disaster preparedness and response. However, the accuracy of LPS genesis forecasts by numerical weather prediction models has remained unknown. Here, we evaluate the performance of two global ensemble models—the U.S. Global Ensemble Forecast System (GEFS) and the Ensemble Prediction System of the European Centre for Medium-Range Weather Forecasts (ECMWF)—in predicting LPS genesis during the years 2021–22. The GEFS successfully predicted about half the observed LPS genesis events 1–2 days in advance; the ECMWF model captured an additional 10% of observed genesis events. Both models had a false alarm ratio (FAR) of around 50% for 1–2-day lead times. In both ensembles, the control run typically exhibited a higher probability of detection (POD) of observed events and a lower FAR compared to the perturbed ensemble members. However, a consensus forecast, in which genesis is predicted when at least 20% of ensemble members forecast LPS formation, had POD values surpassing those of the control run for all lead times. Moreover, probabilistic predictions of genesis over the Bay of Bengal, where most LPSs form, were skillful, with the fraction of ensemble members predicting LPS formation over a 5-day lead time approximating the observed frequency of genesis, without any adjustment or bias correction.

Suhas, D. L.↗
DOE OSTI2020

Communication-Constrained Expansion Planning for Resilient Distribution Systems

Distributed generation and remotely controlled switches have emerged as important technologies to improve the resiliency of distribution grids against extreme weather-related disturbances. Therefore it becomes important to study how best to place them on the grid in order to meet a resiliency criteria, while minimizing costs and capturing their dependencies on the associated communication systems that sustain their distributed operations. This paper introduces the Optimal Resilient Design Problem for Distribution and Communication Systems (ORDPDC) to address this need. The ORDPDC is formulated as a two-stage stochastic mixed-integer program that captures the physical laws of distribution systems, the communication connectivity of the smart grid components, and a set of scenarios that specifies which components are affected by potential disasters. The paper proposes an exact branch-and-price algorithm for the ORDPDC that features a strong lower bound and a variety of acceleration schemes to address degeneracy. The ORDPDC model and branch-and-price algorithm were evaluated on a variety of test cases with varying disaster intensities and network topologies. The results demonstrate the significant impact of the network topologies on the expansion plans and costs, as well as the computational benefits of the proposed approach.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Advanced Materials and Technologies for Resilient Infrastructure Systems

Infrastructure is largely unnoticed until it breaks down and services fail. This includes water supplies, gas pipelines, bridges and highways, phone lines and cell towers, and the electric grid — all of the complex systems that keep our societies and economies running. The secure and reliable functioning of our nation’s critical infrastructure is required; however, U.S. infrastructures face a rising frequency and severity of natural disasters (Figure 1), and a growing number and sophistication of physical and cyber attacks. With increasing technological and economic progress, infrastructures are growing more interconnected, necessitating new considerations for their security. Recent disasters such as Superstorm Sandy provide profound insights into how non-linear interactions combine with network effects to trigger a cascade of events across interdependent systems.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Federal Emergency Management Agency Mobile Housing Unit Running Gear Testing (Final Report)

The Federal Emergency Management Agency (FEMA) stages manufactured housing units (MHUs) at key locations to be used during disasters when other housing accommodations cannot be arranged for individuals or families. Due to the unpredictability of natural disasters and the limitations of the manufactured housing industry to produce large numbers of MHUs in very short periods of time, it is necessary for FEMA to store a large number of units for many months or years. With these long storage periods come degradation issues with frames, tires, bearing, and braking systems. These types of issues are also of interest to the U.S. Department of Transportation (DOT) Federal Motor Carrier Safety Administration (FMCSA) because regulated carriers normally transport these units and 49 CFR 393.75 Tires specifies tire loading restrictions for manufactured homes. To compare the running gear (tires, brakes, drums, bearings, axles, springs, and spring mounting hardware) currently specified in the 2014 Rugged Based Performance Requirements (RBPR) and the newly recommended running gear specified in the upcoming revision to the RBPR, the Oak Ridge National Laboratory (ORNL) outlined a Longevity Test Plan, which focused on the assessment of component longevity (failure rates by component type). The Test Plan also studied the forces imparted to the MHU from the running gear from interaction with the roadway for both the running gear in the 2014 RBPR and the running gear specified in the upcoming RBPR revision. Since the assessment of component longevity and failures are also issues of concern for FMCSA, both agencies collaborated to support the research presented in this report. The tests and data collection were conducted at the Navistar Proving Grounds (NPG) in New Carlisle (near South Bend), Indiana, during the May-November 2018 period. Four alternatives for the suspension system of a typical three-bedroom MHU were considered in this test. Alternative 0 was the MHU that was selected from the FEMA staging area in Selma, Alabama. Empirical data had shown that, on average, this alternative experiences one tire failure every 150 miles (or 0.0067 tire failures per mile traveled). Before testing, Alternative 0 was equipped with similar running gear hardware, although in new condition and installed following the manufacturer’s specifications. This became the Baseline Unit, or Alternative 1. Another unit, also selected from the FEMA staging area in Selma, Alabama, was equipped with better axles (i.e., axles that were rated for 7,000lbs as opposed to 6,000lbs for the Baseline Unit) and better tires. This became the Upgrade Unit, or Alternative 2. At the end of the Longevity Test, the Upgrade Unit was mounted with radial tires. This became Alternative 3.Alternative 1 (Baseline Unit) had, on average, one tire failure every 251 miles (or 0.0040 tire failures per mile traveled). So, by simply following the correct manufacturer’s specifications for the assembly of the transportation system, a reduction of 41% in the per mile tire failure was achieved. In the same test, Alternative 2 (Upgrade Unit) showed, on average, one tire failure every 728 miles traveled (or 0.0014 tire failure s per mile traveled). When the Upgrade Unit was mounted with radial tires in the last part of the test, no tire failures were observed for the 2,400 miles tested. That is, in the case of the radial tires (Alternative 3) the tire failure was less than one per 2,400 miles traveled (or less than 0.0004 tire failures per mile traveled). The data collected for the Longevity Test showed that the maximum accelerations were registered in all cases at the center of the MHU in the vertical direction. The overall maximum was registered by the Baseline Unit, Alternative 1. If that value is normalized to 100%, then the Upgrade Unit (Alternative 2) showed, on average, 81% at the same location, and Alternative 3 (radial-tire test) 59%. That is, the upgraded transportation system showed a reduction of 19% and 41% in the vertical accelerations transmitted to MHU at its center when regular and radial tires, respectively, were used. As part of the Test Protocol, NPG conducted a visual inspection of the MHUs and transportation system at the end of each test day. ORNL reviewed all the inspection reports in an attempt to determine if there was any difference in the damage that the Baseline and Upgrade MHUs showed during the test. The Upgrade Unit always showed lower accelerations transmitted to the MHU than the Baseline Unit. In most cases, these differences were statistically significant. The FEMA inspection report, conducted by a FEMA certified inspector at the end of the tests, included a shorter list of damaged items for the Baseline Unit than for the Upgrade Unit, although similar type of damages was described for both units. This may be an indication that, although lower than those of the Baseline Unit, the accelerations transmitted by the Upgrade Unit were above the threshold at which MHU elements start to fail.

42 ENGINEERING↗
DOE OSTI2020

COVID-19 and the Power Sector in Southeast Asia: Impacts and Opportunities

The COVID-19 pandemic is unique among the range of threats encountered over the last century, and its specific impacts do not necessarily resemble those of other disasters. In the near term, the pandemic is causing demand shocks, workforce impacts, supply chain complications, and a global, economic contraction with long-term consequences as yet unknown. In contrast, with natural disasters the principal impacts are more acute. These include infrastructure destruction, displaced populations, and often localized economic impact; however, the long-term response to both of these threats–pandemics and destructive forces of nature–requires similar approaches to building short-term and long-term resilience that prepare power sectors for safe and reliable operation during times of disruption.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2019

Emergency Management Situation Report (April 2019)

After a major disaster, federal assistance will not be available for up to 72 hours. The Federal Emergency Management Agency recommends that everybody have an emergency kit ready for an unforeseen disaster. FEMA has published a checklist of recommended items here, but it is important to remember that this is your emergency kit - this is just a basic list of suggestions that should be modified to your personal needs. FEMA recommends that everyone have a three-day kit at home, a one-day kit at work, and a one-day kit in the car. An earthquake cannot be predicted, but it can be prepared for - during an emergency, you will be thankful you took the time to prepare beforehand.

58 GEOSCIENCES↗