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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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

OPTOM: Optimization of Parabolic Trough - Operations & Maintenance

The US Department of Energy’s SunShot goals look to reduce the cost of Concentrating Solar Power (CSP) technology to 5¢/kWh for baseload plants. This is about a 50% reduction from current costs. To achieve this cost target, a significant reduction in operation and maintenance (O&M) costs of 40 to 50% is likely needed. Advances are needed in the O&M practices of CSP plants if the technology is to achieve the SunShot cost goals. Digitization of plant performance and O&M data has become a new best practice in the world of renewable energy asset management. Owners and operators of large photovoltaic and wind power plants are working to digitize performance and O&M data at their existing assets, to improve their management of the facilities, to increase performance, reduce O&M costs, and lower the overall life cycle cost of ownership. CSP power plants are behind the curve of other technologies on the digitization of plant information to aid in the plant asset management. This project directly addresses the objective of digitizing the O&M data of the solar field, focusing on three areas: 1) creating a framework for sharing data and information, 2) creating a system for monitoring and managing the maintenance of the solar field collectors, and 3) developing analytic tools to identify issues in the solar field. According to the NREL CSP Best Practices Study, the current practice at many CSP plants is to rely on paper lists, spreadsheets, and email for monitoring and managing problems and maintenance in the solar field. The key element to digitize solar field O&M is the creation of a centralized data archive that all users and systems can interface with. This project developed a centralized relational database framework that allows users and applications to access and share data. Conventional power plants utilize Computerized Maintenance Management Systems (CMMSs) to track the corrective, preventive (scheduled), and predictive maintenance of equipment and subsystems in the power plant. CSP plants use these systems in the power block, but while these systems specialize at tracking maintenance on up to thousands of pieces of equipment, they are not well suited for tracking the tens or hundreds of thousands of components in large commercial CSP or photovoltaic solar fields. In this project we developed a new software application referred to as FieldStatus (TM). This is a specialized database program that is used to track the status of each collector and its components. This application is designed to complement the existing CMMS to enable improved tracking and management of maintenance activities in the solar field. One of the major maintenance tasks for solar fields is maintaining the cleanliness of the mirrors. Although seemingly a relatively straight forward task, it has often proven challenging to maintain high levels of cleanliness in an efficient and cost-effective manner. This project developed new tools and metrics for monitoring and optimizing solar field cleaning resources and overall solar field cleanliness.

14 SOLAR ENERGY↗
NASA NTRS1993

Application of capillary fluid management techniques to the design of a phase separating microgravity bioreactor

Manned space missions require the development of compact, efficient, and reliable life support systems. A number of aqueous biological conversion processes are associated with bioregenerative life support systems. Vessels, or bioreactors, capable of supporting these processes in microgravity must be developed. An annular flow bioreactor has been conceived. It has the potential to incorporate containment, phase separation, gas exchange, and illumination into a single vessel. The bioreactor utilizes capillary fluid management techniques and is configured as a cylindrical tube in which a two-phase liquid-gas flow is maintained. Vanes placed around the inner perimeter enhance capillary forces and cause the liquid phase to attach and flow along the interior surface of the tube. No physical barrier is required to complete phase separation. It is shown analytically that liquid film thickness is limited only by vane geometry and that an annular flow bioreactor capable of managing 284 liters would occupy 0.7 cubic m, less than half the volume of a Spacelab experiment rack.

Finger, Barry W.↗
DOE OSTI2011

Sustainable Development and Energy Geotechnology Potential Roles for Geotechnical Engineering

The world is facing unprecedented challenges related to energy resources, global climate change, material use, and waste generation. Failure to address these challenges will inhibit the growth of the developing world and will negatively impact the standard of living and security of future generations in all nations. The solutions to these challenges will require multidisciplinary research across the social and physical sciences and engineering. Although perhaps not always recognized, geotechnical engineering expertise is critical to the solution of many energy and sustainability-related problems. Hence, geotechnical engineers and academicians have opportunity and responsibility to contribute to the solution of these worldwide problems. Research will need to be extended to non-standard issues such as thermal properties of soils; sediment and rock response to extreme conditions and at very long time scales; coupled hydro-chemo-thermo-bio-mechanical processes; positive feedback systems; the development of discontinuities; biological modification of soil properties; spatial variability; and emergent phenomena. Clearly, the challenges facing geotechnical engineering in the future will require a much broader knowledge base than our traditional educational programs provide. The geotechnical engineering curricula, from undergraduate education through continuing professional education, must address the changing needs of a profession that will increasingly be engaged in alternative/renewable energy production; energy efficiency; sustainable design, enhanced and more efficient use of natural resources, waste management, and underground utilization.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1974

Users guide for information retrieval using APL

A Programming Language (APL) is a precise, concise, and powerful computer programming language. Several features make APL useful to managers and other potential computer users. APL is interactive; therefore, the user can communicate with his program or data base in near real-time. This, coupled with the fact that APL has excellent debugging features, reduces program checkout time to minutes or hours rather than days or months. Of particular importance is the fact that APL can be utilized as a management science tool using such techniques as operations research, statistical analysis, and forecasting. The gap between the scientist and the manager could be narrowed by showing how APL can be used to do what the scientists and the manager each need to do, retrieve information. Sometimes, the information needs to be retrieved rapidly. In this case APL is ideally suited for this challenge.

Shapiro, A.↗
DOE OSTI2018

Efficient Public-key Revocation Management for Secure Smart Meter Communications using One-way Cryptographic Accumulators

Advanced Metering Infrastructure (AMI) forms a communication network for the collection of power data from smart meters in Smart Grid. As the communication within an AMI needs to be secure, public-key cryptography can be used to reduce the overhead of key management. However, it still has certain challenges in terms of certificate revocation and management. In particular, distribution and storage of the Certificate Revocation List (CRL), which holds the revoked certificates, is a major challenge due to its overhead. To address this challenge, in this paper, we propose a novel revocation management scheme by utilizing cryptographic accumulators which not only reduces the space requirements for revocation information but also enables convenient distribution of revocation information to all smart meters. We implemented this oneway cryptographic accumulator-based revocation scheme on ns-3 using IEEE 802.11s mesh standard as a model for AMI and demonstrated its superior performance with respect to traditional methods of CRL management through extensive simulations.

42 ENGINEERING↗
NASA NTRS1983

Development of a statewide Landsat digital data base for forest insect damage assessment

A Joint Research Project (JRP) invlving NASA/Goddard Space Flight Center and the Pennsylvania Bureau of Forestry/Division of Forest Pest Management demonstrates the utility of Landsat data for assessing forest insect damage. A major effort within the project has been the creation of map-registered, statewide Landsat digital data base for Pennsylvania. The data base, developed and stored on computers at the Pennsylvania State University Computation Center, contains Landsat imagery, a Landsat-derived forest resource map, and digitized data layers depicting Forest Pest Management District boundaries and county boundaries. A data management front-end system was also developed to provide an interface between the various layers of information within the data base and image analysis software. This front-end system insures than an automated assessment of defoliation damage can be conducted and summarized by geographic area or jurisdiction of interest.

Williams, D. L.↗
DOE OSTI2013

Guidelines for Datacenter Energy Information System

The purpose of this document is to provide structured guidance to data center owners, operators, and designers, to empower them with information on how to specify and procure data center energy information systems (EIS) for managing the energy utilization of their data centers. Data centers are typically energy-intensive facilities that can consume up to 100 times more energy per unit area than a standard office building (FEMP 2013). This guidance facilitates “data-driven decision making,” which will be enabled by following the approach outlined in the guide. This will bring speed, clarity, and objectivity to any energy or asset management decisions because of the ability to monitor and track an energy management project’s performance.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRS2018

Improving Aquatic Plant Management in the California Sacramento-San Joaquin Delta

Management of aquatic weeds in complex watersheds and river systems present many challenges to assessment, planning and implementation of management practices for floating and submerged aquatic invasive plants. The Delta Region Areawide Aquatic Weed Project (DRAAWP), a USDA sponsored area-wide project, is working to enhance planning, decision-making and operational efficiency in the California Sacramento-San Joaquin Delta. Satellite and airborne remote sensing are used map (area coverage and biomass), direct operations, and assess management impacts on plant communities. Archived satellite records going are used to review results from previous climate and management events and aide in developing long-term strategies. Modeling at local and watershed scales provides insight into land-use effects on water quality. Plant growth models informed by remote sensing are being applied spatially across the Delta to balance location and type of aquatic plant, growth response to altered environments, phenology, environmental regulations, and economics in selection of management practices. Initial utilization of remote sensing tools developed for mapping of aquatic invasive weeds improved operational efficiency by focusing limited chemical use to strategic areas with high plant-control impact and incorporating mechanical harvesting when chemical use is restricted. These assessment methods provide a comprehensive and quantitative view of aquatic invasive plants communities in the California Delta, both spatial and temporal, informed by ecological understanding with the objective of improving management and assessment effectiveness.

Aquatic↗
DOE OSTI2013

Assessment of medical waste management at a primary health-care center in Sao Paulo, Brazil

Highlights: Black-Right-Pointing-Pointer Assessment of medical waste management at health-care center before/after intervention. Black-Right-Pointing-Pointer Qualitative and quantitative results of medical waste management plan are presented. Black-Right-Pointing-Pointer Adjustments to comply with regulation were adopted and reduction of waste was observed. Black-Right-Pointing-Pointer The method applied could be useful for similar establishments. - Abstract: According to the Brazilian law, implementation of a Medical Waste Management Plan (MWMP) in health-care units is mandatory, but as far as we know evaluation of such implementation has not taken place yet. The purpose of the present study is to evaluate the improvements deriving from the implementation of a MWMP in a Primary Health-care Center (PHC) located in the city of Sao Paulo, Brazil. The method proposed for evaluation compares the first situation prevailing at this PHC with the situation 1 year after implementation of the MWMP, thus allowing verification of the evolution of the PHC performance. For prior and post-diagnosis, the method was based on: (1) application of a tool (check list) which considered all legal requirements in force; (2) quantification of solid waste subdivided into three categories: infectious waste and sharp devices, recyclable materials and non-recyclable waste; and (3) identification of non-conformity practices. Lack of knowledge on the pertinent legislation by health workers has contributed to non-conformity instances. The legal requirements in force in Brazil today gave origin to a tool (check list) which was utilized in the management of medical waste at the health-care unit studied. This tool resulted into an adequate and simple instrument, required a low investment, allowed collecting data to feed indicators and also conquered the participation of the unit whole staff. Several non-conformities identified in the first diagnosis could be corrected by the instrument utilized. Total waste generation increased 9.8%, but it was possible to reduce the volume of non-recyclable materials (11%) and increase the volume of recyclable materials (4%). It was also possible to segregate organic waste (7%), which was forwarded for production of compost. The rate of infectious waste generation in critical areas decreased from 0.021 to 0.018 kg/procedure. Many improvements have been observed, and now the PHC complies with most of legal requirements, offers periodic training and better biosafety conditions to workers, has reduced the volume of waste sent to sanitary landfills, and has introduced indicators for monitoring its own performance. This evaluation method might subsidize the creation and evaluation of medical waste management plans in similar heath institutions.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Near-Term Electricity Requirement and Emission Implications for Sustainable Aviation Fuel Production with CO 2 -to-Fuels Technologies

Aviation contributed approximately 10% of the U.S. transportation sector's greenhouse gas (GHG) emissions and about 3% of the nation's total GHG production before the coronavirus disease (COVID-19) pandemic (EPA 2022). Unlike the ground transportation sector, which can be decarbonized by using batteries and hydrogen fuel cell powertrain technologies, the technical and economic challenges of aviation electrification open the opportunity for CO 2 utilization (CO2U) using clean power sources. The U.S. government set a goal to produce 3 billion gallons per year of sustainable aviation fuels (SAF) by 2030 and scale up the production to 35 billion gallons per year by 2050 (Bioenergy Technologies Office 2022). In this report, we examine three potential locations, in California, Iowa, and Louisiana, for SAF production using two production pathways that are expected to be available by 2030. We analyze the electricity cost to satisfy 10% of the SAF production potential for the select locations. Specifically, we consider (1) retail electricity cost from the default local utility in each location; (2) physical power purchase agreement (PPA) for renewable power and battery storage hybrid systems with preset prices; (3) financial PPA from a dedicated renewable plant; and (4) estimated real-time pricing (RTP) from the wholesale power market with utility delivery adders. Retail rates are available for the three potential locations; however, the developer should negotiate with the local utility in Iowa for new tariff riders, because the load of the proposed SAF plant (1.4 GW) is significantly higher than the current industrial tariff structure requirement (200 kW). The developers are not able to claim federal credits (i.e., the Inflation Reduction Act of 2022) when sourcing electricity from local utilities. Developers could consider prioritizing physical and financial PPAs as purchase options. While physical PPAs can be imported out of state, this structure imposes availability issues as developers must locate in the same electricity grid regions. Financial PPAs do not have the same location restrictions and provide the same cost savings as physical PPAs, but financial PPAs impose financial risks in the event of system curtailment and grid interruption. RTPs are available for customers in California with flexible load and hourly load management capability; however, utilities in our studied regions in Louisiana and Iowa only offer time-of-use and curtailment programs to incentivize lower energy usage in peak hours. These utilities do not currently offer RTP programs, and the developer may need to have further negotiations with the local utilities to access RTP programs. The results show that purchased electricity prices may range from 2.6 cents/kWh to 7.1 cents/kWh for the three studied plants.

02 PETROLEUM↗
DOE OSTI2019

Advanced Solar and Load Forecasting Incorporating HD Sky Imaging: BNL Phase II Activities (Final Report)

Over the last ten years, lower costs and government incentives for rooftop and utility scale solar photovoltaic (PV) systems have led to a rapid growth in the amount of power generated from this renewable energy source. For example, the cumulative PV generating capacity of 1,160 MW in New York State at the end of 2018 represents a growth of more than 4,000% over the past seven years and almost 400% over the past five years. But increased dependence on this inherently variable energy source introduces the need to anticipate, i.e., forecast, changes in energy production and manage them appropriately. Utilities and grid operators can then use this forecast information to balance changes and maintain stability of the electric grid by adding additional sources or diverting excess supplies for sale or storage, as needed. Current techniques based on persistence modeling are not accurate enough to provide reliable forecasts. With support from the U.S. Department of Energy’s Solar Energy Technology Office (DOE SETO) and the New York Power Authority (NYPA), Brookhaven National Laboratory (BNL), the National Center for Atmospheric Research (NCAR), and the Electric Power Research Institute (EPRI) formed a collaborative team to provide reliable forecasting over a range of time intervals. In addition, the forecasting area was scaled up to about 50 km2, a factor of 20 times larger than previously achieved, so that available solar irradiance could be forecast throughout an entire region including both large generating facilities and distributed rooftop solar arrays. In its role, BNL developed a technology for predicting changes in available solar energy from zero to 30 minutes ahead. This “nowcasting” approach uses inexpensive, off-the-shelf, high definition (HD) imagers with custom software to identify and track the movement of approaching clouds and predict their impact on available solar irradiance. The BNL Nowcasting model improves forecasting accuracy by 20 to 50% over current techniques. Forecasting reliability for low clouds (worst case scenario since they move over solar panels more rapidly than high clouds) was calculated to be 95% accurate for forecast periods of five minute ahead. Reliability decreases with longer forecast time intervals and was calculated to be about 80% for 10 minute forecasts, and about 70% for 20 minutes ahead. Clouds were still reliably tracked by the imager network at 60% accuracy for forecast lead times up to about 30 minutes ahead, and this was determined to be the practical nowcasting limit for low clouds in a network of this scale. This work represents the second phase of a multi-phase effort to develop and deploy solar forecasting at a regional scale so that contributions from distributed rooftop solar resources can be forecast along with solar generating facilities, giving utilities and stakeholders an accurate assessment of future energy production. Additional work is planned to operate the forecasting network in an area upstate New York to assess system reliability under diverse meteorological conditions and to monitor system performance over a full range of seasonal variability.

14 SOLAR ENERGY↗
DOE OSTI2024

Efficient Parallelization of Irregular Applications on GPU Architectures

With the enlarging computation capacity of general Graphics Processing Units (GPUs), leveraging GPUs to accelerate parallel applications has become a critical topic in academia and industry. However, a wide range of irregular applications with the computation-/memory-intensive nature cannot easily achieve high GPU utilization. The challenges mainly involve the following aspects: first, data dependence leads to coarse-grained kernel and inefficient parallelism; second, heavy GPU memory usage may cause frequent memory evictions and extra overhead of I/O; third, specific computation patterns produce memory redundancies; last, workload balance and data reusability conjunctly benefit the overall performance, but there may exist a dynamic trade-off between them. Targeting these challenges, this dissertation proposes multiple optimizations to accelerate two real-world applications: many-body correlation functions to simulate nuclear physics in a large-scale scientific system; the other is the eALS-based matrix factorization recommendation system. To accelerate the calculations of many-body correlation functions, this dissertation presents three frameworks in GPU memory management and multi-GPU scheduling. Firstly, an optimized systematic GPU memory management framework, MemHC, utilizes a series of new memory reduction designs in GPU memory allocation, CPU/GPU communications, and GPU memory oversubscription. Secondly, an enhanced multi-GPU scheduling framework, MICCO, particularly by taking both data dimension (e.g., data reuse and data eviction) and computation dimension into account. MICCO designs a heuristic scheduling algorithm and a machine learning-based regression model to generate the optimal settings of a proposed new concept to manage the trade-off. Thirdly, a locality-aware multi-GPU scheduling framework. This scheduler leverages pipeline batch generation with a looking-ahead strategy by building local dependency graphs for memory transfer reduction and better data reuse, achieving up to 79.92% memory cost reduction and 1.67x speedup. To parallelize the eALS-based recommendation system, this dissertation proposes an efficient CPU/GPU heterogeneous recommendation system, HEALS. HEALS employs newly designed architecture-adaptive data formats to achieve load balance and good data locality on CPU and GPU. To mitigate the data dependence, HEALS presents a CPU/GPU collaboration model for both task parallelism and data parallelism with multiple kernel computation optimizations. In summary, this dissertation efficiently accelerates two typical irregular applications on GPUs by building four frameworks, including CPU/GPU collaboration, GPU memory management, and multi-GPU scheduling.

Wang, Qihan↗
NASA NTRS2005

Variable Gravity Effects on the Cooling Performance of a Single Phase Confined Spray

The objective of this paper is to discuss the testing of a spray cooling experiment designed to be flown on NASA's KC-135 Reduced Gravity Testing Platform. Spray cooling is an example of a thermal management technique that may be utilized in high flux heat acquisition and high thermal energy transport concepts. Many researchers have investigated the utility of spray cooling for the thermal management of devices generating high heat fluxes. However, there has been little research addressing the physics and ultimate performance of spray cooling in a variable gravity environment. An experimental package, consisting of a spray chamber coupled to a fluid delivery loop system, was fabricated for variable gravity flight tests. The spray chamber contains two opposing nozzles spraying on target Indium Tin Oxide (ITO) heaters. These heaters are mounted on glass pedestals, which are part of a sump system to remove unconstrained liquid from the test chamber. Liquid is collected in the sumps and returned to the fluid delivery loop. Thermocouples mounted in and around the pedestals are used to determine both the heat loss through the underside of the IT0 heater and the heat extracted by the spray. A series of flight tests were carried out aboard the KC-135, utilizing the ability of the aircraft to produce various gravity conditions. During the flight tests, for a fixed flow rate, heat input was varied at 20, 30, 50, and 80W with variable gravities of 0.01, 0.16, 0.36, and 1.8g. Flight test data was compared to terrestrial baseline data in addition to analytical and numerical solutions to evaluate the heat transfer in the heater and support structure . There were significant differences observed in the spray cooling performance as a result of variable gravity conditions and heat inputs. In general, the Nussult number at the heater surface was found to increase with decreasing gravity conditions for heat loads greater than 30W.

Michalak, Travis↗
DOE OSTI2018

Integrating geophysical monitoring data into multiphase fluid flow reservoir simulation

Simulation of multiphase flow systems are of critical importance in managing hydrological systems. Flow simulations are affected by a number of factors including structure and flow properties including porosity and permeability as well as the anisotropy and heterogeneity of these properties. In many cases traditional hydrological and reservoir data are highly affected by these parameters, but are not directly sensitive to them. As such modellers often adjust these parameters in an ad hoc manner until solutions numerically converge. Simulation models are generally based on structural data from reflection seismics whose physical flow properties are then populated using geostatistical extrapolation techniques utilizing a sparse number of borehole logs and core analysis. In multiphase systems including enhanced oil recovery and carbon capture and sequestration uncertainties regarding phase-dependent physical properties confounds this challenge further. Geophysical methods provide a means by which to gain an improved understanding of phase distributions in the subsurface. In this paper we will look at applications from active carbon capture and sequestration and enhanced oil recovery applications, as well as synthetic examples. Geophysical data including electromagnetic and gravity are inverted using structural constraints from the reservoir model. Inversions are then mapped into flow properties using calibrated relations such as Archie’s Equation. The coupled models can then be used to both verify and improve on the reservoir flow model which improves it’s predictive power and utility as a management tool.

02 PETROLEUM↗
NASA NTRS2012

Enhancing Cassini Operations & Science Planning Tools

The Cassini team uses a variety of software utilities as they manage and coordinate their mission to Saturn. Most of these tools have been unchanged for many years, and although stability is a virtue for long-lived space missions, there are some less-fragile tools that could greatly benefit from modern improvements. This report shall describe three such upgrades, including their architectural differences and their overall impact. Emphasis is placed on the motivation and rationale behind architectural choices rather than the final product, so as to illuminate the lessons learned and discoveries made.These three enhancements included developing a strategy for migrating Science Planning utilities to a new execution model, rewriting the team's internal portal for ease of use and maintenance, and developing a web-based agenda application for tracking the sequence of files being transmitted to the Cassini spacecraft. Of this set, the first two have been fully completed, while the agenda application is currently in the early prototype stage.

science planning↗
NASA NTRS2019

Evaluating Combinations of Sentinel-2 Data and Machine-Learning Algorithms for Mangrove Mapping in West Africa

Creating a national baseline for natural resources, such as mangrove forests, and monitoring them regularly often requires a consistent and robust methodology. With freely available satellite data archives and cloud computing resources, it is now more accessible to conduct such large-scale monitoring and assessment. Yet, few studies examine the reproducibility of such mangrove monitoring frameworks, especially in terms of generating consistent spatial extent. Our objective was to evaluate a combination of image processing approaches to classify mangrove forests along the coast of Senegal and The Gambia. We used freely available global satellite data (Sentinel-2), and cloud computing platform (Google Earth Engine) to run two machine learning algorithms, random forest (RF), and classification and regression trees (CART). We calibrated and validated the algorithms using 800 reference points collected using high-resolution images. We further re-ran 10 iterations for each algorithm, utilizing unique subsets of the initial training data. While all iterations resulted in thematic mangrove maps with over 90% accuracy, the mangrove extent ranges between 827-2807 km2 for Senegal and 245-1271 km2 for The Gambia with one outlier for each country. We further report "Places of Agreement" (PoA) to identify areas where all iterations for both methods agree (506.6 km2 and 129.6 km2 for Senegal and The Gambia, respectively), thus have a high confidence in predicting mangrove extent. While we acknowledge the time- and cost-effectiveness of such methods for the landscape managers, we recommend utilizing them with utmost caution, as well as post-classification on-the-ground checks, especially for decision making.

Mondal, Pinki↗
DOE OSTI2013

Utilization of Local Law Enforcement Aerial Resources in Consequence Management (CM) Response

During the past decade the U.S. Department of Homeland Security (DHS) was instrumental in enhancing the nation’s ability to detect and prevent a radiological or nuclear attack in the highest risk cities. Under the DHS Securing the Cities initiative, nearly 13,000 personnel in the New York City region have been trained in preventive radiological and nuclear detection operations, and nearly 8,500 pieces of radiological detection equipment have been funded. As part of the preventive radiological/nuclear detection (PRND) mission, several cities have received funding to purchase commercial aerial radiation detection systems. In 2008, the U.S. Department of Energy, National Nuclear Security Administration Aerial Measuring System (AMS) program started providing Mobile Aerial Radiological Surveillance (MARS) training to such assets, resulting in over 150 HAZMAT teams’ officers and pilots from 10 law enforcement organizations and fire departments being trained in the aerial radiation detection. From the beginning, the MARS training course covered both the PRND and consequence management (CM) missions. Even if the law enforcement main focus is PRND, their aerial assets can be utilized in the collection of initial radiation data for post-event radiological CM response. Based on over 50 years of AMS operational experience and information collected during MARS training, this presentation will focus on the concepts of CM response using aerial assets as well as utilizing law enforcement/fire department aerial assets in CM. Also discussed will be the need for establishing closer relationships between local jurisdictions’ aerial radiation detection capabilities and state and local radiation control program directors, radiological health department managers, etc. During radiological events these individuals may become primary experts/advisers to Incident Commanders for radiological emergency response, especially in the early stages of a response. The knowledge of the existence, specific capabilities, and use of local aerial radiation detection systems would be critical in planning the response, even before federal assets arrive on the scene. The relationship between local and federal aerial assets and the potential role for the further use of the MARS training and expanded AMS Reachback capabilities in facilitating such interactions will be discussed.

consequence management, CM, local law enforcement,↗
DOE OSTI2010

Automated detection and analysis of particle beams in laser-plasma accelerator simulations

Numerical simulations of laser-plasma wakefield (particle) accelerators model the acceleration of electrons trapped in plasma oscillations (wakes) left behind when an intense laser pulse propagates through the plasma. The goal of these simulations is to better understand the process involved in plasma wake generation and how electrons are trapped and accelerated by the wake. Understanding of such accelerators, and their development, offer high accelerating gradients, potentially reducing size and cost of new accelerators. One operating regime of interest is where a trapped subset of electrons loads the wake and forms an isolated group of accelerated particles with low spread in momentum and position, desirable characteristics for many applications. The electrons trapped in the wake may be accelerated to high energies, the plasma gradient in the wake reaching up to a gigaelectronvolt per centimeter. High-energy electron accelerators power intense X-ray radiation to terahertz sources, and are used in many applications including medical radiotherapy and imaging. To extract information from the simulation about the quality of the beam, a typical approach is to examine plots of the entire dataset, visually determining the adequate parameters necessary to select a subset of particles, which is then further analyzed. This procedure requires laborious examination of massive data sets over many time steps using several plots, a routine that is unfeasible for large data collections. Demand for automated analysis is growing along with the volume and size of simulations. Current 2D LWFA simulation datasets are typically between 1GB and 100GB in size, but simulations in 3D are of the order of TBs. The increase in the number of datasets and dataset sizes leads to a need for automatic routines to recognize particle patterns as particle bunches (beam of electrons) for subsequent analysis. Because of the growth in dataset size, the application of machine learning techniques for scientific data mining is increasingly considered. In plasma simulations, Bagherjeiran et al. presented a comprehensive report on applying graph-based techniques for orbit classification. They used the KAM classifier to label points and components in single and multiple orbits. Love et al. conducted an image space analysis of coherent structures in plasma simulations. They used a number of segmentation and region-growing techniques to isolate regions of interest in orbit plots. Both approaches analyzed particle accelerator data, targeting the system dynamics in terms of particle orbits. However, they did not address particle dynamics as a function of time or inspected the behavior of bunches of particles. Ruebel et al. addressed the visual analysis of massive laser wakefield acceleration (LWFA) simulation data using interactive procedures to query the data. Sophisticated visualization tools were provided to inspect the data manually. Ruebel et al. have integrated these tools to the visualization and analysis system VisIt, in addition to utilizing efficient data management based on HDF5, H5Part, and the index/query tool FastBit. In Ruebel et al. proposed automatic beam path analysis using a suite of methods to classify particles in simulation data and to analyze their temporal evolution. To enable researchers to accurately define particle beams, the method computes a set of measures based on the path of particles relative to the distance of the particles to a beam. To achieve good performance, this framework uses an analysis pipeline designed to quickly reduce the amount of data that needs to be considered in the actual path distance computation. As part of this process, region-growing methods are utilized to detect particle bunches at single time steps. Efficient data reduction is essential to enable automated analysis of large data sets as described in the next section, where data reduction methods are steered to the particular requirements of our clustering analysis. Previously, we have described the application of a set of algorithms to automate the data analysis and classification of particle beams in the LWFA simulation data, identifying locations with high density of high energy particles. These algorithms detected high density locations (nodes) in each time step, i.e. maximum points on the particle distribution for only one spatial variable. Each node was correlated to a node in previous or later time steps by linking these nodes according to a pruned minimum spanning tree (PMST). We call the PMST representation 'a lifetime diagram', which is a graphical tool to show temporal information of high dense groups of particles in the longitudinal direction for the time series. Electron bunch compactness was described by another step of the processing, designed to partition each time step, using fuzzy clustering, into a fixed number of clusters.

43 PARTICLE ACCELERATORS↗