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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

The HEPCloud Facility: elastic computing for High Energy Physics – The NOvA Use Case

The need for computing in the HEP community follows cycles of peaks and valleys mainly driven by conference dates, accelerator shutdown, holiday schedules, and other factors. Because of this, the classical method of provisioning these resources at providing facilities has drawbacks such as potential overprovisioning. As the appetite for computing increases, however, so does the need to maximize cost efficiency by developing a model for dynamically provisioning resources only when needed. To address this issue, the HEPCloud project was launched by the Fermilab Scientific Computing Division in June 2015. Its goal is to develop a facility that provides a common interface to a variety of resources, including local clusters, grids, high performance computers, and community and commercial Clouds. Initially targeted experiments include CMS and NOvA, as well as other Fermilab stakeholders. In its first phase, the project has demonstrated the use of the “elastic” provisioning model offered by commercial clouds, such as Amazon Web Services. In this model, resources are rented and provisioned automatically over the Internet upon request. In January 2016, the project demonstrated the ability to increase the total amount of global CMS resources by 58,000 cores from 150,000 cores - a 25 percent increase - in preparation for the Recontres de Moriond. In March 2016, the NOvA experiment has also demonstrated resource burst capabilities with an additional 7,300 cores, achieving a scale almost four times as large as the local allocated resources and utilizing the local AWS s3 storage to optimize data handling operations and costs. NOvA was using the same familiar services used for local computations, such as data handling and job submission, in preparation for the Neutrino 2016 conference. In both cases, the cost was contained by the use of the Amazon Spot Instance Market and the Decision Engine, a HEPCloud component that aims at minimizing cost and job interruption. This paper describes the Fermilab HEPCloud Facility and the challenges overcome for the CMS and NOvA communities.

Fuess, S.↗
DOE OSTI2017

Turbo FRMAC 2016 v. 7.3.0

The Turbo FRMAC (TF) software program is the software implementation of the science and methodologies utilized in the Federal Radiological Monitoring and Assessment Center (FRMAC). The software automates the calculations described in volumes 1 of "The Federal Manual for Assessing Environmental Data during a Radiological Emergency" (2015 version). In the event of the intentional or accidental release of radioactive material, the software is used to guide and govern the response of the Federal, State, Local, and Tribal governments. The manual, upon which the software is based, is unclassified and freely available on the Internet.

Madrid, Gregory J.↗
DOE OSTI2017

Turbo FRMAC 2016 v. 7.2.0

The Turbo FRMAC (TF) software program is the software implementation of the science and methodologies utilized in the Federal Radiological Monitoring and Assessment Center (FRMAC). The software automates the calculations described in volumes 1 of "The Federal Manual for Assessing Environmental Data during a Radiological Emergency" (2015 version). In the event of the intentional or accidental release of radioactive material, the software is used to guide and govern the response of the Federal, State, Local, and Tribal governments. The manual, upon which the software is based, is unclassified and freely available on the Internet.

Madrid, Gregory J.↗
DOE OSTI2014

Turbo FRMAC 2011

The Turbo FRMAC (TF) software automates the calculations described in volumes 1-3 of "The Federal Manual for Assessing Environmental Data During a Radiological Emergency" (2010 version). This software automates the process of assessing radiological data during a Federal Radiological Emergency. The manual upon which the software is based is unclassified and freely available on the Internet. TF takes values generated by field samples or computer dispersion models and assesses the data in a way which is meaningful to a decision maker at a radiological emergency; such as, do radiation values exceed city, state, or federal limits; should the crops be destroyed or can they be utilized; do residents need to be evacuated, sheltered in place, or should another action taken. The software also uses formulas generated by the EPA, FDA, and other federal agencies to generate field observable values specific to the radiological event that can be used to determine where regulatory limit values are exceeded. In addition to these calculations, TF calculates values which indicate how long an emergency worker can work in the contaminated area during a radiological emergency, the dose received from drinking contaminated water or milk, the dose from eating contaminated food, the does expected down or upwind of a given field sample, along with a significant number of other similar radiological health values.

Fulton, John↗
DOE OSTI2017

Big Data, Big Solutions

Data—lots of data—generated in seconds and piling up on the internet, streaming and stored in countless databases. Big data is important for commerce, society and our nation’s security. Yet the volume, velocity, variety and veracity of data is simply too great for any single analyst to make sense of alone. It requires advanced, data-intensive computing. Simply put, data-intensive computing is the use of sophisticated computers to sort through mounds of information and present analysts with solutions in the form of graphics, scenarios, formulas, new hypotheses and more. This scientific capability is foundational to PNNL’s energy, environment and security missions. Senior Scientist and Division Director Bill Pike and his team are developing analytic tools that are used to solve important national challenges, including cyber systems defense, power grid control systems, intelligence analysis, climate change and scientific exploration.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Data-Driven Disease Forecasting

If disease outbreaks could be forecasted like the weather, communities could set up protective measures to mitigate their impact. At Los Alamos National Laboratory, scientists are improving disease-forecasting mathematical models by using clinical data--as well as internet data sources such as Wikipedia, Twitter, and Google--and coupling it with satellite imagery. The goal is to better understanding how diseases spread and, eventually, forecast disease outbreaks.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

FASTMap v. 2010.01

FASTMap is mapping application available for the web or on mobile devices (IOS and Android) that browses geospatial data and produces detailed reports of objects within any area of analysis. FASTMap can access any geospatial dataset. The software can provide immediate access to the selected data through a fully symbolized interactive mapping interface. FASTMap can load arbitrary contours that represent a region of interest and can dynamically identify and geospatially select objects that reside within the region. The software can produce a report listing the objects and aggregations for the region, as well as producing publication quality maps. FASTMap also has the ability to post and maintain authored maps, any GIS data included in the map, areas of interest, as well as any titles, and labels. These defining ingredients of a map are called map contexts. These mao contexts can be instantly broadcast via the internet through any of an infinite number of named channels to small or large numbers of users monitouring any of the channels being posted to, so a user can author a map and immediately share that map with others instantly, whether they are on traditional desktop computer, laptop, mobile tablet or smartphone. Further, users receiving broadcast maps can also alter the maps can also alter the maps, or create new ones and publish back to the channel in a collaborative manner. FASTMap can be configured to access virtually any geospatial data.

Bynum, Leo↗
DOE OSTI2017

Turbo FRMAC 2018

The Turbo FRMAC (TF) software program is the software implementation of the science and methodologies utilized in the Federal Radiological Monitoring and Assessment Center (FRMAC). The software automates the calculations described in volumes 1 of "The Federal Manual for Assessing Environmental Data during a Radiological Emergency" (2015 version). In the event of the intentional or accidental release of radioactive material, the software is used to guide and govern the response of the Federal, State, Local, and Tribal governments. The manual, upon which the software is based, is unclassified and freely available on the Internet.

Fulton, John↗
DOE OSTI2016

Editorial [Special issue on software defined networks and infrastructures, network function virtualisation, autonomous systems and network management]

For last few years, there has been a tremendous growth in data traffic due to high adoption rate of mobile devices and cloud computing. Internet of things (IoT) will stimulate even further growth. This is increasing scale and complexity of telecom/internet service provider (SP) and enterprise data centre (DC) compute and network infrastructures. As a result, managing these large network-compute converged infrastructures is becoming complex and cumbersome. To cope up, network and DC operators are trying to automate network and system operations, administrations and management (OAM) functions. OAM includes all non-functional mechanisms which keep the network running.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

2018 Technology Innovation Program Heartbeat

Heartbeat responds to this problem by focusing instead on the physical behavior of the device being protected, under the hypothesis that malware infection will produce a measurable change in the power consumption state of a device that can be picked up by an outside detector. All code execution uses power, so the execution of malware—especially polymorphic variants—will leave a trace on a power consumption record. The Heartbeat system collects power trace measurements directly from the hardware and so is invisible to malware and resilient to internet service interruption. By collecting power measurement data only during the periodic invocation of a single or of several system functions, Heartbeat will address several challenges that plague current anomaly-based intrusion detection systems and is operational-context agnostic.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Blockchain: Next Generation Supply Chain Security for Energy Infrastructure and NERC Critical Infrastructure Protection (CIP) Compliance

The U.S. power grid is a complex system of systems that requires a secure, reliable and trustworthy global supply chain. This is especially true for the grid’s increasing number of networked energy delivery system (EDS) and industrial control systems (ICS) and associated vendors, distributers, integrators and end users. Grid modernization has increased the use of “smart” energy devices that network, digitize, automate and increasingly converge the cyber-physical energy supply chain. In this Energy Internet of Things (EIoT) environment there is an increasing number of both critical cyber assets as well as data speed and size requirements, creating new cyber supply chain security and North American Electric Reliability Corporation (NERC) CIP compliance challenges for utilities, regulators and vendors. In realization of these goals, improvements are needed in the process and technology to better monitor, audit and realize cyber security and compliance goals in complex EIoT environments. This paper explores how blockchain technology may present a disruptive solution to facilitate NERC CIP compliance and increase the security of the electricity infrastructure supply chain through a cryptographically signed distributed ledger that provides increased data provenance, attribution and auditability.

Blockchain, Cyber security, grid cyber, NERC CIP, ↗
DOE OSTI2018

The EGS Collab Hydroshear Experiment at the Sanford Underground Research Facility – Siting Criteria and Evaluation of Candidate Sites

The objective of the EGS Collab project is to establish a suite of intermediate-scale (~10-20 m) field test beds coupled with stimulation and interwell flow tests to provide a basis to better understand fracture stimulation methods, resulting fracture geometries, and processes that control heat transfer between rock and stimulated fractures. Experiment 1 of the project is being conducted at a depth of ~1.5 km in the Sanford Underground Research Facility (SURF) on the 4850 Level (ft. below the ground surface). The stimulation method planned for Experiment 2 of this project is hydroshearing of an existing natural fracture. In siting this experiment, there are several key geologic criteria that need to be met. These include: 1) the fracture should be least 10 m in length so that it could be intersected by two boreholes that are spaced that far apart; 2) it should be optimally oriented relevant to the stress field so that it is critically stressed; 3) the site should have appropriate stress conditions (not too shallow a depth); 4) the fracture should have sufficient permeability to allow for prestimulation flow testing, but not too high a permeability that would preclude permeability enhancement via shear stimulation; 5) the fracture should not intersect other features (permeable fractures, boreholes, adjacent drifts) that could serve as major leak-off zones; 6) the site should not be complicated by geology (a single lithology would be preferred). In addition, there are logistical criteria that will also influence site selection, including: 1) site availability/access, 2) logistical support, e.g., power, internet, water, operating rail system; 3) drift size and orientation compatible with drilling and site operations; 4) appropriate ground support. There are only two deep levels at SURF that can be accessed by the Yates Shaft: the 4100 and the 4850, so we limited our search to these two levels. Currently, three candidate sites are being evaluated: the existing Experiment 1 site and its surroundings on the West Drift on the 4850 level, and two locations on the 4100 level. This paper will evaluate advantages, disadvantages, and risks associated with these three options at SURF.

EGS Collab, Sanford Underground Research Facility↗
DOE OSTI2019

Explore: An Advanced Computing Agenda for Competitiveness

Over the course of this three-year grant, the Council on Competitiveness (Council) hosted six meetings of its Advanced Computing Roundtable made up of experts from a broad cross section of advanced computing users and manufacturers, and four Advanced Computing for Competitiveness Regional Forums to explore issues related to advanced computing in regions, states and localities. More than two hundred experts, stakeholders and policymakers from the federal and state levels participated in this work and provided their time and expertise to help define the opportunity in advanced computing and the barriers to it reaching its full potential as a game-changing competitive advantage for the United States economy and national security. Building on the insights of the Council’s Advanced Computing Roundtable and findings and recommendations from the four U.S. Department of Energy-supported Forums, the Council has identified several broad policy objectives for the United States related to advanced computing leadership and implementation. The United States must: Compete at the high end of advanced computing. Continue investing to be a technology leader as the world moves toward exascale computing, including in hardware, software and applications. America also must lead in strategic areas like extending Moore’s Law and quantum computing. Improve the ability of HPC-using firms to leverage advanced computing. The Council recommends steps to improve computational skills, increase industry partnerships with laboratories and academia, and expand and strengthen software partnerships. Regulatory agencies also should accelerate efforts to use modeling and simulation within the regulatory process. Expand the number of HPC-using companies in America. Too few firms are able to leverage advanced computing to innovate and compete. Federal, state and local economic development efforts should be utilized to lower barriers and teach small and medium-sized firms, particularly manufacturers, to use advanced modeling, simulation and analytics. Coordinate federal action. Federal agencies should continue to act in a coordinated fashion on advanced computing challenges through the Joint Program Office for Strategic Computing. Leverage HPC to compete in strategic technologies and applications. Leadership in advanced computing is tightly linked to leadership in artificial intelligence, the Internet of Things, cybersecurity, additive manufacturing and other emerging technologies. Public and private sector leaders should collaborate on research and partnership efforts that ensure world-class computing environments for strategic technology leadership.

advanced computing↗
DOE OSTI2019

Soft costs and knowledge pathways in the US solar photovoltaic ecosystem

An enduring puzzle in the US solar industry is that despite substantial reductions in the cost of photovoltaic hardware, soft costs (defined here as all costs not directly driven by hardware) have not done the same (US DOE, 2012). In fact, soft costs now account for the majority of the cost of total cost of installed solar systems, despite decades of efforts by firms and policy-makers to reduce these costs. In this study, we address two questions: a) what drives soft costs within the US solar industry, and b) how do firms gain the knowledge required to address these costs? We address this question through an explorative inductive multiple-case study (e.g., Eisenhardt, 1989; Appleyard, 1996). Our sample consists of 15 actors from across various roles within the industry, including residential and commercial installers (8), distribution intermediaries (3), and business software vendors (4). We conducted extensive interviews with executives at each firm (76 interviews in total), and supplemented this information with archival resources such as press releases, news coverage, analyst reports, and internet articles. This data was synthesized into a comprehensive case for each actor, detailing the activities conducted within each firm, the drivers of soft costs within that firm, and knowledge flows (e.g., new technologies, best practices, etc) within and across firms. We then compared across these cases to identify common patterns in cost and knowledge dynamics. Our study contributes a nuanced perspective on the drivers of soft costs within the solar industry as well as the patterns and mechanisms of knowledge flows within the industry. We find for example that the majority of the soft costs occur at the interface between firms (e.g., utilities, suppliers). We also observe substantive variation in costs across different types of actors and even within firm types (e.g., small vs. large installers). We also provide insight into how firms acquire knowledge and when they are able to apply it in order to reduce these costs. Our data reveal heterogeneity in a) the types of knowledge, and b) the pathways of knowledge flow between the actors in the industry. For example, we observe that distributors and suppliers play a key role in the dissemination of new technologies as well as general management knowledge for smaller firms. In contrast, informal personal networks and internal experimentation appear to be more important for larger firms. We also reveal critical distinctions across markets – e.g., differences in organizational culture that facilitate learning and experimentation more readily in residential vs. commercial markets. Overall, these results contribute preliminary insights into the knowledge dynamics of the solar industry, the persistence of soft costs over time, heterogeneity across firm types and regions, and the effective design of policy to support the solar industry.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2017

Integrated Measurement and Control System for SIF (IMACSS)

The foundation of our biosphere and civilization rests on the food and energy produced by plants using sunlight. Yet currently there is no commercially available technology that can measure, continuously and unattended, plant photosynthesis and physiological stresses in natural environments. To fill this commercial technology gap, a Sun-Induced chlorophyll Fluorescence (SIF) Auto-Measurement Equipment (FAME) that can be applied at scales of leaf, individual plant, or canopy in the field has been developed. The Integrated Measurement and Control System for SIF (IMACSS) is the software used to control the operation of the FAME. IMACSS is a datalogger-operated software which directly controls ALL FUNCTIONS of high-resolution spectrometers for SIF measurements - including the operation temperature and integration time of the Charge-Coupled Device (CCD) detectors of spectrometers, the opening and closing of internal shutter, setting and storing of radiance/irradiance calibration coefficients, wavelength calibration coefficients, and serial port communication parameters, setting and clearing buffer holding capacity, and data retrieval. IMACSS also controls FAME's supporting components (e.g. a motor or supplementary sensors for environmental variables such as air temperature, humidity, soil temperature, moisture content, broadband radiation). This software can flexibly control up to two spectrometers and a motor for multi-target measurements in three designs. It also allows a computer to be linked to FAME's datalogger either directly or remotely (via internet) to monitor and control FAME's operation, set parameters for measurements, and download the data.

GU, Lianhong↗
DOE OSTI2019

Spectral and Microclimate Measurements in Relation to Gold-Standard Methods Field Campaign Report

Arable is an agricultural data and analytics company offering an Internet of things (IOT)-enabled irrigation management tool, weather station, and crop monitor: the Arable Mark. The device synthesizes both climate and plant data to produce actionable insights on natural resource management, mainly commercial agriculture at any scale. Arable collected 11 months of microclimate and radiometric data at the U.S. Department of Energy’s Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) observatory to compare measurements of the Arable Mark to the ARM-SGP gold-standard sensors, and for demonstrating the ease of installation and system value to stakeholders. A member from Arable labs installed the device on January 10, 2018, at the ARM facilities and the site managers were in charge of maintaining the sensors in a clean state until the unit’s removal on January 15, 2019. The sampling was positively uneventful, except for a period during the winter when the device stopped posting data for about one week. The verdict was that the equipment required an external solar panel to stay powered through the shorter days of winter. A solar panel was shipped to the SGP, and the unit came back to full charge to continue sending data for the rest of the sampling period. The main goal of the project is to use the data collected by the Arable Mark and build a model that can establish a close relationship with the current methodologies applied to measure ecosystem response to environmental changes. During the sampling period, our team discovered that there was a drift in some of the meteorological data and also in the radiometry, so all efforts are focused into the development of models that would reduce the errors in the reported values.

Southern Great Plains, evapotranspiration, photosy↗
DOE OSTI2019

Enhancing Operational Performance and Productivity Benefits by Implementing Smart Manufacturing Technologies in Breweries

This paper uses case studies to demonstrate the potential of smart manufacturing (SM) and Internet of Things (IoT) technologies to enhance operational performance and productivity in the industry. The analysis highlights benefits like cost reduction, production flexibility, shorter product times-to-market, energy/water efficiency and environmental impact reduction, and increased productivity. To illustrate the effectiveness of SM and IoT approaches, the authors sought out manufacturers currently implementing or seeking to implement SM & IoT technologies. The authors identified beer brewing (NAICS Code —312120) as a rapidly expanding industry whose members appear eager to implement SM technologies to optimize production lines by revealing bottlenecks and identifying performance-reducing nodes. The paper presents two case studies based on SM and IoT technologies in breweries. It briefly describes a systematic framework introduced elsewhere by the authors and uses it to assess the energy productivity and competitiveness of SM applications in breweries. The paper addresses questions concerning the information and communications technology infrastructure needed to build smart breweries, and how corporations simplify the installation and deployment of SM and IoT components.

Nimbalkar, Sachin U.↗