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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 OSTI2013

A Role-Based Access Control (RBAC) Schema for REAP Web App

This document discusses various issues in implementing a robust access control schema to secure the Reactor Embrittlement Archive Project (REAP) web application. REAP application has been designed to allow different types of users. Consequently, it is vital to ensure that REAP website has a robust security framework in order to prevent intrusion, to protect data and resources from misuse, and protect data from malicious or unintentional modification by users. Various possible alternatives for authentication frameworks in ASP.NET - Windows, Forms, Passport and custom (JOSSO) authentication frameworks are evaluated. It is concluded that Windows Authentication is apt for REAP. Various elements of implementation are discussed with examples.

Klasky, Hilda B.↗
DOE OSTI2013

PVWatts Version 1: Technical Reference

The NREL PVWatts TM calculator is a web application developed by the National Renewable Energy Laboratory (NREL) that estimates the electricity production of a grid-connected photovoltaic system based on a few simple inputs. PVWatts combines a number of sub-models to predict overall system performance, and makes several hidden assumptions about performance parameters. This technical reference details the individual sub-models, documents assumptions and hidden parameters, and explains the sequence of calculations that yield the final system performance estimation.

14 SOLAR ENERGY↗
DOE OSTI2014

Solar Avoided Cost Solution SunShot 6 Final Report

The core objectives of this project were two separate but integrated products, collectively providing game-changing Avoided Cost capabilities. The first was a kit of avoided cost tools and data that any solar provider can use a-lacarte or as a whole. It’s open and easily accessible nature allows the rapid and accurate calculation of avoided cost in whatever context and software that make sense (“Typical and Avoided Cost Tools”). This kit includes a dataset of typical energy rates, costs and usage that can be used for solar prospecting, lead generation and any situation where data about an opportunity is missing or imperfect. The second is a web application and related APIs specifically built for solar providers to radically streamline their lead-to-sale process (“Solar Provider Module”). The typical and Avoided Cost tools are built directly into this, and allow for solar providers to track their opportunities, collaborate with their installers and financiers, and close more sales faster.

14 SOLAR ENERGY↗
DOE OSTI2013

Determine metrics and set targets for soil quality on agriculture residue and energy crop pathways

There are three objectives for this project: 1) support OBP in meeting MYPP stated performance goals for the Sustainability Platform, 2) develop integrated feedstock production system designs that increase total productivity of the land, decrease delivered feedstock cost to the conversion facilities, and increase environmental performance of the production system, and 3) deliver to the bioenergy community robust datasets and flexible analysis tools for establishing sustainable and viable use of agricultural residues and dedicated energy crops. The key project outcome to date has been the development and deployment of a sustainable agricultural residue removal decision support framework. The modeling framework has been used to produce a revised national assessment of sustainable residue removal potential. The national assessment datasets are being used to update national resource assessment supply curves using POLYSIS. The residue removal modeling framework has also been enhanced to support high fidelity sub-field scale sustainable removal analyses. The framework has been deployed through a web application and a mobile application. The mobile application is being used extensively in the field with industry, research, and USDA NRCS partners to support and validate sustainable residue removal decisions. The results detailed in this report have set targets for increasing soil sustainability by focusing on primary soil quality indicators (total organic carbon and erosion) in two agricultural residue management pathways and a dedicated energy crop pathway. The two residue pathway targets were set to, 1) increase residue removal by 50% while maintaining soil quality, and 2) increase soil quality by 5% as measured by Soil Management Assessment Framework indicators. The energy crop pathway was set to increase soil quality by 10% using these same indicators. To demonstrate the feasibility and impact of each of these targets, seven case studies spanning the US are presented. The analysis has shown that the feedstock production systems are capable of simultaneously increasing productivity and soil sustainability.

09 BIOMASS FUELS↗
DOE OSTI2014

PVWatts Version 5 Manual

The NREL PVWatts calculator is a web application developed by the National Renewable Energy Laboratory (NREL) that estimates the electricity production of a grid-connected photovoltaic system based on a few simple inputs. PVWatts combines a number of sub-models to predict overall system performance, and makes includes several built-in parameters that are hidden from the user. This technical reference describes the sub-models, documents assumptions and hidden parameters, and explains the sequence of calculations that yield the final system performance estimate. This reference is applicable to the significantly revised version of PVWatts released by NREL in 2014.

14 SOLAR ENERGY↗
DOE OSTI2016

Final LDRD Report: Using Linkography of Cyber Attack Patterns to Inform Honeytoken Placement

The war to establish cyber supremacy continues, and the literature is crowded with strictly technical cyber security measures. We present the results of a three year LDRD project using Linkography, a methodology new to the field of cyber security, we establish the foundation necessary to track and profile the microbehavior of humans attacking cyber systems. We also propose ways to leverage this understanding to influence and deceive these attackers. We studied the science of linkography, applied it to the cyber security domain, implemented a software package to manage linkographs, generated the preprocessing blocks necessary to ingest raw data, produced machine learning models, created ontology refinement algorithms and prototyped a web application for researchers and practitioners to apply linkography. Machine learning produced some of our key results: We trained and validated multinomial classifiers with a real world data set and predicted the attacker's next category of action with 86 to 98% accuracy; dimension reduction techniques indicated that the linkography-based features were among the most powerful. We also discovered ontology refinement algorithms that advanced the state of the art in linkography in general and cyber security in particular. We conclude that linkography is a viable tool for cyber security; we look forward to expanding our work to other data sources and using our prediction results to enable adversary deception techniques.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

The Long, Long Road to True Single Sign On at Fermilab [Slides]

In 2012 Fermilab started down the road of single sign on for web applications. In 2018 the end of the road to true single sign on is in sight for all of our users – desktop or mobile, on premise or off. Join us as we describe the tools and techniques being used to provide this ease of access to our user community within the unique Fermilab environment.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2017

Triton: Igiugig Video Analysis (Project Report)

This document summarizes the analysis of video data collected around the Ocean Renewable Power Company’s RivGen® device in the Kvichak River during July and August 2015. Human (manual) analysis of the data was undertaken and used to develop automated algorithms to detect fish in the frames and describe interaction behavior. In addition, a web application, EyeSea, was developed to combine manual and automated processing, so that ultimately the automated algorithms could be used to identify where human analysis was needed (i.e., when fish are present in video frames). The aim of the project was to develop algorithms that could identify video frames with fish present that could then be used to enable faster manual analysis. However, the project has also identified recommendations for future data collection, and research that could help analysis and interpretation. The manual analysis started to look at all data from the start of the deployment; this was to ensure rare events were seen, and initially focused on night-time data when more fish were present.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

The Long, Long Road to True Single Sign On at Fermilab [Slides]

In 2012 Fermilab started down the road of single sign on for web applications. In 2018 the end of the road to true single sign on is in sight for all of our users - desktop or mobile, on premise or off. Join us as we describe the tools and techniques being used to provide this ease of access to our user community within the unique Fermilab environment.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Characterizing Vulnerabilities Associated with Connected Lighting: Exploring Authorization Protocols

Cities are upgrading their infrastructure and converting traditional indoor and outdoor luminaires to Connected Lighting Systems equipped with sensors in an aggressive effort to reduce energy consumption, increase sustainability, and improve the quality of life. When you take something seemingly benign like a lighting system and connect it to the internet, if improperly secured a potential attack vector for hackers is created. Hackers could then access sensitive information, pivot into other networks, shut down services, or enslave devices to do their bidding. In attempt to close this attack vector and secure these systems, this paper extends previous work that investigated, compared and contrasted authentication vulnerabilities in Connected Lighting Systems that identified the need for additional testing and improved test method documentation. One additional authentication test and four new authorization tests were developed utilizing the Open Web Application Security Project (OWASP) as a test development and documentation guide. The new tests were integrated with the previous work to develop an updated test method with a focus on describing test procedures to make them easy to understand and repeat. In addition, a first Connected Lighting System use case was established to begin developing threat profiles that will aid in the identification of vulnerabilities whose focus areas extend beyond authentication and authorization. This use case describes the generation and flow of CLS data which assists in specifying methods to harden CLSs from outside interference and exploitation that can be implemented immediately on existing CLSs and as new products come to market.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Distributed Energy Resource Cybersecurity Framework Best Practices

Current cybersecurity challenges for distributed energy resources (DERs) stem from the integration of various systems and the cyber-physical security concerns they bring. Although frameworks exist for industrial control systems and other energy systems, a simple guided tool that can prioritize recommended actions for controls specific to DERs is lacking. Additionally, the novelty of the field has made it difficult to create a standardized procedure for DERs with cybersecurity in mind. In response to this critical need to address cybersecurity risk management, the National Renewable Energy Laboratory (NREL) has developed a framework and accompanying web application known as the Distributed Energy Resources Cybersecurity Framework (DERCF) (Powell, 2019). A brief overview of the DERCF can be found in Section 1.2. This document provides a guide to cybersecurity best practices identified by technical research and site visits where the framework was used to assess the cybersecurity posture of DER systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

GlideinMonitor

This document describes GlideinMonitor. GlideinMonitor is a Web application that allows viewing of GlideinWMS’s Glidein log files: it provides a user interface, tools to do quick searches and to decode the log content; it provides an efficient managed archive of the log files and a framework to add log processing, e.g. log sanitation.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

New Architecture to Support Integration and Processing of Seismic Data from Heterogeneous Sources

The Geophysical Monitoring Program (GMP) at Lawrence Livermore National Lab (LLNL) maintains a database and supporting infrastructure for geophysical data used in support of the Nuclear Detonation Detection mission. This database includes data from multiple sources, many of which do not distribute data to the public or for which there is no automated means of access. For example, Figure 1 shows (left) the distribution of waveform data in our database by source. The Incorporated Research Institutions for Seismology Data Management Center (IRISDMC) is our major source of waveform data and those data may be retrieved at will using the Federated Digital Seismograph Networks FDSN web Application Programming Interface (API). However, the next 6 most important sources of waveform data have no or only limited automated access to waveforms. As Figure 1 (right) shows, it is very common for waveform records associate with an event in our database to come from two or more sources, and in some cases data come from 10 sources. This diversity of data sources drives our need for efficient and correct integration of metadata, parametric data, and waveform data.

58 GEOSCIENCES↗
DOE OSTI2020

Distributed Energy Resources Cybersecurity Framework: Applying the NIST Risk Management Process

In an effort to strengthen the cybersecurity posture for federal agencies and reduce the time and complexities of following the Risk Management Framework (RMF) six-step process, the National Renewable Energy Laboratory has dedicated research into expanding the existing Distributed Energy Resources Cybersecurity Framework to provide functionality that aids in the RMF steps. Users will have the opportunity to learn, document, and review the framework, saving time and resources. Existing functionality within the web application will continue to be available with added features for usability.

14 SOLAR ENERGY↗
DOE OSTI2021

RAVIS: Resource Forecast and Ramp Visualization for Situational Awareness - An Introduction to the Open-Source Tool and Use Cases

The Resource Forecast and Ramp Visualization for Situational Awareness (RAVIS) is an open-source tool for visualizing variable renewable resource forecasts and ramp alerts for significant up/down ramps in renewable resource and the consequent net-load. The modular dashboard of RAVIS contains configurable panes for viewing- probabilistic time series forecasts, ramp event alerts on the look-ahead timeline, spatially resolved resource sites and forecasts, and system simulation and market clearing data such as transmission lines utilization, nodal prices and available generation flexibility. RAVIS uses a technology suite that is assembled to provide optimum visualization facility while maintaining a wide pool of potential deployment and client environments. The tool is designed to take advantage of web application technologies, open source visualization libraries and tooling. Utilizing this technology will enable deployment in any environment, using any operating system, and is scalable to much higher spatial and temporal scales of visualization. As a prototype of the tool and demonstrating a use case of variable renewable integration, RAVIS currently integrates site-specific solar power forecasts in the California Independent System Operator (CAISO) and Mid-continent ISO (MISO) footprint from the IBM WattSun forecasting platform, and also superimposes market simulation data for CAISO footprint from as in-house NREL market clearing tool. The tool has the ability to alert the viewer for excessive up or down ramps for both individual solar sites as well as regionally aggregated net-load ramps, and alerts can also be qualified with respect to available flexible generation. This report will provide an introduction to the RAVIS tool, and summarize the above mentioned capabilities, typical use cases and possible extensions of the tool. The RAVIS development team believes there are likely to be high economic and reliability benefits of integrating probabilistic forecasts of variable renewables into control center visualizations and improved ramp events situational awareness for system operators and forecasting teams in the ISOs and electric utilities in comparison with their business as usual practices.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2021

Development of a Framework for Data Integration, Assimilation, and Learning for Geological Carbon Sequestration (DIAL-GCS) (Final Report)

This project aimed to develop and demonstrate a Data Integration, Assimilation, and Learning framework for geologic carbon sequestration projects (DIAL-GCS). DIAL-GCS is an intelligence monitoring system (IMS) for automating GCS closed-loop management by leveraging recent developments in machine learning technologies, complex event processing (CEP), and reduced-order modeling. The safe and efficient operation of GCS repositories requires integrated monitoring to track the injected CO¬2 as it moves within a storage reservoir. GCS projects are data intensive, as a result of proliferation of digital instrumentation and smart-sensing technologies. GCS projects are also resource intensive, often requiring multidisciplinary teams performing different monitoring, verification, accounting (MVA) tasks throughout the lifecycle of a project to ensure secure containment of injected CO2. The success of GCS thus depends in a large part on our ability to access, assimilate, and analyze heterogeneous data and information sources in a timely manner. This project included a number of meaningful and necessary tasks to transform the human domain knowledge into machine-interpretable rules for automating knowledge extraction and discovery in GCS. The specific technical objectives of the proposed DIAL-GCS project were to develop an ontology-driven GCS data management module for storing, querying, and exchanging GCS data (both historic and live sensor data) from multiple sources and in heterogeneous formats. Incorporate a CEP engine for detecting abnormal situations by seamlessly combining expert knowledge, rule-based reasoning, and machine learning. Enable uncertainty quantification and predictive analytics using a combination of coupled-process modeling, AI/ML methods, and reduced-order modeling, and integrate and demonstrate the system’s capabilities with both real and simulated data. As far as we know, this is one of the first projects aimed to develop intelligent monitoring systems (IMS) targeting the GCS. Under this project, the team had developed a large number of web applications and scientific algorithms that contribute the main theme of intelligent monitoring. The team has published more than a dozen peer reviewed papers and disseminated the research results at multiple technical meetings.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗