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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 811 records · Page 45
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Lafayette, Colorado: Using Energy Data for Electric Vehicle Infrastructure Planning (City Energy: From Data to Decisions)

This fact sheet "Lafayette, Colorado: Using Energy Data for Electric Vehicle Infrastructure Planning" explains how the City of Lafayette used data from the U.S. Department of Energy's Cities Leading through Energy Analysis and Planning (Cities-LEAP) and the State and Local Energy Data (SLED) programs to inform its city energy planning. It is one of ten fact sheets in the "City Energy: From Data to Decisions" series.

Alternative↗
DOE OSTI2017

Moab, Utah: Using Energy Data to Target Carbon Reductions from Building Energy Efficiency (City Energy: From Data to Decisions)

This fact sheet "Moab, Utah: Using Energy Data to Target Carbon Reductions from Building Energy Efficiency" explains how the City of Moab used data from the U.S. Department of Energy's Cities Leading through Energy Analysis and Planning (Cities-LEAP) and the State and Local Energy Data (SLED) programs to inform its city energy planning. It is one of ten fact sheets in the "City Energy: From Data to Decisions" series.

100% renewable electricity↗
DOE OSTI2017

Boise, Idaho: Improving Air Quality through Alternative Fuels & Reduced Vehicular Travel (City Energy: From Data to Decisions)

This fact sheet "Boise, Idaho: Improving Air Quality through Alternative Fuels & Reduced Vehicular Travel" explains how the City of Boise used data from the U.S. Department of Energy's Cities Leading through Energy Analysis and Planning (Cities-LEAP) and the State and Local Energy Data (SLED) programs to inform its city energy planning. It is one of ten fact sheets in the "City Energy: From Data to Decisions" series.

alternative fuel↗
DOE OSTI2017

South Lake Tahoe, California: Using Energy Data to Partner on Building Energy Efficiency Actions (City Energy: From Data to Decisions)

This fact sheet "South Lake Tahoe, California: Using Energy Data to Partner on Building Energy Efficiency Actions" explains how the City of South Lake Tahoe used data from the U.S. Department of Energy's Cities Leading through Energy Analysis and Planning (Cities-LEAP) and the State and Local Energy Data (SLED) programs to inform its city energy planning. It is one of ten fact sheets in the "City Energy: From Data to Decisions" series.

building energy efficiency actions↗
DOE OSTI2017

San Jose, California: Evaluating Local Solar Energy Generation Potential (City Energy: From Data to Decisions)

This fact sheet "San Jose, California: Evaluating Local Solar Energy Generation Potential" explains how the City of San Jose used data from the U.S. Department of Energy's Cities Leading through Energy Analysis and Planning (Cities-LEAP) and the State and Local Energy Data (SLED) programs to inform its city energy planning. It is one of ten fact sheets in the "City Energy: From Data to Decisions" series.

Cities leading through energy analysis and plannin↗
DOE OSTI2017

Columbia, Missouri: Using Energy Data to Reduce Emissions and Achieve Low-Income Household Energy Savings (City Energy: From Data to Decisions)

This fact sheet "Columbia, Missouri: Using Energy Data to Reduce Emissions and Achieve Low-Income Household Energy Savings" explains how the City of Columbia used data from the U.S. Department of Energy's Cities Leading through Energy Analysis and Planning (Cities-LEAP) and the State and Local Energy Data (SLED) programs to inform its city energy planning. It is one of ten fact sheets in the "City Energy: From Data to Decisions" series.

Cities leading through energy analysis and plannin↗
DOE OSTI2017

Asheville, North Carolina: Reducing Electricity Demand through Building Programs & Policies (City Energy: From Data to Decisions)

This fact sheet "Asheville, North Carolina: Reducing Electricity Demand through Building Programs & Policies" explains how the City of Asheville used data from the U.S. Department of Energy's Cities Leading through Energy Analysis and Planning (Cities-LEAP) and the State and Local Energy Data (SLED) programs to inform its city energy planning. It is one of ten fact sheets in the "City Energy: From Data to Decisions" series.

buildings↗
DOE OSTI2017

New Haven, Connecticut: Targeting Low-Income Household Energy Savings (City Energy: From Data to Decisions)

This fact sheet "New Haven, Connecticut: Targeting Low-Income Household Energy Savings" explains how the City of New Haven used data from the U.S. Department of Energy's Cities Leading through Energy Analysis and Planning (Cities-LEAP) and the State and Local Energy Data (SLED) programs to inform its city energy planning. It is one of ten fact sheets in the "City Energy: From Data to Decisions" series.

Cities leading through energy analysis and plannin↗
DOE OSTI2025

Designing robust energy policy packages under deep uncertainty: A multi-metric decision support framework

The complexity of transitioning to sustainable energy systems requires policy frameworks capable of balancing multiple objectives while addressing deep uncertainty. However, existing approaches often lack systematic methods to identify combinations of policy levers that remain effective across a wide range of uncertain futures. This paper presents a novel decision support framework that guides the selection of robust policy packages based on their performance across multiple objectives under uncertainty. Our method leverages a large ensemble of scenarios and applies scenario discovery techniques to identify influential policy levers. Here, we introduce new indicators to assess the robustness of policies by evaluating their ability to mitigate adverse outcomes across metrics. These indicators support an iterative process to build a robust policy package. Finally, we map the technological and energy pathways associated with the robust policy package by leveraging an energy system optimization model. We illustrate the application of this framework to the Spanish energy system, providing insights into how specific combinations of policy levers shape decarbonization pathways under uncertainty.

Decision-support method↗
DOE OSTI2015

Decerns : A framework for multi-criteria decision analysis

A new framework, Decerns , for multicriteria decision analysis (MCDA) of a wide range of practical problems on risk management is introduced. Decerns framework contains a library of modules that are the basis for two scalable systems: DecernsMCDA for analysis of multicriteria problems, and DecernsSDSS for multicriteria analysis of spatial options. DecernsMCDA includes well known MCDA methods and original methods for uncertainty treatment based on probabilistic approaches and fuzzy numbers. As a result, these MCDA methods are described along with a case study on analysis of multicriteria location problem.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

A Cloud-Based Decision Support System Framework for Hydropower Biological Evaluation

Hydropower has become one of the most important energy sources: it accounts for more than 80% of the world’s renewable energy and about 16% of all the energy in the world. Significantly more hydropower capacity is planned to be developed. However, hydro-structures, including powered dams, may have adverse biological effects on fishes, especially on migrating fish. For instance, fish can be injured or even killed when they pass through turbines. This is why biological evaluations on hydro-structures are greatly needed to estimate fish injury and mortality rates. The Hydropower Biological Evaluation Toolset (HBET) is an integrated suite of science-based desktop tools designed to evaluate whether the hydraulic conditions of hydropower structures are fish friendly by analyzing collected data and providing estimated injury and mortality rates. Sensor Fish, a small, autonomous sensor package, is used by HBET to record data describing the conditions that live fish passing through a hydropower structure will face. In this paper, we incorporated cloud computing into HBET, and migrated it into a cloud-based decision support system framework for hydropower biological evaluation. This will make the evaluation systems more scalable and flexible; however, this also introduces a significant challenge: how to maintain the security while retaining scalability and flexibility. We discuss the technical methodologies and algorithms implemented in the proposed framework, and analyze the countermeasures implemented therein.

Decision Support System, Hydropower, Dam, Fish Inj↗
DOE OSTI2023

Decision-making Framework to Support the End-of-Life Management of High-Activity Radioactive Sources

Sealed radioactive sources are used for an extremely wide range of purposes, including as radiation sources in various nuclear facilities, universities, hospitals, biomedical and industrial applications, as well as for geological prospecting and exploration. The proper management of these sealed radioactive sources once they have reached their end-of-life is still a global challenge. Very few field-tested Mobile Hot Cells (MHC) exist in the world to support the end-of-life management of disused high-activity radioactive sources. One of the critical challenges that a source recovery team encounters on each site is to find adequate space, and access to that space to complete the staging and recapture process with a MHC; this process is tedious, uncertain, and time-consuming. Therefore, it is essential to understand the planning and management of the MHC setup and takedown. Currently, there isn't an single capable planning tool that will provide an effective medium to plan, inform, educate, and communicate knowledge about the environment where the MHC will be deployed. We present a novel approach for the planning and management of the deployment of the MHC to several different sites that relies on technology. Furthermore, this planning tool will support collaboration, promote information sharing, and foster better decision making processes, resulting in a more efficient, and reliable setup and source recovery with the MHC.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2013

Data Diodes in Support of Trustworthy Cyber Infrastructure and Net-Centric Cyber Decision Support

Data diodes provide protection of critical cyber assets by the means of physically enforcing traffic direction on the network. In order to deploy data diodes effectively, it is imperative to understand the protection they provide, the protection they do not provide, their limitations, and their place in the larger security infrastructure. In this work, we study data diodes, their functionalities and limitations. We then propose two critical infrastructure systems that can benefit from the additional protection offered by data diodes: process control networks and net-centric cyber decision support systems. We review the security requirements of these systems, describe the architectures, and study the trade-offs. Finally, the architectures are evaluated against different attack patterns.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2013

Epidural Analgesia Versus Patient-Controlled Analgesia for Pain Relief in Uterine Artery Embolization for Uterine Fibroids: A Decision Analysis

Purpose: This study was designed to compare the costs and effects of epidural analgesia (EDA) to those of patient-controlled intravenous analgesia (PCA) for postintervention pain relief in women having uterine artery embolization (UAE) for systematic uterine fibroids. Methods: Cost-effectiveness analysis (CEA) based on data from the literature by constructing a decision tree to model the clinical pathways for estimating the effects and costs of treatment with EDA and PCA. Literature on EDA for pain-relief after UAE was missing, and therefore, data on EDA for abdominal surgery were used. Outcome measures were compared costs to reduce one point in visual analogue score (VAS) or numeric rating scale (NRS) for pain 6 and 24 h after UAE and risk for complications. Results: Six hours after the intervention, the VAS was 3.56 when using PCA and 2.0 when using EDA. The costs for pain relief in women undergoing UAE with PCA and EDA were Euro-Sign 191 and Euro-Sign 355, respectively. The costs for EDA to reduce the VAS score 6 h after the intervention with one point compared with PCA were Euro-Sign 105 and Euro-Sign 179 after 24 h. The risk of having a complication was 2.45 times higher when using EDA. Conclusions: The results of this indirect comparison of EDA for abdominal surgery with PCA for UAE show that EDA would provide superior analgesia for post UAE pain at 6 and 24 h but with higher costs and an increased risk of complications.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2019

Evaluating the decisions of glioma patients regarding clinical trial participation: a retrospective single provider review

Clinical trial accrual is vital to advancing care. A single study elucidated demographic data correlating with glioma patients’ clinical trial enrollment. However, it did not investigate the underlying decision-making process for non-participation. In this study, we seek to understand this key aspect of patient accrual. All notes for glioma patients seen by a single neuro-oncologist from July 2010 to May 2017 were examined for mention of clinical trial offerings. When a trial was declined, the patient’s reasoning was recorded along with the following: diagnosis, KPS, extent of resection, age, gender, race, marital status, income group, religion, trial offered at initial visit versus subsequent, and distance from trial site. Of 279 consecutive glioma patients, 88 were eligible for and offered a clinical trial. Fifty-seven accepted (65%), and 31 (35%) declined participation (Fig. 1). Of those offered a clinical trial, patients with glioblastoma (GBM) were significantly more likely to accept (44 out of 57 (77%) vs. 13 out of 57 (23%), p =0.03). After we adjusted for gender and travel distance, GBM was the only significant predictor of clinical trial acceptance, with an odds ratio of 3.18 (95% CI 1.17, 8.61, p =0.02). Reasons cited for non-participation included: travel distance (39%), lack of interest (39%), visit frequency (16%), and fear of randomization (6%). This study clarified for the first time individual glioma patient rationale for non-participation and potential areas for improving enrollment. Allowing off-site treatment centers or telemedicine visits may entice rural patients to participate. Visit frequency should be carefully considered and minimized whenever possible. Further prospective study of rationale for non-participation may improve enrollment over time.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2018

An (R, S)-norm fuzzy information measure with its applications in multiple-attribute decision-making

In this paper, we introduce a quantity measure which is called (R, S)-norm entropy and discuss some of its major properties with Shannon’s and other entropies in the literature. Based on this (R, S)-norm entropy, we have proposed a new (R, S)-norm fuzzy information measure and discussed its validity and properties. Further, we have given its comparison with other fuzzy information measures to prove its effectiveness. Attribute weights play an important role in multiple-attribute decision-making problems. In the present communication, two methods of determining the attribute weights are introduced. First is the case when the information regarding attribute weights is incompletely known or completely unknown and second is when we have partial information about attribute weights. For the first case, the extension of ordinary entropy weight method is used to calculate attribute weights and minimum entropy principle method based on solving a linear programming model is used in the second case. Finally, two methods are explained through numerical examples.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2018

An (R{sup ′},S{sup ′})-norm fuzzy relative information measure and its applications in strategic decision-making

In this communication, we propose two quantities named ‘An (R{sup ′},S{sup ′})-norm directed divergence measure’ and ‘(R{sup ′},S{sup ′})-norm fuzzy directed divergence measure’, establish their validity and discuss their properties. Further, the performance of proposed divergence measure is compared with some existing measures through a numerical example. Finally, the application of proposed fuzzy directed divergence measure is given in strategic decision-making and the outcome is compared with other methods in literature.

97 MATHEMATICS AND COMPUTING↗