Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Policy”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,549 records · Page 86
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

3% Yield Increase (HH3), All Energy Crops scenario of the 2016 Billion Ton Report

Scientific reason for data generation: to serve as an alternate high-yield scenario for the BT16 volume 1 agricultural scenarios to compare these projections of potential biomass supplies against a reference case (agricultural baseline 10.11578/1337885). The simulation runs from 2015 through 2040; a starting year of 2014 is used but not reported. Date the data set was last modified: 02/02/2016 How each parameter was produced (methods), format, and relationship to other data in the data set: This exogenous price simulations (also referred to as “specified-price” simulations) introduces a farmgate price, and POLYSYS solves for biomass supplies that may be brought to market in response to these prices. In specified-price scenarios, a specified farmgate price is offered constantly in all counties over all years of the simulation. This simulation begins in 2015 with an offered farmgate price for primary crop residues only between 2015 and 2018 and long-term contracts for dedicated crops beginning in 2019. Expected mature energy crop yield grows at a compounding rate of 3% beginning in 2016. The yield growth assumptions are fixed after crops are planted such that yield gains do not apply to crops already planted, but new plantings do take advantage of the gains in expected yield growth. Instruments used: Policy Analysis System –POLYSYS (version POLYS2015_V10_alt_JAN22B), an agricultural policy modeling system of U.S. agriculture (crops and livestock), supplied by the University of Tennessee Institute of Agriculture, Agricultural Policy Analysis Center.

09 BIOMASS FUELS↗
DOE OSTI2016

4% Yield Increase (HH4), All Energy Crops scenario of the 2016 Billion Ton Report

Scientific reason for data generation: to serve as an alternate high-yield scenario for the BT16 volume 1 agricultural scenarios to compare these projections of potential biomass supplies against a reference case (agricultural baseline 10.11578/1337885). The simulation runs from 2015 through 2040; a starting year of 2014 is used but not reported. Date the data set was last modified: 02/02/2016. How each parameter was produced (methods), format, and relationship to other data in the data set: This exogenous price simulations (also referred to as “specified-price” simulations) introduces a farmgate price, and POLYSYS solves for biomass supplies that may be brought to market in response to these prices. In specified-price scenarios, a specified farmgate price is offered constantly in all counties over all years of the simulation. This simulation begins in 2015 with an offered farmgate price for primary crop residues only between 2015 and 2018 and long-term contracts for dedicated crops beginning in 2019. Expected mature energy crop yield grows at a compounding rate of 4% beginning in 2016. The yield growth assumptions are fixed after crops are planted such that yield gains do not apply. Instruments used: Policy Analysis System –POLYSYS (version POLYS2015_V10_alt_JAN22B), an agricultural policy modeling system of U.S. agriculture (crops and livestock), supplied by the University of Tennessee Institute of Agriculture, Agricultural Policy Analysis Center.

09 BIOMASS FUELS↗
DOE OSTI2023

PoliMOR

PoliMOR is a scalable, automated, and customizable policy engine framework for multi-tiered parallel file systems. It is composed of single-purpose agents that handle tasks such as gathering file metadata, making policy decisions, and then executing actions based on those policies. These agents are designed to communicate using distributed message queues, allowing the number of individual agents to be scaled up as needed. PoliMOR automates the data management tasks by precluding the need for admin intervention. The agents in PoliMOR can be customized to integrate any utilities/tools that perform tasks like metadata scanning and data placement management.

Brumgard, Christopher↗
DOE OSTI2026

Dynamic Transmission Line Switching Amid Wildfire-Prone Weather Under Decision-Dependent Uncertainty

During dry and windy seasons, environmental conditions significantly increase the risk of wildfires, exposing power grids to disruptions caused by transmission line failures. Wildfire propagation exacerbates grid vulnerability, potentially leading to prolonged power outages. To address this challenge, we propose a multistage optimization model that dynamically adjusts transmission grid topology in response to wildfire propagation, aiming to develop an optimal response policy. By accounting for decision-dependent uncertainty, where line survival probabilities depend on usage, we employ distributionally robust optimization to model uncertainty in line survival distributions. We adapt the stochastic nested decomposition algorithm and derive a deterministic upper bound for its finite convergence. To enhance computational efficiency, we exploit the Lagrangian dual problem structure for a faster generation of Lagrangian cuts. Using realistic data from the California transmission grid, we demonstrate the superior performance of dynamic response policies against two-stage alternatives through a comprehensive case study. In addition, after solving the multistage formulation, we construct easy-to-implement policies that significantly reduce computational burden while maintaining good performance in real-time deployment. History: Accepted by Russell Bent, Area Editor for Network Optimization: Algorithms and Applications. Funding: This work was supported by the U.S. Department of Energy, Office of Electricity [Grant DE-AC02-05CH11231]. The work of R. Jiang was supported in part by the U.S. National Science Foundation, Division of Electrical, Communications and Cyber Systems [Grant ECCS-1845980] and the U.S. Air Force Office of Scientific Research [Grant FA9550-23-1-0323]. Supplemental Material: The software that supports the findings of this study is available within the paper and its Supplemental Information ( https://pubsonline.informs.org/doi/suppl/10.1287/ijoc.2025.1210 ) as well as from the IJOC GitHub software repository ( https://github.com/INFORMSJoC/2025.1210 ). The complete IJOC Software and Data Repository is available at https://informsjoc.github.io/ .

Estrada-Garcia, Juan-Alberto↗
DOE OSTI2014

Modeling Pollinator Community Response to Contrasting Bioenergy Scenarios

In the United States, policy initiatives aimed at increasing sources of renewable energy are advancing bioenergy production, especially in the Midwest region, where agricultural landscapes dominate. While policy directives are focused on renewable fuel production, biodiversity and ecosystem services will be impacted by the land-use changes required to meet production targets. Using data from field observations, we developed empirical models for predicting abundance, diversity, and community composition of flower-visiting bees based on land cover. We used these models to explore how bees might respond under two contrasting bioenergy scenarios: annual bioenergy crop production and perennial grassland bioenergy production. In the two scenarios, 600,000 ha of marginal annual crop land or marginal grassland were converted to perennial grassland or annual row crop bioenergy production, respectively. Model projections indicate that expansion of annual bioenergy crop production at this scale will reduce bee abundance by 0 to 71%, and bee diversity by 0 to 28%, depending on location. In contrast, converting annual crops on marginal soil to perennial grasslands could increase bee abundance from 0 to 600% and increase bee diversity between 0 and 53%. Our analysis of bee community composition suggested a similar pattern, with bee communities becoming less diverse under annual bioenergy crop production, whereas bee composition transitioned towards a more diverse community dominated by wild bees under perennial bioenergy crop production. Models, like those employed here, suggest that bioenergy policies have important consequences for pollinator conservation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Advanced Control Systems for Wave Energy Converters

This submission contains several papers, a final report, descriptions of a theoretical framework for two types of control systems, and descriptions of eight real-time flap load control policies with the objective of assessing the potential improvement of annual average capture efficiency at a reference site on an MHK device developed by Resolute Marine Energy, Inc. (RME). The submission also contains an LCOE model that estimates the performance and related energy cost improvements that each advanced control system might provide and recommendations for improving DOE's LCOE model. The two types of control systems are for wave energy converters which transform data into commands that, in the case of RME's OWSC wave energy converter, provide real-time adjustments to damping forces applied to the prime mover via the power take-off system (PTO). The control theories developed were: 1) Model Predictive Control (MPC) or so-called "non-causal" control whereby sensors deployed seaward of a wave energy converter measure incoming wave characteristics and transmit that information to a data processor which issues commands to the PTO to adjust the damping force to an optimal value; and 2) "Causal" control which utilizes local sensors on the wave energy converter itself to transmit information to a data processor which then issues appropriate commands to the PTO. The two advanced control policies developed by Scruggs and Re Vision were then compared to a simple control policy, Coulomb damping, which was utilized by RME during the two rounds of ocean trials it had conducted prior to the commencement of this project. The project work plan initially included a provision for RME to conduct hardware-in-the-loop (HIL) testing of the data processors and configurations of valves, sensors and rectifiers needed to implement the two advanced control systems developed by Scruggs and Re Vision Consulting but the funding for that aspect of the project was cut at the conclusion of Budget Period 1. Accordingly, more work needs to be done to determine: a) means and feasibility of implementing real-time control; and b) added costs associated with such implementation taking into account estimated effects on system availability in addition to component costs.

16 TIDAL AND WAVE POWER↗
DOE OSTI2026

ORCHID: Orchestrated Retrieval-Augmented Classification of High-Risk Property with Intelligent Decision-Making

High-Risk Property (HRP) classification is critical at U.S. Department of Energy (DOE) sites, where inventories include sensitive and often dual-use equipment. Compliance must track evolving rules designated by various export control policies to make transparent and auditable decisions. Traditional expert-only workflows are time-consuming, backlog-prone, and struggle to keep pace with shifting regulatory boundaries. We propose ORCHID, a modular agentic framework for HRP classification that pairs retrieval-augmented generation (RAG) with human oversight to produce policy based outputs that can be audited. Small cooperating agents—retrieval, description refiner, classifier, validator, and feedback logger—coordinate via agent-to-agent messaging and invoke tools through the Model Context Protocol (MCP) for model-agnostic on-premise operation. The interface follows an "Item to Evidence to Decision" loop with step-by-step reasoning, on-policy citations, and append-only audit bundles (run-cards, prompts, evidence). In preliminary tests on real HRP cases, ORCHID improves accuracy and traceability over a non-agentic baseline while deferring uncertain items to Subject Matter Experts (SMEs). The demonstration shows single item submission, grounded citations, SME feedback capture, and exportable audit artifacts—illustrating a practical path to trustworthy LLM assistance in sensitive DOE compliance workflows.

Das, Sanjay [ORNL] (ORCID:0009000542591915)↗
DOE OSTI2012

NEAMS Software Licensing, Release, and Distribution: Implications for FY2013 Work Package Planning

The vision of the NEAMS program is to bring truly predictive modeling and simulation (M&S) capabilities to the nuclear engineering community in order to enable a new approach to the analysis of nuclear systems. NEAMS anticipates issuing in FY 2018 a full release of its computational 'Fermi Toolkit' aimed at advanced reactor and fuel cycles. The NEAMS toolkit involves extensive software development activities, some of which have already been underway for several years, however, the Advanced Modeling and Simulation Office (AMSO), which sponsors the NEAMS program, has not yet issued any official guidance regarding software licensing, release, and distribution policies. This motivated an FY12 task in the Capability Transfer work package to develop and recommend an appropriate set of policies. The current preliminary report is intended to provide awareness of issues with implications for work package planning for FY13. We anticipate a small amount of effort associated with putting into place formal licenses and contributor agreements for NEAMS software which doesn't already have them. We do not anticipate any additional effort or costs associated with software release procedures or schedules beyond those dictated by the quality expectations for the software. The largest potential costs we anticipate would be associated with the setup and maintenance of shared code repositories for development and early access to NEAMS software products. We also anticipate an opportunity, with modest associated costs, to work with the Radiation Safety Information Computational Center (RSICC) to clarify export control assessment policies for software under development.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2012

Strategic Analysis of Complex Security Scenarios

Many advanced technical tools are available to prevent attacks on national infrastructure. Nevertheless, while traditional analyses of security problems have succeeded in producing good technical solutions, they have often ignored the human factor integral to these problems. Human attackers (who may be individuals or state-level attackers) expend substantial effort to breach security because they have the incentive for doing so. People involved in implementing security follow individual incentives, which need not align with global security concerns; consequently, desired security solutions are often implemented poorly, or not at all. This complex interplay between individual incentives and global (organizational and/or national) goals can be modeled and analyzed using game theoretic techniques. By analyzing not only what is possible, but also what is motivated, a holistic approach to security problems can be developed, informing policy and providing tools to policy makers. We study game theoretic models that unify several current incentive-based approaches to security, and develop simulation-based and mathematical optimization methods for analyzing such models that exploit the high-performance computing capabilities at Sandia. Our first model studies security in interdependent settings, offering a scalable local search heuristic to approximate optimal security decisions in general, and a linear programming approach, coupled with simulations of consequences, to optimally compute security in an important special case. Our second class of models addresses security patrolling problems when an adversary gets to observe the patrol location. We present a general framework, based on stochastic games, for computing optimal security policies in such settings, and present more scalable tools that apply in the important special cases. Our third contribution is a model of security that involves many defenders, but only models non-adaptive attackers (or natural disasters, inadvertent errors, etc). In this model, we demonstrate that the security decisions of many players result in global security configuration that is not very far from optimal, and is much more resilient to environment changes that an optimal solution. This positive effect dissipates, however, when the number of decision makers becomes too large.

Vorobeychik, Yevgeniy↗
DOE OSTI2013

Energy Transmission and Infrastructure Northern Ohio (OH)

The objective of Energy Transmission and Infrastructure Northern Ohio (OH) was to lay the conceptual and analytical foundation for an energy economy in northern Ohio that will: • improve the efficiency with which energy is used in the residential, commercial, industrial, agricultural, and transportation sectors for Oberlin, Ohio as a district-wide model for Congressional District OH-09; • identify the potential to deploy wind and solar technologies and the most effective configuration for the regional energy system (i.e., the ratio of distributed or centralized power generation); • analyze the potential within the district to utilize farm wastes to produce biofuels; • enhance long-term energy security by identifying ways to deploy local resources and building Ohio-based enterprises; • identify the policy, regulatory, and financial barriers impeding development of a new energy system; and • improve energy infrastructure within Congressional District OH-09. This objective of laying the foundation for a renewable energy system in Ohio was achieved through four primary areas of activity: 1. district-wide energy infrastructure assessments and alternative-energy transmission studies; 2. energy infrastructure improvement projects undertaken by American Municipal Power (AMP) affiliates in the northern Ohio communities of Elmore, Oak Harbor, and Wellington; 3. Oberlin, OH-area energy assessment initiatives; and 4. a district-wide conference held in September 2011 to disseminate year-one findings. The grant supported 17 research studies by leading energy, policy, and financial specialists, including studies on: current energy use in the district and the Oberlin area; regional potential for energy generation from renewable sources such as solar power, wind, and farm-waste; energy and transportation strategies for transitioning the City of Oberlin entirely to renewable resources and considering pedestrians, bicyclists, and public transportation as well as drivers in developing transportation policies; energy audits and efficiency studies for Oberlin-area businesses and Oberlin College; identification of barriers to residential energy efficiency and development of programming to remove these barriers; mapping of the solar-photovoltaic and wind-energy supply chains in northwest Ohio; and opportunities for vehicle sharing and collaboration among the ten organizations in Lorain County from the private, government, non-profit, and educational sectors. With non-grant funds, organizations have begun or completed projects that drew on the findings of the studies, including: creation of a residential energy-efficiency program for the Oberlin community; installation of energy-efficient lighting in Oberlin College facilities; and development by the City of Oberlin and Oberlin College of a 2.27 megawatt solar photovoltaic facility that is expected to produce 3,000 megawatt-hours of renewable energy annually, 12% of the College’s yearly power needs. Implementation of these and other projects is evidence of the economic feasibility and technical effectiveness of grant-supported studies, and additional projects are expected to advance to implementation in the coming years. The public has benefited through improved energy-delivery systems and reduced energy use for street lighting in Elmore, Oak Harbor, and Wellington; new opportunities for assistance and incentives for residential energy efficiency in the Oberlin community; new opportunities for financial and energy savings through vehicle collaboration within Lorain County; and decreased reliance on fossil fuels and expanded production of renewable energy in the region. The dissemination conference and the summary report developed for the conference also benefited the public, but making the findings and recommendations of the regional studies broadly available to elected officials, city managers, educators, representatives of the private sector, and the general public.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2013

Timing is everything :

People save for retirement throughout their career because it is virtually impossible to save all you ll need in retirement the year before you retire. Similarly, without installing incremental amounts of clean fossil, renewable or transformative energy technologies throughout the coming decades, a radical and immediate change will be near impossible the year before a policy goal is set to be in place. Therefore, our research question is, To meet our desired technical and policy goals, what are the factors that affect the rate we must install technology to achieve these goals in the coming decades? Existing models do not include full regulatory constraints due to their often complex, and inflexible approaches to solve for optimal engineering instead of robust and multidisciplinary solutions. This project outlines the theory and then develops an applied software tool to model the laboratory-to-market transition using the traditional technology readiness level (TRL) framework, but develops subsequent and a novel regulatory readiness level (RRL) and market readiness level (MRL). This tool uses the ideally-suited system dynamics framework to incorporate feedbacks and time delays. Future energy-economic-environment models, regardless of their programming platform, may adapt this software model component framework or module to further vet the likelihood of new or innovative technology moving through the laboratory, regulatory and market space. The prototype analytical framework and tool, called the Technology, Regulatory and Market Readiness Level simulation model (TRMsim) illustrates the interaction between technology research, application, policy and market dynamics as they relate to a new or innovative technology moving from the theoretical stage to full market deployment. The initial results that illustrate the model s capabilities indicate for a hypothetical technology, that increasing the key driver behind each of the TRL, RRL and MRL components individually decreases the time required for the technology to progress through each component by 63, 68 and 64%, respectively. Therefore, under the current working assumptions, to decrease the time it may take for a technology to move from the conceptual stage to full scale market adoption one might consider expending additional effort to secure regulatory approval and reducing the uncertainty of the technology s demand in the marketplace.

Kobos, Peter Holmes↗
DOE OSTI2013

Climate Information Needs for Financial Decision Making

Climate Information Needs for Financial Decision Making (Final Report) This Department of Energy workshop award (grant #DE-SC0008480) provided primary support for the American Meteorological Society’s study on climate information needs for financial decision making. The goal of this study was to help advance societal decision making by examining the implications of climate variability and change on near-term financial investments. We explored four key topics: 1) the conditions and criteria that influence returns on investment of major financial decisions, 2) the climate sensitivity of financial decisions, 3) climate information needs of financial decision makers, and 4) potential new mechanisms to promote collaboration between scientists and financial decision makers. Better understanding of these four topics will help scientists provide the most useful information and enable financial decision makers to use scientific information most effectively. As a result, this study will enable leaders in business and government to make well-informed choices that help maximize long-term economic success and social wellbeing in the United States The outcomes of the study include a workshop, which brought together leaders from the scientific and financial decision making communities, a publication of the study report, and a public briefing of the results to the policy community. In addition, we will present the results to the scientific community at the AMS Annual Meeting in February, 2014. The study results were covered well by the media including Bloomberg News and E&E News. Upon request, we also briefed the Office of Science Technology Policy (OSTP) and the Council on Environmental Quality (CEQ) on the outcomes. We presented the results to the policy community through a public briefing in December on Capitol Hill. The full report is publicly available at www.ametsoc.org/cin. Summary of Key Findings The United States invests roughly $1.5 trillion U.S. dollars (USD) in capital assets each year across the public and private sectors (Orszag 2008; United States Census Bureau 2013). Extreme weather events create and exacerbate risks to these financial investments by contributing to: • Direct physical impacts on the investments themselves • Degradation of critical supporting infrastructure • Changes in the availability of key natural resources • Changes to workforce availability or capacity • Changes in the customer base • Supply chain disruptions • Legal liability • Shifts in the regulatory environment • Reductions in credit ratings Even small changes in weather can impact operations in critical economic sectors. As a result, maximizing returns on financial investments depends on accurately understanding and effectively accounting for these risks. Climate variability and change can either exacerbate existing risks or cause new sources of risk to emerge. Managing these risks most effectively will depend on scientific advances and increases in the capacity of financial decision makers to use the scientific knowledge that results. Barriers to using climate information must also be overcome. This study proposes three predefined levels of certainty for communicating about weather and climate risks: 1) possible (i.e., unknown likelihood or less than 50% chance of occurrence), 2) probable (greater than 50% chance of occurrence), and 3) effectively certain (at least 95% chance of occurrence). For example, it is effectively certain that a change in climate will alter weather patterns. It is probable that climate warming will cause increases in the intensity of some extreme events. It is possible that climate change will cause major and widespread disruptions to key planetary life-support services. Key recommendations of this study: 1) Identify climate-related risks and opportunities for financial decision making. 2) Create a framework to translate scientific information in clear and actionable terms for financial decision makers. 3) Analyze existing climate assessments and translate projected impacts into possible, probable, and effectively certain impacts. 4) Improve climate projections with respect to precipitation (timing, amount, and intensity), extreme events, and tails of probability distributions (i.e., low-probability but high-consequence events). 5) Increase spatial resolution of climate projections in order to provide climate information at the scale most relevant to financial investments. 6) Improve projections of the societal consequences of climate impacts through integrated assessments of physical, natural, and social sciences. 7) Create a user-friendly information repository and portal that provides easy access to information relevant to financial decision making. 8) Create and maintain opportunities to bring together financial decision makers, scientists, and service providers. Near-term financial decisions have long-term implications for the United States’ social and economic well-being that depend, in part, on climate variability and change. Investments will be most successful, and will advance the interests of society most effectively, if they are grounded in the best available knowledge & understanding.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2013

Clean Energy Application Center

The Mid Atlantic Clean Energy Application Center (MACEAC), managed by The Penn State College of Engineering, serves the six states in the Mid-Atlantic region (Pennsylvania, New Jersey, Delaware, Maryland, Virginia and West Virginia) plus the District of Columbia. The goals of the Mid-Atlantic CEAC are to promote the adoption of Combined Heat and Power (CHP), Waste Heat Recovery (WHR) and District Energy Systems (DES) in the Mid Atlantic area through education and technical support to more than 1,200 regional industry and government representatives in the region. The successful promotion of these technologies by the MACEAC was accomplished through the following efforts; (1)The MACEAC developed a series of technology transfer networks with State energy and environmental offices, Association of Energy Engineers local chapters, local community development organizations, utilities and, Penn State Department of Architectural Engineering alumni and their firms to effectively educate local practitioners about the energy utilization, environmental and economic advantages of CHP, WHR and DES; (2) Completed assessments of the regional technical and market potential for CHP, WHR and DE technologies application in the context of state specific energy prices, state energy and efficiency portfolio development. The studies were completed for Pennsylvania, New Jersey and Maryland and included a set of incentive adoption probability models used as a to guide during implementation discussions with State energy policy makers; (3) Using the technical and market assessments and adoption incentive models, the Mid Atlantic CEAC developed regional strategic action plans for the promotion of CHP Application technology for Pennsylvania, New Jersey and Maryland; (4) The CHP market assessment and incentive adoption model information was discussed, on a continuing basis, with relevant state agencies, policy makers and Public Utility Commission organizations resulting in CHP favorable incentive programs in New Jersey, Pennsylvania, Maryland and Delaware; (5) Developed and maintained a MACEAC website to provide technical information and regional CHP, WHR and DE case studies and site profiles for use by interested stakeholders in information transfer and policy discussions; (6) Provided Technical Assistance through feasibility studies and on site evaluations. The MACEAC completed 28 technical evaluations and 9 Level 1 CHP analyses ; and (7) the MACEAC provided Technical Education to the region through a series of 29 workshops and webinars, 37 technical presentations, 14 seminars and participation in 13 CHP conferences.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2014

2013 Vehicle Technologies Market Report

This is the fifth edition of this report, which details the major trends in U.S. light-duty vehicle and medium/heavy truck markets as well as the underlying trends that caused them. This report is supported by the U.S. Department of Energy s (DOE) Vehicle Technologies Office (VTO), and, in accord with its mission, pays special attention to the progress of high-efficiency and alternative-fuel technologies. After opening with a discussion of energy and economics, this report features a section each on the light-duty vehicle and heavy/medium truck markets, and concluding with a section each on technology and policy. The first section on Energy and Economics discusses the role of transportation energy and vehicle markets on a national (and even international) scale. For example, Figures 12 through 14 discuss the connections between global oil prices and U.S. GDP, and Figures 21 and 22 show U.S. employment in the automotive sector. The following section examines Light-Duty Vehicle use, markets, manufacture, and supply chains. Figures 24 through 51 offer snapshots of major light-duty vehicle brands in the U.S. and Figures 56 through 64 examine the performance and efficiency characteristics of vehicles sold. The discussion of Medium and Heavy Trucks offers information on truck sales (Figures 73 through 75) and fuel use (Figures 78 through 81). The Technology section offers information on alternative fuel vehicles and infrastructure (Figures 84 through 95), and the Policy section concludes with information on recent, current, and near-future Federal policies like the Corporate Average Fuel Economy standard (Figures 106 through 110). In total, the information contained in this report is intended to communicate a fairly complete understanding of U.S. highway transportation energy through a series of easily digestible nuggets.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2013

Greenhouse Gas Mitigation Options in ISEEM Global Energy Model: 2010-2050 Scenario Analysis for Least-Cost Carbon Reduction in Iron and Steel Sector

The goal of the modeling work carried out in this project was to quantify long-term scenarios for the future emission reduction potentials in the iron and steel sector. The main focus of the project is to examine the impacts of carbon reduction options in the U.S. iron and steel sector under a set of selected scenarios. In order to advance the understanding of carbon emission reduction potential on the national and global scales, and to evaluate the regional impacts of potential U.S. mitigation strategies (e.g., commodity and carbon trading), we also included and examined the carbon reduction scenarios in China’s and India’s iron and steel sectors in this project. For this purpose, a new bottom-up energy modeling framework, the Industrial Sector Energy Efficiency Modeling (ISEEM), (Karali et al. 2012) was used to provide detailed annual projections starting from 2010 through 2050. We used the ISEEM modeling framework to carry out detailed analysis, on a country-by-country basis, for the U.S., China’s, and India’s iron and steel sectors. The ISEEM model applicable to iron and steel section, called ISEEM-IS, is developed to estimate and evaluate carbon emissions scenarios under several alternative mitigation options - including policies (e.g., carbon caps), commodity trading, and carbon trading. The projections will help us to better understand emission reduction potentials with technological and economic implications. The database for input of ISEEM-IS model consists of data and information compiled from various resources such as World Steel Association (WSA), the U.S. Geological Survey (USGS), China Steel Year Books, India Bureau of Mines (IBM), Energy Information Administration (EIA), and recent LBNL studies on bottom-up techno-economic analysis of energy efficiency measures in the iron and steel sector of the U.S., China, and India, including long-term steel production in China. In the ISEEM-IS model, production technology and manufacturing details are represented, in addition to the extensive data compiled from recent studies on bottom-up representation of efficiency measures for the sector. We also defined various mitigation scenarios including long-term production trends to project country-specific production, energy use, trading, carbon emissions, and costs of mitigation. Such analyses can provide useful information to assist policy-makers when considering and shaping future emissions mitigation strategies and policies. The technical objective is to analyze the costs of production and CO 2 emission reduction in the U.S, China, and India’s iron and steel sectors under different emission reduction scenarios, using the ISEEM-IS as a cost optimization model. The scenarios included in this project correspond to various CO 2 emission reduction targets for the iron and steel sector under different strategies such as simple CO 2 emission caps (e.g., specific reduction goals), emission reduction via commodity trading, and emission reduction via carbon trading.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2014

Sampling Approaches for Multi-Domain Internet Performance Measurement Infrastructures

The next-generation of high-performance networks being developed in DOE communities are critical for supporting current and emerging data-intensive science applications. The goal of this project is to investigate multi-domain network status sampling techniques and tools to measure/analyze performance, and thereby provide “network awareness” to end-users and network operators in DOE communities. We leverage the infrastructure and datasets available through perfSONAR, which is a multi-domain measurement framework that has been widely deployed in high-performance computing and networking communities; the DOE community is a core developer and the largest adopter of perfSONAR. Our investigations include development of semantic scheduling algorithms, measurement federation policies, and tools to sample multi-domain and multi-layer network status within perfSONAR deployments. We validate our algorithms and policies with end-to-end measurement analysis tools for various monitoring objectives such as network weather forecasting, anomaly detection, and fault-diagnosis. In addition, we develop a multi-domain architecture for an enterprise-specific perfSONAR deployment that can implement monitoring-objective based sampling and that adheres to any domain-specific measurement policies.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2013

U.S. DOE Southeast Clean Energy Application Center

Between 2010 and 2013, the U.S. Department of Energy (DOE) funded the Southeast Clean Energy Application Center (SE-CEAC), co-located at the North Carolina Solar Center at NC State University (NCSU) and at Mississippi State University. The SE-CEAC was one of eight regional CEACs established to promote and assist in transforming the market for combined heat and power (CHP), district energy (DE) and waste heat to power (WHP) throughout the U.S. CHP locates power generation at the point of demand and makes productive use of the residual thermal energy for process and space heating in factories and businesses, thus lowering the cost of meeting electricity and heat requirements and increasing energy efficiency. The overall goal of the SE-CEAC was to support end-user implementation and overall market transformation for CHP and related clean energy technologies. Five objectives were targeted to achieve the goal: 1. Market Analysis and Information Dissemination 2. Outreach and Education for Potential CHP End-users 3. Policy Support for State and Regional Stakeholders 4. Technical Assistance to Support CHP Deployment 5. Collaboration with DOE and other CEACs Throughout the project, the CEACs provided key services of education and outreach, technical assistance and market analysis in support of project objectives. These services were very effective at achieving key objectives of assisting prospective CHP end-users and informing policy makers, utilities and others about the benefits of CHP. There is a marked increase in the awareness of CHP technologies and applications as an energy resource among end-users, policymakers, utility regulators, electric utilities and natural gas utilities in the Southeast region as a result. At the end of 2013, a number of best-practice policies for CHP were applied or under consideration in various Southeast states. The SE-CEAC met its targets for providing technical assistance with over 50 analyses delivered for 412 MW of potential end-users CHP applications. Of these 50 MW of projects were under consideration at the end of 2013 based on SE-CEAC technical assistance findings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2015

2014 Vehicle Technologies Market Report

This is the sixth edition of this report, which details the major trends in U.S. light-duty vehicle and medium/heavy truck markets as well as the underlying trends that caused them. This report is supported by the U.S. Department of Energy s (DOE) Vehicle Technologies Office (VTO), and, in accord with its mission, pays special attention to the progress of high-efficiency and alternative-fuel technologies. After opening with a discussion of energy and economics, this report features a section each on the light-duty vehicle and heavy/medium truck markets, and concluding with a section each on technology and policy. The first section on Energy and Economics discusses the role of transportation energy and vehicle markets on a national (and even international) scale. The following section examines Light-Duty Vehicle use, markets, manufacture, and supply chains. The discussion of Medium and Heavy Trucks offers information on truck sales and technologies specific to heavy trucks. The Technology section offers information on alternative fuel vehicles and infrastructure, and the Policy section concludes with information on recent, current, and near-future Federal policies like the Corporate Average Fuel Economy standards. In total, the information contained in this report is intended to communicate a fairly complete understanding of U.S. highway transportation energy through a series of easily digestible tables and figures.

33 ADVANCED PROPULSION SYSTEMS↗