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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 OSTI2022

Development of a Configurable DERMS Test System in GridAPPS-D

Distributed Energy Resources and their increased penetration within the power grid are a suitable method to provide essential reliability services. In order to do so, they must operate in aggregate. Aggregation of a wide variety of systems with varying standards and protocols is a complex task, which could benefit from rules and standards to support interoperability. To this end, the Portland State University Power Lab has developed the Energy Grid of Things project, which includes a Distributed Energy Resource Management System to provide aggregation and demonstrate the usage of an Energy Services Interface: a set of rules governing the interface between resource owners and aggregator businesses. This thesis presents a Modeling Environment that provides a simulation and test platform reflecting the complex needs of an aggregator. A grid simulator is required that is able to reflect the effects of thousands of Distributed Energy Resources operating in tandem; furthermore, these effects must be communicated to external actors such as the Grid Operator, which provides grid service requests to the aggregator and requires feedback. The Modeling Environment provides all of this functionality by leveraging the GridAPPS-D platform to develop an interoperable class-based system that provides configurable simulations with modular input and output APIs. The Modeling Environment uses abstractions to allow any feasible type of input to be reflected within the model as a Distributed Energy Resource, and serves as a proof-of-concept for the development of aggregation simulation and testing within GridAPPS-D.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

A quantitative and holistic circular economy assessment framework at the micro level

Circular Economy (CE) aims to solve resource, waste, and emission challenges by creating a production-to-consumption supply chain that is restorative and environmentally benign. A variety of metrics has been developed with the focus mainly on the macro and meso levels. This work introduces a micro level CE assessment framework that provides i) a set of indicators and metrics with sector-specific dimensions, ii) quantitative and holistic CE overall and category-based metrics, iii) media for data visualization and analysis of CE indicators, and iv) an analytical tool to assess multi-national businesses and the multi-scale and interconnected CE supply chains. Using this quantitative tool, companies are able to track their transition towards CE, conduct temporal analysis, and benchmark their performance against their peers and industry’s standards. The applicability and the capabilities of the developed CE assessment framework is demonstrated through three case studies, with the results demonstrating a clear trend towards circularity.

42 ENGINEERING↗
DOE OSTI2024

Energy I-Corps Annual Report 2023

The U.S. Department of Energy Office of Technology Transitions is pleased to provide an update on the Energy I-Corps program. Now in its eighth year, Energy I-Corps delivers workforce development training and funding support to accelerate clean energy technology commercialization. As of November 2023, 215 teams from 12 National Labs have participated in Energy I-Corps over the course of 17 cohorts and the pilot. More than 20 teams have launched new businesses based on their Energy I-Corps technology. Post Energy I-Corps, technologies have attracted more than $177 million in post-program funding and executed 78 licenses.

commercialization↗
DOE OSTI2020

The Hardware of Smaller Clusters (V.3.0)

Chris Saunders and three technologists are in high demand from Sandia’s deep learning teams, and they’re kept busy by building new clusters of computer nodes for researchers who need the power of supercomputing on a smaller scale. Sandia researchers working on Laboratory Directed Research & Development (LDRD) projects, or innovative ideas for solutions on short timeframes, formulate new ideas on old themes and frequently rely on smaller cluster machines to help solve problems before introducing their code to larger HPC resources. These research teams need an agile hardware and software environment where nascent ideas can be tested and cultivated on a smaller scale.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

System Administrator Training Item #25928

External and internal cyber-attacks pose an extreme risk to government, businesses and individuals. System attacks, resulting in compromised information are occurring more frequently and the threat to the Laboratory has never been higher. This training has been developed to help you better understand your role as a System Administrator and recognize your responsibilities within the Laboratory’s Information Security (Cyber) Program and has been revised to address newly implemented ACD 470.6 restrictions for mobile devices in secure areas.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

U.S. ESCO Industry: Industry Size and Recent Market Trends

This study is the latest in a series of LBNL research into U.S. ESCO industry characteristics and market trends. The research is based on interviews with ESCO industry executives conducted during the fall of 2019 and the first half of 2020. Nearly all companies that identified themselves as ESCOs were contacted as part of this project. We find that after a period of little growth (2011-2014), industry revenues reached an estimated $6 billion in 2018, or a 3.4% annual average growth rate from 2015-2018. ESCOs primarily serve the public an institutional sectors (e.g., federal, state, and local governments; university and colleges; and K-12 schools). In 2018, project investments by public and institutional organizations accounted for over 90% of industry revenue, which is consistent with previous industry studies. ESCO activity in the Middle Atlantic, East North Central, and Pacific regions in the U.S. delivered the highest share of revenue in 2018, which is also consistent with earlier research. ESCOs reported that a majority of their customers use energy savings performance contracts (ESPCs) primarily for facility capital improvement needs and resilience rather than utility savings. In addition, the importance of non-energy benefits (e.g., water savings, avoided operations and maintenance costs, and avoided capital costs) accounted for in the project savings guarantee reportedly increased in all markets during 2016-2018 compared to previous time periods. The study found that the ESCO industry faces several key challenges, including: (1) increasing project development times due to more complex projects and other factors; (2) difficulty finding qualified subcontractors in some regions, including minority- women- and disadvantaged population-owned small business enterprises; and (3) difficulty accessing project documents and quickly fulfilling customer requests to justify project payments several years into the performance period of a project.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

A review of privacy in energy applications

As the distribution system continues to experience an increase in distributed energy resource (DER) and electric vehicle (EV) penetration, so does the need for new solutions that can help grid operators manage and leverage their capabilities. This will undoubtedly lead to new operational schemes and business opportunities that will transform the traditional consumer into a prosumer who will be more actively engaged in grid operations. Although the field is still under active development, many of the potential use cases presented in literature or industry are built upon edge computing, two-way communications, and other innovative computational constructs to attain their goals. However, at their core, many use cases assume a great level of data access to aid with the decision-making process, an assumption that may need to be revised to ensure fair and equitable operational processes are maintained. This may be particularly true as edge resources are predicted to participate in retail-side, many-to-many, or peer-to-peer markets and thus may lead to financial impacts if data access considerations are ignored. The need to revise data access mechanisms can be further justified by the introduction of new participants into the operational process, who do not have the same level of trust, nor the incentives to focus on energy delivery as their primary objective. At the same time, more consumers are becoming aware of their own data, and the potential impacts of its abuse. To help solution developers better understand these risks, this report has been developed to offer an initial introduction to the topic of privacy. This is achieved by 1) Highlighting the need for privacy-aware solutions; 2) Encouraging system designers to be inquisitive about the status quo; 3) Documenting the existing threat space; 4) Presenting and evaluating tools that may be helpful towards enabling better privacy postures; and 5) Making recommendations to encourage the adoption of better practices. From a technical perspective, the report focuses on evaluating two potential techniques by applying them to the Transactive Energy Space. Based on the obtained results, it can be established that differential privacy (DP) methods may have limited applicability when highly correlated, time-series data records need to be protected. However, DP may be a powerful tool when it is used to aggregate and analyze mid-size and large-size data sets in a more traditional statistical environment. The second tool under evaluation is threshold cryptography, which can guarantee complete secrecy (and thus privacy) but requires the establishment of key management procedures and dedicated communication channels for key coordination. Therefore, due to its increased computational overhead, the use of threshold cryptography must be weighted using a cost/benefit analysis on a per-application basis.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Transport Affordable Clean Hydrogen Energy via Existing Pipeline Infrastructure (CRADA 573)

Our Nation’s vast network of oil pipelines span over 230,000 miles connecting remote energy producing regions to distant markets. The COVID-19 pandemic’s influence on oil prices intensified technical and economic vulnerabilities afflicting the Trans-Alaska Pipeline System (TAPS, operating below 25% capacity) that may soon resurface as energy demand shifts to low carbon sources. Through the opportunity afforded by the Arctic Advanced Manufacturing Program, I’ve toured the great State of Alaska learning about its culture, unique energy challenges, business ecosystem, research institutions, and regulatory agencies. With encouragement and support from dedicated Alaskans and my professional mentors, I’ve founded Mighty Pipeline for the purpose of developing and commercializing proprietary technology and hardware to convert oil pipelines into clean hydrogen energy transmission systems. Leveraging the advanced technical capabilities of Pacific Northwest National Laboratory, we’ve demonstrated proof-of-concept (TRL = 3) and are seeking pre-pilot development project opportunities to conduct hardware and system level tests. If we successfully achieve technical and regulatory milestones, Mighty Pipeline’s technology could be available to help facilitate bulk clean hydrogen energy export this decade.

08 HYDROGEN↗
DOE OSTI2022

Energy Storage Valuation: A Review of Use Cases and Modeling Tools

An enticing prospect that drives adoption of energy storage systems (ESS) is its ability to be used in a diverse set of use cases and the potential to take advantage of multiple unique value streams. The Energy Storage Grand Challenge (ESGC) technology development pathways for storage technologies draw from a set of use cases in the electrical power system, each with their own specific cost and performance needs. In addition to the need for cost and performance improvements for storage technologies, there a need for robust valuation methods to enable effective policy, investment, business models, and resource planning. There are numerous storage valuation tools available to the public, many of which can analyze the value of an ESS project with inputs and characteristics that reflect a specific storage use case. To effectively reach ESS stakeholders that may be interested in learning about valuation models, this report will draw from publicly available tools developed by the Department of Energy (DOE) and frame their functionalities and capabilities within the context of three distinct use case families. This report examines three of the ESGC use case families in depth and provides a methodology in which interested stakeholders can determine which DOE modeling tool is best suited to value ESS for their specific case. The high-level objectives for this report include: (1) Provide specific sub use-cases for each use case family for further characterization; (2) Provide technical parameters and relevant data for three example use cases that could be used in a valuation tool; (3) Identify a list of publicly available DOE tools that can provide energy storage valuation insights for ESS use case stakeholders; (4) Provide information on the capabilities and different options in each modeling tool; (5) Make conclusions on which are best suited for valuing certain functional/performance requirements and which tools might be applicable to other use cases; and (6) Show the methodology that informs a Model Selection Platform (MSP) framework that educates stakeholders on different DOE models and provides a streamlined way to choose the right model that most closely matches their needs.

25 ENERGY STORAGE↗
DOE OSTI2021

Controlled Pyrolysis: A Robust Scalable Composite Recycling Technology

The reinforced composites industry is facing significant challenges in handling the scrap composite material from automobile manufacturing, the wind turbine industry, and others. The fibers in the material, whether they be carbon, glass, or other materials have commercial value if they can be recovered successfully. Successfully means the fibers are clean with no sizing or other binders and have adequate strength and physical properties that would allow them to be economically reprocessed into valuable product. The composites recycling project was an industry-collaborative effort to develop a composite recycling technology using controlled pyrolysis. Through the recycling of scrap and end-of-life (EOL) cured composite materials, this pilot study was intended to create a business case by realizing a cost-effective means for recycling EOL and production scrap composite materials, ultimately reducing the volume of composite materials destined for landfill. The project was led by the Institute for Advanced Composites Manufacturing Innovation (IACMI), the American Composites Manufacturers Association (ACMA), Oak Ridge National Laboratory (ORNL), Continental Structural Plastics (CSP) a Teijin Group Company, CHZ Technologies, and A. Schulman with support from Owens Corning, John Deere, General Electric (GE), Ashland LLC, and Plastics Europe (CEFIC). The team studied and tested CHZ Technologies’ controlled pyrolysis system, known as the Thermolyzer TM , which operates on a scalable basis to convert organic polymer materials into a clean synthesis gas and char containing the recoverable carbon and glass fiber reinforcement. The recoverable energy contained in the input polymers creates the synthesis gas that can be used to provide heat to the Thermolyzer TM primary reactor in a sustainable manner. That is, once the Thermolyzer TM is started with a small amount of external natural gas, the synthesis gas that is created from the polymers will continue to operate the burners so long as feedstock is supplied. The reinforcing fiber materials remaining in the solid phase char were separated and cleaned for re-use in other polymer systems based on the retained properties of the fibers. The study created reports (attached in the appendix) on the Mass and Energy Balances, syngas analytics, VOC assessment, yield analysis and other analytics necessary for a Techno-Economic Analysis (TEA) to quantify the economic impact of the recovery and sustainable re-use of the carbon and glass fibers. The process consisted of 4 steps: Selection of 4 samples of cured composite waste materials from project partners interested in materials recycling and recovering the reinforcing fibers for best case re-use. The materials included glass fiber (GF) polyester/vinyl ester automotive SMC from CSP, GF epoxy balsa/PVC foam wind blades from GE, carbon fiber (CF) epoxy wind blade laminated spar caps from GE, and GF/CF epoxy hybrid assembly from John Deere. Processing the waste composite samples into 1-2” shreds. Packaging the shredded composites into bulk sacks on international shipping pallets for shipment to KUG in Forst (Lausitz), Germany. Pyrolysis of the shredded composites under controlled conditions designed for each polymer system. Collecting samples of the gas and char for analysis. Shipping the char containing the CF/GF back to the US for the next steps of testing the fibers and developing protocols for sustainable re-use of the fibers in composite applications.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Differentially Private Map Matching (DPMM) v1.0

Human mobility trajectories provide valuable information for developing mobility applications, as they contain diverse and rich information about the users. User mobility data is valuable for various applications such as intelligent transportation systems (ITS), commercial business models, and disease-spread models. However, such spatio-temporal traces may pose a threat to user privacy. GPS trajectories in their raw form are not suitable for transportation studies, as they require matching locations with nearest road links — a process called map-matching. This software implements a differential privacy (DP)-based map-matching algorithm, called DPMM, that generates link-level location trajectories in a privacy-preserving manner to protect users' origin destinations (OD) and travel paths. OD privacy is achieved by injecting Planar Laplace noise to the user OD GPS points. Travel-path privacy is provided with randomized travel path construction using exponential DP mechanism. The injected noise level is selected adaptively, by considering the link density of the location and the functional category of the localized links. For path privacy, our mechanism samples waypoints and selects candidate paths between waypoints. DPMM provides privacy effectively with respect to link density instead of other trajectory samples in the database compared to other privacy mechanisms. Compared to the different baseline models our DP-based privacy model offers closer query responses to the raw data in terms of individual and aggregate trajectory-level statistics with an average at absolute deviation from the baseline for individual statistics on ϵ = 1.0. Beyond individual trajectory statistics, the DPMM outperforms the other benchmark DP-based mechanisms on different aggregate statistics with up to 8x improvement in utility.

Peisert, Sean [Lawrence Berkeley National Laborato↗
DOE OSTI2021

SiPA | Simple Partnership Agreement for accelerating early-stage collaborations between startups and large corporations

The technologies required to advance society will come from research from a broad range of scientific disciplines including materials science, chemistry, physics, and biology where the innovation relies on a scientific breakthrough rather than a software or business model innovation. This science-based technology focus can be referred to as “hardtech,” although there is much crossover with the concept of “cleantech.” These new technology developments will have vast reach across most industrial sectors - energy, materials, manufacturing, electronics, life sciences, etc. - with great economic consequences. The majority of these scientific breakthroughs will be produced and developed by those companies best suited for high-risk, early-stage development work: startups.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Multi-level impacts of climate change and supply disruption events on a potato supply chain: An agent-based modeling approach

Context: The world is experiencing frequent extreme weather events like droughts, snowstorms, and shifting of seasons due to climate change. Increased frequency and severity of these extreme weather events threaten food security because agriculture depends on climate conditions. Impacts of climate change on the agricultural system not only occur at the grower’s level, but also cascade to other levels along the supply chain. Objective: In this study, we aim to quantify a wide range of economic impacts of different extreme climate events on different stages of a food supply chain. Methods: We chose the potato supply chain in Idaho as a case study. We developed a multi-echelon supply chain simulation model using an agent-based modeling (ABM) approach with five types of agents—farmers, shippers, processors, retailers, and logistics companies. In addition to the business-as-usual (BAU) scenario, we designed two climate-related disruption events—drought and snowstorm. We quantified the heterogeneous impacts at different stages of the supply chain for both fresh and processed potatoes using key performance indicators (KPIs) including revenues, prices, lead times, traded quantities, and food waste quantity. Results and Conclusion: The impacts of the disruption events are different on different agents in the supply chain for different product categories. The price hike of fresh potatoes is far higher than processed potatoes during disruption events. This price hike makes consumers switch to processed potatoes, which require more fresh potatoes as an input that further reinforces the price hike. However, because processed potatoes have an elastic demand, once their prices go up due to higher input cost, their demand drops. Non-contracted farmers gain additional revenues from the disruption events, whereas contracted farmers incur a loss due to lock-in price and lower than usual harvest. Significance: The methodology developed in this study could be applied to other food and agricultural supply chains for understanding the vulnerabilities at agent levels due to climate change disruption events. Furthermore, the findings would help develop mitigation strategies or policies to improve the well-being of the overall supply chain.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Dynamic projection of anthropogenic emissions in China: methodology and 2015–2050 emission pathways under a range of socio-economic, climate policy, and pollution control scenarios

Abstract. Future trends in air pollution and greenhouse gas (GHG)emissions for China are of great concern to the community. A set of globalscenarios regarding future socio-economic and climate developments, combiningshared socio-economic pathways (SSPs) with climate forcing outcomes asdescribed by the Representative Concentration Pathways (RCPs), was createdby the Intergovernmental Panel on Climate Change (IPCC). Chinese researchers have also developed various emission scenarios by considering detailed local environmental and climate policies. However, a comprehensive scenario set connecting SSP–RCP scenarios with local policies and representing dynamic emission changes under local policies is still missing. In this work, to fill this gap, we developed a dynamic projection model, the Dynamic Projection model for Emissions in China (DPEC), to explore China'sfuture anthropogenic emission pathways. The DPEC is designed tointegrate the energy system model, emission inventory model, dynamicprojection model, and parameterized scheme of Chinese policies. The modelcontains two main modules, an energy-model-driven activity rate projectionmodule and a sector-based emission projection module. The activity rateprojection module provides the standardized and unified future energyscenarios after reorganizing and refining the outputs from the energy systemmodel. Here we use a new China-focused version of the Global ChangeAssessment Model (GCAM-China) to project future energy demand and supply inChina under different SSP–RCP scenarios at the provincial level. Theemission projection module links a bottom-up emission inventory model, theMulti-resolution Emission Inventory for China (MEIC), to GCAM-China andaccurately tracks the evolution of future combustion and production technologiesand control measures under different environmental policies. We developedtechnology-based turnover models for several key emitting sectors (e.g.coal-fired power plants, key industries, and on-road transportationsectors), which can simulate the dynamic changes in the unit/vehicle fleetturnover process by tracking the lifespan of each unit/vehicle on an annualbasis. With the integrated modelling framework, we connected five SSP scenarios(SSP1–5), five RCP scenarios (RCP8.5, 7.0, 6.0, 4.5, and 2.6), and threepollution control scenarios (business as usual, BAU; enhanced controlpolicy, ECP; and best health effect, BHE) to produce six combined emissionscenarios. With those scenarios, we presented a wide range of China's futureemissions to 2050 under different development and policy pathways. We foundthat, with a combination of strong low-carbon policy and air pollutioncontrol policy (i.e. SSP1-26-BHE scenario), emissions of major airpollutants (i.e. SO 2 , NO x , PM 2.5 , and non-methane volatile organic compounds – NMVOCs) in China willbe reduced by 34%–66% in 2030 and 58%–87% in 2050 compared to 2015. End-of-pipe control measures are more effective for reducing air pollutant emissions before 2030, while low-carbon policy will play a more important rolein continuous emission reduction until 2050. In contrast, China's emissionswill remain at a high level until 2050 under a reference scenario without activeactions (i.e. SSP3-70-BAU). Compared to similar scenarios set from theCMIP6 (Coupled Model Intercomparison Project Phase 6), our estimates ofemission ranges are much lower than the estimates from the harmonized CMIP6 emissions dataset in2020–2030, but their emission ranges become similar in the year 2050.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Projected changes in extreme streamflow and inland flooding in the mid-21st century over Northeastern United States using ensemble WRF-Hydro simulations

Study region: Northeastern United States (NEUS). Study focus: We investigate the potential impacts of climate change on precipitation, streamflow, and inland flooding in the NEUS during the mid-21st century. Dynamically downscaled climate projections from three global climate models for historical (1995-2004) and future (2045-2054) periods under business-as-usual scenarios were used to force the hydrologic model WRF-Hydro at 200-meter resolution and create ensemble hydrologic simulations. Additionally, an extreme value model was developed to project the risks associated with low-frequency hydrologic events. New hydrological insights for the region: Results from four major watersheds indicate a significantly wetter regime in winter months and potential drier conditions during late spring to early summer. Discharges in fall are projected to decrease in the northern watersheds and increase toward the south. Extreme flow and water depths resulting from extreme inland flooding are projected to increase by 5-20% and > 100%, respectively. The extent of the total flooded area is likely to be 20% greater by the mid-century. These increased risks can be attributed to (i) an approximate 25% increase in decadal mean and > 40% increase in decadal extreme precipitation intensity, (ii) up to 30% lower snow availability and 5-25% higher evapotranspiration throughout the year, and (iii) a projected 5% increase in soil moisture in all seasons except summer. Furthermore, rapid snow melting in winter will likely cause an earlier peak flow in the rivers.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Improving Performance via Energy Efficiency JUSTIFI: Open-Source Software for Identifying and Quantifying Non-Energy Benefits

Energy efficiency is pivotal to achieving operational excellence, as it enhances value while reducing waste. This presentation explores the integration of non-energy benefits (NEBs) into energy efficiency projects, which can lead to risk reduction, value creation, and cost savings. By quantifying NEBs - such as improved safety, decreased pollution, and increased productivity - companies can strengthen their business cases for energy investments, ultimately improving payback periods and aligning with strategic goals. Designed for a diverse audience, from trained auditors to novices in energy assessments, we have developed open-source software called JUSTIFI, NEB finding methodology, and training materials which build on existing frameworks and leverages resources from the U.S. Department of Energy and Better Plants energy system analysis software suite such as MEASUR. This work aims to maximize ROI through NEB identification, utilizing tools like JUSTIFI and the NEBs Discovery Protocol.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Cybersecurity Education, Training, and WFD

Availability of skilled workforce in sufficient number is one of the most often cited barriers to improving cybersecurity. INL's research has determined that this is not a cybersecurity problem but rather a strategic business imperative; in response INL created the Cyber Competency Health and Maturity Progression Model (Cyber-CHAMP) to help organizations learn the realities of their cyber workforce and their development needs. The presentation starts with an overview of Cyber-CHAMP as a unifying theme for workforce development and then provides brief introductions to selected DHS (ICS cybersecurity hands-on training), DOE (CyberStrike, OT Defender Fellowship, Liberty Eclipse), and INL (Cybercore Summer Camp, University Collaboration Laboratory) programs. Cyber-Informed Engineering discussion concludes the presentation, with an update on activities conducted by the CIE Education Working Group to further the second pillar of the National CIE Strategy, Education.

42 ENGINEERING↗