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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Options For Large-Scale Installation of Individual Heat Substations Based on International Best Practices

The purpose of this report is to provide recommendations for actions Ukraine could take to implement large-scale installation of IHSs as part of comprehensive district heating reform. The report discusses the importance of IHS in the district heating sector, then presents several case studies of approaches that European countries have taken to facilitate large-scale IHS installation in multi-apartment buildings. These case studies focus on the ownership and financing of IHS, as there are different models for how this can be done (the DH company can make the investments and recover the costs through the tariff, or building residents can make the investments themselves). They also include details on the approval process and technical specifications, as these can add additional barriers and time to the installation process.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Capital Structure for Techno-Economic Analysis of Hydrogen Projects

This report provides updated generally accepted accounting principles (GAAP) parameter estimates of assumptions that may be used to reflect the cost of financing hydrogen infrastructure deployment. The report also provides parameter estimation for more streamlined financial analysis frameworks such as discounted cash flow and annualized financial models. Parameter values are derived from industry feedback and are reflective of current macro-economic factors such as higher interest rates and higher risk profile of emerging hydrogen technologies, given a myriad of factors such as projects’ construction inexperience, capital costs, and rising inflation, among others.

08 HYDROGEN↗
DOE OSTI2021

Electrifying Transit: A Guidebook for Implementing Battery Electric Buses

This guidebook is organized to give transit decision-makers and relevant stakeholders an overview of BEB facts, data, and considerations important for planning their implementation in a variety of jurisdictions. First, the benefits and barriers for BEB are identified. Second, BEB basics in terms of the major components, including a) the bus, b) the battery, and c) the numerous charging options. BEB introduces new, high demand loads as the buses are charging and thus have a number of interactions with the electricity grid and the utility, which are explored third. Operation and maintenance of BEBs are considered fourth as BEBs should not be operated and maintained in the same approach as diesel buses. Fifth, the costs of BEB prices are summarized – and the choices of bus and battery are explored in how they impact BEB prices. Funding and financing options that support BEBs and their charging stations are also explored. Safety is a key consideration for BEBs and the guidebook touches upon codes and standards, hazards, and emergencies. The final section examines project execution, bringing together information from all the other sections so that long-term planning, route analysis, and fleet and infrastructure planning can be considered in the preparation of BEB deployment, and then deployment can be evaluated on a regular basis. A final conclusion revisits the information covered in the guidebook.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Continuous-variable quantum Boltzmann machine

Here, we propose a continuous-variable quantum Boltzmann machine (CVQBM) using a powerful energy-based neural network. It can be realized experimentally on a continuous-variable (CV) photonic quantum computer. We used a CV quantum imaginary time evolution (QITE) algorithm to prepare the essential thermal state and then designed the CVQBM to proficiently generate continuous probability distributions. We applied our method to both classical and quantum data. Using real-world classical data, such as synthetic-aperture radar (SAR) images, we generated probability distributions. For quantum data, we used the output of CV quantum circuits. We obtained high fidelity and low Kullback–Leibler (KL) divergence showing that our CVQBM learns distributions from given data well and generates data sampling from that distribution efficiently. We also discussed the experimental feasibility of our proposed CVQBM. Our method can be applied to a wide range of real-world problems by choosing an appropriate target distribution (corresponding to, e.g., SAR images, medical images, and risk management in finance). Moreover, our CVQBM is versatile and could be programmed to perform tasks beyond generation, such as anomaly detection.

SAR images↗
DOE OSTI2022

Cost of Capturing CO 2 from Industrial Sources

This systems analysis by the National Energy Technology Laboratory's Strategic Systems Analysis and Engineering directorate) evaluates the cost and performance impacts of capturing CO 2 emissions from nine industrial sources (ammonia, ethylene oxide, and ethanol production, natural gas process, coal- and gas-to-liquids, refinery hydrogen production, iron and steel, and cement manufacturing). The industrial sectors examined are segregated according to the CO 2 purity level of the flue gas stream, prior to treatment. Certain sectors naturally produce a gas stream that is inherently high in CO 2 purity, and these sectors can achieve 99-100% removal. Other sectors produce a lower purity CO 2 flue gas stream and achieving 90-99% removal requires deeper levels of treatment, adding cost. In addition to the report that documents the analysis, a Carbon Capture Retrofit Database tool was also created that allows users to apply CO 2 capture to selected industries, to evaluate the cost of capture and compare across multiple plants, as well as across different industries. Users have the ability to change select input parameters (such as fuel price, capture rate, and financing assumptions) to evaluate the impact on industrial CO 2 capture economics.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2022

Front End Engineering Design of Linde-BASF Advanced Post-Combustion CO 2 Capture Technology at a Southern Company Natural Gas-Fired Power Plant (Final Scientific/Technical Report)

This document details the execution of Cooperative Agreement DE-FE0031847, “Front End Engineering Design of Linde-BASF Advanced Post-Combustion Carbon Dioxide (CO 2 ) Capture Technology at a Southern Company Natural Gas-Fired Power Plant” during the period of 10/1/2019 to 6/30/2022. The project was funded by the U.S. Department of Energy’s Office of Fossil Energy and Carbon Management (FECM) and managed by the National Energy Technology Laboratory (NETL). Southern Company Services, Inc. (SCS) was the prime recipient and led the project team. Other members of the project team included Linde, Inc. (Linde), Linde Engineering – Dresden (LED), and BASF. The overall goal of the project was to complete a front-end engineering design (FEED) study for installing the Linde-BASF post-combustion capture (PCC) technology at an existing domestic natural gas-fired combined cycle (NGCC) power plant within Southern Company’s portfolio of assets. The CO 2 capture plant was to be of commercial scale (at least 375 MWe) and include process units for pre-conditioning of the flue gas system, the CO 2 capture plant island, storage vessels, the CO 2 compression train, and any necessary components for integration into the NGCC plant. Mississippi Power’s Plant Daniel Unit #4 was chosen as the host site for the FEED with the target of capturing 90% of CO 2 emissions from the existing combustion turbines. The information produced by the FEED was used to develop a cost estimate of +/- 15% accuracy. Capital costs, excluding financing, are estimated at approximately $\$752$ million dollars (2021). The execution of a project based on this FEED study has an estimated duration of almost five years.

03 NATURAL GAS↗
DOE OSTI2022

twoaxistracking – a python package for simulating self-shading of two-axis tracking solar collectors

Self-shading in fields of two-axis tracking collectors typically ranges from 1% to 6% of the annual incident irradiation. It is thus essential to account for shading in order to obtain accurate yield estimates and financing for such solar projects. The present study presents the free and open-source Python package twoaxistracking for simulating self-shading in fields of two-axis tracking collectors. The package is freely available at: https://github.com/pvlib/twoaxistracking. The main steps of the method and mathematical formulation are described. Additionally, a demonstration of how to use the package is presented. The shading calculation method excels over previous methods found in the literature in that it can: handle arbitrary aperture geometries and distinguish between the total and active areas; account for sloped ground and collectors with different heights within the same field; reduce computation time by skipping calculations at high solar elevation angles.

14 SOLAR ENERGY↗
DOE OSTI2024

The potential of carbon markets to accelerate green infrastructure based water quality trading

Green infrastructure solutions can improve in-stream water quality in lieu of building electricity-consuming gray infrastructure. Permitted under the United States Clean Water Act, these programs allow regulated utilities to trade point-source water quality obligations with non-point source mitigation efforts in the watershed. Carbon financing can provide an incentive for water quality trading. Here we combine data on impaired waters, treatment technologies, and life cycle greenhouse gas emissions in the Contiguous United States, and compare traditional treatment technologies to alternative green infrastructure. We find green infrastructure could save $\$15.6$ billion dollars, 21.2 terawatt-hours of electricity, and 29.8 million tonnes of carbon dioxide equivalent emissions per year while sequestering over 4.2 million tonnes CO2e per year over a 40 year time horizon. Green infrastructure solutions may have the potential to generate $\$679$ million annually in carbon credit revenue (at $\$20$ per credit), which represents a unique opportunity to help accelerate water quality trading.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Information Searching in the Residential Solar PV Market

This paper examines the consumer information search behavior of households in San Diego County with solar photovoltaic (PV) systems. We focus on whether solar PV households financing the technology through third-party ownership (TPO) versus host-ownership (HO), which is equivalent to leasing or buying goods in other markets, have heterogeneous preferences as reflected by information search. Conditional on adoption, we find that TPO households tend to seek more information on home modifications required for solar installation whereas HO households seek more information on the financial returns of solar investments. These preferences may be correlated with the consumption of other goods and services, and thus, if used to inform marketing strategies, our results could help reduce solar PV customer acquisition costs and accelerate technology diffusion. They also have indirect implications for marketing goods and services in other contexts where consumers exhibit similar preferences.

California↗
DOE OSTI2022

Cyber Threat Landscape for Distribution Systems

INL cyber analysts will present an overview of the current threat landscape for distribution systems. We will begin with examples of known attacks that have occurred recently to motivate the threat analysis and mitigation discussed in the remainder of the presentation. Examples may include the attacks affecting wind plants in Europe in Spring 2022, ransomware attacks on city utilities and commercial distribution systems, and advanced persistent threats (APTs) including the attacks on Ukrainian electric system in 2015 and 2016, as well as more recent evidence of other APT activity. We will present the end-to-end attack paths and discuss the various attacker skills, financing, motivations, and access that contributed to these attacks. In the second part of this presentation, we will discuss mitigating the cyber threats for distribution systems. We will discuss recent publicly disclosed vulnerabilities and explain their relevant context for distribution system security. Likely attacks to affect distribution systems, such as denial-of-service (DoS), ransomware, edge-device compromise, and advanced persistent threats (APTs) will be described. In addition to an overview of these kinds of attacks, we will provide examples of the various ways in which these attacks can start and what systems they can affect. Simple, cost-effective counter-measures to these attacks will be discussed and we will emphasize how these mitigations can reduce threats when properly applied and maintained.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Policies and Programs Available in the United States in Support of Carbon Capture and Utilization

The article seeks to compile policies and programs that provide revenue and financing support for carbon capture and utilizations projects, which are available in the United States. Often technically minded entrepreneurs and investors new to this space are unaware of available support, which could help successful development of carbon capture and utilization projects.Covered in this article are the 45Q tax credit, green bonds, loan guarantee programs, the regional greenhouse gas initiative, and low carbon fuel standards.1This article covers the eligibility and effect of each policy and program. The article also briefly reviews the current state of technology and summarizes how each technology pathway pairs with the policies covered in the article.The goal of the article is to serve as a primer for lawyers, corporate development professionals, and practitioners, who seek to learn about policies and programs available to support carbon capture and utilization (CCU) projects.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Understanding the Challenges of Financing Modular Construction: A Case Study for Prospective Multifamily Units

Compared to traditional site build, modular construction can significantly shorten construction schedules and speed income generation. Modular construction may also reduce construction costs. Yet access to commercial financing remains one of the most significant barriers to modular construction. Materials must be purchased, and production lines reconfigured for each project months ahead of fabrication. Materials alone can be 60% or more of the total cost of production. As a result, manufacturers require large upfront deposits—often 30% or more of the off-site contract. In addition, the capital-intensive nature of modular construction requires frequent progress payments for manufacturers to maintain cash flow. For those lenders willing to fund modular projects, many require the developer to share more of the risk. This may include the developer paying for line reservation fees and material deposits 3–6 months prior to production. Because these are unsecured loans, interest rates may be higher and loan amounts lower. As suppliers, modular manufacturers discourage retainage. Together, these and other factors may contribute to higher equity requirements for the developer—particularly at the beginning of the project.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

Performance of solar leasing for low- and middle-income customers in Connecticut

Policymakers are increasingly interested in expanding access to rooftop photovoltaic systems. This study analyzes the financial performance of a Connecticut Green Bank (CGB) solar leasing program, run in partnership with PosiGen, that targets low- and moderate-income customers. We show that this program has successfully reached underserved customers and has reasonable repayment rates given the credit characteristics of the participants. The CGB/PosiGen program reaches many more underserved customers than other PV financing programs in Connecticut.For example, the majority of CGB/PosiGen participants (58%) live in census tracts that have a median income of less than 80% of the area median income (AMI). In contrast, only 9% of participants in the other CGB solar financing programs live in these census tracts. Furthermore, the majority of CGB/PosiGen participants (56%) have FICO scores that would generally be considered non-prime (<670), whereas only 2% of participants in the other programs have similarly low scores. Credit, not income, is the primary factor that explains participants’ financial performance. Overall, we find that delinquency and annualized losses are higher for PosiGen (2.3% and 0.9%) than for other CGB programs (1.4% and 0.1%). Across the CGB programs, lower credit scores are associated with higher rates of delinquency and loss. Therefore, participants’ lower credit scores explain much of the program’s higher rates of delinquency and annualized losses. PosiGen leases perform competitively with market-rate solar and non-solar leases and loans. When compared to securities backed by market-rate PV loans and leases with similar amounts of seasoning, we find that the PosiGen leases have higher delinquency rates but comparable gross loss rates. The similarity in losses is notable given that loss rates for PosiGen leases were higher than those of the other CGB leases and loans. Rather than the PosiGen leases having high loss rates, other CGB leases and loans have unusually low loss rates. We also compare PosiGen to non-solar benchmarks, including indices of auto and consumer loans. We find that the PosiGen leases have significantly less delinquency than non-prime auto loans and have performance comparable to many consumer loans. The U.S. Department of Energy’s Solar Energy Technologies Office supported this research.

14 SOLAR ENERGY↗
DOE OSTI2021

Deciphering Degradation: Machine Learning on Real-World Performance Data (Final Report)

This project addresses a fundamental flaw in solar PV research and solar project financing; the assumed rate of degradation for solar plants. The solar industry currently relies on an out-dated report that observed a 0.5% degradation rate based on a small sample size of systems (~100). While the research conducted at the time was new and innovative, the solar community has not updated this research and universally applies this 0.5% degradation assumption in financial models. Our project updates this assumption by analyzing observed degradation from the industry’s largest dataset of operating solar assets (>10,000 systems) and creating the first machine-learning model based on these observed results to quantify and identify features that drive degradation. There are two strategic goals for this award: reduce the cost of capital (enable solar to attract more capital) and improve the reliability of solar itself. These dual goals are achieved by leveraging an industry dataset to observe system degradation on a large scale, deploying advanced data analysis and machine learning methods to quantify and predict system reliability, and engaging with industry stakeholders to help them accurately price degradation in financial models.

14 SOLAR ENERGY↗
DOE OSTI2026

Evolution of storage monitoring – update in response to commercial and regulatory drivers

Carbon Capture and Storage (CCS) is in transition from first-of-a kind projects and research-orientated pilots to commercially-motivated applications. Monitoring results from many newly developed and planned large scale commercial projects are limited; however, it is worthwhile to assess their evolution and consider new strategies as part of an effort to assess and document best practices. Commercial monitoring is targeted to activities that comply with regulatory drivers and de-risk investments. Commercial monitoring also supports accounting that storage has occurred and is tied to project financing. It deals with long time frames and large volumes injected into multiple wells and multiple projects in favorable areas. We see developing trends toward reproducible workflows that systematically reduce risks and clarify expectations for oversight and long-term surveillance. Monitoring techniques showing increasing trends include injection zone pressure as a history-matching and compliance tool. To reduce cost and environmental impact of time-lapse seismic data collection, deploying new approaches and tools, such as use of fibre and installed sources are increasingly applied. Concern over the risk of induced seismicity by regulatory bodies and the general public has increased, which has also resulted in increased monitoring. Some techniques used in the early research phases have been sidelined or used only in restricted applications. For example, geochemical analyses in the injection zone as well as the environment are now being deployed less than it was in research-oriented programs, except in the US where it is required by the permitting process. Expectations of frequent area-wide near surface monitoring have also decreased.

25 ENERGY STORAGE↗
DOE OSTI2025

Securing Federated Learning Against Active Reconstruction Attacks

Federated Learning (FL) has amassed notable attention for its ability to preserve user privacy while emphasizing the retainment of model training efficiency. Due to this potential, FL has been integrated in many domains, such as healthcare, finance, law, and industrial engineering, where data cannot be easily exchanged due to sensitive information and strict privacy laws. However, current research has indicated that FL protocols are easily compromised by active data reconstruction attacks employed by actively dishonest servers. The malicious modification of global model parameters allows an actively dishonest server to obtain a direct copy of users’ private data via gradient inversion. Here, this class of attacks is highly underexplored and continues to be a major challenge due to the intense threat model. In this paper, we propose OASIS as a scalable and modality-agnostic defense based on data augmentation that counteracts active data reconstruction attacks while preserving model performance. To generalize our defense, we uncover the intuition behind gradient inversion that enables these attacks and theoretically establish the conditions by which the defense can be considered robust regardless of attack design. From this, we formulate our defense with data augmentation that illustrates its ability to undermine the attack principle. We evaluate OASIS on five real-world datasets–two image-based (ImageNet and CIFAR100) and three text-based (Wikitext, Stack Overflow, and Shakespeare)–which span diverse uses cases such as vision tasks and language modeling. Comprehensive evaluations on these datasets exhibit the efficacy of OASIS and highlight its feasibility as a solution.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Development and Demonstration of a Fuel-Efficient, Class 8 Tractor & Trailer Engine System (SuperTruck II)

Navistar presents the SuperTruck II (ST II) Final Report to the Unites States Department of Energy (US DOE), which covers the five Budget Periods (BPs) from 10-1-2016 through 6-30-2022. For ST II, Navistar built on the achievements of the SuperTruck I (ST I) Program as a catalyst to continue critical research, design and development, testing, and operations to reach the ambitious goals of the ST II project. This approach allowed Navistar to continue contributing to the essential needs of our nation for safe, efficient, and cost-effective delivery of goods and services, as we reduced negative environmental effects and improved operational productivity. This document contains information specified in DOE F 4600.2, Final Scientific/Technical Report DOE F 241.3, B. SCIENTIFIC/TECHNICAL REPORTS, explaining how we met and exceeded program requirements. Throughout this Final Report, Navistar extracted information from documents prepared during the project that represent our management, design and development, building, and testing efforts to meet and exceed SuperTruck II project goals. Navistar followed Plan requirements to achieve / exceed Project Objectives: a) >100% improvement in vehicle freight efficiency (FE) (on ton-MPG basis) relative to 2009 baseline with stretch goal of 140% improvement [actual: 170%); b) >55% engine brake thermal efficiency (BTE) demonstrated in operational engine at a 65-mph cruise point on a dynamometer – ≥31% increase from 2009 baseline [actual: 55.20% of combined BTE) ; and c) development and implementation of commercially cost effective technologies (in terms of a simple payback). Technology selection / development path focused on developing technologies applicable for production within 3-year approach, while ensuring technology readiness and cost of ownership for end users. The Program was organized into five budget periods: Requirements / Technology Assessment and Initial Hardware Testing; Technology Development and Concept Readiness Demonstration; Technology Finalization and Validation Tractor / Trailer Fabrication, Integration and Commissioning Demonstration; and Fuel Economy (FE) and Brake Thermal Efficiency (BTE) and Program Completion. Leadership was provided by DOE, with tasks performed by laboratories (Argonne National Laboratory, Lawrence Livermore National Laboratory); partners at Bosch, TPI, Dana, and J.B. Hunt; , and support from University of Michigan and Clemson University. Navistar lead this team with Principal Investigator / Contracting Officer; Project Manager (PM); Vehicle, Engine, and Aftertreatment Engineers; Finance Manager, Technical Program Leads, and Legal/IP; and other key personnel. Work also included personnel in risk management; funding / budget / finance. Work involved analysis, development, testing, and down selection of individual/system engine, aftertreatment, and vehicle technologies, with integration of selected technologies into a prototype vehicle for demonstration of fuel-efficiency gain. Work also included component/integrated system level development of truck and trailer aerodynamics, base engine efficiency, advanced aftertreatment, combustion efficiency, waste heat recovery, hybrid powertrain, reduced rolling resistance, weight reduction, idle reduction, and driver feedback. As ST II progressed, Navistar performed computer-based modeling / simulations of technologies focused on the primary operational areas: Engine, Aftertreatment, and Vehicle. During the ST II Program, the COVID Virus outbreak unexpectedly challenged by the effects of, which affected staffing, scheduling, design, supplies, availability of materials, production procedures, and testing. The DOE responded by extending the program by three quarters to ensure that project tasks were completed for this vital project. Focus continued on analyzing, developing, testing, and down selecting individual-/system-level engine and vehicle technologies for integration of the final selected technologies into a prototype vehicle that would demonstrate fuel-efficiency gains made possible through these technologies. This included component/integrated system-level development of truck and trailer aerodynamics, base engine efficiency, advanced aftertreatment, combustion efficiency, waste heat recovery, solar power, distributed and intelligent vehicle power, hybrid powertrain, reduced rolling resistance, weight reduction, idle reduction, and driver feedback. Throughout the program, function, reliability, and performance at all levels were ensured through testing. Proof of this approach was demonstrated in multiple, on-road demonstrations: Scenario A (Flatland) Fuel Economy, Scenario B (Hilly) Fuel Economy, and City Cycle Tests. Other benefits derived from ST II included new/improved products, publications, patents, and next-step capabilities related to electric/hydrogen vehicles and autonomous driving.

Zukouski, Russ↗
DOE OSTI2026

All Systems Go: Regional Collaborations for Scaling AEC Innovation: Preprint

The high and rising cost of preserving and delivering housing in the U.S. requires changes to existing practices of finance, design, and construction. Innovative methods such as industrialized construction could offer the means to address housing undersupply while reducing delivery costs, operational costs and material waste in the building industry, but they face challenges to success and to scale. Simultaneously, construction and cleantech innovators themselves face skepticism from the traditional entrepreneurial ecosystem such as incubators and accelerators while attempting to navigate systems level challenges. To respond to this need, various public and private sector stakeholders have launched initiatives to support innovative companies. These include nonprofits such as Terner Labs and Ivory Innovations offering curated programming to architecture, engineering, and construction (AEC) startups; housing developers in Minnesota and California "bundling" multiple projects together to reach economies of scale with a consistent project team; public and private sector entities developing "catalogues" of pre-approved home designs in the U.S. and Canada. This exploratory paper documents several of these emerging ecosystem-development efforts to support innovative housing approaches, characterizing them by leading stakeholder and intervention strategy based on publicly available information. The paper finds that these initiatives share similar high level goals but vary in implementation, reflecting different stakeholder priorities, regional market and policy dynamics, and housing typologies. The early stage of these efforts offer limited data for comparing actual outcomes, but the paper highlights common qualitative themes and identifies opportunities for further research and potential coordination among these efforts.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗